FormalPara Key Points for Decision Makers

High willingness to financially contribute to coronavirus disease 2019 (COVID-19) vaccine procurement, either partially or fully, highlights the significant importance of vaccination in combating the pandemic, from the public perspective.

The unaffected willingness to contribute to financing vaccines, whether imported or domestically produced, indicates that achieving higher protection against the pandemic is more important than the vaccine country of origin.

Individuals in higher socioeconomic groups are significantly more likely to contribute to vaccine financing, suggesting the importance of addressing socioeconomic disparities in vaccine financing to support health systems in controlling pandemics.

1 Introduction

The coronavirus disease 2019 (COVID-19) pandemic has led to international attempts to discover a vaccine for preventive strategies because of the disease's high mortality rates as well as its catastrophic consequences for the world [1,2,3]. Several vaccines have been developed and distributed globally to overcome these problems [4, 5]. Epidemiologists consider an effective vaccine essential for herd immunity in disease pandemics, although people's uptake rate and their acceptance of the vaccines play an essential role in the success of vaccination programs [6,7,8]. The potential acceptance rate for the COVID-19 vaccine was 71.5% in a sample of 13,426 participants over 19 countries [9], although it does not reflect people's monetary valuation of the COVID-19 vaccines.

Willingness to pay (WTP) for the COVID-19 vaccines was addressed in some studies to estimate the monetary value of vaccines, and the majority of the studies were performed during the first- and second-wave peak of the COVID-19 crisis across the world. For instance, the mean WTP for the COVID-19 vaccine in a sample of 566 Chileans was about $US184 per person, and was 1.09% of the country's gross national product (GNP) based on the study by García and Cerda [10]. The WTP of 1050 Ecuadorians for the vaccine ranged from $US147 to $US196, and their WTP for vaccines with higher protection was 30% more than the average value [11]. Most Nigerian people were unwilling to pay for the COVID-19 vaccine because of its unaffordability, although the WTP for the vaccine increased in proportion to income [12]. Meshkani et al. found that the mean WTP was about US$22 per person for a hypothetical vaccine, with more than 80% efficacy and one-time vaccination in a sample of Iranians surveyed from 2 to 20 May 2020 [13]. In that study, positive WTP was about 80% (of 878 participants), while another Persian study by Adeli and Rahimikahkashi in 2021, with 370 participants, found a positive WTP of around 66%. Their average WTP by contingent valuation method for long-term vaccination was US$16.3 [14]. The study by Soofi et al. on Iranians’ WTP for the vaccine revealed 90.87% positive WTP, with an estimated mean of US$60.13 [15]. However, it should be mentioned that the absolute amount of the WTP value is insufficient evidence for policymaking, particularly in reimbursement policies, and identifying the most affected variables in paying for vaccines is critical. These studies revealed that different factors affect the monetary value of the COVID-19 vaccine. For example, two important factors for the WTP for the COVID-19 vaccine were its efficacy rate and duration of protection, based on a national survey with 1285 individuals in the United States (US) in the initial week of November 2020. This survey coincided with the dissemination of news about vaccine development in the media, although no vaccine had yet obtained US FDA approval [16]. Income, pre-existing conditions of household members, and perceived risk of the COVID-19 virus were the other significant variables [16]. The presence of chronic and coronary heart diseases, knowledge about COVID-19 vaccination, and occupation were among the variables causing differences in the WTP for the vaccine in China. In this way, healthcare workers reported a higher WTP for the vaccine, which was attributed to their risk perception for the virus [17]. The study on the Iranian population also revealed that in addition to efficacy, self-assessment virus risk, age, gender, education, income, and working in the health sector were significant factors [13].

One of the main issues seemingly overlooked in preference studies for the COVID-19 vaccine is the financing of vaccination programs in the long term [18, 19]. This may be because of the timing, as most WTP studies were conducted in the first and subsequent peaks of the pandemic before the vaccines were developed. Similar situations are observed in studies conducted in Iran [13, 15]. Therefore, besides estimating the monetary value of the vaccines from the general public's perspective, which can vary due to diversity in WTP elicitation methods, socioeconomic variables and psychological factors, understanding the public's preferences for financing of vaccination programs, as the primary stakeholder, becomes pivotal. This understanding plays a crucial role in developing successful long-term financing policies, particularly for low- and middle-income countries.

