thesis statement on covid 19 vaccine

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http://orcid.org/0000-0003-1691-6403 Julian Savulescu 1 , 2 , 3
1 Faculty of Philosophy , University of Oxford , Oxford , UK
2 Murdoch Childrens Research Institute , Parkville , Victoria , Australia
3 Melbourne Law School , University of Melbourne , Melbourne , Victoria , Australia
Correspondence to Professor Julian Savulescu, Faculty of Philosophy, University of Oxford, Oxford, UK; julian.savulescu{at}philosophy.ox.ac.uk

Mandatory vaccination, including for COVID-19, can be ethically justified if the threat to public health is grave, the confidence in safety and effectiveness is high, the expected utility of mandatory vaccination is greater than the alternatives, and the penalties or costs for non-compliance are proportionate. I describe an algorithm for justified mandatory vaccination. Penalties or costs could include withholding of benefits, imposition of fines, provision of community service or loss of freedoms. I argue that under conditions of risk or perceived risk of a novel vaccination, a system of payment for risk in vaccination may be superior. I defend a payment model against various objections, including that it constitutes coercion and undermines solidarity. I argue that payment can be in cash or in kind, and opportunity for altruistic vaccinations can be preserved by offering people who have been vaccinated the opportunity to donate any cash payment back to the health service.

behaviour modification
technology/risk assessment
philosophical ethics
public health ethics

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/medethics-2020-106821

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Introduction

We are in the midst of a global pandemic with COVID-19 and there is a race to develop a vaccine. At the time of writing, there are 53 vaccines in clinical trials on humans (plus five that have bypassed the full trial process) and at least 92 preclinical vaccines under active investigation in animals. There are a number of different approaches: (1) genetic—using mRNA to cause the body to produce viral proteins; (2) viral vector—using genetically modified viruses such as adenovirus to carry sections of coronavirus genetic material; (3) protein—delivering viral proteins (but not genetic material) to provoke an immune response; (4) inactivated or attenuated coronavirus; (5) repurposing existing vaccines, eg, BCG (bacillus Calmette–Guérin). 1

Given the mounting number of deaths globally, and the apparent failure of many countries to contain the pandemic without severely damaging or problematic lockdowns and other measures, there have been calls to make a vaccine, if it were approved, mandatory. 2 Mandatory vaccination has not been ruled out within the UK. 3

The first part of this article asks when, if ever, a vaccine should be mandatory. I will create a set of criteria and a decision algorithm for mandatory vaccination. I will argue that in the case of COVID-19, some of these criteria may not be satisfied. The second part of the article argues that in the case of COVID-19, it may be ethically preferable to incentivise vaccine uptake. I will justify incentivisation and discuss different kinds of incentives.

Ethics of mandatory COVID-19 vaccination

There is a large body of literature on the justification for the use of coercion in public health and infectious disease in particular. Mandatory vaccination is typically justified on Millian grounds: harm to others. According to John Stuart Mill, the sole ground for the use of state coercion (and restriction of liberty) is when one individual risks harming others. 4 The most prominent arguments from bioethicists appeal to preventing harm to others. 5–7 In the case of children, significant risk of harm to the child is also a ground for state protection. Bambery et al 8 give the example of a child taking a box of toxic bleach to school, potentially harming himself and other children. Teachers are entitled to restrain the child and remove the poison both because of risk to the child and to other children. 8 Flanigan uses a similar example of a person shooting a gun into a crowd. 5

The Nuffield Council of Bioethics produced an influential report on public health which considers when coercion and mandatory vaccination might be justified:

When assessing whether more directive policies are acceptable, the following factors should be taken into account: the risks associated with the vaccination and with the disease itself, and the seriousness of the threat of the disease to the population. In the case of incentivised policies, the size of the incentive involved should be appropriate so that it would not unduly compromise the voluntariness of consent. We identified two circumstances in which quasi-mandatory vaccination measures are more likely to be justified. First, for highly contagious and serious diseases, for example with characteristics similar to smallpox. Second, for disease eradication if the disease is serious and if eradication is within reach. 9

I will elaborate on these brief suggestions and provide a novel structured algorithm for when vaccination should be mandatory.

COVID-19 is almost unique because of the gravity of the problem at the global level: not only is there cost in terms of lives from COVID-19, there is also the extraordinary economic, health and well-being consequences of various virus-control measures, including lockdown, which will extend into the future. Probably never before has a vaccine been developed so rapidly and the pressure to use it so great, at least at the global level.

There is a strong case for making any vaccination mandatory (or compulsory) if four conditions are met:

There is a grave threat to public health

The vaccine is safe and effective

Mandatory vaccination has a superior cost/benefit profile compared with other alternatives

The level of coercion is proportionate.

Each of these conditions involves value judgements.

Grave threat to public health

So far, there have been over 1 million deaths attributed to COVID-19 globally (as of 30 September 2020). 10 In the UK alone, it was predicted in influential early modelling that 500 000 would have died if nothing was done to prevent its spread. Even with the subsequent introduction of a range of highly restrictive lockdown measures (measures which could themselves come at a cost of 200 000 non-COVID-19 lives according to a recent UK government report), 11 more than 42 000 (as of 30 September 2020) 12 have died in the UK within 28 days of a positive test.

The case fatality rate was originally estimated to be as high as 11%, but (as is typical with new diseases) this was quickly scaled down to 1.5% or even lower. 13 The infection fatality rate (IFR, which accounts for asymptomatic and undiagnosed cases) is lower still as it has become clear that there are a large number of asymptomatic and mild cases. For example, the Centre for Evidence Based Medicine reports that “In Iceland, where the most testing per capita has occurred, the IFR lies somewhere between 0.03% and 0.28%”. 14

Of course, how you define “grave” is a value judgement. One of the worst-affected countries in the world in terms of COVID-19-attributed deaths per million is Belgium. The mortality is (at the time of writing) around 877 per million population, which is still under 0.1%, and the average age of death is 80. Of course, Belgium and most other countries have taken strict measures to control the virus and so we are not seeing the greatest possible impact the virus could have. Yet others such as Brazil and Sweden have intervened to a much lesser degree, yet (currently) have rates of 687 and 578 deaths per million respectively. Sweden’s April all-cause deaths and death rate at the peak of its pandemic so far, while extremely high, were surpassed by months in 1993 and 2000. 15

The data are complex and difficult to compare with different testing rates, and ways of assigning deaths and collecting data differing from country to country. For example, Belgium counts deaths in care homes where there is a suspicion that COVID-19 was the cause (without the need for a positive test) and, until recently, the UK counted a death which followed any time from a COVID-19 positive test as a COVID-19 death. Moreover, there have been huge behavioural changes even in countries without legally enforced lockdowns. Furthermore, the IFR varies wildly by age-group and other factors. Even among survivors, there is emerging evidence that there may be long-term consequences for those who have been infected but survived. Long COVID-19 health implications may present a grave future public health problem. Nevertheless, some might still argue that this disease has not entered the “grave” range that would warrant mandatory vaccination. The Spanish influenza killed many more (50–100 million), 16 and it afflicted younger rather than older people, meaning even more “life years” were lost. It is not difficult to imagine a Superflu, or bioengineered bug, which killed 10% across all ages. This would certainly be a grave public health emergency where it is likely mandatory vaccination would be employed.

Deciding whether COVID-19 is sufficiently grave requires both more data than we have and also a value judgement over the gravity that would warrant this kind of intervention. But let us grant for the sake of argument that COVID-19 is a grave public health emergency.

Vaccine is safe and effective

There are concerns that testing has been rushed and the vaccine may not be safe or effective. 17

First, although the technology being used in many of these vaccine candidates has been successfully used in other vaccines, no country has ever produced a safe and effective vaccine against a coronavirus. So in one way, we are all in uncharted waters.

Second, any vaccine development will be accelerated in the context of a grave public health emergency.The inherent probabilistic nature of the development of any biologic means that no vaccine could be said to be 100% safe. There will be risks and those risks are likely to be greater than with well-established vaccines.

Thirdly, some side effects may take time to manifest.

This is not to support the anti-vaccination movement. Vaccines are one of the greatest medical accomplishments and a cornerstone of public health. There are robust testing procedures in place in most jurisdictions to ensure that licensed COVID-19 vaccines are both effective and safe. It is only to acknowledge that everything, including vaccination, has risks. Perhaps the biggest challenge in the development of a vaccine for COVID-19 will be to be honest about the extent of those risks and convey the limitations of confidence in safety and efficacy relative to the evidence accrued.

There is an ethical balance to be struck: introducing a vaccine early and saving more lives from COVID-19, but risking side effects or ineffectiveness versus engaging in longer and more rigorous testing, and having more confidence in safety and efficacy, but more people dying of COVID-19 while such testing occurs. There is no magic answer and, given the economic, social and health catastrophe of various anti-COVID-19 measures such as lockdown, there will be considerable pressure to introduce a vaccine earlier.

To be maximally effective, particularly in protecting the most vulnerable in the population, vaccination would need to achieve herd immunity (the exact percentage of the population that would need to be immune for herd immunity to be reached depends on various factors, but current estimates range up to 82% of the population). 18

There are huge logistical issues around finding a vaccine, proving it to be safe, and then producing and administering it to the world’s population. Even if those issues are resolved, the pandemic has come at a time where there is another growing problem in public health: vaccine hesitancy.

US polls “suggest only 3 in 4 people would get vaccinated if a COVID-19 vaccine were available, and only 30% would want to receive the vaccine soon after it becomes available.” 18

Indeed, vaccine refusal appears to be going up. A recent Pew survey suggested 49% of adults in the USA would refuse a COVID-19 vaccine in September 2020. 19

If these results prove accurate then even if a safe and effective vaccine is produced, at best, herd immunity will be significantly delayed by vaccine hesitancy at a cost both to lives and to the resumption of normal life, and at worst, it may never be achieved.

There remain some community concerns about the safety of all pre-existing vaccines, including many that have been rigorously tested and employed for years.

In the case of COVID-19, the hesitancy may be exacerbated by the accelerated testing and approval process which applies not only to Sputnik V (the controversial “Russian vaccine”). Speaking about America’s vaccine programme, Warp Speed, Donald Trump applauded its unprecedented pace:

…my administration cut through every piece of red tape to achieve the fastest-ever, by far, launch of a vaccine trial for this new virus, this very vicious virus. And I want to thank all of the doctors and scientists and researchers involved because they’ve never moved like this, or never even close. 20

The large impact on society means the vaccine will be put to market much more quickly than usual, perhaps employing challenge studies or other innovative designs, or by condensing or running certain non-safety critical parts of the process in parallel (for example, creating candidate vaccines before its approval).

While the speed is welcomed by politicians and some members of the public, the pressure to produce a candidate vaccine, and the speed at which it has been done, may be also perceived (perhaps unfairly) to increase the likelihood of the kind of concerns that lead to vaccine hesitancy: concerns over side-effects that are unexpected or rare, or that take longer to appear than the testing process allows for, or that for another reason may be missed in the testing process.

The job to be done will not only be to prove scientifically that the vaccine is safe and effective, but also to inform and reassure the public, especially the group who are willing to take the vaccine in theory—but only after others have tried it out first.

The question remains of how safe is safe enough to warrant mandatory vaccination. It is vanishingly unlikely that there will be absolutely no risk of harm from any biomedical intervention, and the disease itself has dramatically different risk profiles in different groups of the population. In an ideal world, the vaccine would be proven to be 100% safe. But there will likely be some risk remaining. Any mandatory vaccination programme would therefore need to make a value judgement about what level of safety and what level of certainty are safe and certain enough. Of course, it would need to be very high, but a 0% risk option is very unlikely.

A COVID-19 vaccine may be effective in reducing community spread and/or preventing disease in individuals. Mandatory vaccination is most justifiable when there are benefits to both the individual and in terms of preventing transmission. If the benefits are only to individual adults, it is more difficult to support mandatory vaccination. One justification would be to prevent exhaustion of healthcare services in an emergency (eg, running out of ventilators), which has been used a basis of restriction of liberty (it was the main justification for lockdown). It could also be justified in the case of protection of children and others who cannot decide for themselves, and of other adults who either cannot be vaccinated for medical reasons.

Better than the alternatives

It is a standard principle of decision theory that the expected utility of a proposed option must be compared with the expected utility of relevant alternatives. There are many alternatives to mandatory vaccination. See figure 1 for a summary of the range of strategies for preventing infectious disease.

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Strategies for prevention of infectious disease.

A popular position, especially among medical professionals, 7 is that we don’t need mandatory vaccination because people are self-interested or altruistic enough to come forward for vaccination. We can reach herd immunity without mandatory vaccination.

If this were true, all well and good, but the surveys mentioned above cast doubt on this claim with regard to the future COVID-19 vaccine. Moreover, reaching herd immunity is not good enough.

First, how fast we reach herd immunity is also important. In a pandemic, time is lives. If it takes a year to reach herd immunity, that could be thousands or tens of thousands of lives in one country.

Second, herd immunity is necessary because some people cannot be vaccinated for medical reasons: they have allergies, immune problems, or other illnesses. The elderly often don’t mount a strong immune response (that is why it is better to vaccinate children for influenza because they are the biggest spreaders of that disease 7 —although COVID-19 appears to be different on the current evidence). And immunity wanes over time—so even people previously vaccinated may become vulnerable.

Even when national herd immunity is achieved, local areas can fall below that level over time, causing outbreaks, as happened with measles recently. This is especially likely to happen where people opposed to vaccines tend to cluster toghether—for example, in the case of certain religious communities. So ideally we need better than herd immunity to ensure that people are protected both over time and in every place.

These are thus reasons to doubt whether a policy of voluntary vaccination will be good enough, though it remains to be seen.

There are other policies that might obviate the need for mandatory vaccination. South Korea has kept deaths down to about 300 (at the time of writing) with a population of 60 000 000 with a vigorous track and trace programme (although it was criticised for exposing extra-marital affairs and other stigmatised behaviours). 21 Other countries have enforced quarantine with tracking devices. There could be selective lockdown of certain groups, 22 or for intermittent periods of time.

The long-term costs and benefits of such policies would have to be evaluated. That is, we should calculate the expected utility of mandatory vaccination (in combination with other policies) and compare it to alternative strategies (or some other combination of these). How utility should be evaluated is an ethical question. Should we count deaths averted (no matter how old), life years lost or lost well-being (perhaps measured by quality adjusted life years)? 23 Should we count loss of liberty or privacy into the other side the equation?

It may be that a one-off mandatory vaccination is a significantly smaller loss of well-being or liberty than these other complex resource intensive strategies.

So we cannot say whether a mandatory policy of COVID-19 vaccination is ethically justified until we can assess the nature of the vaccine, the gravity of the problem and the likely costs/benefit of alternatives. But it is certainly feasible that it could be justified.

It is important to recognise that coercive vaccination can be justified. This is easy to see by comparing it to other coercive interventions in the public interest.

Conscription in war

In the gravest emergencies, where the existence and freedom of the whole population is at stake, people are conscripted to serve their country, often with high risk of death or permanent injury. We often analogise the pandemic to a war: we are fighting the virus. If people can be sent to war against their will, in certain circumstances some levels of coercion are justified in the war on the virus. Notably, in conditions of extreme emergency in past wars (graver than currently exist for COVID-19), imprisonment or compulsion have even been employed. 24

A more mundane example is the payment of taxes. Taxes benefit individuals because tax revenue allows the preservation of public goods. But if sufficient numbers of others are paying their taxes, it is in a person’s self-interest to free ride and avoid taxes. Indeed, paying taxes may result in harm in some circumstances. 24 In the USA, where there is a large private healthcare sector, paying your taxes may mean you cannot pay for lifesaving medical care that you would otherwise have been able to afford. Still, taxes are mandatory based on considerations of fairness and utility.

Seat belts are mandatory in the UK and many other countries, whereas they were previously voluntary. Interestingly, 50% or so of Americans initially opposed making seat belts mandatory, but now 70% believe mandatory laws are justified. 25

Seat belts reduce the chance of death if you are involved in a car accident by 50%. They are very safe and effective. Notably, they do cause injuries (seat belt syndrome) and even, very occasionally, death. But the chances of being benefitted by wearing them vastly outweigh these risks, so they are mandatory, with enforcement through fines . I have previously likened vaccination to wearing a seat belt. 25

Pre-existing mandatory vaccination

Mandatory vaccination policies are already in place in different parts of the world. Mandatory vaccination policies are those that include a non-voluntary element to vaccine consent and impose a penalty or cost for unjustified refusal (justified refusal includes those who have a contraindicating medical condition, or those who already have natural immunity). There are a range of possible penalties or costs which can coerce people. Australia has the “No Jab, No Pay” scheme which withholds child benefits if the child is not vaccinated, and a “No Jab, No Play” scheme which withholds kindergarten childcare benefits. Italy introduced fines for unvaccinated children who attend school. In the USA, state regulations mandate that children cannot attend school if they are not vaccinated, and healthcare workers are required to vaccinate. Some US states (eg, Michigan) make exemptions difficult to obtain by requiring parents to attend immunisation education courses 26 (see also 27 28 ).

Figure 2 summarises the range of coercive policies that can constitute mandatory vaccination.

Cost of mandatory/coercive vaccination.

Coercion is proportionate

In public health ethics, there is a familiar concept of the “least restrictive alternative”. 28 The least restrictive alternative is the option which achieves a given outcome with the least coercion (and least restriction of liberty).

This is a very weak principle: it uses liberty as tie breaker between options with the same expected utility. More commonly, however, we need to weigh utility against liberty. That is, a more restrictive policy will achieve more expected utility—but is it justified?

According to a principle of proportionality, the additional coercion or infringement in liberty is justified if it is proportionate to the gain in expected utility of the more coercive intervention compared with next best option. That is, additional coercion is justified when the restriction of liberty is both minimised and proportionate to the expected advantages offered by the more coercive policy.

As we can see from the previous section and figure 2, there are a variety of coercive measures. (The Nuffield Council has created a related “Intervention Ladder”, 29 though this includes education and incentives, as well as coercive measures.) Penalties can be high. In war, those who conscientiously objected to fighting went to jail or were forced to perform community service (or participate in medical research). In France, parents were given a suspended prison sentence for refusing to vaccinate their child. 30

While there are legitimate concerns that the effectiveness of these policies in different contexts has been inadequately investigated, a number of these policies have been shown to increase vaccination rates. 31

Notably, the fine or punishment for avoiding taxes varies according to the gravity of the offence. The fine for not wearing a seat belt is typically small. A modest penalty for not being vaccinated in a grave public health emergency could be justifiable. For example, a fine or restriction of movement might be justified.

Figure 3 combines these four factors into an algorithm for justified mandatory vaccination.

Algorithm for mandatory vaccination.

These four factors can be justified in several ways. They represent a distillation and development of existing principles in public health ethics, for example, the least restrictive alternative. They can also be justified by the four principles of biomedical ethics.

For example, justice is about the distribution of benefits and burdens across a population in a fair manner. Justice and beneficence, in the context of vaccination policies, both require that the problem addressed is significant and vaccination is an effective means of addressing it. Non-maleficence requires that the risk imposed on individuals be small. Respect for autonomy and justice both require that coercion be applied only if necessary and that it be proportionate to additional utility of mandatory vaccination (and that such coercion be minimised, which is a feature of proportionality).

It is important to recognise that vaccines may have benefits both to the individual and to others (the community). If the vaccine has an overall net expected utility for the individual, beneficence supports its administration.

How great a sacrifice (loss of liberty or risk) can be justified? The most plausible account is provided by a duty of easy rescue: when the cost to an individual is small of some act, but the benefit or harm to another is large, then there is a moral obligation to perform that act. I have elsewhere argued for a collective duty of easy rescue: where the cost of some act to an individual is small, and the benefit of everyone doing that act to the collective is large, there is a collective duty of easy rescue. 32 Such a principle appropriately balances respect for autonomy with justice.

Whether mandatory vaccination for any disease can be justified will depend on precise facts around the magnitude of the problem, the nature of the disease and vaccination, the availability and effectiveness of alternative strategies and the level of coercion. Elsewhere I compare mandatory vaccination for influenza and COVID-19 in more detail. 27

Better than coercion? Payment for risk

Given the risks, or perceived risks, of a novel COVID-19 vaccine, it would be practically and perhaps ethically problematic to introduce a mandatory policy, at least initially (when uncertainty around safety will be greater). Is there a more attractive alternative?

The arguments in favour of vaccination, particularly for those at lower risk (children, young people and those previously infected) can be based on a principle of solidarity. After all, “We are in this together” has been a recurrent slogan supporting pandemic measures in different countries. Those at low risk are asked to do their duty to their fellow citizens, which is a kind of community service. Yet they have little to personally gain from vaccination. The risk/benefit profile looms large for those at lowest risk.

However, another way of looking at this is that those at low risk are being asked to do a job which entails some risk., so they should be paid for the risk they are taking for the sake of providing a public good. And although it may be unlikely to influence so-called 'anti-vaxxers', it may influence a good portion of the 60% of American adults who responded in a March 2020 poll that they would either delay vaccination or didn’t know about vaccination. 33

I have previously argued that we should reconceive live organ donation and participation in risky research, including challenge studies, 34 as jobs where risk should be remunerated, much like we pay construction workers and other dangerous professions both for the job and for the risk involved. 35 36 While the risk profile for approved vaccinations means that it differs from these examples, it could be compared to a job such as social work as a further argument in favour of payment. People may legitimately be incentivised to take on risks, as the Nuffield Council recognises in its Intervention Ladder. 29

The advantage of payment for risk is that people are choosing voluntarily to take it on. As long as we are accurate in conveying the limitations in our confidence about the risks and benefits of a vaccine, then it is up to individuals to judge whether they are worth payment.

Of course, that is a big ask. It would require government to be transparent, explicit and comprehensive in disclosure of data, what should be inferred and the limitations on the data and confidence. This has often not been the case—one only has to remember the denial of the risks of bovine spongiform encephalopathy (BSE) at the height of the crisis by the British government, when in 1990 the Minister for Agriculture, Fisheries and Food, John Gummer proudly fed his 4-year-old daughter, Cordelia, a hamburger in front of the world’s media, declaring British beef safe. (Gummer was awarded a peerage in 2010 and is now Lord Deben.) 37

There is also a danger that payment might signal lack of confidence in safety. That is a real risk and one that I will address in the “payment in kind” section below.

But the basic ethical point (public acceptability aside) is that, if a vaccine is judged to be safe enough to be used without payment, then it is safe enough to be used with payment. 36 Payment itself does not make a vaccine riskier. If a vaccine is considered too risky to be administered to the population, then it should not be administered, no matter whether coercively, through incentives, or through some other policy.

A standard objection to payment for risk (whether it is risky research or live organ donation) is that it is coercive: it forces people to take risks against their better judgement. In Macklin’s words:

The reason for holding that it is ethically inappropriate to pay patients to be research subjects is that it is likely to be coercive, violating the ethical requirement that participation in research should be fully voluntary. 38

As I have previously argued, 39 this demonstrates deep conceptual confusion. Coercion exists when an option which is either desired or good is removed or made very unappealing. The standard example is a robber who demands “Your money or your life”. This removes the most desired and best option: your money and your life. The Australian “No Jab, No Pay”scheme arguably does constitute coercion as it removes an option that one is entitled to, that is, non-vaccination with the “Pay”. So too is the Italian scheme of fines coercive.

However, paying people is not coercive. Adding an option, like payment, without affecting the status quo is not coercive. If a person chooses that option, it is because they believe that overall their life will go better with it, in this case, with the vaccination and the payment. The gamble may not pay off: some risk might eventuate and then it wasn’t worth it. But that is life—and probability.

It is true that the value of the option might exercise force over our rational capacities, but that is no different from offering a lot of money to attract a favoured job applicant.

What can be problematic about offers is exploitation. Exploitation exists where one offers less than a fair deal and a person only accepts it because of vulnerability from background injustice.

There are two ways to prevent exploitation. First, we can correct any background injustice that might cause it. In this case, the person would have little reason to accept the offer. Second, we can pay a fair minimum price for risk, as when we pay construction workers danger money. Paradoxically, this requires paying more, rather than less. 40

But there is an important additional feature of vaccination. If a vaccine were deemed to be safe enough to offer on a voluntary basis without payment, it must be safe enough to incentivise with payment because the risks are reasonable. It may be that those who are poorer may be more inclined to take the money and the risk, but this applies to all risky or unpleasant jobs in a market economy. It is not necessarily exploitation if there are protections in place such as a minimum wage or a fair price is paid to take on risk.

So payment for vaccination which passes independent safety standards (and could reasonably be offered without payment) is not exploitation, if the payment is adequate.

Undue influence?

A related concern is undue influence. Undue influence means that because of the attractiveness of the offer, I can’t autonomously and rationally weigh up the risks and benefits. It is sometimes understood as “were it not for the money, he would not do it”.

But that formulation is too broad—were it not for the money, many people would not go to work. Rather what the concept of ‘undue influence’ intends to capture is that the offer, usually money, bedazzles a person so that he or she makes a mistake in weighing up the risks and benefits. Someone offers Jones a million dollars to take on a risk of 99.99% of dying in a dangerous experiment. He just focuses on the money and takes a deal which is unfair and unreasonable. However, taking such an offer might be rational. If Jones’ daughter is about to die without a million dollars and he values her life more than his own, it might be both autonomous and rational to take the deal.

Because we cannot get into people’s minds, it is difficult in practice to unravel whether undue influence is occurring—how can you differentiate it from a rational decision? In practice, if it would be acceptable to be vaccinated for nothing, it is acceptable to do it for money. Concerns about undue influence are best met by implementing procedures to minimise bias and irrational decision making, such as cooling off periods, information reframing, and so on.

There remains a lurking concern that a decision where payment is involved may not be fully autonomous or authentic. For example, racial and ethnic minorities are among the groups most gravely affected by COVID-19, but given concerns about systemic racism in research and medicine, these communities may have good reason to distrust the medical machine. Is it acceptable to use payment to get over those concerns?

All we can do practically to address concerns about autonomy and authenticity is to redouble efforts: to ensure we do know the risks and they are reasonable (and that the underpinning research is not itself subject to concerns about systemic racism), and try to foster trust with such public education campaigns. This can work alongside a payment scheme. People still need to understand what the facts are. They still need to make as autonomous and authentic a decision as possible.

Practical advantages

A payment model could also be superior to a mandatory model from a practical point of view. There may be considerable resistance to a mandatory model which may make it difficult, expensive and time-consuming to implement, with considerable invasion of liberty. In a payment model, people are doing what they want to do.

A payment model could also be very cheap, compared with the alternatives. The cost of the UK’s furlough scheme is estimated to reach £60 billion by its planned end in October, 41 and the economic shut down is likely to cost many billions more, as well as the estimated 200 000 lives expected to be lost as a result. 11 It would make economic sense to pay people quite a lot to incentivise them to vaccinate sooner rather than later—which, for example, would speed up their full return to work.