The current study was conducted aiming to explore Iranian preferences to participate in vaccine financing, at different levels of public/government participation and the contributing factors. The second aim was to re-estimate the stated WTP value, because the previous studies, as mentioned earlier, were conducted at the beginning of the COVID-19 pandemic, which may have biased the WTP values by psychological factors such as virus fear, anxiety, depressive symptoms and lack of knowledge about the vulnerability of the virus. Over time, the individuals' perceptions of the COVID-19 threat have become more objective due to increased exposure to COVID-19 and its consequential impacts [16]. As a result, people's decision making about vaccination, including willingness to vaccinate and WTP, is likely different from their initial reactions and necessitates conducting such studies. Additionally, this idea can be supported by the recent findings from a panel survey, encompassing longitudinal data from 24,952 adults across seven European countries between 2020 and 2022, highlighting the dynamic nature of COVID-19 vaccine intentions over time. [20]

2 Methods

2.1 Study Design

During the third wave of COVID-19 in Iran and the onset of vaccination against COVID-19 with globally approved vaccines, we conducted a cross-sectional survey using various data collection methods, including in-person and online questionnaires, from 1 to 20 February 2021.

2.2 Study Instrument

The survey instrument was an updated self-administered questionnaire (Online Resource 1) that was based on a previous study for eliciting public preference for a hypothetical COVID-19 vaccine [13]. The questionnaire had three sections: socioeconomic and demographic information of respondents and their households; the health status of respondents; COVID-19 risk perception and personal experience with the virus and stated preference for COVID-19 vaccines. However, since the previous study was conducted before developing and approving COVID-19 vaccines, we improved and updated the vaccine preference section by considering recently approved vaccines worldwide and a scenario for a domestically produced vaccine in future months.

To do this, a sequential questioning approach was taken, i.e., a three-layered question was asked to understand respondents' preference for contributing to vaccine financing as follows.

  • Initially, respondents were asked if they would pay for vaccines if they were not available for free, with different response options ranging from yes at any price to an undecided or definite refusal (Q3: Layer 1).

  • Respondents showing a positive WTP for vaccination were provided details about the approved vaccines, including vaccine names, originating country (Russia, China, US, and forthcoming Iranian vaccines), needed dose, total cost in US dollars, and the international and local agencies that provided the vaccine approval. They were then asked about their preferences regarding financial contributions, choosing among three alternatives that spanned from full or partial government financial contribution to a complete user-fee payment option (Q3: Layer 2)

  • For respondents selecting government contribution options, a follow-up question examined their preference based on a payment scale concerning the proportion of the vaccine cost that the government should bear, providing choices of 25%, 50%, and 75% (Q3: Layer 3)

Furthermore, to have a better picture of Iranians’ WTP for the domestic vaccine, for respondents who had stated a preference for partial contribution in vaccine financing (25%, 50%, or 75%), the weighted mean of their willingness to contribute for two doses was calculated in three price scenarios based on the lowest, average, and highest vaccine prices that were presented to the respondents for the Chinese, Russian, and FDA-approved vaccines in the survey questionaries, accordingly. It should be mentioned that this approach was employed because during the study period, the Iranian vaccine was still in production and did not have an established price.

Considering the highlighted changes, before the launch of the survey the face validity of this questionnaire was assessed by experts through a focus group consisting of two pharmacoeconomists, a community-medicine specialist, an epidemiologist, and three health/pharmaceutical policymakers. The questionnaire was revised in line with these comments. Lastly, the clarity, comprehensibility, and appropriateness of the final questionnaire were confirmed and a pilot study was then administered to 50 respondents to check the reliability of the questionnaire (Cronbach’s alpha = 0.86).

2.3 Sample

The target population was adults aged 18 years and above. For the face-to-face survey that was conducted in Shiraz, the capital of the Fars province (south of Iran), a random sampling method was employed considering location, age and gender proportion. Hence, Shiraz was divided into five geographical clusters, including North, South, East, West, and the Center. To define the proportion sample size of each geographical zone, the pedestrian traffic at the three main streets of each zone during rush hour was measured.

There was no sampling framework for the online survey, however at the beginning of the survey, a focal point (typically a health economist academic colleague from a collaborating research center at the university in each province) was selected as the start point to disseminate the questionnaire link. Hence, the questionnaire was distributed randomly through a snowball method. Participants could anonymously respond or forward the link. It should be mentioned an invitation letter and a written consent form that included information about research purposes and ethical issues were provided. The final sample consisted of 2071 respondents, after excluding incomplete and invalid responses. As shown in Table 1, the face-to-face survey constituted 60% of the overall sample, while the remaining 40% of the population sample was obtained through an online survey. Details regarding the distribution of the online survey sample are presented in Table A1 (Online Resource 2).

Table 1 Sample size and distribution
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2.4 Statistical Analysis

We modeled determinants of public preference for financing Iranian, Chinese, Russian, and FDA-approved vaccines using ordered probit models; an ordered-probit analysis requires specifying a latent variable. In our model, the latent variable is a continuous variable representing people's willingness to contribute to financing available vaccines. The observed variable is five categories of people's willingness to finance vaccines from 0 to 100% of the price in 25% increments. Five categories resulted from participant responses to a three-part question: first, WTP for vaccination; second, preference for financing options, including full or partial government contribution, or user fee payment; and third, for those choosing government contribution, preference for the proportion of vaccine cost, with options of 25%, 50%, or 75%. Individuals without an interest in financing the vaccine were included in the first category (0); individuals who were interested in vaccination, even if they had to pay the full cost, were in the last category (100%); and for the remaining individuals, preference for government contribution was asked on a 3-point scale, i.e. 25%, 50%, and 75% of the vaccine price, which indicated to us those who were interested in paying 75%, 50%, or 25% of the price, respectively. Public preference for financing different vaccines is determined by Eq. 1.

$${f}^{*}={\beta }_{0}+{\beta }_{1}Hj+{\beta }_{2}Hs+{\beta }_{3}D+{\beta }_{4}{E}_{i}+{\beta }_{5}{E}_{f}+{\beta }_{6}{N}_{i}+{\beta }_{7}{N}_{f}+{\beta }_{8}I+{\beta }_{9}L+\gamma DEI+\delta {X}_{i}+u$$
(1)

where \(u\) is normally distributed with mean zero and variance normalized to unity. Equation 1 can be written in compact form as \({f}^{*}=\beta X+u\). The regressors listed in Eq. 1 are as follows.

  • Hj is a dummy variable that is equal to 1 if the respondent is working in the health sector, or a value equal to 0 otherwise.

  • Hs gives the self-reported health status of participants in ascending order.

  • D is a 5-level Likert item indicating the perceived risk of COVID-19 in ascending order.

  • \({E}_{i}\) is a 5-level Likert item indicating participants' perceived exposure to COVID-19 in ascending order. Similarly, \({E}_{f}\) measures participants' perceived exposure to family members.

  • \({N}_{i}\) is a dummy variable that takes a value of 1 if the respondent has non-communicable diseases, and a value of 0 otherwise. Similarly, \({N}_{f}\) measures whether family members have non-communicable diseases.

  • I is a 4-level Likert item indicating the participant's history of infection with COVID-19 in ascending order from no such record to be hospitalized.

  • L is a dummy variable that takes a value of 1 if the respondent has lost a family member due to COVID-19, and a value of 0 otherwise.

The vector \({X}_{i}\) contains a number of subject-specific control variables as follows.

  • Income is the participants' income with five categories, starting at none and moving to < 30 million Rials, > 30 and < 70 million Rials, > 70 and < 100 million Rials, and > 100 million Rials.

  • Age gives the self-reported age of participants.

  • Gender is a dummy variable and takes a value of 0 for males and 1 for females.

  • Education gives self-reported education levels in ascending order.

  • Family size is the size of the respondents' families.

  • Head is a dummy variable that takes a value of 1 for family heads and a value of 0 otherwise.

  • City is a dummy variable that takes a value of 1 if the participant is living in a city and a value of 0 otherwise.