It may be that payment is only required to incentivise certain groups. For example, it may be that young people require incentivising because they are at lower risk from the disease itself. On the other hand, justice might require payment for all taking the risk. Although the elderly and those at higher risk have more to gain personally, they are also providing a service by being vaccinated and not using limited health resources. (There is an enormous backlog of patients in the NHS—another grave threat to public health.)

One particularly difficult case is paying parents to vaccinate their children. It is one thing to pay people to take on risk for themselves; it is quite another to pay them to enable their children to take on risks, particularly when the children have little to gain as they are at lowest risk. In part, the answer to this issue is determined by how safe the vaccine is and how confident we can be in that assessment. If it were safe, to a level that even a mandatory programme would be justified, it may be appropriate to instead incentivise parents to volunteer their children for vaccination. If safety is less certain, payment for risk in this group is the most problematic.

It is true that some mandatory vaccination programmes already fine parents for failure to vaccinate their children. However, in those cases vaccination is clearly in the child’s best interest, as the child receives the benefit of immunity to diseases such as measles, that pose a greater risk to that child than we currently believe COVID-19 does. Moreover, they are for vaccines that have been in place for many years and have a well-established safety profile.

A standard objection to paying people to do their duty, particularly civic duty, is that it undermines solidarity, trust, reciprocity and other community values. This is the argument given by Richard Titmuss for a voluntary blood donation scheme. 42

The UK does not pay donors for blood or blood products, but does purchase blood products from other countries, including Austria where donors are paid a “travel allowance” for plasma donation. In Australia, which runs a donor system, more than 50% of the plasma comes from paid donors in the USA. 43 Altruism is insufficient. Germany recently moved to paying for plasma donors. It does not appear to have undermined German society.

In the end, the policy we should adopt towards COVID-19 vaccination will depend on the precise risks and benefits of the vaccine (and our confidence in them), the state of the pandemic, the nature of the alternatives, and particularly the public appetite for a vaccine.

In the right circumstances, mandatory vaccination could be ethically justified, if the penalty is suitably proportionate.

Payment for vaccination, perhaps, has even more to be said for it.

For those attached to the gift of altruism, the vaccinated could be offered the opportunity to donate their fee back to the NHS (or similar health service provider). This combined “payment-donation” model would be a happy marriage of ethics and economics. It would give altruists a double chance to be altruistic: first by vaccinating and second by donating the fee. It would also couple self-interest with morality for free-riders (as they would have greater self-interest to do what is moral), and it would give those who face obstacles to vaccination an additional reason to overcome these.

Payment in kind

Of course, benefits can come in cash or kind. An alternative “payment” model is to pay those who vaccinate in kind. This could take the form of greater freedom to travel, opportunity to work or socialise. With some colleagues, I have given similar arguments in favour of immunity passports. 44

One attractive benefit would be the freedom to not wear a mask in public places if you carried a vaccination certificate, and not to socially distance. Currently, everyone has to wear a mask and practise social distancing. Relaxing this requirement for those who have been vaccinated (or otherwise have immunity) would be an attractive benefit. Moreover, it would help ameliorate the risks the unvaccinated would pose to others.

Payment in kind has one advantage over cash in that it might not send the signal that vaccination is perceived to be unsafe. A cash payment may paradoxically undermine vaccination uptake by introducing unwarranted suspicion (though this is an intuition that may need to be tested). Benefits in kind are less susceptible to this concern because they are directly linked to the benefit provided by the vaccine itself: the vaccinated person is no longer a threat to others.

Some might object that this represents a form of shaming the non-vaccinators (some of whom might be excluded from vaccination for health reasons), just as presenting those who evaded conscription with a white feather was a method of shaming perceived free-riders. But this could be managed through an education campaign about the justification for face covering requirements. There is a good reason to require the non-vaccinated to continue to wear masks and practice social distancing, regardless of whether their refusal is justified—they do represent a greater direct threat to others.

It is quite possible that some mixture of altruism, financial and non-financial benefits will obviate the need to introduce mandatory vaccination. It is better that people voluntarily choose on the basis of reasons to act well, rather than being forced to do so. Structuring the rewards and punishments in a just and fair way is one way of giving people reasons for action.

Mandatory vaccination can be ethically justified (see figure 3), but when risks are more uncertain, payment for vaccination (whether in cash or kind) may be an ethically superior option.

Acknowledgments

This piece builds on a previous piece I published on the JME blog, Good Reasons to Vaccinate: COVID19 Vaccine, Mandatory or Payment Model? [ https://blogs.bmj.com/medical-ethics/2020/07/29/good-reasons-to-vaccinate-covid19-vaccine-mandatory-or-payment-model/ ]. I would like to thank an anonymous reviewer for very many helpful and constructive comments. I would also like to thank Alberto Giubilini for his help.

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Supplementary materials

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Contributors Sole authorship.

Funding JS is supported by the Uehiro Foundation on Ethics and Education. He received funding from the Wellcome Trust WT104848 and WT203132. Through his involvement with the Murdoch Children’s Research Institute, he has received funding through from the Victorian State Government through the Operational Infrastructure Support (OIS) Program.

Competing interests None declared.

Patient consent for publication Not required.

Provenance and peer review Not commissioned; externally peer reviewed.

Data availability statement No data are available.

Linked Articles

Response Persuasion, not coercion or incentivisation, is the best means of promoting COVID-19 vaccination Susan Pennings Xavier Symons Journal of Medical Ethics 2021; 47 709-711 Published Online First: 27 Jan 2021. doi: 10.1136/medethics-2020-107076

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Feldstein LR , Britton A , Grant L, et al. Effectiveness of Bivalent mRNA COVID-19 Vaccines in Preventing SARS-CoV-2 Infection in Children and Adolescents Aged 5 to 17 Years. JAMA. 2024;331(5):408–416. doi:10.1001/jama.2023.27022

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Effectiveness of Bivalent mRNA COVID-19 Vaccines in Preventing SARS-CoV-2 Infection in Children and Adolescents Aged 5 to 17 Years

1 Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, US Centers for Disease Control and Prevention, Atlanta, Georgia
2 Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle
3 University of Arizona, Tucson
4 Department of Public Health Science, University of Miami, Miami, Florida
5 Children’s Research Institute, Seattle, Washington
6 University of Utah Health, Salt Lake City
7 Abt Associates Inc, Rockville, Maryland
8 Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor
9 Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor
10 Baylor Scott and White Health, Temple, Texas
11 Marshfield Clinic Research Institute, Marshfield, Wisconsin
12 Kaiser Permanente Center for Health Research, Portland, Oregon
13 St Luke’s Regional Health Care System, Duluth, Minnesota
Original Investigation Neonatal Outcomes After COVID-19 Vaccination in Pregnancy Mikael Norman, MD, PhD; Maria C. Magnus, PhD; Jonas Söderling, PhD; Petur B. Juliusson, MD, PhD; Lars Navér, MD, PhD; Anne K. Örtqvist, MD, PhD; Siri Håberg, MD, PhD; Olof Stephansson, MD, PhD JAMA

Question What is the effectiveness of the bivalent COVID-19 vaccines among children and adolescents aged 5 to 17 years?

Findings In this prospective cohort study including 2959 participants aged 5 to 17 years, vaccine effectiveness against laboratory-confirmed SARS-CoV-2 infection was 54.0% and vaccine effectiveness against symptomatic COVID-19 was 49.4%.

Meaning During a period when the Omicron BA.4/5 sublineages were the predominant circulating variants, children and adolescents received protection against SARS-CoV-2 infection and symptomatic COVID-19 from the bivalent COVID-19 vaccines compared with those who were unvaccinated or received only the monovalent COVID-19 vaccine.

Importance Bivalent mRNA COVID-19 vaccines were recommended in the US for children and adolescents aged 12 years or older on September 1, 2022, and for children aged 5 to 11 years on October 12, 2022; however, data demonstrating the effectiveness of bivalent COVID-19 vaccines are limited.

Objective To assess the effectiveness of bivalent COVID-19 vaccines against SARS-CoV-2 infection and symptomatic COVID-19 among children and adolescents.

Design, Setting, and Participants Data for the period September 4, 2022, to January 31, 2023, were combined from 3 prospective US cohort studies (6 sites total) and used to estimate COVID-19 vaccine effectiveness among children and adolescents aged 5 to 17 years. A total of 2959 participants completed periodic surveys (demographics, household characteristics, chronic medical conditions, and COVID-19 symptoms) and submitted weekly self-collected nasal swabs (irrespective of symptoms); participants submitted additional nasal swabs at the onset of any symptoms.

Exposure Vaccination status was captured from the periodic surveys and supplemented with data from state immunization information systems and electronic medical records.

Main Outcome and Measures Respiratory swabs were tested for the presence of the SARS-CoV-2 virus using reverse transcriptase–polymerase chain reaction . SARS-CoV-2 infection was defined as a positive test regardless of symptoms. Symptomatic COVID-19 was defined as a positive test and 2 or more COVID-19 symptoms within 7 days of specimen collection. Cox proportional hazards models were used to estimate hazard ratios for SARS-CoV-2 infection and symptomatic COVID-19 among participants who received a bivalent COVID-19 vaccine dose vs participants who received no vaccine or monovalent vaccine doses only. Models were adjusted for age, sex, race, ethnicity, underlying health conditions, prior SARS-CoV-2 infection status, geographic site, proportion of circulating variants by site, and local virus prevalence.

Results Of the 2959 participants (47.8% were female; median age, 10.6 years [IQR, 8.0-13.2 years]; 64.6% were non-Hispanic White) included in this analysis, 25.4% received a bivalent COVID-19 vaccine dose. During the study period, 426 participants (14.4%) had laboratory-confirmed SARS-CoV-2 infection. Among these 426 participants, 184 (43.2%) had symptomatic COVID-19, 383 (89.9%) were not vaccinated or had received only monovalent COVID-19 vaccine doses (1.38 SARS-CoV-2 infections per 1000 person-days), and 43 (10.1%) had received a bivalent COVID-19 vaccine dose (0.84 SARS-CoV-2 infections per 1000 person-days). Bivalent vaccine effectiveness against SARS-CoV-2 infection was 54.0% (95% CI, 36.6%-69.1%) and vaccine effectiveness against symptomatic COVID-19 was 49.4% (95% CI, 22.2%-70.7%). The median observation time after vaccination was 276 days (IQR, 142-350 days) for participants who received only monovalent COVID-19 vaccine doses vs 50 days (IQR, 27-74 days) for those who received a bivalent COVID-19 vaccine dose.

Conclusion and Relevance The bivalent COVID-19 vaccines protected children and adolescents against SARS-CoV-2 infection and symptomatic COVID-19. These data demonstrate the benefit of COVID-19 vaccine in children and adolescents. All eligible children and adolescents should remain up to date with recommended COVID-19 vaccinations.

Although rates of SARS-CoV-2–related hospitalizations and death among children and adolescents are lower than rates in adults, 1 severe disease can still occur and lead to hospitalization, life-threatening complications (such as multisystem inflammatory syndrome in children), 2 - 5 and postinfection sequelae. 6 - 8 As of December 31, 2023, there have been at least 911 COVID-19–associated deaths among individuals aged 5 to 17 years in the US. 9

The Omicron variant was more transmissible and included lineages with greater potential to evade vaccine-induced immunity than previous variants. 10 - 12 To provide protection against the Omicron variant, the US Food and Drug Administration authorized use of the bivalent mRNA COVID-19 vaccine, which was composed of ancestral and Omicron BA.4/5 strains. 13 On September 1, 2022, the bivalent mRNA COVID-19 vaccine was recommended for persons aged 12 years or older (to be administered ≥2 months after completion of any monovalent primary series or monovalent booster dose authorized by the Food and Drug Administration), and on October 12, 2022, the bivalent COVID-19 vaccine was recommended for children aged 5 to 11 years. 14 , 15

Although data have shown that bivalent mRNA COVID-19 vaccination among adults is effective at reducing the risk of COVID-19, 16 - 20 including severe outcomes, limited data exist on the effectiveness of bivalent COVID-19 vaccine doses among children and adolescents. Available studies are limited by small sample size and a short duration of follow-up and reliance on voluntary testing. 21 , 22 Understanding how well children and adolescents are protected by a bivalent COVID-19 vaccine dose is important for informing public health strategies, especially in the context of updated vaccine formulations and emergence of new variants.

During a period in which the Omicron BA.4/5 sublineages and subsequent Omicron lineages were predominant, this analysis used merged data from 3 prospective cohort studies to estimate vaccine effectiveness of authorized COVID-19 bivalent vaccines against laboratory-confirmed SARS-CoV-2 infection and symptomatic COVID-19 among children and adolescents aged 5 to 17 years.

From September 4, 2022, to January 31, 2023, we conducted an analysis across 6 sites in the US to estimate COVID-19 vaccine effectiveness among children and adolescents aged 5 to 17 years by combining data from 3 prospective cohort studies (Pediatric Research Observing Trends and Exposures in COVID-19 Timelines [PROTECT], CASCADIA, and Community Vaccine Effectiveness [CoVE], which is an expansion of the Household Influenza Vaccine Evaluation [HIVE] cohort). 23 - 25 Children and adolescents living in Arizona, Michigan, Oregon, Texas, Utah, and Washington, including individuals from the same household, were eligible for inclusion.

Written informed consent was obtained from the parents or guardians of the enrolled children and assent was obtained from children and adolescents aged 7 to 17 years. This study was reviewed by the US Centers for Disease Control and Prevention and approved by the institutional review boards at participating sites, or under a reliance agreement with the Abt Associates institutional review board, and was conducted in a manner consistent with applicable federal law and policy of the Centers for Disease Control and Prevention. 26 - 30

Each participant or a parent or legal guardian (on behalf of the participant) completed an enrollment survey regarding demographics, household characteristics, chronic medical conditions, COVID-19 vaccination history, and prior SARS-CoV-2 infection. Participants were resurveyed at regular intervals to capture up-to-date demographic information.

As part of the demographic information, race and ethnicity were collected because vaccine uptake and risk of SARS-CoV-2 infection may vary by race and ethnicity. This information was reported by each participant or a parent or legal guardian using predefined race and ethnicity categories.

Blood specimens were collected from participants who consented to phlebotomy. Weekly surveillance was conducted for COVID-19 symptoms. Participants were asked to self-collect (performed by the parent, legal guardian, child, or adolescent) upper respiratory specimens weekly, irrespective of symptoms. To optimally capture all infections, participants were instructed to collect an additional respiratory specimen upon onset of symptoms if outside the timing of their regular weekly specimen collection (swab).

All respiratory specimens were tested for the presence of the SARS-CoV-2 virus using multiplex reverse transcriptase–polymerase chain reaction (RT-PCR) (eTable 1 in Supplement 1 ). Specimens that failed molecular testing due to contamination or that were misidentified or had a cycle threshold value in the inconclusive range were considered negative. Whole-genome sequencing was attempted on all SARS-CoV-2 infection–positive specimens with an adequate viral quantity in the CASCADIA and CoVE studies and on a representative subset in the PROTECT study. 31 - 34

Available serum specimens were tested for the presence of antinucleocapsid IgG using a qualitative IgG enzyme-linked immunosorbent assay or quantitative Meso Scale Discovery VPLEX assays (eTable 1 in Supplement 1 ). For the Meso Scale Discovery assay, antinucleocapsid IgG titers were compared with a standard curve provided by the manufacturer to determine titer quantity. Specimens below the lower limit of quantitation per assay insert were set to a value of half the lower limit. Per the assay insert, specimens were determined to have detectable antinucleocapsid IgG if they had a titer equal to or greater than 5000 AU/mL.

COVID-19 vaccination status was captured from enrollment, weekly, and monthly surveys (self-report); vaccine cards provided by the participant; and from queries of the state immunization information systems and electronic medical records when available. Vaccination data included vaccination dates, number of doses, and manufacturer. If discrepant information was recorded across multiple data sources, information from the electronic medical record and state immunization information systems was used preferentially over self-reported information.

SARS-CoV-2 infection was defined as a positive RT-PCR test regardless of symptoms. Symptomatic COVID-19 was defined as a positive RT-PCR test and 2 or more COVID-19 symptoms reported within 7 days before or after the specimen collection date. The surveyed list of COVID-19 symptoms varied by study cohort (eTable 2 in Supplement 1 ).

Prior SARS-CoV-2 infection was defined as a positive RT-PCR test from a specimen collected during study enrollment but before the start of the study period, self-report of infection prior to enrollment or start of the study period (whichever occurred later), or a positive antinucleocapsid SARS-CoV-2 antibody. Time since prior SARS-CoV-2 infection was defined as less than 4 months, 4 months to less than 6 months, 6 months to less than 12 months, 12 months or longer, and no prior infection. Dates of prior SARS-CoV-2 infection were imputed for 146 participants (4.9%) who only had serological results and, therefore, did not have dates associated with prior SARS-CoV-2 infection. Imputation was done using results from linear regression models, in which the baseline nucleocapsid blood draw date and the numeric nucleocapsid values served as the predictors for the date of prior infection among study participants with known prior infection dates (eMethods in Supplement 1 ).

Descriptive statistics comparing participants who had SARS-CoV-2 infection during the study period vs participants who remained uninfected included frequency (proportion) for categorical variables and median (IQR) for continuous variables. The P values were calculated using χ 2 tests for categorical variables and Wilcoxon tests for continuous variables at the .01 level. The Andersen-Gill extension of the Cox proportional hazards model with time-varying vaccination status was used to estimate the hazard ratios for first occurrence of SARS-CoV-2 infection in each participant, comparing participants who received a bivalent COVID-19 vaccine dose (>7 days after receipt) vs those who did not receive a bivalent COVID-19 vaccine dose (either unvaccinated or received monovalent COVID-19 vaccine doses only). 35

Multivariable models used L2 regularization to adjust for potential confounders, 36 specifically age, sex, race, ethnicity, underlying health conditions, time since prior SARS-CoV-2 infection, geographic site, 7-day average of COVID-19 cases per 100 000 by site (local incidence was modeled as a continuous linear variable), and proportion of circulating variants by site (categorized by those containing the spike substitution R346T). 37 The L2-regularized models used bootstrap resampling by household to estimate the 95% CIs and account for household clustering because 30.6% of households had 2 or more children and adolescents included in the analysis. 38

Person-time was calculated as the total number of days under surveillance for a given vaccination status during the study period. The study period started on September 4, 2022, for children and adolescents aged 12 to 17 years and on October 16, 2022, for children aged 5 to 11 years. Surveillance ended on the date of a participant’s first positive RT-PCR test result for SARS-CoV-2 infection, the participant’s study withdrawal date, 18th birthday, or at the end of the study period (January 31, 2023). For the participants who enrolled in 1 of the cohorts after the start of the study period, time at risk started at their enrollment or at 6 weeks after SARS-CoV-2 infection if recently infected prior to enrollment.

Surveillance weeks were not censored for missing specimen result (eg, participant skipped a weekly swab) or if there were problems with specimen testing. The 2 weeks after a monovalent COVID-19 primary vaccine dose and the week after bivalent and monovalent COVID-19 booster vaccine doses were excluded from person-time. COVID-19 vaccine effectiveness was calculated as vaccine effectiveness = (1 − hazard ratio) × 100.

In the primary analysis, the effectiveness of a dose of bivalent COVID-19 vaccine compared with no vaccine or monovalent only doses was estimated against laboratory-confirmed SARS-CoV-2 infection (inclusive of asymptomatic and symptomatic infections) and symptomatic COVID-19. For the outcome of laboratory-confirmed SARS-CoV-2 infection, the estimates were also stratified by age group (5-11 years and 12-17 years) and prior SARS-CoV-2 infection status. In a secondary analysis, the effectiveness of bivalent COVID-19 vaccine was estimated stratified by time since bivalent vaccination (7-60 days or 61-150 days) compared with no vaccine or monovalent doses received 180 or more days ago.

Two sensitivity analyses for vaccine effectiveness were conducted. The first analysis restricted the reference category to only participants who received a monovalent COVID-19 vaccine dose. The second analysis restricted to only participants from the Arizona study sites because they constituted 52% of the study population and had low coverage for the bivalent COVID-19 vaccine.

All analyses were conducted using SAS software version 9.4 (SAS Institute Inc) or R software version 4.1.2 (R Foundation for Statistical Computing).

Between September 4, 2022, and January 31, 2023, a total of 2959 participants were included in the analyses ( Table 1 ). The median adherence to weekly upper respiratory specimen collection (swabbing) throughout the study period was 93.8% (IQR, 84%-100%). Overall, 47.8% of the participants were female, the median age was 10.6 years (IQR, 8.0-13.2 years), the majority were non-Hispanic White (64.6%), 25.4% had received a bivalent COVID-19 vaccine dose, and 61.7% had self-reported or confirmed SARS-CoV-2 infection prior to the study period ( Table 1 ).

During the study period, 426 participants (14.4%) had a laboratory-confirmed SARS-CoV-2 infection (eTable 3 in Supplement 1 ); of those with SARS-CoV-2 infection, 184 (43.2%) had symptomatic COVID-19 ( Table 1 ). Participants living in Michigan (20.2%; 24/119) and those without documented prior SARS-CoV-2 infection (22.5%; 255/1134) had the highest proportion of in-study SARS-CoV-2 infection. Of the 426 participants with SARS-CoV-2 infection, 238 (56.0%) had genetic sequencing results. Of the 238 participants with genetic sequencing results, the most prevalent lineages were BA.4 or BA.5 (50.0%), BQ.1.1 (36.5%), XBB (5.9%), and BA.2 (3.8%) (eFigure in Supplement 1 ).

Participants living in Oregon had the highest uptake of bivalent COVID-19 vaccine (56.2%; 246/438), whereas those living in Texas had the lowest (2.4%; 3/124). Participants reporting Hispanic ethnicity had lower bivalent COVID-19 vaccine uptake (17.1%; 87/509) compared with non-Hispanic participants of all races (27.1%; 665/2450). Participants with 1 or more chronic medical conditions had higher uptake of bivalent COVID-19 vaccine (34.5%; 154/447) compared with those without a chronic medical condition (23.8%; 598/2512). Of the 2207 participants who did not receive a bivalent COVID-19 vaccine dose, 535 (24.2%) were unvaccinated and 1672 (75.8%) received at least 1 monovalent COVID-19 vaccine dose.

Of the 426 participants with SARS-CoV-2 infection, 383 (89.9%) were either unvaccinated or received monovalent COVID-19 vaccine doses only (1.38 infections per 1000 person-days) and 43 (10.1%) received a bivalent COVID-19 vaccine dose (0.84 infections per 1000 person-days) ( Table 2 ). Compared with being unvaccinated or receiving only monovalent COVID-19 vaccine doses, the adjusted vaccine effectiveness of a bivalent COVID-19 vaccine dose was 54.0% (95% CI, 36.6%-69.1%) against laboratory-confirmed SARS-CoV-2 infection ( Table 2 ). The median number of observation days after COVID-19 vaccination was 276 (IQR, 142-350 days) for those who received any monovalent COVID-19 vaccine doses and 50 (IQR, 27-74 days) for those who received a bivalent COVID-19 vaccine dose.

When stratified by age, the adjusted bivalent COVID-19 vaccine effectiveness was 58.3% (95% CI, 34.0%-76.5%) for children aged 5 to 11 years and 47.5% (95% CI, 18.2%-71.9%) for children and adolescents aged 12 to 17 years ( Table 3 ). Among children aged 5 to 11 years, the median number of observation days after COVID-19 vaccination was 221 (IQR, 140-349 days) for those who received any monovalent COVID-19 vaccine doses and 44 (IQR, 24-66 days) for those who received a bivalent COVID-19 vaccine dose. Among children and adolescents aged 12 to 17 years, the median number of observation days after COVID-19 vaccination was 313 (IQR, 241-404 days) for those who received any monovalent COVID-19 vaccine doses and 59 (IQR, 32-87 days) for those who received a bivalent COVID-19 vaccine dose.

Of the 184 participants with symptomatic COVID-19, 164 (89.1%) were either unvaccinated or received monovalent COVID-19 vaccine doses only (0.59 infections per 1000 person-days) and 20 (10.9%) received a bivalent COVID-19 vaccine dose (0.39 infections per 1000 person-days) ( Table 2 ). The adjusted vaccine effectiveness of a bivalent COVID-19 vaccine dose against symptomatic COVID-19 was 49.4% (95% CI, 22.2%-70.7%). Among participants with symptomatic COVID-19, the median number of observation days after vaccination was 276 (IQR, 142-350 days) for those who received any monovalent COVID-19 vaccine doses and 50 (IQR, 27-74 days) for those who received a bivalent COVID-19 vaccine dose.

Compared with participants who did not receive the COVID-19 vaccine or received monovalent only doses 180 days or more ago, the adjusted vaccine effectiveness of a bivalent COVID-19 vaccine dose against SARS-CoV-2 infection was 51.3% (95% CI, 23.6%-71.9%) 7 to 60 days after vaccination and was 62.4% (95% CI, 38.5%-81.1%) 61 to 150 days after vaccination. The median number of observation days after vaccination was 350 (IQR, 303-392 days) for monovalent COVID-19 vaccine doses administered 180 days or more ago, 34 (IQR, 20-47 days) for a bivalent COVID-19 vaccine dose administered 7 to 60 days ago, and 81 (IQR, 70-95 days) for a bivalent COVID-19 vaccine dose administered 61 to 150 days ago.

Among participants who had prior SARS-CoV-2 infection before the start of the study, the adjusted effectiveness of bivalent COVID-19 vaccine against SARS-CoV-2 infection was 63.6% (95% CI, 33.0%-84.0%) ( Table 3 ). Among participants with no prior SARS-CoV-2 infection, COVID-19 vaccine effectiveness was 47.2% (95% CI, 26.7%-67.8%) ( Table 3 ). Among participants with prior SARS-CoV-2 infection, the median number of observation days after COVID-19 vaccination was 288 (IQR, 156-357 days) for monovalent doses and 47 (IQR, 25-71 days) for a bivalent dose. Among participants without prior SARS-CoV-2 infection, the median number of observation days after COVID-19 vaccination was 241 (IQR, 127-334 days) for monovalent doses and 54 (IQR, 29-78 days) for a bivalent dose.

In a sensitivity analysis restricting the reference group to persons who had received at least 1 dose of monovalent COVID-19 vaccine (ie, excluding unvaccinated individuals), the adjusted vaccine effectiveness of bivalent COVID-19 vaccine against SARS-CoV-2 infection was 56.3% (95% CI, 40.5%-70.1%) and was 51.1% (95% CI, 26.9%-72.1%) against symptomatic COVID-19 ( Table 2 ). In a subsequent sensitivity analysis restricted to participants from the Arizona study site, the adjusted bivalent COVID-19 vaccine effectiveness was 51.5% (95% CI, 20.3%-77.2%) (eTable 4 in Supplement 1 ).

In this analysis of data from 3 prospective cohort studies in the US, children and adolescents aged 5 to 17 years who received an mRNA bivalent COVID-19 vaccine dose were less likely to be infected with SARS-CoV-2 than those who were unvaccinated or who received only monovalent COVID-19 vaccine doses. The vaccine effectiveness of a bivalent COVID-19 vaccine dose against SARS-CoV-2 infection was not significantly different when stratified by age group (5-11 years vs 12-17 years).

There was no observed waning 61 to 150 days after receipt of a bivalent COVID-19 vaccine dose, although there may not have been sufficient follow-up time to assess waning. Nevertheless, these results suggest that, during a period when the Omicron BA.4/5 sublineages were the predominant circulating variants, bivalent COVID-19 vaccines provided protection against SARS-CoV-2 infection and symptomatic COVID-19 among children and adolescents.

We conducted several sensitivity analyses to address potential confounding, including using an alternative reference category and restricting the analysis only to participants from the Arizona study site because they constituted half of all study participants. We found the bivalent COVID-19 vaccine effectiveness estimates from these analyses to be consistent with the overall estimate. We also examined COVID-19 vaccine effectiveness by prior SARS-CoV-2 infection status to determine whether hybrid immunity from both vaccination and prior infection provided greater protection than COVID-19 vaccination alone. 39 , 40 Even though the bivalent COVID-19 vaccine effectiveness estimate among those with reported SARS-CoV-2 infection or with evidence of prior SARS-CoV-2 infection was higher than among those without prior SARS-CoV-2 infection, the difference was not statistically significant.

These findings are consistent with the limited other data available on protection provided by the bivalent vaccine for children and adolescents. In a study by Lin et al 21 among children aged 5 to 11 years, effectiveness of the bivalent COVID-19 vaccine 2 months after receipt was 47.3% (95% CI, −17.9% to 76.4%). The estimate for vaccine effectiveness 1 month after receipt of a bivalent COVID-19 vaccine dose (76.7% [95% CI, 45.7 to 90.0]) by Lin et al 21 was higher than the estimate (51.3% [95% CI, 23.6% to 71.9%]) in the current study for those who received a bivalent COVID-19 vaccine dose within 7 to 60 days. However, the 95% CIs overlap, and the difference in vaccine effectiveness may be due to different sites and study periods.

In addition, the current multistate study followed up participants through January 31, 2023, whereas Lin et al 21 followed up North Carolina residents until January 6, 2023. National surveillance data 37 show increased circulation of variants other than BA.4/5 during those 4 weeks, and it is possible that the bivalent COVID-19 vaccine may not be as protective against those variants (eg, XBB), thus decreasing the vaccine effectiveness estimate for the entire study period.

This study had many strengths, including almost 3000 participants enrolled from 6 diverse sites across multiple states in the US. Participants collected weekly swabs regardless of symptoms, which greatly reduces the risk of missing an asymptomatic SARS-CoV-2 infection, and adherence to weekly swabbing was high (median, 94%). Weekly and quarterly surveys, as well as data from the state immunization information systems and electronic medical records, ensured detailed and complete information on potential confounding variables and vaccination status. Although there was no observed waning 61 to 150 days after receipt of the bivalent COVID-19 vaccine dose, the 95% CIs were wide because of small sample size and this analysis could not examine vaccine waning beyond 150 days. The continuation of the participant cohorts will present future opportunities for examination of longer-term waning patterns to support future vaccine decision-making.

There are several important limitations of this study. First, RT-PCR testing methods and the list of COVID-19 symptoms surveyed varied by cohort; therefore, some differences in the definition of SARS-CoV-2 infection or symptomatic COVID-19 may be present.

Second, weekly or symptomatic RT-PCR testing prior to the analytic study start date for estimation of prior SARS-CoV-2 infection history was only available among a subset of participants. To address this concern, we incorporated serological data to identify additional prior SARS-CoV-2 infections. The sensitivity and specificity of the serological assays varied by cohort site and, due to antinucleocapsid SARS-CoV-2 antibody waning, the assays may not have detected some prior infections.

Third, social desirability or recall bias may have affected self- or parent-report of prior SARS-CoV-2 infection when RT-PCR and serological test results were unavailable, and self- or parent-reported vaccination status when data were unavailable from the state immunization information systems and electronic medical records.

Fourth, our analysis did not account for the social vulnerability index and immunocompromised status, which may be associated with vaccine uptake and risk of SARS-CoV-2 infection.

Fifth, limited sample sizes resulted in imprecise subgroup estimates and precluded us from examining vaccine effectiveness against symptomatic COVID-19 and vaccine waning by age group.

The bivalent COVID-19 vaccine protected children and adolescents against SARS-CoV-2 infection and symptomatic COVID-19. These data demonstrate the benefit of COVID-19 vaccine in children and adolescents. All eligible children and adolescents should remain up to date with recommended COVID-19 vaccinations.

Accepted for Publication: December 11, 2023.

Corresponding Author: Leora R. Feldstein, PhD, US Centers for Disease Control and Prevention, 1600 Clifton Rd NE, Atlanta, GA 30329 ( [email protected] ).

Author Contributions: Drs Feldstein and Britton had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Feldstein, Britton, Grant, Wiegand, Babu, Briggs Hagen, Burgess, Caban-Martinez, Chu, Englund, Hegmann, Lutrick, Martin, Meece, Midgley, Monto, Phillips, Saydah, Smith, Vandermeer, Yoon, Naleway.

Acquisition, analysis, or interpretation of data: Feldstein, Britton, Grant, Wiegand, Ruffin, Babu, Briggs Hagen, Burgess, Caban-Martinez, Chu, Ellingson, Englund, Hegmann, Jeddy, Lauring, Martin, Mathenge, Meece, Midgley, Monto, Newes-Adeyi, Odame-Bamfo, Olsho, Phillips, Rai, Saydah, Steinhardt, Tyner, Vaughan, Yoon, Gaglani, Naleway.

Drafting of the manuscript: Feldstein, Britton, Wiegand, Babu, Hegmann, Martin, Vandermeer.

Critical review of the manuscript for important intellectual content: Feldstein, Britton, Grant, Wiegand, Ruffin, Babu, Briggs Hagen, Burgess, Caban-Martinez, Chu, Ellingson, Englund, Hegmann, Jeddy, Lauring, Lutrick, Martin, Mathenge, Meece, Midgley, Monto, Newes-Adeyi, Odame-Bamfo, Olsho, Phillips, Rai, Saydah, Smith, Steinhardt, Tyner, Vaughan, Yoon, Gaglani, Naleway.

Statistical analysis: Feldstein, Grant, Wiegand, Odame-Bamfo, Smith.

Obtained funding: Briggs Hagen, Burgess, Chu, Englund, Lutrick, Martin, Midgley, Olsho, Phillips, Yoon.

Administrative, technical, or material support: Feldstein, Britton, Ruffin, Caban-Martinez, Chu, Ellingson, Englund, Hegmann, Jeddy, Lauring, Martin, Meece, Midgley, Monto, Newes-Adeyi, Olsho, Phillips, Rai, Steinhardt, Vandermeer, Vaughan, Yoon.

Supervision: Feldstein, Britton, Briggs Hagen, Burgess, Chu, Englund, Hegmann, Jeddy, Martin, Meece, Olsho, Phillips, Yoon, Gaglani.

Conflict of Interest Disclosures: Dr Caban-Martinez reported receiving grants from the Florida Firefighter Cancer Initiative and the Florida Department of Health. Dr Chu reported receiving personal fees from AbbVie, Vindico, Ellume, Medscape, Merck, Clinical Care Options, Cataylst Medical Education, Vir, Pfizer, and Prime Education. Dr Englund reported receiving personal fees from AbbVie, AstraZeneca, Merck, Meissa Vaccines, Moderna, Sanofi Pasteur, Pfizer, Ark Biopharma, GSK (formerly GlaxoSmithKline), and Shinogi. Dr Hegmann reported being the editor of the American College of Occupational and Environmental Medicine practice guidelines. Ms Jeddy reported being an employee of Abt Associates. Dr Lauring reported receiving personal fees from Roche and Sanofi and receiving grants from the Flu Lab and the Burroughs Wellcome Fund. Dr Martin reported receiving grants from Merck. Dr Monto reported receiving personal fees from Roche. Dr Newes-Adeyi reported being an employee of Abt Associates. Dr Olsho reported being an employee of Abt Associates and a study participant in CASCADIA. Dr Phillips reported receiving personal fees from Novavax. Ms Rai reported being an employee of Abt Associates. Dr Vaughan reported being an employee of Abt Associates. Dr Yoon reported receiving personal fees from Novavax. Dr Gaglani reported serving as co-chair of the infectious diseases and immunization committee and the respiratory syncytial virus taskforce lead for the Texas Pediatric Society and the Texas Chapter of the American Academy of Pediatrics. No other disclosures were reported.

Funding/Support: This study was supported by the National Center for Immunization and Respiratory Diseases, US Centers for Disease Control and Prevention under contracts 75D30121C12297 (Kaiser Foundation Hospitals), 75D30122C13149 (University of Michigan), 75D30120C08150 (Abt Associates Inc), and 75D30122C14188 (University of Arizona) and by the National Institute of Allergy and Infectious Diseases (contract 75N93021C00015).

Role of the Funder/Sponsor: The US Centers for Disease Control and Prevention, but not the National Institute of Allergy and Infectious Diseases, collaborated with partner sites to design and conduct the study; managed, analyzed, and interpreted the data; prepared, reviewed, and approved the manuscript; and had a role in the decision to submit the manuscript for publication.

Disclaimer: The findings and conclusions are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention.

Data Sharing Statement: See Supplement 2 .

Additional Contributions: There is an extensive list of additional contributions listed in the eContributions section in Supplement 1 .

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Open access
Published: 24 May 2023

Unraveling attributes of COVID-19 vaccine acceptance and uptake in the U.S.: a large nationwide study

Sean D. McCabe 1 , 2 na1 ,
E. Adrianne Hammershaimb 1 , 3 , 4 na1 ,
David Cheng 1 ,
Andy Shi 1 , 2 ,
Derek Shyr 1 , 2 ,
Shuting Shen 1 , 2 ,
Lyndsey D. Cole 5 ,
Jessica R. Cataldi 5 , 6 ,
William Allen 1 , 7 ,
Ryan Probasco 1 ,
Ben Silbermann 1 ,
Feng Zhang 1 , 8 , 9 , 10 , 11 ,
Regan Marsh 12 , 13 , 14 ,
Mark A. Travassos ORCID: orcid.org/0000-0002-6045-3322 1 , 3 , 4 &
Xihong Lin ORCID: orcid.org/0000-0001-7067-7752 1 , 2 , 15 , 16

Scientific Reports volume 13 , Article number: 8360 ( 2023 ) Cite this article

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Disease prevention
Infectious diseases
Public health

SARS-CoV-2 vaccines are useful tools to combat the Coronavirus Disease 2019 (COVID-19) pandemic, but vaccine reluctance threatens these vaccines’ effectiveness. To address COVID-19 vaccine reluctance and ensure equitable distribution, understanding the extent of and factors associated with vaccine acceptance and uptake is critical. We report the results of a large nationwide study in the US conducted December 2020-May 2021 of 36,711 users from COVID-19-focused smartphone-based app How We Feel on their willingness to receive a COVID-19 vaccine. We identified sociodemographic and behavioral factors that were associated with COVID-19 vaccine acceptance and uptake, and we found several vulnerable groups at increased risk of COVID-19 burden, morbidity, and mortality were more likely to be reluctant to accept a vaccine and had lower rates of vaccination. Our findings highlight specific populations in which targeted efforts to develop education and outreach programs are needed to overcome poor vaccine acceptance and improve equitable access, diversity, and inclusion in the national response to COVID-19.

A systematic review and meta-analysis of the global prevalence and determinants of COVID-19 vaccine acceptance and uptake in people living with HIV

Self-reported COVID-19 vaccine hesitancy and uptake among participants from different racial and ethnic groups in the United States and United Kingdom

A global survey of potential acceptance of a COVID-19 vaccine

Introduction.

The emergence in late 2019 of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as a novel human pathogen and causative agent of the global coronavirus disease 2019 (COVID-19) pandemic 1 fueled an unprecedented effort to rapidly develop a vaccine 2 . While the successful development of several effective SARS-CoV-2 vaccines was a major achievement, the defining challenge of the COVID-19 pandemic is ensuring equitable vaccine distribution and high vaccine uptake.

Soon after the identification of the virus, it was estimated that at least 70% of the U.S. population would need to acquire immunity to SARS-CoV-2 to end the COVID-19 pandemic 3 . It was unclear whether natural infection alone would produce sufficient, durable immunity, and vaccination became a major pillar of the public health strategy to control the pandemic. Public opinion polling in early 2020 suggested that as many as 72% of U.S. adults were willing to receive a COVID-19 vaccine once licensed and available. Four months later, the number of U.S. adults willing to receive a SARS-CoV-2 vaccine had sharply declined to as low as 51% 4 . Resistance to vaccination has posed a public health challenge since the smallpox vaccine was first invented, and although the vaccine targets and the cultural context may vary over time and place, common factors associated with reluctance, refusal, and even anti-vaccination activism include mistrust, misinformation, and a belief in the primacy of individual liberty.

In December 2020, two vaccines against COVID-19 received Emergency Use Authorization (EUA) from the U.S. Food and Drug Administration 5 , 6 . The results of phase 3 clinical trials and the subsequent rollout of the Pfizer-BioNTech and Moderna vaccines received significant attention in the media. Opinion polls conducted in December 2020 suggested a subsequent increase in public willingness to receive a COVID-19 vaccine, likely due to the widespread availability of data showing the vaccines to be both safe and effective 7 . Despite Johnson & Johnson’s Janssen COVID-19 vaccine also receiving EUA, national uptake of vaccines declined from mid-April 2021 onward as those reluctant to be vaccinated occupied a greater percentage of the unvaccinated population and information emerged about rare vaccine-related adverse events 8 , 9 , 10 .

How We Feel (HWF) is a web and mobile-phone application developed to facilitate the large-scale collection of data about COVID-19 symptoms, SARS-CoV-2 test results, and transmission-mitigating behaviors and sentiments 11 . Users are assigned a randomly generated number that tracks logins from the same device and are otherwise unidentifiable. Beginning in December 2020, we fielded a question about users’ COVID-19 vaccine intentions. These responses were then related to the user’s subsequent COVID-19 vaccine uptake or refusal.

We hypothesized that responses could provide significant insights into understanding vaccine acceptance across the United States, identifying populations that could be a promising focus of vaccine outreach efforts. We aimed to evaluate associations of the degree of COVID-19 vaccine acceptance in the U.S. and identify characteristics that might influence vaccine acceptance and eventual COVID-19 vaccine uptake. This has the potential to help public health and community leaders develop effective education and outreach programs to overcome vaccine reluctance and ensure equitable vaccine distribution and improved vaccine uptake.

A total of 36,711 users responded to the vaccine acceptance question. The largest number of respondents came from Connecticut and California with 8697 and 4668, respectively (Supplementary Fig. 1 a). HWF’s user base is approximately 79% female (Supplementary Fig. 1 b) and 83% white (Supplementary Fig. 1 c). Users are 18 years of age or older and are equally distributed by age groups (Supplementary Fig. 1 d). More than 68% of respondents were non-essential workers, and users cover a diverse range of income groups. All descriptive statistics of the study participants are available in Supplementary Table 1 .

In total, 30,618 (83%) were willing (“Likely” or “Very Likely”) to be vaccinated (Fig. 1 a). After applying a census-based post-stratification weight (see Methods), Vermont (92%) and Washington D.C. (88%) had the highest rates of vaccine reluctance while South Dakota (27%) and Louisiana (23%) had the highest rates of undecided users (Fig. 1 b). Weighted bar plots of vaccine reluctance across demographic characteristics revealed that “Undecided” users represented the largest proportion of non-willing users across all demographic groups (Fig. 2 a, Supplementary Table 2 ).

COVID-19 Acceptance rates: ( a ) (Left) Number of responses and (Right) unweighted and weighted percentages. ( b ) Weighted average willingness and undecided rates by state.

Demographic Acceptance Rates: ( a ) Weighted percentages of reluctant responses by race/ethnicity, profession, location, age, income, and use of protective measures. State level weighted reluctance rates by ( b ) cumulative case rates (/100 individuals), ( c ) cumulative death rates (/1000 individuals), ( d ) and average number of users practicing protective behavior.

State level reluctance (“Undecided”, “Unlikely”, or “Very Unlikely”) rates were negatively associated with the average number of users that practiced transmission mitigating behaviors and were positively associated with cumulative COVID-19 case and death rates by January 10, 2021 (Fig. 2 b–d). Unweighted plots are available in Supplementary Fig. 2 .

To assess demographic associations with vaccine acceptance, we fit a univariate logistic regression with socio-demographic, occupation, preexisting medical conditions, geographical and COVID-19 related predictors (Supplementary Table 3 ) and a multivariable logistic regression model to adjust for potential relationships between the predictors (Fig. 3 , Supplementary Table 4 ). We implemented post-stratification weights using census estimates of sex, age, race, and census location (see Methods). People of color reported higher rates of vaccine reluctance compared to white non-Hispanic users (African American OR, 3.94; CI, 3.47, 4.48; p = 1.26e−96). Vaccine reluctance was more likely among females than males (OR,1.67; CI, 1.51, 1.83; p = 4.09e−25); younger users than those over 65 years old (18–30 OR, 2.17; CI, 1.86, 2.53; p = 1.03e−22); those with three or more preexisting conditions than those with zero (OR, 1.19; CI, 1.06, 1.34; p = 0.0036); and parents than non-parents (OR, 1.26; CI, 1.15, 1.38; p = 9.61e−7). Individuals that were furloughed or job-seeking were also more vaccine reluctant compared to those working full- or part-time (OR, 1.48; CI, 1.29, 1.70; p = 4.04e−8). Respondents from the South (OR, 1.25; CI, 1.05, 1.48; p = 0.0105), from less densely populated areas, or with lower incomes were all more likely to be vaccine reluctant. Users that responded before the Pfizer Emergency Use Authorization (EUA) on December 11, 2020 were more vaccine reluctant than users who responded after the Pfizer EUA (OR, 1.48; CI, 1.37, 1.60; p = 9.96e−23), users who practiced behavior protective against COVID-19 such as mask-wearing or social distancing were less vaccine reluctant (OR, 0.78; CI, 0.72, 0.85; p = 6.12e−9), and users that received a COVID test were less vaccine reluctant (OR, 0.79; CI, 0.71, 0.89, p = 5.88e-5).

Logistic regression-based association analysis results of vaccine acceptance: Forest plots for (Left) unweighted and (Right) weighted multivariable logistic regression analyses for vaccine reluctance with 95% confidence intervals. Non-significant variables at the 0.05 level (white), significant positive associations (red), and significant negative associations (blue).

Nominal logistic regression (see Methods) evaluated whether vaccine reluctance was driven by “Undecided” vs. “Unlikely/Very Unlikely” responses (Supplementary Table 5 ) and was also conducted with a weighted analysis (Supplementary Table 6 ). Reluctance in healthcare workers, those aged 55–64, Asian users, and those in locations with a median income between $70,000 and $100,000 was driven by the “Undecided” group, whereas reluctance in the unemployed, those with 3 + preexisting conditions, and southern users was driven by the “Unlikely” group. Sensitivity analyses were performed for the weighted multivariable and nominal regression analyses with a less restrictive threshold for the trimming weights (Supplementary Table 7 – 8 ) and found similar results. We conducted a sensitivity analysis to assess differences in reluctance in individuals that tested positive for COVID-19 and found no difference in intention based on testing results (see Methods, Supplementary Table 9 – 10 ).

Of the 36,711 users who responded to the vaccine acceptance question, 23,429 also responded to the vaccine uptake question and its distribution is provided in Fig. 4 a. Demographic distributions remained similar to those of respondents of the vaccine acceptance question with a slight increase in the proportion of users ages 65 + (Supplementary Fig. 3 ). Vaccination rates by state are shown in Fig. 4 b for all users that responded to the vaccine uptake question and subset to respondents who were offered a vaccine. Users with lower levels of vaccine acceptance had lower rates of vaccination (Fig. 4 c), and Black and Hispanic/Latinx users reported lower rates of vaccination than White, Non-Hispanic users (Fig. 4 d). Plots of weighted and unweighted vaccination rates across all demographic features are available in Supplementary Figs. 4 – 5 .

Vaccine Uptake Rates: ( a ) Vaccine uptake question responses for all users. ( b ) Weighted vaccination rates by state of (Left) all users that responded to the vaccine uptake question and (right) users that were offered a vaccine. ( c ) Weighted vaccination uptake of users that were offered a vaccine by vaccine acceptance and ( d ) race/ethnicity.

To formally identify demographic features associated with differences in vaccination rates, we conducted an unweighted and weighted multiple logistic regression analysis (see Methods, Fig. 5 , Supplementary Tables 11 – 12 ). All age groups reported lower rates of vaccinations compared to users over 65 (18–30 OR: 0.10; CI, 0.06, 0.18; p = 1.43e−16); Black users reported lower rates of vaccinations (OR, 0.58; CI, 0.38, 0.91; p = 0.0165) compared to White non-Hispanic users; essential workers outside of healthcare reported lower rates of vaccinations (OR, 0.64; CI, 0.44, 0.92; p = 0.0162) compared to non-essential workers; parents reported lower rates of vaccination (OR, 0.63; CI, 0.45, 0.89; p = 0.0086) compared to users who are not parents; users in areas with a median household income (MHI) of $40–70 K (OR, 0.56; CI, 0.37, 0.85; p = 0.0066) and $70–100 K (OR, 0.63; CI, 0.42, 0.96; p = 0.0316) reported lower rates of vaccinations compared to those in areas with a MHI $100 K + ; users logging in from areas with 0–149 people/sq. mi reported lower rates of vaccinations (OR, 0.53; CI, 0.34, 0.82; p = 0.0049) compared to users in high population density areas; and users that responded “Unlikely/Very Unlikely” (OR, 0.02; CI, 0.01, 0.03; p = 2.07e−114) and “Undecided” (OR, 0.08; CI, 0.06, 0.12; p = 1.06e−39) to the vaccine acceptance question reported lower rates of vaccinations compared to willing users.

Logistic regression-based association analysis results of vaccine uptake: Forest plots for (Left) unweighted and (Right) weighted multivariable logistic regression analyses for vaccination uptake with 95% confidence intervals. Non-significant variables at the 0.05 level (white), significant positive associations (red), and significant negative associations (blue).

While vaccination rates were lower in the reluctant group compared to the acceptant group, 86% (2157/2520) of reluctant users were vaccinated. In a formal multiple regression analysis looking at demographic associations with vaccine uptake among reluctant users, similar associations were found (see Methods, Supplementary Table 13 ). Younger age groups, healthcare workers, people from lower income households, and residents of areas with lower population density had lower vaccination rates. Users who responded to the vaccine acceptance question as “Undecided” reported higher rates of vaccination compared to those that responded “Unlikely/Very Unlikely” (OR, 4.57; CI, 3.47, 6.03; p = 2.26e−26).

In our analysis, increased reluctance was associated with minority race/ethnicity, living in less densely populated regions, and being a healthcare worker. A large proportion of these populations were undecided about COVID-19 vaccination, suggesting that targeted outreach may improve vaccine uptake. In fact, a significant portion of those skeptical or undecided about vaccination were ultimately vaccinated, supporting the idea that perspectives on COVID-19 vaccination are not immutable and may respond to such outreach.

Black respondents had the highest rates of COVID-19 vaccine reluctance and the lowest rates of vaccine uptake relative to other racial and ethnic groups, consistent with other surveys 4 , 9 , 10 , 12 , 13 , 14 , 15 . The history of racist practices within the U.S. healthcare system and research community, such as during the Tuskegee Syphilis Study 16 , and disparities in social determinants of health including poor access to healthcare and limited time off work likely contribute to our findings. Dispelling concerns within the Black community requires extensive, sustained, structured outreach and will be critical to efforts to contain and eliminate COVID-19. The National Institutes of Health’s Community Engagement Alliance (CEAL) provides a model for such outreach, targeting populations that have been hardest hit by the COVID-19 pandemic 17 .

Education and outreach efforts must target several additional populations. This includes rural residents and young adults. Because large proportions of these populations were undecided about COVID-19 vaccination, outreach to these groups must also provide reliable vaccine information tailored to the needs of each community, and different outreach strategies may be needed to address the concerns of those who were undecided and those who were unlikely.

Vaccine acceptance in healthcare workers warrants particular attention. We found that reluctant healthcare workers were less likely than other reluctant workers to change their mind (Supplementary Table 13 ). Others have found that U.S. nurses had the highest degree of COVID-19 vaccine reluctance among healthcare workers 18 . As the profession that enjoys the highest degree of public trust, nurses have an important role to play in promoting vaccine confidence 19 . Furthermore, inadequate vaccine uptake among healthcare workers raises the possibility of sustained COVID-19 transmission in an essential worker population critical to caring for vulnerable members of society, including immunocompromised individuals and children, the majority of whom were not yet eligible for a COVID-19 vaccine by the conclusion of this study 20 , 21 , 22 , 23 .

Addressing regional foci of reluctance to accept a COVID-19 vaccine will be critical in federal resource allocation to combat vaccine reluctance in general. We identified the greatest level of reluctance to accept a COVID-19 vaccine in the South followed by the Midwest. While a survey sponsored by the United States Centers for Disease Control and Prevention (CDC) and conducted in December 2020 found that COVID-19 vaccine hesitancy was most prevalent in the Northeast, followed by the South 15 , other data from the CDC detailing U.S. state and county-level vaccination rates and allocated dose usage have consistently shown that Southern states have lower vaccination rates and lower allocated dose usages compared to other areas of the country 9 . The significance of these phenomena is highlighted by the resurgence of COVID-19 with the spread of the delta variant in the South 24 .

Initial reluctance or indecision regarding COVID-19 vaccination was not fixed and did not necessarily reflect a respondent's eventual vaccination decision. This suggests the need for a multi-pronged approach that includes interventions directed at behavior change. Even if receptivity towards vaccination is low, there may still be significant potential for increasing vaccine uptake, indicating the need for continued implementation of strategies known to be effective, such as health care provider outreach and reminders 25 , 26 .