  • Insurance is a dummy variable that takes a value of 1 if the participant has basic insurance and a value of 0 otherwise.

  • Insurance supplement is a dummy variable that takes a value of 1 if the participant has supplementary insurance and a value of 0 otherwise.

  • \(D{E}_{i}\) is the interaction term between \(D\) and \({E}_{i}.\)

Introducing constants \({c}_{1}\),\({c}_{2}\), \({c}_{3}\), and \({c}_{4}\) (to be determined in the ordered probit regression analysis), the ordered dependent variable is related to the latent variable in Eq. 1, as shown in Eqs. 2–6 below.

$$f=0 {\text{if respondent declared no interest for financing the vaccine}}, {f}^{*}<{c}_{1}$$
(2)
$$f=1 {\text{if respondent was willing to pay }}25{\text{\% of the vaccine price}}, {c}_{1}<{f}^{*}<{c}_{2}$$
(3)
$$f=2 {\text{ if respondent was willing to pay }}50{\text{\% of the vaccine price}}, {c}_{2}<{f}^{*}<{c}_{3}$$
(4)
$$f=3 {\text{if respondent was willing to pay }}75{\text{\% of the vaccine price}}, {c}_{3}<{f}^{*}<{c}_{4}$$
(5)
$$f=4 {\text{if respondent was willing to pay }}100{\text{\% of the vaccine price}}, {c}_{4}<{f}^{*}$$
(6)

Using our assumptions on the error term and the expression in Eq. 1, denoting probability by P and the cumulative distribution function of the normal distribution by \(\phi \), we have (Eqs. 7–11):

$$P\left(f=0\right)=P\left({f}^{*}<{c}_{1}\right)=P\left(u<{c}_{1}-\beta X\right)=\phi ({c}_{1}-\beta X)$$
(7)
$$P\left(f=1\right)=P\left({{c}_{1}<f}^{*}<{c}_{2}\right)=\phi \left({c}_{2}-\beta X\right)-\phi ({c}_{1}-\beta X)$$
(8)
$$P\left(f=2\right)=P\left({{c}_{2}<f}^{*}<{c}_{3}\right)=\phi \left({c}_{3}-\beta X\right)-\phi ({c}_{2}-\beta X)$$
(9)
$$P\left(f=3\right)=P\left({{c}_{3}<f}^{*}<{c}_{4}\right)=\phi \left({c}_{4}-\beta X\right)-\phi ({c}_{3}-\beta X)$$
(10)
$$P\left(f=4\right)=P\left({{c}_{4}<f}^{*}\right)=1-\phi ({c}_{3}-\beta X)$$
(11)

Thus, we analyzed how different factors influence people's likelihood of choosing to cover 0%, 25%, 50%, 75%, or 100% of the vaccine price. The ordered probit regression coefficient is the marginal index effect on the average value of the latent variable conditional on the data, E[f^* |.]. The marginal probability effects describe the change in probability of being in a particular category, P(f = k),k = 0,1,2,3,4, which arises from a unit change in an explanatory variable.

3 Results

3.1 Summary Statistics

In total, 2071 respondents completed the questionnaire. Respondents were located in all 31 provinces of Iran (Online Resource 2, Table A1). The mean age of respondents was 38 ± 13.39 years; 50.7% (1049 individuals) were female, 889 (42.9%) had a university degree, and 280 (13.5%) were health workers. The monthly family income of respondents was mainly (about 45%) in the range of 30,000,000–70,000,000 Rials (US$130.4–US$304.3). During the survey, 23% of respondents stated that they or their family members were confirmed cases of COVID-19 (n = 462); 51.1% (n = 1058) of participants or their family members did not have a chronic disease, while the remainder did. More than 75% (n = 1557) of participants perceived the risk of COVID-19 as high or very high (for more detail, see Online Resource 2, Table A2).

Table 2 Determinants of public preference for financing COVID-19 vaccines
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3.2 Preference for Financing Options

As shown in Fig. 1, the majority of respondents stated that they would be willing to be vaccinated if the government funded the COVID-19 vaccine either fully or partially. Public preference for financing vaccines is not related to the country of origin.