A study limitation is that our sample may not be generalizable to the broader American public or to populations outside of the U.S., particularly lower- and middle-income countries. How We Feel users are self-selecting, technologically literate, and more likely to have a high baseline level of concern about COVID-19. The user base is inherently skewed by a large proportion of users residing in Connecticut and California and by regional age discrepancies. Given the Connecticut government’s involvement in promoting the application, it’s possible users from Connecticut are more trusting of their state’s government. Census-adjusted, weighted analysis help correct the sampling bias but may not completely remove the potential for bias, and interpretation of our findings should note this. Furthermore, interstate movement of respondents during the pandemic may have affected the geographic distribution of responses. Additionally, we were unable to objectively verify self-reported vaccination; however, in other independent studies, there was a high degree of concordance between self-reported influenza vaccination and respondents’ actual influenza vaccination status 27 , 28 . This provides indirect evidence that self-reported COVID-19 vaccination status is a good proxy of verified vaccination status. Future research needs to be conducted to verify the concordance between the self-reported and registry-based vaccination records.

Further work is needed to better understand how vaccine reluctance relates to novel vaccine uptake in the U.S. and to understand how knowledge, attitudes, and behaviors surrounding COVID-19 vaccines change over time. As COVID-19 vaccines have become widely available to adults and adolescents in the U.S. and COVID-19 restrictions are lifting, our findings affirm the ongoing need to address vaccine reluctance and issues related to access.

Open-source software

We used the following open-source software in the analysis.

R: http://www.r-project.org

Tidyverse: http://www.tidyverse.org

Data.table: https://CRAN.R-project.org/package=data.table

nnet https://CRAN.R-project.org/package=nnet

censusapi https://CRAN.R-project.org/package=censusapi

survey https://CRAN.R-project.org/package=survey

ggplot2 https://CRAN.R-project.org/package=ggplot2

cowplot https://CRAN.R-project.org/package=cowplot

Data collection

Users could freely download the application which was available for both Android and Apple devices. The application was advertised widely on various social media outlets and through a partnership with the Connecticut state government which provided press releases to encourage residents to download the application. Users also heard about the application through word of mouth and through general media coverage. Data on vaccine acceptance was collected between December 4th, 2020 and May 6th 2021 11 . Following guidance from the CDC, users were asked “If a safe, effective coronavirus vaccine were available, how likely would you be to get yourself vaccinated?” Responses were given on a bipolar 5-point Likert scale from “Very Unlikely” to “Very Likely”, with “Undecided” being the middle value. The users first recorded response to the vaccine acceptance question was used in this analysis. On February 12th, 2021, a vaccine uptake question was added. Users were asked “Have you received a COVID-19 vaccine?” and could respond with “Yes”, “No, I haven’t been offered one”, or “No, I have been offered one but declined”. For all uptake models the most recent response was used. A consort diagram is available in Supplementary Fig. 7 to further clarify the number of respondents.

Users also self-reported race/ethnicity, sex, age, occupation, and preexisting conditions. Users who identified as “other” in the gender response were dropped due to small sample size. Neighborhood specific median household income was obtained from the user’s zip code at the time of answering the vaccine acceptance question by using the American Community Survey 5-year average results from 2018. Population density was calculated at the county level for each user based on data from the Yu Group at University of California at Berkeley 29 . State level case and death rates were obtained from USAFACTS 30 . As a proxy for user’s education status, the percentage of residents without a high school degree was included for each user’s county from the Census database.

Race/ethnicity was defined using distinct groups corresponding to “White,” “Black/African-American,” “Hispanic/Latino,” and “Asian” if the user only selected that respective racial group. Users who answered more than one race or ethnicity or selected an option other than the ones listed above were placed in a “multiracial/other” category.

During each login, users reported whether they left their home and for what reason. If they left home, they were then asked what types of protective measurements they used while away (mask, social distancing, cloth mask, and/or avoiding public transportation). We defined “protective behavior” to be if a user either stayed home or wore a mask when outside the home. If the user said that they did not wear a mask outside the home but engaged only in outdoor exercise and maintained physical distance from others, then they were also considered to be practicing protective behavior. We then created a variable that was coded as “1” if they always practiced protective behavior during all logins and a “0” if they failed to be protective during at least one login.

Users were considered to be reluctant to accept a vaccine if they responded as “Very Unlikely,” “Unlikely,” or “Undecided” to the vaccine acceptance question. Using vaccine reluctance as the outcome, a logistic regression was fit using several demographic variables as predictors to identify characteristics of users that were more or less vaccine reluctant. Both a univariate (Supplementary Table 3 ) and a multivariable model (Fig. 3 , Supplementary Table 4 ) were performed to adjust for potential confounding. Only responses from users residing within the United States were used in the modelling. Corresponding odds ratios and 95% confidence intervals are provided, and statistical significance was assessed at the 0.05 level. Analyses were conducted using R (v 3.5.1).

Using the same covariates as in the logistic regression, a nominal logistic regression was fit to assess if results from the logistic regression were driven by individuals being more likely to be in the “Undecided” or “Unlikely” groups. The 5-point Likert scale was reduced to a 3-level bipolar variable for modelling purposes by combining “Very Unlikely” with “Unlikely” and “Very Likely” with “Likely” (Supplementary Table 5 ).

Weighted analysis

To adjust our analyses to a user base that matches the major U.S. census demographics, we implemented a weighted analysis using post-stratification weights. Using the census population estimates of sex, race, age, and census location, a population-based joint distribution was obtained. A user base distribution was also calculated using the same breakdown, and the two proportions were then matched per user. The post-stratification weight was then calculated by dividing the census proportion by the sample proportion plus 1e−4 to avoid issues with smaller user base probabilities. To avoid over or underweighting individuals, the post-stratification weights were trimmed to be between 0.3 and 3 prior to the weighted analysis (Supplementary Table 4 ). For the nominal regression analysis, two separate weighted logistic regressions were conducted. One compared the “Undecided” group vs. the “Likely” group, while the other compared the “Unlikely” group vs. the “Likely” group (Supplementary Table 6 ). To assess the choice of the weight trimming bounds, sensitivity analyses were conducted for both above weighted analyses (Supplementary Table 7 – 8 ) using a threshold of 0.1 and 5. Supplementary Fig. 6 provides the distribution of the post-stratification weights.

IPW analysis

To formally assess if there was a difference in vaccine reluctance between those that received a prior positive COVID test and those that received a negative test, we adjust for the demographic biases associated with receiving a COVID test. We first fit a weighted logistic regression to model the probability of receiving a test using all individuals and all demographic features that have been reported in previous analyses while applying the same weighted procedure as above. The coefficients, 95% confidence intervals, and p -values for this analysis are available in Supplementary Table 9 . The fitted probabilities were then used as inverse probability weights (IPWs) in a weighted logistic regression model for vaccine reluctance only including individuals which had received a COVID test. The same predictors for previous weighted models were used and a new variable designating if a user tested positive or negative was included. To avoid extreme high or low weights, the fitted probabilities were trimmed to be between 0.1 and 0.9 or 0.05 and 0.95. The results of both models are available in Supplementary Table 10 .

Vaccine uptake

An unweighted multivariable logistic regression model was fit to identify which demographic features were associated with accepting or rejecting a COVID-19 vaccine. Along with the covariates included in the vaccine intent model, the three-level vaccine acceptance variable (“Very Likely/Likely”, “Undecided”, “Very Unlikely/Unlikely”) was also included in the analysis. Results are available in Supplementary Table 12 (left). To account for the biased sampling, non-response bias, and demographic differences in being offered a vaccine, a weighted multivariable model was fit. First, a weighted multivariable logistic regression model was fit for the probability of an individual responding to the vaccine uptake question with the inclusion of post-stratification weights as was done in the weighted vaccine acceptance model (Supplementary Table 11 A). The fitted probabilities from this model were then used as inverse probability weights to model the probability of a user being offered a vaccine (Supplementary Table 11 B). A user was defined as being offered a vaccine if the user responded to the question “Have you received a COVID-19 vaccine?” with “Yes,” or “No, I have been offered one but declined,” compared to users responding “No, I have not been offered a vaccine.” The fitted probabilities from this model were multiplied by the fitted probabilities from the response model and used as inverse probability weights in a final model which models the probability of accepting or rejecting the vaccine. The coefficients, 95% confidence intervals, and p -values for the final weighted model are available in Supplementary Table 12 . To more formally characterize the attributes associated with vaccine uptake within users that responded as vaccine reluctant, we fit a weighted multivariable logistic regression model subset to only the users who initially responded they were “Very Unlikely” or “Unlikely” to receive a COVID-19 vaccine. Models were fit identically to the above weighted models for all users and results of the final model are available in Supplementary Table 13 .

Ethics statement

Data was obtained from the non-profit organization the How We Feel Project which obtained a commercial IRB approval for the collection of the data. Due to receiving a deidentified dataset, the analysis in this paper was exempt from Institutional Review Board (IRB) approval by Harvard University Longwood Medical Area (HULC) IRB (HULC IRB Protocol No. IRB20-0514) and the Broad Institute of MIT and Harvard IRB (Broad/Harvard IRB Protocol no. EX-1653). When downloading the application, users were informed that their data would be shared securely with scientists, doctors, and public health professionals to stop the spread of COVID-19 and provided informd consent.

Data availability

This work used data from the How We Feel project. The data are not publicly available, but researchers can apply to use the resource. Researchers with an appropriate IRB approval and data security approval to perform research involving human subjects using the How We Feel data can apply to obtain access to data used in the analysis.

Code availability

The analysis code developed for this paper can be found online at https://github.com/mccabes292/HWF_VaccineHes_Paper .

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Acknowledgements

S.D.M. was supported by the United States National Institutes of Health [Grant T32ES007069] and a grant from the Partners in Health during preparation and writing of this manuscript. E.A.H. was supported by the United States National Institutes of Health [Grant T32A1007524] during preparation and writing of this manuscript. X.L. is supported by a grant from the Partners in Health. D.S. is supported by United States National Institutes of Health [Grant T32GM135117]. F.Z. is supported by the Howard Hughes Medical Institute, the McGovern Foundation, and J. and P. Poitras and the Poitras Center. The How We Feel Project is a non-profit corporation. The How We Feel Project thanks many operational volunteers and the HWF participants who took our survey and allowed us to share our analysis. Funding and in-kind donations for the How We Feel Project came from B. and D. Silbermann, F. Zhang and Y. Shi, L. Harp McGovern, D. Cheng, A. Azhir, K.H. Yoon and the Bill & Melinda Gates Foundation.

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These authors contributed equally: Sean D. McCabe and E. Adrianne Hammershaimb.

Authors and Affiliations

The How We Feel Project, San Leandro, CA, USA

Sean D. McCabe, E. Adrianne Hammershaimb, David Cheng, Andy Shi, Derek Shyr, Shuting Shen, William Allen, Ryan Probasco, Ben Silbermann, Feng Zhang, Mark A. Travassos & Xihong Lin

Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA

Sean D. McCabe, Andy Shi, Derek Shyr, Shuting Shen & Xihong Lin

Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA

E. Adrianne Hammershaimb & Mark A. Travassos

Department of Pediatrics, University of Maryland School of Medicine, Baltimore, MD, USA

Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, USA

Lyndsey D. Cole & Jessica R. Cataldi

Adult and Child Consortium for Health Outcomes Research and Delivery Science, University of Colorado Anschutz Medical Campus and Children’s Hospital Colorado, Aurora, CO, USA

Jessica R. Cataldi

Harvard University, Cambridge, MA, USA

William Allen

Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA

Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

Howard Hughes Medical Institute, Chevy Chase, MD, USA

Department of Emergency Medicine, Brigham and Women’s Hospital, Boston, MA, USA

Regan Marsh

Department of Emergency Medicine, Harvard Medical School, Boston, MA, USA

Partners in Health, Boston, MA, USA

Broad Institute of MIT and Harvard, Cambridge, MA, USA

Department of Statistics, Harvard University, Cambridge, MA, USA

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Contributions

E.A.H. and S.D.M. initiated the project. S.D.M. led data analysis and figure production. S.D.M., D. S. and S. S. cleaned the data. E.A.H., and A.S. contributed to analysis. R. M. provided feedback on analysis. S.D.M. and E.A.H. wrote the manuscript with M.T. and X.L. D. C., W. A., R.P., B.S., F. Z., X. L. designed and implemented the How We Feel application. E.A.H., L.D.C., J.R.C., and R.M. developed the vaccine reluctance and uptake instrument. M.T. and X.L. supervised all aspects of the work.

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Correspondence to Mark A. Travassos or Xihong Lin .

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McCabe, S.D., Hammershaimb, E.A., Cheng, D. et al. Unraveling attributes of COVID-19 vaccine acceptance and uptake in the U.S.: a large nationwide study. Sci Rep 13 , 8360 (2023). https://doi.org/10.1038/s41598-023-34340-3

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Social science and the COVID-19 vaccines

As COVID-19 vaccines become available to wider segments of the population, psychological science will play a key role in ensuring everyone can benefit

Vol. 52 No. 2 Print version: page 36

Health and Behavior

Psychological science will be at the forefront of combating vaccine hesitancy brought on by misinformation now that several vaccines have proven to be safe and effective against COVID-19.

Right now, more people want a vaccine than can get one, due to low supply. But as a long pandemic winter eases into spring and summer, it will be important to ensure that everyone who could benefit from the vaccine actually rolls up their sleeve to get it. The politicization of COVID-19, messaging about masks, and the mental health impact of social distancing have all made clear how important psychology is during a pandemic. Vaccination is no different.

Psychologists will play an important role in ensuring vaccine uptake by determining the best way to fight back against misinformation, along with smoothing logistics and communicating benefits and risks.

“It doesn’t matter how great your biomedical innovation is, if people aren’t convinced to use that innovation, then the innovation has no impact at all,” says Gregory Zimet, PhD, a clinical psychologist at the Indiana University School of Medicine who studies vaccine decision-making.

Vaccine uptake

Psychologists have been tracking vaccination attitudes since spring 2020, trying to understand who is hesitant to receive a COVID-19 vaccine and why. National surveys painted a promising picture as the vaccine rollout began: After a low point of only 50% of Americans saying they were willing to be vaccinated in September, 63% expressed willingness in a national poll taken in late November ( Gallup, 2020 ). Gallup researchers speculated that reports of side effects in the AstraZeneca vaccine trials and fears of a politically driven approval process were the reason for the September slump. A Henry J. Kaiser Family Foundation survey taken in December put willingness to be vaccinated at 71% ( KFF COVID-19 Vaccine Monitor, 2020 ), also up from September’s numbers.

However, research also suggests that acceptance is unevenly distributed. Kaiser’s ongoing COVID-19 Vaccine Monitor project finds consistent gaps between groups. Those most likely to be hesitant are Republicans, people ages 30 to 49, rural Americans, and Black Americans. Those most likely to be enthusiastic are Democrats, people over 65, the college-educated, and those with major health issues. Reasons for hesitancy vary among these groups, with Republicans less likely to believe COVID-19 is a risk than other hesitant groups, and hesitant Black Americans more worried that the vaccine might have dangerous side effects or give them COVID-19.

It’s not clear how many people need to be vaccinated to achieve community immunity, in which the coronavirus pandemic fizzles out because the virus can’t find vulnerable hosts. National Institute of Allergy and Infectious Diseases director Anthony Fauci, MD, gave a range of 70% to 85% in December. But if some groups are less likely to be vaccinated than others, pockets of vulnerability could still persist even if overall acceptance is high. Thus, vaccine acceptance is an important part of equity in the fight against COVID-19.

Vaccine communication

Psychologists and other behavioral scientists are working to inform the communication efforts around the vaccine. A recent report from the National Academies of Sciences, Engineering, and Medicine on equitable vaccination allocation calls for drawing on the established research in risk communication to drive outreach ( NASEM Framework for Equitable Allocation of COVID-19 Vaccine, 2020 ). The National Institutes of Health also released a report in December calling for evidence-based strategies, including tailored messaging and framing vaccination as a beneficial, apolitical decision ( COVID-19 Vaccination Communication: Applying Behavioral and Social Science to Address Vaccine Hesitancy and Foster Vaccine Confidence, 2020 ). “It shouldn’t be amateur hour with the stakes so high,” says Baruch Fischhoff, PhD, a psychologist at Carnegie Mellon University and a member of the committee which wrote the report. “We should rely on psychological science, not intuition about what people think.”

For example, many of the vaccine-eager may be tempted to shame those who have questions or are hesitant. But research shows that positive emotional messages, such as altruism and hope, are more effective than negative ones in encouraging vaccination ( Chou, W. S., & Budenz, A., Health Communication, Vol. 35, No. 14, 2020 ).

It’s also important to know that the Mayo clinic notes that people with certain health conditions are not currently advised to get the vaccine and encourages people to talk to their health care provider if they have questions. Psychologists need to be sensitive to those who are desperate for the relief of a vaccine but aren’t medically advised to receive one.

Many who are hesitant to get vaccinated have deeply personal reasons to feel that way. Mistrust of the medical community among Black Americans, for example, is often rooted in historical events such as the Tuskegee Syphilis Study, in which the United States Public Health Service misled and withheld treatment for syphilis from poor Black men between 1932 and 1972. Personal experiences with racism may also foster mistrust; a Kaiser Family Foundation survey in 2020 found that 20% of Black Americans reported personally experiencing racism while seeking health care in the previous 12 months ( KFF Survey on Race and Health, October 2020 ).

Tailoring messaging to specific communities is thus very important, Fischhoff says. For historically marginalized communities, it’s particularly crucial to open up two-way lines of communication, he says. One way to do this might be to leverage the power of professional organizations such as APA and the American Public Health Association, which have members in diverse communities all over the country. “They can get the word out and listen to what’s on people’s minds, and they can also get the content and tone right in a way that somebody sitting at a major advertising agency just can’t do,” Fischhoff says.

Some collaborations already exist. The Johns Hopkins Bloomberg School of Public Health Center for Health Security is addressing vaccine equity and hesitancy with five multidisciplinary local teams in Alabama, southern California, Idaho, Baltimore, and Prince George’s County, Maryland. Neil Lewis Jr., PhD, a social psychologist at Cornell University, is working with a multidisciplinary group to help the New York City health department respond to questions that people ask the doctors administering the COVID-19 vaccine. Often, these concerns contain a kernel of truth, Lewis says. After all, early in the pandemic, experts warned the public that safe vaccines take years to develop. It’s not surprising, then, that people have worries about the safety of a vaccine developed in less than a year. “People have concerns,” Lewis says, “and we have to acknowledge that those are legitimate concerns, let them ask their questions, and respond to them.”

The CDC’s Vaccine Adverse Event Reporting System gives a sense of the types of adverse reactions reported, ranging from benign and expected (headache, soreness) to serious (anaphylactic shock and heart attack). However, psychologists using this data should be aware that anyone can enter a report, and the system is not designed to show that an event was caused by the vaccine.

Personal experience may also be a powerful tool for vaccine communication. Many doctors and nurses—especially doctors and nurses of color—have been sharing their own vaccine experiences on social media, including any common side effects they may experience. “The slow rollout might end up having this unintended benefit of creating enough time that the broader public can see that yes, the vaccine is working, the people who are getting it are doing well, so that could help to increase trust in it over time,” Lewis says.

For those who are strongly opposed to vaccines based on emotion or ideology, the messaging is more difficult—but not impossible. These strong anti-vax, anti-mask attitudes appear driven by a phenomenon called psychological reactance, says Steven Taylor, PhD, a clinical psychologist at the University of British Columbia in Canada, which is a motivational state driven by the feeling that someone is trying to curtail one’s freedom. For this group, any messaging suggesting that authorities want people to get vaccinated is aversive. Instead, Taylor says, it’s best not to frame vaccination as an obligation. “The best message could be, ‘Getting vaccinated is a right you have, don’t let people take that away from you,’” he says. “That’s not a disingenuous message; it’s an accurate one.”

Intent versus action

Even among the willing, vaccination intent does not equal vaccination behavior. There are many people who are not ideologically against vaccines who still don’t get around to getting their annual flu shot. With COVID-19 case rates high this winter, motivation to get the vaccine is also high for many. As spring and summer begin, case numbers and deaths may begin to decline due to virus seasonality and the vaccination of high-risk individuals. With the danger less immediate, people may be less motivated to make vaccination appointments, says Gretchen Chapman, PhD, a professor of social and decision sciences at Carnegie Mellon University.

Another complication is that the Pfizer and Moderna vaccines require two doses, administered three or four weeks apart, to be most effective. Getting people to come in for the second dose at the right time is a separate problem from getting them to come in for the first dose, Chapman says: “In the first round, you’ll take whoever shows up, but in the second round you need the exact people who were there the first time, exactly 3 weeks later.”

However, while intervening to change people’s vaccination beliefs can be difficult, there are proven methods for changing vaccine behavior, Chapman says. These include reminders, automatically scheduled appointments, and strategies to make logistics for the patient as seamless as possible. Health systems or pharmacy chains could capitalize on winter’s vaccine enthusiasm by having people sign up to be notified when vaccines are available for their risk group, Chapman says. People may also need paid time off from work to get the vaccine and recover from mild side effects, including localized and temporary pain, swelling or redness at the injection site, Lewis says. “If people don’t have the time or have other logistical hurdles in the way, we’re in trouble,” he says.

Behavioral science can help smooth the logistics of vaccination for underserved populations. University of California, Los Angeles, psychologist Vickie Mays, PhD, has developed a model of neighborhood vulnerability to COVID-19 in Los Angeles County, based on indicators like pre-existing health conditions of residents and social exposure to the virus ( Brite Center, 2020 ). Similar models could be used across the country to open vaccination sites and focus outreach for the most vulnerable.

Natural incentives may also encourage vaccination even among people who are not worried about the coronavirus and their own health. Incentives might include airlines requiring proof of vaccination for international travel, or sports venues requiring proof of vaccination for entry to events, Chapman says. However, such incentives might also deepen inequities for groups who are less able to access the vaccine. Direct monetary incentives are likely to backfire. Research led by psychologist and marketing professor Cynthia Cryder, PhD, of Washington University in St. Louis, found that paying people to participate in potentially risky research studies made the participants believe that the studies were more risky than if they weren’t paid ( Social Science & Medicine, Vol. 70, No. 3, 2010 ). The money “conveys that this is a risky thing that you don’t want to do unless we’re paying you,” Chapman says.

Such results highlight the importance of field studies going forward during the COVID-19 vaccine deployment, she says. Interventions need to be tested in a real-world context. At the Behavior Change for Good Initiative at the University of Pennsylvania, economist Katy Milkman, PhD, and colleagues have tested nearly two dozen text message reminder strategies for flu vaccinations with real patients at health systems and customers at Walmart pharmacies. Preliminary results from doctors’ offices, currently being prepared for publication, suggest that a variety of messages can boost vaccination, with 21% of messages tested significantly boosting vaccination rates. The most successful, a two-part reminder that told patients that a flu vaccine had been reserved for them at their upcoming well-check visit, boosted vaccination 10% at essentially zero cost, Milkman said in a Jan. 6 webinar hosted by the Science of Behavior Change Research Network . Milkman and her colleagues plan to release results from more than 500,000 Walmart pharmacy customers in late January.

Building the knowledge and capacity to enact COVID-19 vaccination will pay off long after the pandemic is over, Taylor says. “Now, having lived it, we all know how important psychology is,” he says. “We need to keep these platforms up and running. We shouldn’t dismantle them after the pandemic is over, because they’re going to be important for preparing for the next pandemic.”

Hesitancy by the numbers

In late November and early December, 27% of respondents to a Kaiser Family Foundation Health poll on the COVID-19 vaccine said they probably or definitely would not be vaccinated. Among groups more hesitant than average, the percent who said they probably or definitely wouldn’t get the vaccine were as follows:

Republicans: 42%
Ages 30–49: 36%
Rural residents: 35%
Black adults: 35%
Essential workers: 33%
Independents: 31%
Health care workers: 29%
Ages 18–29: 28%

The main concerns among the 27% who did not want to be vaccinated were:

Worries about possible side effects (59% total, but 71% among hesitant Black adults)
Distrust in government to make sure vaccine is safe and effective (55%)
Vaccine too new, want to wait and see how it works for others (53%)
Politics has played too large of a role in vaccine development (51%)
Risk of COVID-19 is exaggerated (43% total, but 57% among hesitant Republicans)

Source: KFF COVID-19 Vaccine Monitor (KFF Health Tracking Poll, Nov. 30–Dec. 8, 2020).

A Top Vaccine Expert Answers Important Questions About a COVID-19 Vaccine

The covid-19 vaccine is on track to become the fastest-developed vaccine in history. that doesn’t mean the process is skipping any critical steps..

Understanding what we know—and still don’t—about a vaccine for COVID-19 can help shed light on its safety and efficacy.

Ruth Karron, MD , is one of the top vaccine experts in the world, serving on vaccine committees for the CDC, the WHO, and the FDA. Karron, who leads the Center for Immunization Research at the Johns Hopkins Bloomberg School of Public Health, recently spoke with Josh Sharfstein and answered a list of important questions about the COVID-19 vaccine.

How close are we to a vaccine?

There are some very encouraging developments. We have a few vaccines now that will go into Phase 3 clinical trials, also known as efficacy trials. That means that those vaccines have passed certain goalposts in terms of initial evaluations of safety and immune response such that they can be evaluated in larger trials.

We know that these vaccines are promising, but we don’t yet know if they are going to work. That’s what the purpose of an efficacy trial is—as well as to provide a broader assessment of safety of the vaccine in a large number of people.

Tell me more about these efficacy trials. What do they actually entail?

They involve large numbers of people: In these particular trials for COVID vaccines, there are going to be about 30,000 people enrolled per trial. Individuals are given a vaccine, and then they are followed both to make sure that the side effects from the vaccine are acceptable and to see whether they develop a SARS-CoV-2 infection along with some symptoms.

These are placebo-controlled trials, meaning that some individuals will get a COVID vaccine and some will get a placebo. Then, the rates of disease will be compared in the people who got placebo and the people who got the vaccine to determine the efficacy of the vaccine.

How successful does a vaccine have to be in one of these studies for it to be considered effective?

Recently, the FDA issued guidance about the development of COVID vaccines. The guidance that they issued to vaccine manufacturers— this is a document that is available to the general public —is that a vaccine would need to be at least 50% effective. This means that an individual who was vaccinated would be 50% less likely to get COVID disease—or whatever the particular endpoint is that’s measured in the trial—than individuals that weren’t vaccinated.

This is a reasonable goal for a number of reasons. Typically, the more severe a disease is, the better chance a vaccine has of preventing that disease. So, a vaccine that’s 50% effective against mild COVID disease—which might be the endpoint that’s measured in a clinical trial, or any evidence of COVID infection with any symptom, which is how a lot of trials are designed—might be more effective against severe disease.

When you have a disease that’s as prevalent as COVID—and if we think about what the U.S. has experienced in the past several months in terms of severe disease and death—even if we were only able to cut those numbers in half, that would be a major achievement.

How long would a vaccine be effective for? If you get 50% effectiveness or more, that’s good news. But if it’s only effective for a few months, that’s not such good news.

Time will tell for that. The short answer is that we don’t yet know. Even for the data we have on the vaccine so far in smaller studies, we haven’t yet had the opportunity to follow individuals for very long. The very first people who got the very first vaccine were immunized in March and it’s only July. So, we don’t know very much about the durability of the immune response in people.

Our hope would be [that protection would last] at least a year or more and then people might need boosters.

It’s also possible that a vaccine might not entirely protect against mild disease. So you might actually experience mild disease and then have a boost in your immune response and not suffer severe disease. From a public health perspective, that would be completely acceptable. If we turned a severe disease not into “ no disease ” but into mild disease, that would be a real victory.

Let’s talk about safety. What are they looking for in a 30,000-person study to figure out whether a vaccine is considered safe enough to use?

Every person who is enrolled in the trial will complete information about the kinds of acute symptoms that you might expect following an infection. People will need to provide information about swelling, redness, tenderness around the injection site, fever, and any other symptoms they might experience in the three to seven days following vaccination.

More long term, people will be looking to make sure that when COVID disease is experienced, there’s not any evidence of more severe disease with vaccination [which is known as disease enhancement].

There was a lot of discussion as these vaccines were being developed of a concern about disease enhancement. This is based on some animal models—not with SARS-CoV-2 but with other coronaviruses. We haven’t seen any evidence of enhanced disease thus far and there are a number of scientific reasons why we don’t think it should occur with these vaccines. But, of course, it’s something we would still watch for very carefully just as with any other safety signal.

How should we think about the possibility of adverse effects that might come up after the period of the vaccine trial?

There are a couple of things to mention about that, and one is that individuals with these trials will be followed for a year or longer. It may be that a vaccine is either approved for emergency use or licensed before all of that long-term follow up is completed. Nevertheless, companies will be obligated to complete that follow up and report those results back to the FDA.

It’s important to enroll older adults in these studies. All of these large efficacy trials will be stratified so there will be some younger adults and some older adults enrolled.

In addition, it’s very likely—and this would not just happen with COVID vaccines, but whenever the FDA licenses vaccines—that there is an obligation for post-licensure assessments. If a COVID vaccine is licensed, the companies will work with the FDA to determine exactly what kind of post-licensure safety assessments will need to be done.

COVID affects certain populations more than others—particularly older adults and people with chronic illnesses. What do these studies need [in order] to address the question of whether a vaccine will be protective for them?

I also think it will be important to enroll older adults across an age span. A 65-year-old is not the same as an 85-year-old. Also, a healthy older adult is not the same as a frail older adult who might be living in a care facility.

We’ll need some information about diverse elderly populations in order to think about how to allocate vaccines. There may also be other alternatives for older adults if they don’t respond well to vaccines. There’s a lot of work going on on development of monoclonal antibodies [ learn more about lab-produced antibodies in a recent podcast episode with Arturo Casadevall ] as an alternative for groups that don’t respond well to vaccines such as elderly, frail adults.

Let’s say there are 30,000 patients in the study and only a few hundred who are over 80 years old. What can you learn about a relatively small population of much older adults that would be informative about that group?

We may not have a large enough number of people in that subgroup to directly look at efficacy of a vaccine. But we might have enough to look at the immune response—the antibody response, for example, of a vaccine.

If, in the course of these trials, we can determine a correlative protection—for example, a laboratory measure like a level of a particular kind of antibody that correlates with protection against COVID disease—we can at least look at the immune responses in that subset of very elderly and decide if they are the same or different than the younger groups’. If they are the same, we may be more comfortable making the leap to say that it’s likely those individuals will also be protected by the vaccine.

So, we will learn more from a vaccine trial than just whether or not a vaccine works. We’re going to find out, perhaps, what predicts whether the vaccine works. That information might help us understand—without having to do a whole new trial—who might be protected by a vaccine.

It’s certainly a hope.

The majority of vaccines that we use today don’t have such a marker of protection and they’re very effective. Just because we can’t detect a marker doesn’t mean that a vaccine is not effective. It means that we’re not smart enough to figure out what that marker should be.

We really hope that there will be such a marker of protection because then we can link that—and, in FDA speak, that’s called “bridging”—to another population where we can just look at that marker of immunity rather than doing a whole efficacy trial.

How should we think about the need for racial and ethnic diversity in these clinical trials?

It’s critically important that we have racial and ethnic diversity.

We know that COVID causes increased rates of severe disease in Latinx and Black populations and in Native American populations. We will certainly want to be able to offer these COVID vaccines to these high-risk populations and encourage their use. But we need to know how well these vaccines work in these populations—if different vaccines work differently—so that we can offer the most effective vaccines.

It would not be an understatement to say that there can be a measure of distrust from some communities that have experienced discrimination from the health care system. How does that play into vaccine research?

It’s really important to engage those communities in a number of ways. One way is to engage local leaders early in the process. Lay leaders and leaders of faith communities can have focus groups to find out what their concerns are and how those can be allayed.

I think a very important issue that has been raised by some people who might potentially volunteer for some of these trials has to do with eventual access. People want to have some sense that if they participate in a trial, not only might they have access to the vaccine at the end of that trial, but their families and their communities would, too. Ensuring access among these high risk and vulnerable communities is really critical.

A clear policy decision to make sure that a vaccine is widely available without charge might actually help with the studies to prove whether or not that vaccine is safe and effective?

That’s absolutely the case. It’s great that you brought up the “without charge” piece, too, because a vaccine that’s made available but costs something to the individual may not be used. Particularly for people who don’t have health insurance or people who are undocumented. It has to be broadly and freely available.

Let’s talk about other specific populations. One of those is pregnant women. We know that they can certainly get COVID-19 and that there are some signs that they can have a more severe course. How do you think about the issue of pregnant women in vaccine studies?

I’ve done some work in this area —particularly with Ruth Faden and Carleigh Krubiner in the Berman Institute of Bioethics —specifically related to ensuring that pregnant women are considered and included in vaccine development and implementation for vaccines against epidemic and pandemic diseases.

When thinking about trials, there needs to be a justification for excluding pregnant women from trials rather than a justification for including them. The justification often is—and certainly is the case with these early COVID vaccines—that we don’t know enough yet about the vaccine or the vaccine platform or the safety of the vaccine to do a study in pregnant people.

With the mRNA vaccine, for example, [the type of vaccine being considered for COVID-19] we don’t currently have a licensed mRNA vaccine. It’s a new platform and we’re just learning about the safety of that platform so it wouldn’t have been appropriate to include pregnant women in the early stage trials.

But these 30,000-person studies are going to be really big studies. They will certainly enroll people of child-bearing potential. And even though there’s what we call an exclusion criterion—women are not supposed to be pregnant at the time they are enrolled, and usually women of child-bearing potential will take a pregnancy test prior to enrollment and immunization—we know from previous experience that it’s quite likely that some women will become pregnant in the months immediately following immunization. It happens quite frequently. So, it’s important for companies and the government to anticipate that this will be the case and to think about how they will systematically collect data from women who do become pregnant during these trials.

It’s not that the data needs to be interpreted cautiously—because pregnant women aren’t being formally randomized and we don’t have that kind of trial design—but there are things that could be learned and it’s important to think now about how to collect those data. It’s also important to think about how pregnant women could be directly included in both trials and deployment later down the road.

What about young children who are less likely to get severe disease? Would your approach to clinical trials be different?

Yes. I think we need to learn a bit more about the epidemiology in children. Fortunately, children don’t seem to suffer from acute COVID disease at the rates that adults do. But we need to learn more about that and we also need to learn from our trials in adults before we make decisions about how and whether children will be included in vaccine trials.

Once we have a vaccine that has made it through these various stages and we’re ready to start immunizing people outside of a pure clinical trial, how close are we to really getting the benefit of the vaccine? How does all the work it takes to develop a vaccine compare to what comes next?

The best vaccine in the world won’t work if it isn’t used.

Use has two parts to it: One is availability and access, and the other part is acceptance.

We need to think about what kind of infrastructure we should be planning now for what we’re going to need to deliver this vaccine. We’ll set priorities; certainly not everyone is going to get a vaccine all at once. But certainly, over time we will expect that all adults will receive the vaccine and perhaps children. So we’ll need to have systems in place that can deliver the vaccine. At the same time, we need to make sure that the vaccine is acceptable. We need to communicate the importance of vaccination to the public and address their concerns so that we can not only be able to deliver vaccines, but have those be accepted by the public.

So, there’s a lot of work to be done. But this isn’t science fiction: We are really on a path to a vaccine for a brand new infectious disease.

Yes. If you think back to the fact that in January, we barely knew what this virus was, and here we are, seven months later, embarking on efficacy trials, it’s really a remarkable accomplishment. We have a lot to do yet, but in the time that we’re assessing the efficacy of these vaccines and making sure that they can be delivered to the public, people really need to stay safe and to do all the things we’ve been encouraging them to do all along.

But we are well on our way to developing vaccines not only for people in the U.S., but for people all over the world.

Public Health On Call

This conversation is excerpted from the July 31 episode of Public Health On Call.

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Joint CDC and FDA Statement on Johnson & Johnson COVID-19 Vaccine

FDA Statement

The following statement is attributed to Dr. Peter Marks, director of the FDA’s Center for Biologics Evaluation and Research and Dr. Anne Schuchat, Principal Deputy Director of the CDC

As of April 12, more than 6.8 million doses of the Johnson & Johnson (Janssen) vaccine have been administered in the U.S. CDC and FDA are reviewing data involving six reported U.S. cases of a rare and severe type of blood clot in individuals after receiving the J&J vaccine. In these cases, a type of blood clot called cerebral venous sinus thrombosis (CVST) was seen in combination with low levels of blood platelets (thrombocytopenia). All six cases occurred among women between the ages of 18 and 48, and symptoms occurred 6 to 13 days after vaccination. Treatment of this specific type of blood clot is different from the treatment that might typically be administered. Usually, an anticoagulant drug called heparin is used to treat blood clots. In this setting, administration of heparin may be dangerous, and alternative treatments need to be given.

CDC will convene a meeting of the Advisory Committee on Immunization Practices (ACIP) on Wednesday to further review these cases and assess their potential significance. FDA will review that analysis as it also investigates these cases. Until that process is complete, we are recommending a pause in the use of this vaccine out of an abundance of caution. This is important, in part, to ensure that the health care provider community is aware of the potential for these adverse events and can plan for proper recognition and management due to the unique treatment required with this type of blood clot.

Right now, these adverse events appear to be extremely rare. COVID-19 vaccine safety is a top priority for the federal government, and we take all reports of health problems following COVID-19 vaccination very seriously. People who have received the J&J vaccine who develop severe headache, abdominal pain, leg pain, or shortness of breath within three weeks after vaccination should contact their health care provider. Health care providers are asked to report adverse events to the Vaccine Adverse Event Reporting System at https://vaers.hhs.gov/reportevent.html .

CDC and FDA will provide additional information and answer questions later today at a media briefing. A recording of that media call is available on the FDA’s YouTube channel.

The FDA, an agency within the U.S. Department of Health and Human Services, protects the public health by assuring the safety, effectiveness, and security of human and veterinary drugs, vaccines and other biological products for human use, and medical devices. The agency also is responsible for the safety and security of our nation’s food supply, cosmetics, dietary supplements, products that give off electronic radiation, and for regulating tobacco products.

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http://orcid.org/0000-0002-9077-1436 Cephas Sialubanje 1 ,
http://orcid.org/0000-0003-2360-2752 Nawa Mukumbuta 1 , 2 ,
Mary Ng'andu 3 ,
Ernest Malangizo Sumani 2 ,
Mpala Nkonkomalimba 2 , 4 ,
Daniel EM Lyatumba 2 ,
Alick Mwale 2 ,
Francis Mpiana 2 ,
Joseph Makadani Zulu 2 ,
Basil Mweempwa 5 ,
Denise Endres 5 ,
Maurice Mbolela 4 ,
Mpatanji Namumba 4 ,
Wolff-Christian Peters 5
1 School of Public Health , Levy Mwanawasa Medical University , Lusaka , Zambia
2 COVID-19 Advisory Centre for Local Authorities , Local Gover Government of Association of Zambia , Lusaka , Zambia
3 Health Sciences , Levy Mwanawasa Medical University , Lusaka , Zambia
4 Administrative unit , Local Government Association of Zambia , Lusaka , Zambia
5 Decentralisation for Development (D4D), Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH /German Cooperation , Lusaka , Zambia
Correspondence to Dr Cephas Sialubanje; csialubanje{at}yahoo.com

Objective Since introduction of the programme in April 2021, COVID-19 vaccine uptake has been low at less than 20%. This study explored community members’ and health workers’ perspectives on the COVID-19 vaccine uptake and its influencing factors in Zambia.

Study design A qualitative study employing focus group discussions (FGDs) and in-depth interviews (IDIs).

Study setting Sixteen primary healthcare facilities selected from Lusaka, Copperbelt, Central and Southern provinces.

Participants A total of 32 FGDs comprising local community members and 30 IDIs including health workers, traditional, religious and civic leaders (n=272). FGDs were separated based on age (youth and adults), sex (male and female) and place of residence (urban and rural).

Results Both FGD and IDI participants agreed that vaccine uptake was low. Limited knowledge, access to information, myths and misconceptions, negative attitude, low-risk perception and supply in remote areas affected vaccine uptake. Overall, FGD participants expressed limited knowledge about the COVID-19 vaccine compared with health workers. Further, FGD participants from urban sites were more aware about the vaccine than those from rural areas. Health workers perceived the vaccine to be beneficial; the benefits included prevention of infection and limiting the severity of the disease. Moreover, FGD participants from urban sites expressed a negative attitude towards the vaccine. They believed the vaccine conferred no benefits. By contrast, participants from rural communities had mixed views; they needed more information about the vaccine benefits. Participants’ attitude seems to have been influenced by personal or family experience with the COVID-19 disease or vaccination; those who had experienced the disease had a more positive attitude. In contrast, most young people believed they were not at risk of the COVID-19 disease. Misinformation from social media influenced their attitude.

Conclusion These results provide starting points for future policies and interventions for increasing COVID-19 vaccine uptake.

public health
primary care
qualitative research

Data availability statement

Data are available on reasonable request. Data are available on reasonable request from the corresponding author and with permission of the UNZABREC Institutional review board.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2021-058028

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STRENGTHS AND LIMITATIONS OF THIS STUDY

Purposive sampling of participants comprising health workers and community members with different demographic and socioeconomic characteristics (sex: male and female; age; place and province of residence: urban and rural settings) allows for comparing and contrasting of participant views, which in turn provides an in-depth understanding of the subject under investigation.

Use of different data collection techniques (focus group discussions and in-depth interviews) as well as data sources allow for triangulation of findings and increases internal validity of the study.

Training data collectors and use of an inductive approach to data analysis increase the internal validity of study findings.

Conducting the study at the beginning of the COVID-19 national mass vaccination when the programme was still new in the country may have affected the views of the participants.

Use of the qualitative design affects external validity and limits generalisation of the study findings.

Introduction

SARS-CoV-2 has spread to most parts of the world, including Zambia. 1 2 As at the end of August, 2022, a total of 332, 058 cases and 4016 deaths had been reported in the country. 3 To prevent further spread of the virus and increased mortality in the country, the Zambian government enacted the public health statutory instrument number 22, 4 5 which instituted preventive and control measures—restricting social gatherings (ie, work places, church services, weddings, kitchen parties, casinos, funerals), local and international travel, and closing public institutions such as schools and markets. 6 In addition, the Zambian government implemented a national mass vaccination campaign 7 following approval of the COVID-19 vaccines in developed countries. 8–10 Initially, the COVID-19 national vaccination programme targeted the health workers and persons aged above 65 years. 10 The criteria were later revised to include all persons aged 18 years and above. 10 A second revision was made to include children aged 10 years and above. Three types of COVID-19 vaccines have been administered: Oxford/AstraZeneca, Sinopharm, John and Johnson and Pfizer vaccines. Access to the COVID-19 vaccine is voluntary and free in the country; people do not need to pay anything. 11 To be protected, one needs to receive two doses of the Oxford/AstraZeneca vaccine−8 weeks apart. On the contrary, only one dose of Johnson & Johnson vaccine is needed to be fully immunised. 12 13

Over the centuries, vaccines have been shown to be an effective way to combat outbreaks and the only efficient and reliable method for disease prevention. 14 15 COVID-19 vaccines—with an efficacy ranging from 70% to 95%, have been shown to provide protection against the virus 15 by preventing its spread in the community, mitigating the severity of the disease and reducing mortality among the infected people. 16 17 Studies and ongoing clinical trials 18–22 have shown that COVID-19 vaccines offer the best means to control the ongoing pandemic. They are effective in preventing a wide range of COVID-19-related outcomes, reduce symptomatic cases, hospitalisation, disease severity and death among the infected individuals. Nevertheless, national reports show that the vaccine uptake has been low in the country. At the end of August 2022, a total of 5 576 827 have been fully vaccinated with the AstraZeneca, Sinopharm and Johnson & Johnson vaccine since the commencement of the programme in April 2021. This represents a national vaccine coverage of 52.9% of the eligible population. 23

Limited supply and vaccine hesitance—the delay in acceptance or refusal of vaccination despite availability of vaccination services 24 —have been attributed to the low vaccine coverage in the country. Vaccine hesitance has been reported both in Zambia and other countries, and has been shown to be an important obstacle to the fight against COVID-19. 25–27 For example, in their recently published article, Mutombo et al 28 observed that the gradual effort to distribute COVID-19 vaccines to low-income and middle-income countries (LMICs) is threatened by the ubiquitous vaccine hesitancy, especially in Africa, where it undermines efforts to fight the COVID-19 pandemic. A qualitative study 29 using focus group discussions (FGDs) with mothers who brought their children for measles vaccination in southern Zambia a few months before the COVID-19 national vaccination programme was implemented, reported that, although parents were willing to allow their children to receive the vaccine, majority expressed substantial uncertainty and hesitancy about receiving the vaccine themselves. The study also revealed beliefs around COVID-19 risk and severity, as well as vaccine safety and effectiveness affected the participants’ intention to be vaccinated. However, vaccine hesitance is not peculiar to the COVID-19 vaccine. For example, Garcia and others 30 reported low levels of Cholera vaccine acceptance among community members and health workers in the slums of Lusaka, Zambia. The authors also showed that religious beliefs and distrust towards western medicine, fear of injections and adverse events, low perceived need for immunisation and limited understanding of how vaccines work were important factors affecting acceptance of the cholera vaccine.

Although these studies provided important insights on vaccine hesitance and its contributing factors, most were conducted outside the country. The one conducted in Zambia explored mothers’ intentions to receive the COVID-19 vaccine and not the actual behaviour. Moreover, the study was conducted before the COVID-19 was implemented. The other Zambian study focused on the Cholera vaccine. It thus, not clear how the Zambian population perceive the COVID-19 vaccination programme. Available evidence suggests that vaccine hesitance is complex and context specific, varying across time, place and vaccines. A study is therefore needed to explore people’s perspectives and attitude towards COVID-19 vaccine uptake in the country. The aim of this study, therefore, was to explore community members’ and health workers’ perspectives on the COVID-19 vaccine uptake and the reasons that affect its uptake in Zambia. This information can provide insight to the COVID-19 vaccine hesitancy and the contributing factors, which in turn, can inform design of interventions to increase vaccine intentions and uptake in the general population. To date, no such study has been conducted in Zambia.

Study design

This study employed a qualitative design comprising FGDs and in-depth interviews (IDIs) as the data collection techniques. FGDs have been used in public health research for over three decades now. 31 They aim to explore participants’ experiences, beliefs and attitudes towards a target behaviour, by using group processes to stimulate responses and gain insights through participants’ exchanging views, questioning and challenging one another. 32 IDIs enable the researcher to understand participants' lived experiences through their own words and perspectives. 32 33 Use of both FGDs and IDIs allows for in-depth exploration and understanding of various aspects regarding the subject under investigation. The approach also allows for triangulation and corroboration of the FGD and IDI findings, which, in turn, increases the internal validity of the study. 34 35

Study setting

The study was conducted in 16 primary health facilities and their catchment communities—3 from Lusaka city, 2 each from Chongwe, Ndola, Masaiti, Kabwe, Chibombo and Kafue, 1 one from Mazabuka districts. Selection of health facilities was done in consultation with various stakeholders including health staff working in the COVID-19 vaccination programme and health promotion departments at the provincial and district health offices, Zambia National Public Health Institute and Ministry of Health (MoH) headquarters. To be selected, health facilities needed to have been providing COVID-19 vaccination services as well as other COVID-19 prevention, control and care services including screening, contact tracing, isolation and treatment facilities. In addition, health facilities needed to be accessible by road during the study period. Health facilities from Lusaka and Copperbelt provinces were selected because they were COVID-19 epi-centres due to huge populations and commercial activities; Central province is a transit area for traffic from Tanzania and the Democratic Republic of Congo in the north and north-east, respectively; Southern province is a transit region for travellers from the Southern region (South Africa, Zimbabwe, Namibia and Botswana)—all of which reported high numbers of COVID-19 cases. 36 37

From each health facility one community was selected, in consultation with the health facility managers and local community leaders. Efforts were made to ensure an equable distribution of urban and rural communities in the study. To be included in the study, communities needed to be accessible with passable roads, and within 2 hours drive from the health facility. In addition, the local community leaders needed to authorise the team to conduct the study in the community.

Participants and sampling technique

Fgd participants.

A total of 32 FGD (n=242) were conducted with community members. Each FGD comprised between 6 and 10 participants (n=242). To gain insight into the differences and similarities in the participants’ views, FGDs were separated based on age, sex and place of residence. Half of the FGDs (50%) were held in urban communities and the other half in rural settings. To compare and contrast the views based on sex, separate FGDs were held with male and female participants. In addition, a total of eight FGDs were separately held with the youth to gain insight into their perspectives on the subject. Efforts were made to balance the eight FGDs on sex (four male and four female) and place of residence. Initially, a total of 40 FGDs (10 per province) were planned by the research team. However, after conducting 10 FGDs in Lusaka province (men=4, women=4, youth=2), the point of saturation was achieved (ie, no further substantial information was obtained from the participants). At this point, the research team decided to reduce the number of FGDs and conduct only a few more FGDs in the other districts. At the end, 24 FGDs were conducted with the adults (males=12, females=12) and 8 with the youth (18–24 years) (see table 1 ).

View inline

Distribution of FGDs

Using a purposive sampling technique, community health workers assisted by local community leaders (traditional and civic) conducted the recruitment of FGD participants from the local communities. Purposive sampling allows for selection of participants with similar experiences regarding the health behaviour under investigation (ie, perspective and attitude towards COVID-19 vaccine), while, at the same time, allowing for recruitment of participants with different demographic and socioeconomic characteristics—such as age, sex and place of residence and occupation. This, in turn, helps provide insight into the similarities and differences in the participants’ experiences with regard to the health problem under investigation.

Recruitment of the participants was done in multiple steps. First, the research field supervisor together with the district health promotion officer held meetings with the local health facility staff, community health workers and community leaders to inform them about the study and its objectives, and to identify the communities where the FGD participants would be recruited from. Following this meeting, community health workers and local leaders called for a meeting to inform the community members about the study. Community members willing to participate in the study were asked to register with the community health workers and leave their details (place of residence and phone number). A few days after the meeting, the community health workers contacted the potential participants to provide more details about the study and assess their suitability to participate in the study. The assessment was based on the participant eligibility criteria described below. Next, the community health workers compiled a comprehensive list of community members who were eligible to participate in the FGDs and made arrangements for the selected participants to come for the actual discussion to an agreed on place (usually the headman’s place, school or church) on the set time.

In-depth Interviews

To gain insight into the views of the local health staff and community leaders, a total of 30 IDIs (n=30) were conducted. IDI participants were recruited from their places of work and homes. Health promotion officers helped recruit the health staff; community health workers recruited the community leaders. Following identification of the potential participants, the recruiting staff compiled a comprehensive list of IDI participants and contacted them before the day of the interview. Health staff were selected from the district health offices and local health facilities and comprised public health officers, clinicians, nurses and community health workers (n=16). Community leaders were selected from the local communities and included traditional, religious and civic leaders (n=10). In addition, staff (n=4) from non-governmental organisations (NGOs) working with the MoH in the provision of COVID-19 services at the local district level were included in the study.

Eligibility criteria

To participate in both the FGDs and IDIs, participants needed to be:

Aged 18 years and above.

Residing or working in the study area for not less than 3 months.

Health workers involved in the COVID-19 vaccination programme from the selected primary health facilities.

Prisoners and mentally ill people were not included in the study.

Before each FGD/ IDI, written informed consent was obtained from each participant; those who could not read or write were asked to mark with an ‘X’. To make it easy for the study participants to understand, the consent form ( online supplemental material 1 ) was translated into the local language (Bemba, Nyanja and Tonga). After signing the consent form ( online supplemental material 2 ), each FGD/IDI participant was asked to complete a short demographic questionnaire ( online supplemental material 3 ). To make it easy for those who could not read or write, research assistants read the consent form and the short questionnaire and filled it in for them.

Supplemental material

Training of data collectors.

Research assistants were a group of six (three male and three female) final year Master of Public Health (MPH) students recruited from the Schools of Public Health at the University of Zambia (n=3) and Levy Mwanawasa Medical University (n=3) in Lusaka. MPH students were selected because they were skilled and experienced in qualitative research methods: facilitating FGDs and conducting IDIs. To avoid information concealment during FGDs and IDIs, efforts were made to select students who spoke both English and one or two of the local languages, Nyanja, Bemba or Tonga. Before commencement of the data collection process, research assistants underwent a 5-day training in FDG facilitation and interviewing techniques: 3 days of theory and 2 days of practical fieldwork. Topics covered during the 3 days theoretical training included: (1) basic principles of qualitative research, (2) objectives of the study, (3) FGD facilitation techniques, (4) interviewing techniques, (5) research ethics and informed consent in human subjects’ research and (6) FGD and IDI interview guide. Phase 2 of the study was a practical exercise in FGD facilitation techniques, conducting interviews and obtaining informed consent. On the first day of the pactical phase, the research assistants worked in pairs and took turns to facilitate an FGD with their fellow trainees. They also took turns interviewing each other. At the end of eachFGD/IDI, research assistants were asked to provide feedback on each other’s performance. At the end, the trainer also provided feedback and guidance on group dynamics, participant interaction, body language, avoiding conflict and managing it when it arises. On the second day, the team was taken into the nearby neighbourhood to facilitate FGDs with community members and conduct IDIs with health staff and community leaders. The FGDs and IDIs were transcribed and analysed, after which the FGD and interview guides were revised based on the analysed data and feedback from the data collectors.

Data collection

Each FGD was facilitated by a pair of research assistants: one facilitated the discussion and took notes, the other one was in charge of the digital voice recorder. As they facilitated the FDGs, research assistants ensured that each participant was given an opportunity to speak; they also tactfully controlled the dominant individuals and prompted the passive ones to speak. They also ensured that the discussion flowed smoothly among the participants without turning it into an interview, personal attack or conflict. Where necessary, the facilitator asked for elaboration, clarification or probed for detail. Interviews were also conducted by a pair of research assistants: one conducted the interview and took notes; the other recorded the interview with a digital audio recorder. IDIs were conducted at the participant’s preferred place including the office or home. On average, each FGD lasted between 1 hour and 1.5hrours. IDIs lasted between 30 and 45 min. To ensure quality in data collection, a digital voice recorder was used for both IDIs and FDGs.