Fig. 1
figure 1

Preferences for financing the COVID-19 vaccine. COVID-19 coronavirus disease-19

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About 40% of respondents stated that they were willing to be vaccinated if the vaccine was free, and about 35% indicated they were willing to be vaccinated in the case of partial contribution; 20–25% accepted the full out-of-pocket user fee financing option.

3.3 Determinants of Public Preference for Contribution in Financing Coronavirus Disease 2019 (COVID-19) Vaccines

Table 2 presents the determinants of public preference for financing COVID-19 vaccines. We estimated the ordered-probit model for all four vaccines using maximum likelihood methods. In column 1, we show the preferences to finance the Iranian vaccine as the dependent variable, and in columns 2–4, the dependent variable corresponds to preferences for financing the Chinese, Russian, and FDA-approved vaccines, respectively.

In all four models, the significant coefficients have the same sign. The coefficients of income, D (perceived danger), and Ei (exposure) are positive and significant. Interestingly, the coefficient of an interaction term between Ei and D is negative and significant in all models. Thus, individuals who perceive COVID-19 as dangerous and are exposed to it are less likely to be willing to pay higher amounts for its vaccine. This may be caused by a lack of trust in vaccine efficiency, fear of adverse effects, or overconfidence derived from being exposed and healthy with no record of infection to COVID-19. Indeed, if we add a three-way interaction term between D, Ei, and I, we get positive coefficients. Since these coefficients were insignificant, they were not included in Table 2.

The coefficient of \({E}_{f}\), which measures the participant's perceived exposure to family members, is significant and negative for Iranian and Chinese vaccines. One explanation for this finding is the lack of trust in these two vaccines. Individuals who have lost a family member to COVID-19 are more likely to pay higher amounts for the vaccines. The coefficient of L is positive and significant in models 1 and 3. Interestingly, compared with residents of rural areas, city residents are less likely to pay higher amounts for the vaccine.

We have reported marginal probability effects for all models in Online Resource 2, Tables B1–B4. The results from these marginal probability effects are similar to marginal index effects. For example, the marginal probability effects of income, D, and L for the last category (fully paid user fee: 100% of a vaccine’s price) are all positive and significant for all vaccines. For example, each unit increase in D (perceived risk of COVID-19) increases the probability of a contribution to finance the vaccine completely by 3.1, 3.5, 4.9, and 4.8% for Iranian, Chinese, Russian, and FDA-approved vaccines, respectively. Similarly, moving from no income to the highest possible income increases the probability of willingness to fully finance the vaccine by 33.60, 28.90, 36.80, and 50.10% for Iranian, Chinese, Russian, and FDA-approved vaccines, respectively.

Having supplementary insurance increases the probability of financing the Iranian vaccine completely. Compared with males, females are less inclined to finance the Iranian vaccine completely. Surprisingly, more exposure of family members to COVID-19 decreases the probability of financing the Iranian, Chinese, and Russian vaccines completely. Those who live in cities are less likely to finance Chinese, Russian, and FDA-approved vaccines completely. More educated people have a higher probability of completely financing Russian and FDA-approved vaccines. It seems those who work in the health sector have only a higher probability of completely financing the FDA-approved vaccine.

3.3.1 Willingness to Pay for an Iranian COVID-19 Vaccine

Table 3 shows the amount of money, on average, Iranian people who preferred a partial contribution to vaccine financing were willing to pay for two doses of domestic vaccine financing. This was calculated by summing the total contributions across levels of 25%, 50%, and 75%, and dividing by the total number of respondents expressing a preference for partial vaccine financing in three price assumptions. In the survey, three scenarios were presented to respondents, with prices of $20, $55, and $60. To estimate the average amount that Iranian participants were willing to contribute, we considered the lowest and highest prices ($20 and $60), and the average of $20, $60, and $55, resulting in an average of $45 (see Online Resource 1). This resulted in an average WTP of $10.9, $24.6, and $32.8 at prices of $20, $45, and $60, respectively. However, when considering respondents who preferred a full government contribution and those willing to fully pay a user fee, the weighted mean will be decreased since the number of respondents with no preference in vaccine financing is more (40%) compared with those with a preference for a fully paid user fee (23%), equal to $8.8, $19.8, and $26.4 for the same price scenarios, respectively.