Data collection tools

FGDs/IDIs were conducted using a paper-based, FGD/interview guide ( online supplemental material 2 ). The FGD/interview guide had predetermined themes, including: (1) perspectives on acceptance of the COVID-19 vaccine and (2) factors affecting vaccine uptake. The second theme had several probes including knowledge and information sources, and attitude towards COVID-19 vaccine. The same interview guide was used for both the FGDs and IDIs, with minor elaboration for the IDIs to elicit some detail. During the FGDs, the focus was on the community perspectives; for IDIs the focus was more on the participant’s perspectives regarding the issues under investigation. In addition, a short questionnaire ( online supplemental material 3 ) was prepared to collect FGD and KII participants’ demographic, socioeconomic and vaccination data. To ensure internal validity, the FGD/interview guide went through a rigorous development process. First, the principal investigator with vast experience in qualitative research and familiar with the subject, drafted the initial version. The themes in the FGD/interview guide were adapted from various sources, including review of the available literature on COVID-19 vaccine and the researchers’ experience in qualitative research methods. Next, the document was shared with the research team members for their comments and feedback. The document was revised based on the research team’s comments. Two independent bilingual experts translated the document into the local languages, Bemba, Tonga and Nyanga. The translated document was pretested in an urban slum of Lusaka during the research assistant training, after which both the KII and FGD recordings were transcribed and analysed. The tool was then revised based on the pre-test findings and feedback from the data collectors.

The data management and analysis

Audiorecordings from the FGDs and IDIs were transcribed and translated into English by four independent people who never participated in the data collection, and were proficient in English and the local language. To check for accuracy, 10% of the transcripts were back-translated into the local language. NVivo V.11 MAC was used for coding and analysis. To make it easy to compare differences and similarities in the participants’ perspectives by different attributes, a separate codebook was created for FGD and IDI data using a framework based on the FGD/interview guide. An inductive approach to data analysis was used, ensuring that subthemes were derived from the predetermined themes and grouping all similar statements concerning particular themes. In order to determine similarities and differences in the responses, findings for the FGDs and IDIs were analysed separately, according to the FGD participants: age (adults vs youth), sex (male vs female) and place of residence (urban vs rural). Summary and descriptive statistics were computed for FGD and IDI participants' demographic characteristics using SPSS V.25 (IBM SPSS Statistics 25)

Quality assurance and control

The team ensured the quality of data collection by: (A) recruiting skilled and experienced data collectors who were trained for 5 days on the theoretical and practical aspects of the study, (B) ensuring that data collectors worked in pairs, (C) using an interview guide (translated into the local language), (D) using a digital voice recorder and taking extensive notes during the FGDs and interviews, (E) by comparing notes and voice recordings each day after the interviews, (F) using experienced and independent staff to transcribe the recordings from the FGDs and KIIs.

Patient and public involvement

Study participants and the public were not directly involved in the design of the study. Rather, the study was designed in response to the call for consultancy for a research proposal on COVID-19 vaccine issued by the COVID-19 Centre, funded by GIZ in Lusaka. However, selection of the primary health facilities, communities and study participants was done in collaboration with stakeholders from the provincial, district and primary health facility and community levels. First, prefield meetings were held with the provincial and district managers to select primary healthcare facilities and local communities to be included in the study. Next, local district managers selected the primary health facilities to be included in the study. In turn, primary healthcare facilities together with the local community leaders recruited the FGD participants and made arrangements for them to come for the actual discussion; they also contacted and prepared a comprehensive list of IDI participants. Finally, a report was written and shared with the funding organisation, GIZ and the COVID-19 centre for dissemination of study findings.

Demographics

Our sample comprised a total of 272 respondents (FGD=242 and IDIs=30). The majority (51.5%) of the participants were female, with a mean age just above 34.04 years and between 2 and 3 children. Almost half (47.1%) of the participants were married. Most participants (55.2%) had secondary school education, 18% had tertiary level education and 1.5% had never attended school. Majority (62.1%) of the participants had an average income of less than K500 per month. Most of the participants (69.5%) mentioned that they were aware about COVID-19, and 52.9% reported that the COVID-19 vaccine was beneficial. Less than 1/10th (9.9%) of the respondents were vaccinated (see table 2 ).

Demographic characteristics of the respondents (n=272)

Theme 1: perspectives on acceptance of the COVID-19 vaccine

Analysis of the findings from the short demographic questionnaire administered to the respondents before each FGD and IDI showed that less than 1/10th (9.9%) of the total sample (FGD and IDI participants) had received the vaccine ( table 2 ). Out of the 27 (9.9%) that reported being vaccinated, 18 (66.7%) were health workers. Our analysis of IDIs also confirmed that most health workers and participants from the NGOs had a positive attitude towards the COVID-19 vaccine and were willing to be vaccinated. Both the community leaders and participants from the NGOs confirmed that they had accepted the vaccine and that many people were willing to be vaccinated. They clarified that the low vaccine coverage reported, especially in rural areas, was a result of the limited access, low supply and stock-out of the vaccine. They mentioned that the vaccine was mainly available and administered in the urban health facilities. Those that lived in remote areas, far from the health facilities, had difficulties accessing the vaccine.

The vaccine has been accepted…. because people have been vaccinated; if they had not accepted the vaccine, they wouldn't have been vaccinated ( IDI informant, health worker, Ndola district ). They aren’t so many people that have been vaccinated. It is because the people vaccinating are rarely seen here ( Community leader, IDI participant, Pemba district ). For those who live in far-flung places, we don’t know if they get vaccinated. I think it would be best to ask them ( Community leader, IDI participant, Mazabuka district )

Most adult participants (both male and female) confirmed that they had not been vaccinated. However, most expressed willingness to be vaccinated. Especially, participants from the rural sites mentioned that many people would accept the vaccine if they had adequate information about its benefits and if it were made available in the health facilities. Our analysis showed no much difference between male and female FGD participants with regard to their attitude towards the COVID-19 vaccine and their intention to be vaccinated.

We can accept the vaccine, but we need sensitisation because even when we were going to school, our parents would tell us whether to accept the vaccine or not ( FGD participant, Lusaka ).

In contrast, analysis of FGD findings showed a striking difference in perspectives between the youth and adult participants. Most youth participants (from both the urban and rural areas) believed that the vaccine was not beneficial and confirmed that most young people had not accepted it.

We have not accepted the vaccine because we don’t know how it’s going to affect the life of someone in future. In short, we don’t know what the life span of people will be. This is the reason why we have not accepted it in our communities ( Youth FGD participant, Kabwe district ).

Theme 2: factors affecting acceptance of the COVID-19 vaccine

Our analysis of both FGD and IDI data showed various factors contributing to the low acceptance of the vaccine among study participant including lack of knowledge and information, myths and misconceptions, and negative attitude towards the vaccine. These factors are presented below.

Knowledge about COVID-19 vaccines

Overall, IDI participants (ie, health workers and participants from the NGOs) expressed better knowledge about COVID-19 vaccine than the FGD participants. Health workers and participants from NGOs knew the types of the COVID-19 vaccines, their mode of administration, benefits and side effects. They also knew about the COVID-19 national vaccination programme. Although most community members (both IDI and FGD participants) perceived the vaccines to be beneficial, majority lacked information about the vaccine-–the various types, mode and frequency of administration. They explained that many would accept the vaccine if they had adequate information. Limited access to information, especially in rural areas, was cited as the main reason for the low acceptance of the vaccine. Community leaders and health workers were unanimous on the information gaps in their communities.

People don't have the truth about the vaccine. The health team should come to educate us on how the vaccine works. They should come to communities, gather people and teach them about the COVID-19 vaccine ( Female FGD participant, Masaiti district )

A contrast was noted among the FGD participants with regard to their knowledge about the vaccine. In general, participants from urban areas expressed better knowledge than those from rural communities. Differences were also noted between the adults and youth FGD participants. Although most youth confessed that they did not know much about the vaccines, they explained that young people had heard about the vaccine, especially those from urban areas.

We know about the COVID-vaccine…most of us youth have heard about COVID-19 and know about the new vaccine ( Youth FGD Participant, Chainda, Lusaka city )

Limited access to information about the COVID-19 vaccine

Overall, our findings show that there was limited access to correct and quality information about the COVID-19 vaccine among most community members who participated in both the FGDs and IDIs. Limited access to information was mentioned as a major reason for the low vaccine acceptance among the participants. Participants from urban settings had better access to information than those from rural areas. Both the IDI and FGD participants confirmed that mass media (radio, televion (TV)), internet and social media were the main sources of information on the COVID-19 vaccine.

A contrast was observed in perspectives on the access to information between the FGD participants from urban and rural settings. Most adult FGD participants from urban sites confirmed that they had access to the major sources of information—media (radio and TV). However, they complained that they could not understand most messages on TV and radio because they were in English. They observed that broadcasting the same messages in local languages would greatly help increase community awareness about the vaccine.

Many people get the information from the radio and TV. They listen to the radio and TV to hear what the Minister is saying. ( Community leader, IDI participant, Chongwe district )

Participants from rural sites did not perceive the media (TV and radio) and internet to be the main sources of COVID-19 information. Poor TV and radio signal reception limited their access to information. Rather, they received information from the health staff, schools, churches, community health workers and community leaders (during community meetings). Health staff disseminated the information about the COVID-19 vaccine when people visited health facilities for various health needs. Community health workers shared the information during community meetings; community members, in turn, would share the information with their families and social networks.

Many people don’t watch TV here….they try to listen to the radio… They have TVs but they can’t see anything….the signal is poor. Government needs to improve TV and radio signal here ( Health worke, IDI participant, Pemba district )

Although community health workers played an important role in disseminating information about the COVID-19 vaccine in the community, most IDI and FGD participants (mainly community leaders and health staff) expressed concerns about the accuracy of the information. They complained that most community health workers did not have adequate knowledge about the vaccine and that, in some instances, the information was incorrect and distorted. As a result, most people did not trust the information they received from the community health workers. They suggested that people in their communities needed more sensitisation and education about the COVID-19 vaccine. They bemoaned that the local health facility staff did not do much to disseminate the information about the COVID-19 vaccine in their communities. Asked on the kind of information their communities needed, most community health workers and leaders mentioned information on the vaccine benefits, safety and the associated risks or side effects. They believed that accurate and adequate information would help the community members make an informed decision about taking the vaccine.

People in this area know nothing about the vaccine because they have never been sensitised. We need to be told what we can do so that we have an idea, but the way it is at the moment, we don't have any idea ( Community leaders, IDI participant, Pemba district ) We just hear from others in the community, because here most of the things we just hear them from these health workers when they pass and tell us, so we also believe what they tell us ( Female FGD participant, Masaiti district ).

In contrast, most young people, especially from urban sites, cited the internet and social media accessed through their phones as their main sources of information for COVID-19-related matters including the vaccine. However, poor internet and mobile phone signals in rural and remote areas made it difficult for most young people to access information.

Most of us use our phones to get information….we get everything from social media on our phones ( Youth FGD participant, Ndola city )

Myths and misconceptions about the COVID-19 vaccine

Our findings elicited many myths and misconceptions about the COVID-19 vaccine among both the IDI and FGD participants. Especially FGD participants were unanimous on the existence of various myths and misconceptions concerning the vaccine. These myths and misconceptions had a negative influence on people’s attitude towards the COVID-19 vaccine and seem to be some of the most important reasons for the high vaccine hesitance.

One of the myths held among most FGD participants (especially in urban settings) was that western countries brought the vaccine in order to eliminate the African population. According to them, westerners brought the vaccine because they wanted to collect people’s blood and kill them. They were concerned why certain vaccines given to the Africans had been rejected in Western countries.

There is a rumour that people in our community are spreading that the medicine [vaccine] was made to kill us Africans because we are too many. So even as we accept that this must be true ( Community leader, IDI participant, Ndola ).

The other strongly held belief by both male and female FGD participants from urban and rural sites (but not the youth) was that the vaccine was brought into the country for political reasons. They explained that politicians had gone into some contractual agreement with western countries to administer vaccines to their people in exchange for money. The money would then be used for political campaigns since it was a presidential and parliamentary election year (2021) in the country.

Some people are saying that they have brought the vaccine in an election period because they want them [community members] to die after giving them the injection so that they are sacrificed ( Female FGD participant, Lusaka )

The other firmly held belief (especially among rural participants) seemed to be influenced by participants’ religious background or inclination. They explained that people believed that the COVID-19 vaccine was part of the mark of the beast (666) mentioned in the Bible (see Revelation 13) and that those who receive the vaccine are initiated into the ritual.

Some people say this is 666, that’s what I heard others say. So that’s why we are scared, because we think that they will initiate us into the 666 rituals ( Female FGD participant, Kabwe ).

Other beliefs seem to be influenced by health reasons. For example, both the FGD and IDI participants from rural and urban settings explained that people in their communities believed that the vaccine is a slow poison which health staff introduced into the body.They believed that the vaccine dries up and makes the blood clot and that one will die after several months or years. Some participants also believed that after receiving the vaccine, one would start fitting and die immediately after being vaccinated; those who survived would only live for a few years afterwards.

Some say when you get vaccinated, you will just live for a few years, and then you get sick and die; that is why we are scared of getting vaccinated ( Traditional leader, IDI participant, Mazabuka district ).

Attitude towards the COVID-19 vaccine

Overall, our analysis of the data from the short demographic questionnaire showed that half (52.9%) of participants (both the FGD and IDI participants) perceived the vaccine to be beneficial ( table 2 ). However, analysis of FGD and IDI data shows that participants expressed different types of attitude towards the COVID-19 vaccine: positive, negative and ambivalent. The detailed findings on these attitudes are presented below.

Most health workers and some FGD participants from both urban and rural settings expressed a positive attitude towards the COVID-19 vaccine and perceived it to be beneficial. Perceived benefits were that the vaccine confers protection against the coronavirus infection among the vaccinated individuals. They also believed that the vaccine reduces the chances of a vaccinated individual to transmit the virus to other people. The other cited benefit was that the vaccine reduces the risk of developing severe disease. If one got infected, the disease would not be as severe as it is among those who are not vaccinated.

Most FGD participants expressed a negative attitude towards the COVID-19 vaccine. Interestingly, our findings did not show differences in attitude between male and female participants. Rather, rampant myths and misconceptions about the COVID-19 vaccine and personal or family’s previous experience with the COVID-19 disease or vaccination seemed to have influenced the participants’ attitude. In general, individuals or families who had not experienced the disease or seen someone suffer or die from COVID-19 disease expressed a negative attitude. They believed that the vaccine was not beneficial. Further, lack of information (especially in rural areas) and wide spread misinformation about the COVID-19 vaccine—such as exaggeration of the vaccine side effects—seemed to influence participants’ attitude towards the COVID-19 vaccine.

I know the benefits are building our immunity and we don’t get a chance to catch COVID-19, though people are saying even those that got the jab have tested positive, they don't have severe disease (IDI participant, Health worker, Ndola district).

Moreover, cultural beliefs and stigma about COVID-19 seem to have affected many people’s attitude and prevented them from accepting the vaccine. Especially health staff explained that some people did not believe in the existence of COVID-19. They cited examples of communities where a family member would suffer and die from COVID-19, but relatives would hide the information and mention another disease, such as asthma, as the cause of death. Because of denial and low-risk perception, such people refused to take the vaccine.

Lack of confidence in the health workers (who came from outside their communities) was perceived as an important factor influencing participants’ attitude towards the vaccine, especially among the community leaders and FGD participants from rural communities. They argued that people in their communities would only be convinced to take the vaccine if the health workers from their local communities administered the vaccine.

The people to vaccinate us must be from our community; otherwise, when an outsider comes to vaccinate us, we will be sceptical because we don't know them ( Village headman/IDI participant, Chongwe district )

In addition, most participants from rural towns and communities expressed an ambivalent attitude towards the vaccine; they were not sure about the benefits of receiving the vaccine. They argued that they did not know the vaccine benefits because they had not seen anyone take it. They explained that they would only believe in the vaccine benefits if someone or a group of people who had taken the vaccine went to explain how they felt after receiving it.

We do not know the truth, and we are scared, that is why we don't go for the vaccine injection. We have been told that the vaccine injection is harmful to consumers ( Male FGD participant, Masait district ). What we are saying is that they should bring us someone who has been vaccinated so that they tell us about the goodness of being vaccinated ( Male FGD participant, Chongwe district) We don't know how these things came, we are scared that we may die, and we can also be infected with other diseases. We don't see people who have been vaccinated, to tell us how they feel ( Civic leader, IDI participant, Masaiti district).

In general, young FGD participants from both urban and rural communities had a negative attitude towards the COVID-19 vaccine. Low-risk perception seemed to influence their attitude towards the vaccine. They believed that they were not at risk of getting the infection and that those who got infected would have mild or no symptoms at all. They also believed that the vaccine was not beneficial. Access to the internet and use of social media among the young people (especially from the urban communities with good internet connectivity) seems to have exposed them to incorrect information regarding the benefits and side effects of the vaccine. This, in turn, influenced their attitude. In addition, poor mobile phone signals, TV and radio reception in rural areas made it difficult for most young people to access information about the COVID-19 vaccine.

The aim of this study was to explore community members’ and health workers’ perspectives on the COVID-19 vaccine and the reasons that affect its uptake in Zambia. Overall, our findings showed low vaccine uptake among the participants. Several factors including limited knowledge, access to information, myths and misconceptions, negative attitude towards the vaccine and low-risk perception about the COVID-19 disease contributed to vaccine hesitance among the participants.

Our finding corroborates previous studies from LMICs and elsewhere which reported vaccine hesitance among health staff and community members. For example, a study conducted in Zambia 29 reported substantial uncertainty and hesitancy about receiving the vaccine among parents, despite expressing high intentions to have their children receive the COVID-19 vaccine. Similar findings were reported by Botwe et al 38 in Ghana who reported a vaccine hesitance of 44% among the health staff. These findings are also consistent with those by Baniak et al 39 who reported vaccine hesitance among nursing staff in the USA. The authors concluded that, despite the increase in vaccine uptake during the active vaccine rollout, there was still widespread and sustained hesitancy and unwillingness to take the vaccine. Other authors, Wong et al 40 and Luk et al 41 in Hong Kong also reported a low intention to vaccinate. They concluded that vaccine hesitance was a major challenge to effective programming and implementation. Thus, formulation and implementation of evidence-based vaccination strategies focusing on increasing the intention to take the vaccine has a potential to mitigate vaccine hesitance

Limited knowledge about the COVID-19 vaccine, its benefits and potential harms, was found to be one of the important barriers to effective vaccine uptake. The media (TV, radio and internet) play an important role in informing people about the vaccine. However, poor TV and radio signal reception in rural and remote areas limit access people’s access to these important sources of information. This explains the stark contrast in the levels of knowledge about the COVID-19 vaccine between participants from rural and urban communities. Moreover, our findings suggest that social media accessed through the internet on mobile phones is a major source of information among young people. However, poor internet and mobile phone signals in rural areas make it difficult for young people to access information. This finding is consistent with previous studies 42–46 which reported low knowledge levels concerning the COVID-19 vaccine. Interestingly, these studies showed that knowledge about the vaccine was positively correlated with one’s vaccine uptake. This finding suggests that information is an important factor influencing vaccine acceptance, and that lack of information affects peoples' willingness to take the vaccine. This result is consistent with the theory of reasoned action which highlights the importance of background factors such as knowledge and access to information in influencing people’s intention to adopt a health behaviour such as COVID-19 vaccination. 47–49 Public health interventions aiming at mitigating vaccine hesitancy and increasing vaccine uptake could benefit from focusing on knowledge and access to information about the COVID-19 vaccine, its benefits and safety.

Widespread myths and misconceptions about the reality of the COVID-19 disease and the benefits of the vaccine appear to be an important factor contributing to vaccine hesitance among our sample. These myths and misconceptions seem to be more rampant in rural communities where there is limited or no access to accurate information about the benefits and safety of the vaccine. For example, due to limited access to accurate information, many people in rural communities depend on the information from health workers and traditional leaders. Our findings suggest that such information, though important, is either inadequate or inaccurate with a potential to be misinterpreted. When people discover that such information is inaccurate untrustworthy, they seek alternative sources such as social media−which may also be misleading, resulting in the emergency of conspiracy and rampant myths and misconceptions. 49 However, especially in urban areas the situation is different; most myths and misconceptions seem to be influenced by the incorrect information spread by social media users, especially young people, with ready access to the phone and internet. For example, many participants (both FGDs and IDIs) believed that the vaccine is a poison: it dries up one’s blood, causes it to clot and eventually kills the victim. Our findings suggest that these strongly held beliefs have a negative influence on people’s intention to take the vaccine. These findings corroborate those reported elsewhere 50–53 regarding the importance of social media in propagating myths and misconceptions about the vaccine. These findings are also consistent with previous studies, for example, Bertin et al , 54 which reported that myths and misconceptions do not only instil fear among the people, but also influence them not to take the vaccine. Public health interventions can benefit from provision of correct and accessible information to prevent and address myths and misconceptions which negatively influence people’s perspectives and adoption of health behaviour, such as vaccine uptake. Thus, increasing access to correct information in the community has the potential to prevent and address the widespread myths and misconceptions about the vaccine and help mitigate vaccine hesitance. 55

Our findings suggest that attitude towards the COVID-19 vaccine has an important influence on the intention to take the vaccine. Although half of the participants perceived the COVID-19 vaccine to be beneficial, most had mixed attitudes towards the vaccine: positive, negative and ambivalent. Participants’ attitude seems to have been influenced by various factors including place of residence, age, access to information, myths and misconceptions about the vaccine, and one’s experience with the COVID-19 disease and the vaccine. Participants who had either experienced the disease, seen a friend or family member suffer from the disease expressed a positive attitude towards the vaccine compared with those who had not. Similarly, those who had either been vaccinated, seen or heard about someone who had been vaccinated appreciated the benefits of the vaccine and expressed a more positive attitude than those who had no such experience. Protection against COVID-19 and reduction in the severity of the disease if one got infected were the main perceived benefits. Perceived benefits appear to play an important role in influencing people’s attitude towards the vaccine. Participants who perceived no benefits from the vaccine expressed a negative attitude. This finding is in keeping with the reasoned action approach which postulates that, before engaging in a healthy behaviour, people evaluate the benefits against the risks. 56 An individual’s attitude, therefore, will depend on their evaluation of the perceived benefits compared with the risks. Those who perceive more benefits are likely to have a positive attitude towards the target behaviour, and possibly adopt it. This finding is also consistent with those reported by Elhadi et al in Libya. 57 These authors found that people who had a family member or friend infected with COVID-19 were more likely to accept the vaccine. Strategies that use a collaborative approach with community role models who have either experienced the disease or received the vaccine have the potential to change community attitudes towards the vaccine and possibly increase vaccine uptake.

Finally, our findings on low-risk perception and personal susceptibility to the COVID-19 disease, especially among young people, are worthy noting. It appears that young people’s ‘false sense of safety’—that they are not susceptible to the COVID-19 disease and that, if they get infected, the disease would not be severe—seem to influence their attitude towards the vaccine. Access to social media and incorrect information from the internet, especially among the young participants from urban communities, appears to contribute to the low-risk perception and vaccine hesitance. Interestingly, we did not find a striking difference in risk perception between the male and female participants or according to place of residence (urban or rural). This finding contradicts Elhadi et al 57 who reported low vaccine hesitance among young people—that, compared with older people, young people were more likely to accept the vaccine. However, this finding is in line with Lazarus et al 58 who (in their survey of over 13 420 people from 19 countries) reported that young people were less likely to accept the vaccine than older people. The finding is consistent with previous studies that reported that age, and not sex, had a signiﬁcant association with one’s attitude towards acceptance of the vaccine. These studies also reported a positive correlation between age and vaccine acceptance. They also showed that high risk perception about the severity and one’s personal susceptibility to the disease, benefits from the vaccine, cues to action and trust in the healthcare system or vaccine manufacturers were positive correlates of vaccine acceptance. Interventions that use social media to provide correct information to young people—about their personal risk and susceptibility to the disease—has a potential to mitigate vaccine hesitance among this age group. To be successful, such interventions should focus on addressing behavioural beliefs, risk perception and outcome expectancy. 59

Study limitations

Potential limitations of our study should be noted. First, this study was conducted at the beginning of the COVID-19 national mass vaccination programme in the country when people’s knowledge about the vaccine was still limited; it is not clear how knowledge in the community has evolved over time. Second, like other qualitative study designs, this study could not establish a causal link between knowledge and attitude, and vaccine uptake. Further research with a longitudinal quantitative design is required to measure knowledge and attitude, and test their relationship with vaccine uptake in order to establish the causal pathway.

Nevertheless, we believe that use of FGDs and IDIs comprising adult male and female as well as young participants from both urban and rural settings provided in-depth information on vaccine uptake and the influencing factors, based on the views of the health workers and community members. We believe this study design increased the validity of our findings. Furthermore, selecting participants (both community members and health staff) from both urban and rural settings, increased the internal validity of the study. It also provides a balanced view of the Zambian people’s perspectives on the subject under investigation. Our study also highlights the importance of using an integrated community-based approach to maximise vaccine uptake. This approach is in accordance with the WHO guidelines, 60 which suggest that a comprehensive approach, targeting multiple facets of social interaction, is more likely to dispel COVID-19 myths and misconceptions, and address vaccine hesitancy. Thus, our findings can save as basis for policy and intervention design to mitigate vaccine hesitance and increase vaccine uptake. To our knowledge, no such study has been conducted in Zambia; this is the first one.

Our findings demonstrate low vaccine uptake among our participants; it also highlights several factors—including limited knowledge and access to information, myths and misconceptions, negative attitude towards the vaccine and low-risk perception about COVID-19 disease–which affect vaccine uptake. These results can provide starting points for future Public health policies and interventions which, in our opinion, should focus on: (A) increasing access to information and knowledge about the benefits and safety of the vaccine; (B) addressing myths and misconceptions about the vaccine; (C) increasing risk perception and perceived personal susceptibility to the COVID-19 and its severity, especially among young people; (D) making the vaccine accessible, especially in the rural and remote areas; (E) identifying role models in the community who have either experienced the disease or received the vaccine; (F) establishing linkages and collaboration between health workers and role models; (G) establishing a community operational and vaccine delivery mechanism through strengthened linkages with key community leaders such as local traditional, civic and religious leaders, and (H) addressing systemic barriers such as human resource shortage and stock-outs of the vaccine to increase access to the vaccine in the rural and remote communities.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

This study involves human participants and was approved by University of Zambia Biomedical Research Ethics Committee (ref: 1774-2021). Participants gave informed consent to participate in the study before taking part.

Acknowledgments

We thank Levy Mwanawasa medical University, Mary Ng’andu for supervising the data collection and the research assistants who helped with the data collection. Our gratitude also goes to the study participants for their valuable time and input into the study.

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

Data supplement 1
Data supplement 2
Data supplement 3

Contributors All authors contributed substantially to the development of the manuscript. CS designed the study. Under the oversight of CS, MN supervised the data collection process. CS and NM conducted data analysis. CS wrote the first draft of the manuscript. NM, EMS, W-CP, JMZ, DEML, AM, BM, DE and MM read and provided feedback on the draft manuscript. CS, NM and EMS revised the manuscript. All other coauthors advised on the final draft of the manuscript. All authors read, commented on and approved the final manuscript. CS had access to the data, controlled the decision to publish and is the study guarantor.

Funding The study was made possible by grant number 20.2095.6-001.00 from Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ)/German Cooperation through the Decentralisation for Development (Zambia).

Competing interests None declared.

Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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Research Article

A model of factors influencing COVID-19 vaccine acceptance: A synthesis of the theory of reasoned action, conspiracy theory belief, awareness, perceived usefulness, and perceived ease of use

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Supervision, Validation, Visualization, Writing – original draft

* E-mail: [email protected]

Affiliation Department of Accounting & Information Systems, Faculty of Business Studies, Jagannath University, Dhaka, Bangladesh

Roles Data curation, Investigation, Project administration, Writing – review & editing

Affiliation Institute of Chartered Accountants of Bangladesh, Dhaka, Bangladesh

Taslima Akther,
Tasnima Nur

Published: January 12, 2022
https://doi.org/10.1371/journal.pone.0261869
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The aim of this study is to investigate the key factors influencing the acceptance of COVID-19 vaccines and develop a model based on the theory of reasoned action, belief in conspiracy theory, awareness, perceived usefulness, and perceived ease of use. The authors created and distributed a self-administered online questionnaire using Google Forms. Data were collected from 351 respondents ranging in age from 19 to 30 years, studying at the graduate and postgraduate levels at various public universities in Bangladesh. The Partial Least Squares Structural Equation Modeling (PLS-SEM) method was used to analyze the data. The results indicate that belief in conspiracy theory undermines COVID-19 vaccine acceptance, thereby negatively impacting the individual attitudes, subjective norms, and acceptance. Individual awareness, on the other hand, has a strong positive influence on the COVID-19 vaccine acceptance. Furthermore, the perceived usefulness of vaccination and the perceived ease of obtaining the vaccine positively impact attitude and the acceptance of immunization. Individuals’ positive attitudes toward immunization and constructive subjective norms have a positive impact on vaccine acceptance. This study contributes to the literature by combining the theory of reasoned action with conspiracy theory, awareness, perceived usefulness, and perceived ease of use to understand vaccine acceptance behavior. Authorities should focus on campaigns that could reduce misinformation and conspiracy surrounding COVID-19 vaccination. The perceived usefulness of vaccination to prevent pandemics and continue normal education will lead to vaccination success. Furthermore, the ease with which people can obtain the vaccine and that it is free of cost will encourage students to get vaccinated to protect themselves, their families, and society.

Citation: Akther T, Nur T (2022) A model of factors influencing COVID-19 vaccine acceptance: A synthesis of the theory of reasoned action, conspiracy theory belief, awareness, perceived usefulness, and perceived ease of use. PLoS ONE 17(1): e0261869. https://doi.org/10.1371/journal.pone.0261869

Editor: Dejan Dragan, Univerza v Mariboru, SLOVENIA

Received: August 27, 2021; Accepted: December 12, 2021; Published: January 12, 2022

Copyright: © 2022 Akther, Nur. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting information files.

Funding: The authors receive no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

In December 2019, the first human cases of COVID-19, a coronavirus disease caused by SARS-CoV-2, were reported in Wuhan, China [ 1 , 2 ]. The virus was initially called the novel or “New” coronavirus, but was later renamed SARS-CoV-2 by the International Committee on Taxonomy of Viruses, and the disease it causes was named “coronavirus disease 2019 or “COVID-19” by the World Health Organization (WHO) on February 11, 2020 [ 3 ]. Within a month, the novel coronavirus spread to 25 countries, including China and the WHO Director-General declared COVID-19 as the first pandemic caused by a coronavirus, causing over 118,000 infections in 114 countries and 4,291 deaths [ 4 , 5 ]. After the initial infection in Wuhan, China, the first million COVID-19 cases were reported on April 2, 2020; the highest daily case count of 906,008 was on April 28, 2021. On May 18, 2021, over 4,500 people died in India, and over 4,400 people died in the US on January 12, 2021 [ 6 ]. The first COVID-19 patient was discovered in Bangladesh on March 8, 2020, and it was fatal on March 18, 2020. By June 2021, there were 840,000 cases, with 112 deaths in a single day on April 19, 2021. In Bangladesh, the Case Fatality Rate (CFR), which is the ratio of confirmed deaths to confirmed cases, increased by 58%, indicating that a greater proportion of infected people began to die [ 7 ].

During the public health emergency caused by COVID-19, the WHO placed unlicensed, still-in-development vaccines on the Emergency Use List as a temporary measure to make such vaccines available to those in need [ 8 ]. The WHO approved five vaccines for emergency use against COVID-19 as of June 3, 2021, because they met the necessary safety and efficacy criteria, including AstraZeneca/Oxford, Johnson and Johnson, Moderna, Pfizer/BioNTech, Sinopharm, and Sinovac [ 9 ]. Up until June 9, 2021, more than 944 million people received vaccine doses, and more than 480 million were fully vaccinated, representing 6.16 percent of the world’s population [ 6 ]. COVID-19 vaccines are expected to provide minimal protection against new virus variants while also preventing serious illness and death [ 10 ]. Rumors and conspiracy theories, on the other hand, contribute to COVID-19 vaccine hesitancy [ 11 ].

Conspiracy theories are primarily inferential beliefs derived from outside sources that extend beyond observable events [ 12 ]. Belief in conspiracy theories (BC) historically impeded population immunization. Previously, people refused immunizations due to false claims that vaccines contained infertility agents or spread infectious pathogens like the human immunodeficiency virus (HIV) [ 13 ]. People in many countries boycotted the polio vaccine due to rumors that it caused infertility, resulting in an increase in polio cases [ 13 , 14 ]. Conspiracy theories about COVID-19 being a hoax or a bioweapon designed in a Chinese laboratory began to circulate on social media almost immediately after the first reports of the virus [ 15 ]. Bertin et al. [ 16 ] found that the more participants believed in COVID-19 conspiracy theories, the less likely they were to support vaccination. Sallam et al. [ 17 ] report a high prevalence of COVID-19 vaccine hesitancy among Jordanian university students, associated with conspiracy beliefs such as COVID-19 is a man-made disease, vaccination will be used to implant microchips into humans to control them, and vaccination can lead to infertility.

The theory of reasoned action (TRA) explains individual behavior by emphasizing the importance of beliefs in predicting behavior [ 18 ]. According to TRA, an individual’s attitude toward the outcome of the behavior and subjective norms (the opinions of the person’s social environment) predict individual behavior intention [ 19 ]. Positive vaccination attitudes will increase the rate of COVID-19 vaccine acceptance. Those who intend to receive the COVID-19 see high perceived benefits in doing so for the purpose of protecting themselves and others in their circle, implying vaccination compliance [ 20 ]. Raising public and individual awareness is the most important factor in the fight against diseases, crime, and social injustice [ 21 , 22 ]. People are either unaware of or fearful of the current vaccination program [ 23 ].

This study investigates the factors that influence COVID-19 vaccine acceptance among the young generations of Bangladeshi public university students. Bangladesh, a developing country in South Asia, accounts for 0.58% of the world’s COVID-19 cases and is in the top 26 countries worldwide.. As a tertiary educational institute, public universities provide higher education, and the pandemic wreaked havoc on the students’ education and future prospects. At the height of the pandemic, we assessed the acceptance of COVID-19 vaccines among students at various public universities in Bangladesh, for whom vaccination is a critical issue in allowing them to resume their education and prepare them for their profession. We construct a model of COVID-19 vaccine acceptance using the frames of TRA, belief in conspiracy theory (BC), awareness (AW), perceived usefulness (PU), and perceived ease of use (PE). Our findings are a valuable resource for understanding vaccine acceptance behavior during this critical pandemic period and providing policymakers with some practical recommendations. Furthermore, this study makes a significant theoretical contribution to the literature by decomposing TRA using BC, AW, PU, and PE.

The remainder of the paper proceeds as follows. Section 2 discusses the COVID-19 pandemic and vaccination in the context of Bangladesh. Section 3 describes the theoretical framework and hypothesis development, followed by a description of the data and methodology in Section 4. Section 5 reports the analysis and results, and Section 6 provides a discussion, the implications of the study, the limitations, and conclusion.

2. The COVID-19 pandemic in Bangladesh and the vaccination context

Till June 2021, Bangladesh had 840,000 cases and over 13,000 deaths due to COVID-19. Prothomalo [ 24 ] published news of a study by the International Centre for Diarrhoea Disease Research, Bangladesh (ICDDR,B) showing that 71% and 55% residents of Dhaka and Chittagong, respectively, developed COVID-19 antibodies between October 2020 and February 2021 and many of these people were asymptomatic and so more dangerous to others in terms of spreading the virus unknowingly. Data reported by WHO in the following Fig 1 depicts that among the Southeast nations, Bangladesh has an upward trend in active cases, deaths, and the CFR rate from 1 January 2020 to 18 July 2021.

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COVID-19 primarily infected young professionals, students, and working people in Bangladesh. According to the IEDCR, 68% of COVID-19 cases were observed in people aged 21 to 50 years, whereas infected patients aged >50 years made up 21% of total infected people, and children and youths aged 20 years made up were 11% of total infected cases [ 25 ]. Aside from direct consequences such as infection and death, COVID-19 affected the economic and social lives of Bangladeshis due to the nationwide lockdowns beginning March 24, 2020. The COVID-19 pandemic also highlighted flaws in Bangladesh’s healthcare system. As healthcare workers work to save the lives of COVID-19 patients, regular healthcare services and vaccination programs are hampered [ 26 , 27 ]. On February 7, 2021, mass vaccination against COVID-19 began across the country based on online registration. Bangladesh has 53 government-funded public universities that operate as self-governing organizations. These universities are classified into agricultural universities, science and technology universities, engineering universities, medical universities, and general studies universities [ 28 ]. Due to the COVID-19 pandemic outbreak in Bangladesh, all educational institutions have been closed since March 2020. Many of these students also live in rented houses, as residential halls are also closed, which increases their expenses or reduces their savings. Due to a lack of digital learning opportunities in rural areas, education for a whole generation was disrupted.

3. Theoretical framework and hypothesis development

3.1. belief in conspiracy theories and covid-19 vaccination.

Conspiracy theories are explanations for significant events that involve secret plots by powerful malevolent groups [ 29 ]. Commonly accepted conspiracy theories contend that climate change is a hoax [ 30 ]; NASA faked the moon landings [ 31 ]; the US government orchestrated the 9/11 terrorist attacks [ 32 ]; and vaccinations are harmful, but this fact is concealed to maintain profits [ 33 ]. A conspiracy belief is the unwarranted assumption of a conspiracy when other explanations are more likely [ 34 ]. A growing body of research shows that BC can have negative consequences on attitudes and behavior [ 35 ]. In addition to the social and political domains, BC has a significant impact on health. Conspiracy beliefs about the origin and treatment of HIV/AIDS had a negative impact on attitudes toward preventative measures and adherence to treatment programs [ 36 ]. Fears about the safety of childhood vaccinations contributed to a drop in polio vaccination rates in some countries [ 37 ].

3.2. Impact of conspiracy beliefs on attitude toward vaccination

Although vaccines are the most effective way to prevent infectious diseases, their safety and efficacy have long been the subject of conspiracy theories, with the central argument being that large pharmaceutical companies and/or governments conceal vaccine information for personal gain [ 37 , 38 ]. Belief in anti-vaccine conspiracy theories reduces vaccination intentions [ 39 ]. Rumors about COVID-19 vaccine development delays, or that vaccines will be freely available only to supporters of the ruling government, may foster distrust between government stakeholders and the general public. This could affect the implementation of any vaccine-related policy. Online health information is frequently amplified by rumors and conspiracy theories that are not always based on scientific evidence [ 40 ]. Users who seek health information on online platforms are at risk of exposure to misinformation that could endanger public health [ 41 ]. Stecula et al. [ 42 ] discovered that people exposed to COVID-19 vaccine-related information on social media were more likely to be misinformed and vaccine-hesitant. We therefore hypothesize that

H1: BC has a negative impact on attitude toward COVID-19 vaccine acceptance .

3.3. Impact of conspiracy beliefs on subjective norms

Conspiracy beliefs are widespread and can have negative consequences because perceived social norms have a strong influence on individuals [ 43 ]. Social influence is the process by which perceptions of what other people think and do influence beliefs and behaviors [ 44 ]. Social norms guide behavior by implicitly defining what is and is not acceptable in a given context [ 44 ]. Sherif [ 45 ] defined social norms as mutually agreed-upon rules for social behavior. People who identify more strongly with the group are more likely to act in accordance with group norms [ 46 ]. Thus, perceived norms of conspiracy belief may influence personal BC, especially if people perceive groups with which they identify strongly as endorsing conspiracy theories [ 46 , 47 ].

BC, particularly anti-vaccine conspiracy theories, is regarded as more normative than it is [ 43 ]. This is significant because the overestimation of in-group conspiracy beliefs may result in unwarranted social pressure to also endorse conspiracy beliefs given the negative social and health consequences of harboring conspiracy beliefs, particularly anti-vaccine conspiracy theories [ 30 , 48 ]. It is concerning that perceived social norms may be driving conspiracy belief. We thus hypothesize

H2: BC has a negative impact on subjective norms regarding COVID-19 vaccine acceptance .

3. 4. Impact of conspiracy beliefs on COVID-19 vaccine acceptance

Rumors and conspiracy theories can contribute to vaccine apprehension [ 49 ]. Negative claims about vaccine effectiveness historically influenced vaccine uptake. Rumors about vaccination campaigns being used for political purposes are not new, and such rumors affected vaccination campaigns in some countries [ 50 ]. One prevalent rumor holds that critical phases of clinical trials in the vaccine development were skipped because pharmaceutical companies would not compensate participants for adverse side effects experienced during the trial. The most widely circulated rumor is that the COVID-19 vaccine would be a messenger Ribonucleic acid (mRNA) vaccine that could change people’s Deoxyribonucleic acid (DNA), transforming them into genetically modified humans, or cause cancers and infertility. Some claims emphasize that the COVID-19 vaccine was intended to reduce the global population. In Bangladesh, there was a rumor that China wanted to use Bangladeshi citizens as genuine pigs for a vaccine trial [ 49 ]. Therefore, we hypothesize

H3: BC has a negative impact on COVID-19 vaccine acceptance .

3. 5. Awareness

Awareness is the extent to which a target population is aware of an innovation and formed a general perception of what it entails [ 51 ]. The concept of awareness first appeared in innovation diffusion theory, which states that the decision-making process for adopting new technologies includes awareness, attitude formation, decision, implementation, and confirmation [ 52 ]. It is further defined as an individual’s active participation and increased interest in focal issues [ 53 , 54 ]. The concept of awareness is central to human behavior in the social science, criminal justice, and medical behavioral science literature [ 21 ]. Awareness is one of the most important components of consciousness-raising because it fosters an understanding of the needs, impetus, and specificity of issues, events, and processes, and it is positively related to individuals’ attitudes and cognitive development [ 22 , 55 ].

One study shows that people are either unaware of or fearful of the current vaccination program [ 23 ]. Vaccine hesitancy and misinformation are major impediments to achieving coverage and population immunization in many countries [ 56 , 57 ]. Awareness can have positive impact on the vaccine acceptance. Thus, we propose

H4: Awareness positively influences attitudes toward COVID-19 vaccine acceptance .

In addition to an individual’s attitude toward behavior, the behavioral norms of an individual user’s social group have a strong influence on the individual’s behavioral intention [ 58 ]. The process of increasing problem awareness guides the development of a social network of organizations that strongly advocate for policies and programs to reduce such problems [ 59 ]. In the case of the COVID-19 vaccine, raising awareness among various social groups and communities raises community norms about COVID-19 and influences immunization through the COVID-19 vaccine. We therefore hypothesize that

H5: Awareness positively influences subjective norms about taking the COVID-19 vaccine .

Awareness is critical to technology acceptance. Identity theft, negative publicity, significant financial loss, and uncertain legal consequences could be devastating to individuals and organizations if they do not adopt protective technologies. Because such consequences are frequently reported in the popular media, we contend that awareness alone can motivate a user to act, regardless of whether he or she formed a positive attitude or is influenced by social group norms. Other studies on crime and disease prevention show that increased awareness has a direct influence on the intention to engage in certain behaviors [ 60 , 61 ]. Consequently, we postulate that

H6: Awareness has a positive impact on COVID-19 vaccine acceptance .

3. 6. Perceived usefulness (PU) and perceived ease of use (PE)

3. 6. 1. perceived usefulness (pu)..

PU is peoples’ subjective assessments of the extent to which using a system would improve their job performance [ 62 ]. It is the magnitude to which an individual considers using something that provides more benefits [ 63 ]. PU is a predictor of attitude [ 62 , 64 – 66 ]. Users can develop a positive attitude because engaging in a particular behavior has numerous benefits. Islam et al. [ 67 ] demonstrated that the majority of participants had a positive attitude toward vaccination for its usefulness in protecting against COVID-19 disease. Perceived benefits, such as the COVID-19 vaccine’s high effectiveness in preventing significant suffering and complications of the disease, as well as the risk of becoming infected or infecting others, can predict COVID-19 vaccine acceptance. For recent graduates, a vaccine certificate may be required for new job applications, higher education applications, and proper continuation of their current studies and life activities. The usefulness of the vaccine creates a favorable attitude toward the acceptance of vaccines and the COVID-19 vaccine. Thus, we hypothesize that

H7: The PU of the COVID-19 vaccine is positively related to attitude toward its acceptance .

H8: The PU of the COVID-19 vaccine has a positive impact on its acceptance .

3. 6. 2. Perceived ease of use (PE).

PE is an individual’s expectation of how easy the target system will be to understand, learn, and use [ 62 , 63 ]. The complexity of a single system will impede the adoption of an innovation [ 52 ]. With less complexity in a system’s operation, a user can develop a positive attitude toward intention and behavior. PE has a direct relationship with attitude and acceptance [ 62 , 66 , 68 ]. Vaccination convenience is the ease of obtaining the vaccine, including factors such as physical availability, affordability, and accessibility [ 69 ]. When investigating vaccine acceptability, it is critical to consider vaccine convenience in terms of availability and affordability. If the COVID-19 vaccine can be obtained with less effort and is freely available, its acceptance will increase. Therefore, we propose

H9: The PE of the COVID-19 vaccine is positively related to its acceptance .

H10: The PE of the COVID-19 vaccine is positively related to its acceptance .

3. 7. Attitude, subjective norms, and COVID-19 vaccine acceptance

The theory of reasoned action, TRA [ 19 ], developed in the field of Social Psychology, has been widely used to explain individual behavior. The TRA hypothesizes that an individual’s intention to engage in a given behavior predicts behavior. In turn, subjective norms, that is, the individual’s attitude toward the outcome of the behavior and the opinions of the person’s social environment predict intention [ 19 ]. TRA is a general structure designed to explain almost all human behavior based on the significance of an individual’s beliefs in predicting their behavior [ 19 , 70 ].

Vaccines are effective interventions that can help to reduce the global disease burden. Public vaccine hesitancy, on the other hand, is a pressing issue for public health officials. With the availability of COVID-19 vaccines, there is little information available on public acceptability and attitudes toward the COVID-19 vaccines. A positive attitude toward the vaccination will help to prevent COVID-19 and impact vaccinate acceptance. In a survey conducted across 19 countries, 71.5% respondents stated that they would take a vaccine if it were proven safe and effective [ 71 ]. We anticipate that positive attitudes toward vaccination will increase the rate of COVID-19 vaccine acceptance.

H11: COVID-19 vaccine acceptance is related to attitude .

Subjective norms are an individual’s perception of the social pressure to perform or refrain from performing a target behavior [ 19 ]. Normative beliefs reflect an individual’s perception of the influence of opinion among reference groups, whereas motivation to comply reflects the extent to which the individual wishes to comply with the wishes of the referent other [ 72 ]. Hence, people frequently act based on their perception of what others think they should do, and people close to them may influence their intention to adopt a behavior.

Subjective norms and self-efficacy are significant predictors of COVID-19 vaccination intention [ 73 ]. Subjective norms that particularly influenced respondents were when friends and family members responded positively to the vaccination. Individuals with a constructive outlook regarding COVID-19 vaccines would recommend it to their friends, family and the community. Hence, we postulate that

H12: COVID-19 vaccine acceptance is related to subjective norms .

Fig 2 depicts the conceptual model of this study, while Table 1 summarizes the constructs and measurement items.

https://doi.org/10.1371/journal.pone.0261869.g002

https://doi.org/10.1371/journal.pone.0261869.t001

4. Materials and methods

We examined COVID-19 vaccine acceptance using a structured questionnaire. The survey questionnaire was answered using a five-point Likert scale, with 5 indicating strong agreement and 1 indicating strong disagreement. The model was evaluated using PLS-SEM. This study aims to predict the key target construct and test new hypotheses. We used the PLS-SEM technique to evaluate the model because it offers the required features. PLS-SEM has widely used to measure causal relations among indicators and to reveal pivotal connections between the latent constructs [ 75 , 76 ]. With the innovations in PLS simulations, PLS is a fully-fledged SEM approach [ 77 – 79 ].

4.1 Measurements of constructs and items

The Belief in conspiracy theory (BC) scale about COVID-19 vaccine was measured with a seven-item scale adopted from Brotherton et al. [ 34 ]. The adopted scales relate mostly to conspiracy belief about diseases or vaccines. We measured aawareness (AW) with a five-item scale adopted from Dinev and Hu [ 51 ]. PU, PU, and AB are measured on a three-item scale; slightly modified based on the purpose of the current study and adopted from Davis [ 62 ] and Thurasamy et al. [ 74 ]. Subjective norm (SN) is measured on a five-item scale adopted from Thurasamy et al. [ 74 ]. Finally, we measured COVID-19 vaccine acceptance (AV) using a four-item scale slightly modified for our context inspired by Davis et al. [ 64 ] and Taylor and Todd [ 66 ]. All the items were measured on a 5-point Likert scale ranging from 1 = strongly disagree, 3 = neutral, and 5 = strongly agree. The BC scale was reverse-coded. The questionnaire contains three parts. Part A contains demographic information; part 2 is on COVID-19 vaccine acceptance in terms of BC, AW, PU, PE, and the TRA. Finally, we asked some general questions about vaccines. We asked general questions in part 3 so that the respondents do not lose patience and answer the questions about the COVID-19 vaccine acceptance carefully.

4.2 Participants and data collection

The country was about to experience the third wave of COVID-19 at the time of this paper’s writing. The country-wide shutdown began with lockdowns. Almost all public universities are closed, and students are being housed in villages or in remote locations far from their universities. The best way to collect data was thus through an online survey. The ability to use an online survey is attributed to the proliferation of internet usage in Bangladesh as a result of increased government digitalization initiatives [ 80 ]. Using Google Forms, we created an online questionnaire and distributed the questionnaire to various universities’ Facebook pages. The most effective method was to ask teachers to distribute the questionnaire to different class and batch groups of students. Various Facebook Messenger and WhatsApp groups are being used during the pandemic to ensure proper communication with the students and to conduct online classes smoothly. Teachers distributed the survey to those groups, and the data were gathered from them between June 23rd and July 11th, 2021. We polled 351 respondents for their opinions. Participants in the survey were asked to provide informed consent. We kept a section in the Google form for respondents to express their open-ended opinions about the survey, and the majorities of respondents appreciated this research effort and see the survey as a medium to present their thoughts about the current pandemic and vaccination issues. 351 correct answers were used in this study, leaving out cases where the answers were incorrect or incomplete. In order to avoid overstating or exaggerating the study’s findings, all unmatched and incomplete cases were omitted. We include a mandatory step before submitting a response to the questionnaire in Google form to agree to the survey’s voluntary participation. The survey was conducted solely for research purposes and will not be used for commercial gain, with strict adherence to anonymity. Respondents were also assured that they could opt out of the study at any time. Table 2 contains the demographic information.

https://doi.org/10.1371/journal.pone.0261869.t002

4. 2. 1. Ethics statement.

Respondents provided informed consent and written statements about the voluntary participation, and their anonymity was strictly maintained. The study does not report a retrospective study of medical records or archived samples, and no minorities were reported.

Further, we asked the respondents in part 3 of the questionnaire to rank the currently available and approved vaccines (as of 15th June 2021) in Bangladesh. Moderna Vaccine is not included in the rank as it was approved in Bangladesh on 29th June, 2021 (see Fig 3 ). We also inquired whether or not the vaccine would be provided free of charge (see Fig 4 ).

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5.1 Measurement model

As a variance-based SEM technique, the PLS path model involved two sets of linear equations: the measurement model and the structural model. The measurement model stipulates the interactions between a construct and its observed indicators, while the structural model stipulates the interactions between the constructs [ 77 ]. The reflective indicators are measured in terms of internal consistency, indicator reliability, convergent validity, and discriminant validity. To assess indicator reliability, indicator loadings should be higher than 0.70. For internal consistency, the Cronbach’s alpha value should be higher than 0.70, although in exploratory studies, 0.6 is acceptable. [ 81 ]. Composite reliability should be higher than 0.70 (in exploratory research, 0.60 to 0.70 is considered acceptable) [ 82 ]. Convergent validity is indicated by the average variance extracted (AVE), which should be higher than 0.50. For discriminant validity, the AVE of each latent construct should higher than the construct’s highest squared correlation with any other latent construct (Fornell–Larcker criterion) and an indicator’s loadings should be higher than all of its cross loadings [ 83 ]. We deleted BC2 and BC4 as they had considerably lower loadings; all other loadings were above 0.70. The reliability and convergent validity were quite satisfactory. Table 3 summarizes the assessment of the measurement model.

https://doi.org/10.1371/journal.pone.0261869.t003

5.2 Structural model evaluation

The bootstrapping technique (resampling = 5,000 minimum) was implemented to evaluate the statistical significance of the path coefficients [ 82 ]. In this step, we examined the proposed relationships between the exogenous and endogenous variables by the path coefficient (β) and t- statistics at a significance level of 0.1% (p< .001) and 5% (p< .05). As Table 4 reports, all postulated hypotheses for this study are confirmed and all were significant. We provide the structural model test results in Fig 5 and Table 4 .

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https://doi.org/10.1371/journal.pone.0261869.t004

5.3 Predictive relevance, R 2 and Q 2

The R 2 indicates the variance explained in each of the endogenous constructs by the exogenous construct. It ranges from 0 to 1, with higher levels indicting more predictive accuracy. Hair et al. [ 82 ] advocated that R 2 values of 0.25, 0.50, or 0.75 for dependent constructs in the structural model can be treated as weak, moderate, or strong, respectively. We find moderate R 2 values for AB (0.412), SN (0.682), and AV (0.709), which are close to high, indicating that the proposed conceptual model explains an adequate portion of the variance in the COVID-19 vaccine acceptance.

The Q 2 value provides another means to assess a model’s predictive accuracy [ 84 , 85 ]. The Q 2 value builds on the blindfolding procedure, which omits single points in the data matrix, imputes the omitted elements, and estimates the model parameters. Using these estimates as input, the blindfolding procedure predicts the omitted data points. This process is repeated until every data point has been omitted and the model re-estimated. The smaller the difference between the predicted and the original values, the greater the Q 2 criterion and, thus, the model’s predictive accuracy and relevance. As a rule of thumb, Q 2 values larger than zero for a particular endogenous construct indicate that the path model’s predictive accuracy is acceptable for this particular construct [ 86 ]. Our Q 2 values for AB (0.299), SN (0.205), and AV (0.458) show good predictive relevance for the model of COVID-19 vaccine acceptance (see Table 5 ).

https://doi.org/10.1371/journal.pone.0261869.t005

6. Discussion, contribution, limitation and conclusion

6.1 discussion on the results.

We aim to assess the factors that influence COVID-19 vaccine acceptance in the context of the pandemic. As 62.96% of the respondents were between the ages of 19 and 22, this study included a young sample with a university education. Females made up 41.88% of those polled. This survey was carried out at various universities throughout Bangladesh. The highest number of respondents came from two universities in Dhaka, the capital city, namely Jagannath University (38.18%) and the University of Dhaka (27.17%). We obtained no responses from Barisal out of the eight divisions of Bangladesh, and the highest response from Dhaka, 54.99%.

According to the study’s findings, BC undermines COVID-19 vaccine acceptance. The results for H1, H2, and H3 show that BC has a negative impact on individual attitudes and subjective norms toward immunization, which ultimately has a negative effect on COVID-19 vaccine acceptance. Individual awareness (AW), on the other hand, has a strong positive influence on COVID-19 vaccine acceptance. The results for H4, H5, and H6 show that AW has a positive impact on attitude, subjective norms, and COVID-19 vaccine acceptance. Furthermore, according to the findings for H7, H8, H9, and H10, PU and PE have a positive impact on attitude, subjective norms, and acceptance of immunization to protect against COVID-19. Individuals’ positive attitudes toward acceptance and constructive subjective norms have a positive impact on vaccine acceptance, as stated in H11 and H12.

Individual BC and rumors about vaccine formulation, development, distribution, and even effectiveness would have a negative impact on willingness to immunize. These negative thoughts would spread as normative behavior among their social groups, communities, and circles of belonging, potentially jeopardizing the overall success of the immunization program. Individual-level awareness can spread good thoughts among individuals and groups, leading to vaccination success and a reduction in overall infection. The perception that vaccination can protect against COVID-19 virus infection, severe illness, and death, can make students more willing to take the vaccine and to encourage others in their community to do so. The perceived ease of registering for and receiving vaccines without hassle or difficulty and receiving vaccines at no cost would encourage more students to get vaccinated.

6.2 Contribution of the study

Protective behaviors are critical in pandemic management, and vaccination may be a key protective behavior for COVID-19. Theoretically, we evaluate factors influencing COVID-19 vaccine acceptance by combining TRA with BC, individual awareness level, PU, and PE. Thurasamy et al. [ 74 ] decomposed the TRA and stated that PU and PE affect attitude. We find that BC affects attitude and subjective norms negatively and that awareness (AW), PU, and PE affect attitudes, which also affects acceptance positively.

Additionally, each of these objects can directly impact acceptance without affecting attitude or subjective norms. In this study, the path relationship of BC on AB is BC-AB, subjective norms BC-SN, and vaccine acceptance BC-AV is theoretically unique. BC has a negative impact on AB, SN, and AV. Individual-level awareness is related to AB, AW-AB, subjective norms AW-SN, and vaccine acceptance. Theoretically, AW- AV is also distinct here. AW has a negative impact on AB, SN, and AV. We also find that PU and PE have a positive impact on individual attitudes toward vaccination, which leads to acceptance. Both PU and PE have a positive effect on AB and AV.

This study makes an important contribution to policy development. Bangladesh is already considered a high-risk country, with the highest daily positive rate of 22.6% and an average positive rate of more than 9% from January to June 2021. Many of these people were asymptomatic and thus more dangerous to others in unknowingly spreading the virus. Hence, all people require vaccinations. Due to an increase in COVID-19 cases and a lack of vaccination, the plan to reopen universities has been postponed several times. This study aims to understand vaccine acceptance behavior among young people who attend public universities, whose health is a concern, and who will lead the nation in the future. The findings of this study will assist policymakers in their effort to improve vaccination success in a developing country context such as Bangladesh.

6.3 Limitations

This study employs an online questionnaire survey rather than a face-to-face administration. Students took part in the survey during the COVID-19 pandemic, when they were likely to be worried, frustrated, and living in uncertainty. This type of survey can be conducted with people from various segments of society, and comparisons can be made between their attitudes, beliefs, level of awareness, and acceptance of vaccines. In addition, we found a strong relationship between predictor variables and endogenous constructs. This model can be further tested by including mediating or moderating variables such as age, gender, religious beliefs, previous vaccination history, and so on, to gain a thorough understanding and exploration of the other influential factors to guide policymakers and save humanity from the COVID-19 pandemic.

6.4 Conclusion

This study investigated the factors influencing COVID-19 vaccine acceptance, which is a critical issue in the fight against the pandemic. The respondents were public university students studying various courses at the graduate and postgraduate levels, who will lead the nation in the future. Misinformation and conspiracy theories harmed vaccination programs in the past, including the recent COVID-19 outbreak. It is a cause for concern that if university students believe in conspiracy theories, they will spread faster and discourage people from taking vaccines. Additionally, if they are aware, have a positive attitude and beliefs, find vaccination useful in combating COVID-19, and can obtain the vaccine easily and free of charge, they can spread positivity, which will spread rapidly. According to our findings, BC has a negative impact, whereas individual awareness has a positive impact on individual attitude toward vaccination; group beliefs, which represent subjective norms; and actual acceptance of vaccines. The PU of the vaccines in combating COVID-19 disease, as well as the ease of the vaccination process, would have a positive impact on attitudes toward vaccination and ultimately vaccination acceptance.

The relevant authorities should focus on campaigns that could reduce misinformation and conspiracy surrounding the COVID-19 vaccine. Awareness programs are more important than ever, and individual-level awareness raising programs are required. Universities are tertiary-level educational institutes where students prepare for their future careers. A greater sense of awareness (free from conspiracy belief), usefulness of the vaccines, and ease of getting the vaccine would definitely help students immunize through the COVID-19 vaccine. If students are encouraged to believe that a vaccination certificate will be required to return to classes, continue their education, apply for full- or part-time jobs, apply for competitive government recruitment examinations, and that it may be necessary to travel abroad for higher education or a better job, they will gladly vaccinate themselves. Furthermore, easy, cost-free access to the vaccine will encourage them to get vaccinated. Because no medicine has yet been invented, vaccination is the only way to reduce infection, spread, serious illness, and deaths. Vaccination is the most effective way to protect individuals, families, and society as a whole. Families and communities will be able to gradually return to a more normal routine as more people are vaccinated.

Supporting information

https://doi.org/10.1371/journal.pone.0261869.s001

Acknowledgments

The authors express their gratitude to the anonymous reviewers for their insightful comments. We appreciate the time and effort of the survey respondents who participated voluntarily and made this research possible in the midst of the pandemic and strict lockdowns.

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DHS Statement on Equal Access to COVID-19 Vaccines and Vaccine Distribution Sites

DHS and its Federal government partners fully support equal access to the COVID-19 vaccines and vaccine distribution sites for undocumented immigrants. It is a moral and public health imperative to ensure that all individuals residing in the United States have access to the vaccine. DHS encourages all individuals, regardless of immigration status, to receive the COVID-19 vaccine once eligible under local distribution guidelines.

DHS carries out its mission, including all areas within its COVID-19 response, without discrimination on the basis of race, ethnicity, nationality, or other protected class, and in compliance with law and policy. Further, DHS supports the equitable and efficient distribution of the COVID-19 vaccine to all populations, including historically underserved communities.

To reach underserved and rural communities, the Federal Emergency Management Agency (FEMA), in collaboration with federal partners, will coordinate efforts to establish and support fixed facilities, pop-up or temporary vaccination sites, and mobile vaccination clinics. U.S. Immigration and Customs Enforcement (ICE) and U.S. Customs and Border Protection will not conduct enforcement operations at or near vaccine distribution sites or clinics. Consistent with ICE’s long-standing sensitive locations policy, ICE does not and will not carry out enforcement operations at or near health care facilities, such as hospitals, doctors' offices, accredited health clinics, and emergent or urgent care facilities, except in the most extraordinary of circumstances.

DHS is committed to ensuring that every individual who needs a vaccine can get one, regardless of their immigration status.

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Public statement for collaboration on COVID-19 vaccine development

Last updated 16 April 2020

On 31 December 2019, WHO was informed of a cluster of cases of pneumonia of unknown cause detected in Wuhan City, Hubei Province of China. Chinese authorities identified the SARS-CoV-2 as the causative virus on 7 January 2020, and the disease was named coronavirus disease 2019 (COVID-19) by WHO on 11 February 2020. As part of WHO’s response to the outbreak, a Research and Development (R&D) Blueprint has been activated to accelerate the development of diagnostics, vaccines and therapeutics for this novel coronavirus.

Under WHO’s coordination, a group of experts with diverse backgrounds is working towards the development of vaccines against COVID-19.

The group makes a call to everyone to follow recommendations to prevent the transmission of the COVID-19 virus and protect the health of individuals. The group also thanks everyone for putting their trust in the scientific community.

Declaration

We are scientists, physicians, funders and manufacturers who have come together as part of an international collaboration, coordinated by the World Health Organization (WHO), to help speed the availability of a vaccine against COVID-19. While a vaccine for general use takes time to develop, a vaccine may ultimately be instrumental in controlling this worldwide pandemic. In the interim, we applaud the implementation of community intervention measures that reduce spread of the virus and protect people, including vulnerable populations, and pledge to use the time gained by the widespread adoption of such measures to develop a vaccine as rapidly as possible. We will continue efforts to strengthen the unprecedented worldwide collaboration, cooperation and sharing of data already underway. We believe these efforts will help reduce inefficiencies and duplication of effort, and we will work tenaciously to increase the likelihood that one or more safe and effective vaccines will soon be made available to all.

Signatories in alphabetical order

Randy A. Albrecht, Icahn School of Medicine at Mount Sinai, USA

Mohamad Assoum, Mercy Global Health

Luigi Aurisicchio, on behalf of Takis Biotech, Italy

Dan Barouch, Center for Virology and Vaccine Research, USA

Trevor Brasel, The University of Texas Medical Branch (UTMB), USA

Jennifer L Bath, ImmunoPrecise Antibodies, Canada

Sina Bavari, Edge BioInnovation Consulting and Management, USA

Maria Elena Bottazzi, Baylor College of Medicine, Houston, USA

Gerhard Beck, Austrian Medicines and Medical Devices, Austria

Tom Brady, Flow Pharma Inc, USA

Kate Broderick, Inovio, USA

Will Brown, Altimmune Inc, USA

Dirk Busch, Maura Dandri, Dirk Heinz and Hans-Georg Kraeusslich, on behalf of the German Center for Infection Research - DZIF, Germany

Scot Bryson, Orbital Farm, Canada

Ricardo Carrión, Texas Biomedical Research Institute, USA

Miles Carroll, Public Health England, UK

Keith Chappell, University of Queensland, Australia

Daniel S. Chertow, National Institutes of Health, U.S. Department of Health and Human Services, USA

Sandra Cordo, Universidad de Buenos Aires, Argentina

Wian de Jongh, on behalf of the Prevent n-CoV consortium (AdaptVac, ExpreS2ion, Copenhagen University, Leiden University Medical Centre, Wageningen University and Tubingen University)

Natalie Dean, University of Florida, USA

Rafael Delgado, Hospital Universitario 12 de Octubre, Spain

Dimiter Dimitrov

David A. Dodd, GeoVax, Inc., USA

Paul Duprex, Center for Vaccine Research, University of Pittsburgh, USA

Luis Enjuanes; Centro Nacional Biotecnología, Spain

Jeremy Farrar, Josie Golding, Charlie Weller, on behalf of Wellcome Trust, UK

Mark Feinberg, Swati Gupta and Ripley Ballou, on behalf of IAVI, USA

Antonella Folgori, on behalf of ReiThera, Italy

Thomas Friedrich, University of Wisconsin, School of Veterinary Medicine, USA

Simon Funnel, Public Health England, UK

Luc Gagnon, Nexelis, Canada

Adolfo Garcia-Sastre, Icahn School of Medicine at Mount Sinai, USA

Vipin Garg, Altimmune Inc., USA

Volker Gerdts, on behalf of VIDO-Intervac, University of Saskatchewan, Canada

Nora Gerhards, Wageningen Bioveterinary Research, The Netherlands

Christiane Gerke, Head of Vaccine Programs/Head of Vaccine Innovation Development, Institut Pasteur, France

Carlo Giaquinto, Department of Women and Child Health, University of Padova, Italy

Prakash Ghimire, Tribhuvan University, Nepal

Nikolaj Gilbert, Program for Appropriate Technology in Health (PATH), USA

Sarah Gilbert, University of Oxford, UK

Marion F. Gruber, Food and Drug Administration, U.S. Department of Health and Human Services, USA

Farshad Guirakhoo, GeoVax Inc, USA

Bart L Haagmans, Erasmus Medical Center, The Netherlands

M. Elizabeth Halloran, Center for Inference and Dynamics of Infectious Diseases, Fred Hutchinson Cancer Research Center, and University of Washington, USA

Scott Harris, Altimmune Inc, USA

Hideki Hasegawa, National Institute of Infectious Diseases, Japan

Richard Hatchett, on behalf of the Coalition for Epidemic Preparedness Innovations (CEPI), Norway

James Hayward, Applied DNA Sciences, USA

Sheri Ann Hild

Peter Hotez, Baylor College of Medicine, USA

Youngmee Jee, Seoul National University, College of Medicine, Republic of Korea

Charu Kaushic, Institute of Infection and Immunity, Canadian Institutes of Health Research (CIHR), Government of Canada

Alyson A. Kelvin, Dalhousie University, Canada

Larry D. Kerr, Office of Global Affairs, U.S. Department of Health and Human Services, USA

Bernard Kerscher, PEI, Germany

Jae-Ouk Kim, International Vaccine Institute, Republic of Korea

Seungtaek Kim, Institut Pasteur Korea, Republic of Korea

Jason Kindrachuk, University of Manitoba, Canada

Otfried Kistner, Senior Consultant and Independent Vaccine Expert, Austria

Gary Kobinger, Université Laval, Canada

Marion Koopmans, Viroscience Department, Erasmus Medical Centre, The Netherlands

Jeroen Kortekaas, Wageningen Bioveterinary Research, the Netherlands

Philip R. Krause, Food and Drug Administration, U.S. Department of Health and Human Services, USA

Greg Kulnis, Nexelis, Canada

Paul Henri Lambert, Centre of Vaccinology, University of Geneva, Switzerland

Nathalie Landry, Medicago Inc., Canada

Roger Le Grand, Inserm-CEA-Université Paris Saclay, France

Robin Levis, Food and Drug Administration, U.S. Department of Health and Human Services, USA

Mark G Lewis, Bioqual Inc, USA

Joshua Liang, Clover Biopharmaceuticals, China

Jinzhong Lin, on behalf of Fudan University, China

Ira Longini, University of Florida, USA

Shabir Madhi, University of the Witwatersrand, Johannesburg, South Africa

Jessica E. Manning, National Institutes of Health, U.S. Department of Health and Human Services, USA

Peter Marks, Director, on behalf of Food and Drug Administration/Center for Biologics Evaluation and Research

Hilary D. Marston, National Institutes of Health, U.S. Department of Health and Human Services, USA

Federico Martinón-Torres, Hospital Clínico Universitario de Santiago de Compostela, Spain

Sebastian Maurer-Stroh, on behalf of the GISAID Initiative

John W. Mellors, University of Pittsburgh School of Medicine, USA

Ali Mirazimi, Department of Laboratory medicin, Karolinska institutet, Sweden

Kayvon Modjarrad, Walter Reed Army Institute of Research, USA

Stefan O. Mueller, CureVac, Germany

Vincent J. Munster, National Institutes of Health, U.S. Department of Health and Human Services, USA

César Muñoz-Fontela, Bernhard-Nocht-Institute for Tropical Medicine, Germany

Aysegul Nalca, U.S. Army Medical Research Institute of Infectious Diseases (USAMRIID), USA

José Manuel Ochoa, Altimmune Inc., USA

Dave O'Connor, University of Wisconsin-Madison, USA

Lidia Oostvogels, CureVac, Germany

Nisreen M. A. Okba, Erasmus Medical Center, The Netherlands

L. Jean Patterson, National Institutes of Health, U.S. Department of Health and Human Services, USA

Joe Payne, on behalf of Arcturus Therapeutics

Jonathan Pearce, on behalf of the UK Research and Innovation (UKRI) and the Medical Research Council (MRC), UK

Stanley Perlman, University of Iowa, USA

Margaret Louise Pitt, WRAIR/ U.S. Army Medical Research Institute of Infectious Diseases (USAMRIID), USA

Anuradha Poonepalli, Health Products Regulation Group, Health Sciences Authority, Singapore

Dieter Pullirsch, Austrian Medicines and Medical Devices Agency, Austria

Damian Purcell, Doherty Institute, Australia

Chuan Qin, Institute of Laboratory Animal Sciences (ILAS), CAMS & PUMC, China

Angela Rasmussen, Columbia University Mailman School of Public Health, USA

Scott Roberts, Altimmune Inc., USA

Estefania Rodriguez, Bernhard Nocht Institute for Tropical Medicine, Germany

Ted M Ross, Center for Vaccines and Immunology, University of Georgia, USA

Chad J Roy, Tulane National Primate Research Center and Tulane School of Medicine, USA

Reid Rubsamen, Flow Pharma Inc, USA

Anna Laura Salvati, Italy

Andrew Satz, EVQLV Inc, USA

Hanneke Schuitemaker and Johan Van Hoof, on behalf of Janssen Pharmaceuticals Companies of Johnson & Johnson, USA

Robert Shattock, Imperial College, UK

John Shriver, Sanofi, USA

Gale Smith, Novavax Inc. USA

Peter Smith, London School of Hygiene and Tropical Medicine, UK

Isabel Sola, Centro Nacional Biotecnología, Spain

James Southern, Adviser to South African Health Products Regulatory Authority

Ryan Spencer and David Novack, on behalf of Dynavax Technologies Corporation, USA.

Jonathan M Spergel, Children’s Hospital of Philadelphia, Perelman School of Medicine at University of Pennsylvania, USA

Sybil Tasker, Codagenix Inc, USA

Chien-Te Kent Tseng, University of Texas Medical Branch, Galveston, Texas, USA

U.S. Department of Health and Human Services, USA, Assistant Secretary for Preparedness and Response/Biodefense Advanced Research and Development Authority

U.S. Department of Health and Human Services, USA, Centers for Disease Control and Prevention

Jean Marie Vianney Habarugira, on behalf of the European & Developing Countries Clinical Trials Partnership (EDCTP)

Veronika von Messling, on behalf of German Federal Ministry of Education and Research, Germany

Tony T. Wang, Food and Drug Administration, U.S. Department of Health and Human Services, USA

Jeffrey Wolf, Heat Biologics Inc, USA

Ningshao Xia, Xiamen University of China, China

Yingjie Xu, on behalf of Shanghai Jiaotong University, China

Paul R Young, University of Queensland, Australia

Hang Yu, on behalf of Shanghai RNACure, China

Xuefeng Yu, CanSino Biologics, China

Tal Zaks, on behalf of Moderna, USA

Peter Daszak, President, EcoHealth Alliance, New York, USA

Media Contacts

Tarik Jasarevic

Spokesperson / Media Relations WHO

Research and Development (R&D) Blueprint

Coronavirus disease (COVID-2019) R&D

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Oxford University/AstraZeneca vaccine authorised by UK medicines regulator

Government update on the Oxford University/AstraZeneca COVID-19 vaccine.

The government has today accepted the recommendation from the Medicines and Healthcare products Regulatory Agency (MHRA) to authorise Oxford University/AstraZeneca’s COVID-19 vaccine for use. This follows rigorous clinical trials and a thorough analysis of the data by experts at the MHRA, which has concluded that the vaccine has met its strict standards of safety, quality and effectiveness.

The Joint Committee on Vaccination and Immunisation (JCVI) will also publish its latest advice for the priority groups to receive this vaccine.

The NHS has a clear vaccine delivery plan and decades of experience in delivering large scale vaccination programmes. It has already vaccinated hundreds of thousands of patients with the Pfizer/BioNTech vaccine and its roll out will continue. Now the NHS will begin putting their extensive preparations into action to roll out the Oxford University/AstraZeneca vaccine.

Throughout this global pandemic we have always been guided by the latest scientific advice. Having studied evidence on both the Pfizer/BioNTech and Oxford University/AstraZeneca vaccines, the JCVI has advised the priority should be to give as many people in at-risk groups their first dose, rather than providing the required two doses in as short a time as possible.

Everyone will still receive their second dose and this will be within 12 weeks of their first. The second dose completes the course and is important for longer term protection.

From today the NHS across the UK will prioritise giving the first dose of the vaccine to those in the most high-risk groups. With 2 vaccines now approved, we will be able to vaccinate a greater number of people who are at highest risk, protecting them from the disease and reducing mortality and hospitalisation.

The JCVI’s independent advice is that this approach will maximise the benefits of both vaccines. It will ensure that more at-risk people are able to get meaningful protection from a vaccine in the coming weeks and months, reducing deaths and starting to ease pressure on our NHS.

To aid the success of the vaccination programme, it is vital everyone continues to play their part, abides by the restrictions in their area and remembers hands, face, space so we can suppress this virus and allow the NHS to do its work without being overwhelmed.

Further details will be set out shortly.

See the press release on the second COVID-19 vaccine authorised by the medicines regulator and the statement from the UK Chief Medical Officers on the prioritisation of first doses of COVID-19 vaccines .

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Perspectives on the COVID-19 vaccine uptake: a qualitative study of
Objective Since introduction of the programme in April 2021, COVID-19 vaccine uptake has been low at less than 20%. This study explored community members' and health workers' perspectives on the COVID-19 vaccine uptake and its influencing factors in Zambia. Study design A qualitative study employing focus group discussions (FGDs) and in-depth interviews (IDIs). Study setting Sixteen ...
A model of factors influencing COVID-19 vaccine acceptance: A ...
The aim of this study is to investigate the key factors influencing the acceptance of COVID-19 vaccines and develop a model based on the theory of reasoned action, belief in conspiracy theory, awareness, perceived usefulness, and perceived ease of use. The authors created and distributed a self-administered online questionnaire using Google Forms. Data were collected from 351 respondents ...
The Perception and Attitudes toward COVID-19 Vaccines: A Cross
Vaccine hesitancy is a major threat to the success of COVID-19 vaccination programs. The present cross-sectional online survey of adult Poles (n = 1020) expressing a willingness to receive the COVID-19 vaccine was conducted between February and March 2021 and aimed to assess (i) the general trust in different types of vaccines, (ii) the level of acceptance of the COVID-19 vaccines already in ...
DHS Statement on Equal Access to COVID-19 Vaccines and Vaccine
DHS encourages all individuals, regardless of immigration status, to receive the COVID-19 vaccine once eligible under local distribution guidelines. DHS carries out its mission, including all areas within its COVID-19 response, without discrimination on the basis of race, ethnicity, nationality, or other protected class, and in compliance with ...
Strategies to Address COVID-19 Vaccine Hesitancy and Mitigate Health
Introduction. The COVID-19 pandemic has delivered many sobering lesson-among the most pressing the need to confront disparities in COVID-19 outcomes in minority communities 1.Disproportionate rates of infection and death from COVID-19 within communities of color have laid bare the tragic consequences of systemic and pervasive inequities in medical care and working, living, and environmental ...
Public statement for collaboration on COVID-19 vaccine development
Under WHO's coordination, a group of experts with diverse backgrounds is working towards the development of vaccines against COVID-19. The group makes a call to everyone to follow recommendations to prevent the transmission of the COVID-19 virus and protect the health of individuals. The group also thanks everyone for putting their trust in ...
Increase of Hepatitis B Surface Antibody Levels After Inactivated COVID
The patients with a history of kidney transplant and those with a history of COVID-19 had significant differences between anti-HBs-B3 and anti-HBs-A3 (p = 0.002, p = 0.003, respectively). Conclusion. Our findings revealed that inactivated COVID-19 vaccine may be involved in the humoral immune response to hepatitis B in HD patients.
Oxford University/AstraZeneca vaccine authorised by UK medicines
See the press release on the second COVID-19 vaccine authorised by the medicines regulator and the statement from the UK Chief Medical Officers on the prioritisation of first doses of COVID-19 ...

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Introduction

Ethics of mandatory COVID-19 vaccination

Grave threat to public health

Vaccine is safe and effective

Better than the alternatives

Conscription in war

Pre-existing mandatory vaccination

Coercion is proportionate

Better than coercion? Payment for risk

Undue influence?

Practical advantages

Payment in kind

Acknowledgments

Supplementary materials

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Social science and the COVID-19 vaccines

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Intent versus action

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U.S. Food and Drug Administration

Joint CDC and FDA Statement on Johnson & Johnson COVID-19 Vaccine

The following statement is attributed to Dr. Peter Marks, director of the FDA’s Center for Biologics Evaluation and Research and Dr. Anne Schuchat, Principal Deputy Director of the CDC

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Data availability statement

Statistics from Altmetric.com

STRENGTHS AND LIMITATIONS OF THIS STUDY

Introduction

Study design

Study setting

Participants and sampling technique

In-depth Interviews

Eligibility criteria

Supplemental material

Data collection

Data collection tools

The data management and analysis

Quality assurance and control

Patient and public involvement

Demographics

Theme 1: perspectives on acceptance of the COVID-19 vaccine