Table 3 Iranians’ willingness to pay for COVID-19 vaccines in different scenario prices
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4 Discussion

It has been demonstrated that immunization is one of the most cost-effective strategies to save lives and increase population health. Hence, this study assessed public preference for financing available vaccines by the Iranian population surveyed during the COVID-19 pandemic. At the time of this study, Iran was experiencing the third wave of COVID-19; the number of cases and deaths due to COVID-19 were 18,133 and 307, respectively (11 May 2020); however, since 19 October 2020, when the first WTP study was conducted in Iran, a steep increase in new cases and deaths has occurred [22]. We conducted this study considering the impact of the rising daily mortality rate due to COVID-19 on a WTP for the vaccine, and the necessity of providing reliable information about people's preferences to policymakers to adopt better vaccination promotion strategies and manage the crisis.

Our study findings underscore the significance of vaccination to Iranian individuals, irrespective of the vaccine's original features, such as the vaccine’s platform, evidenced by a high percentage (60%) exhibiting a positive WTP. This encompassed a range of 20–25% for fully paid user fees and 35–37% for partial contributions. About 40% of respondents considered the provision of free vaccination as a government responsibility.

However, about 60% of respondents had a preference for making a contribution to vaccine financing. Providing such evidence is so critical, particularly for a health system with limited health care resources and under sanction, and is the main novelty of the study, compared with other studies, because it could be beneficial for a health insurance organization and health ministry immunization program to develop more efficient strategies. The study by Hou et al. of factors affecting a WTP for self-paid vaccines revealed that vaccine price is the main barrier, and in the case of diseases with high burden, they have a lower WTP. Eliminating economic barriers to increase vaccine uptake was recommended as a policy option [23]. Additionally, the two separate studies conducted by García and Cerda in 2020 and 2021, with a 3-month interval between the first and second studies, indicated there is a sharp difference between Chilean populations for the COVID-19 vaccine in different sample populations [10, 24]. With the progression of the pandemic, the WTP value increased; this amount was estimated at US$184.72 in 2020 and US$232 in 2021. Income was identified as the common factor affecting the WTP preference in the two mentioned studies. [10, 24]

The study by Wong et al. emphasized the financing of vaccines [1]. The study examined COVID-19 vaccine acceptance and WTP in Malaysia using a health belief model; they indicated that although vaccine safety and efficacy are more concerning than its cost, individuals in the lower-income group have a lower WTP, and vaccination against COVID-19 may need financial support for this proportion of the Malaysian population [1]. The China study revealed that most respondents preferred government and health insurance as financing sources for the COVID-19 vaccination; one of the factors that significantly affected respondents' WTP was annual family income [21]. Income was one of the main factors that affected Iranians’ WTP and their contribution rate to COVID-19 financing. Hence, the results are consistent in this era. The role of income was assessed in the study by Catma and Varol that was conducted in the US. Based on the results of their study, individuals with a lower annual income (US$60,000) had a lower WTP than those who were in higher-income groups (US$100,000). Moreover, it revealed that 42% of respondents stated that in the case of a full user fee, they would not purchase the vaccine [16]. In Iran, 40% of the public stated they would be willing to get vaccinated if full government funding was available. Among the remaining 60%, only 24% of participants preferred to pay out-of-pocket for the vaccines, while the remainder tended to favor a partial contribution to financing the COVID-19 vaccine.

In line with previous research, a higher perceived risk is positively correlated with a WTP [15, 19]. Additionally, factors such as exposure to COVID-19 have influenced Iranians’ WTP and their contribution rates to COVID-19 financing, aligning with the findings of Soofi et al. [15] Consistent with the study by Zhou et al. in 2022, individuals with a high vaccination status are less inclined to pay for a vaccine [19]. According to this study, factors such as gender, place of residence, annual household income, chronic disease status, actual vaccination status, concerns about the safety and cost of vaccination, and willingness to vaccinate significantly impact WTP. Our study validates these factors, except for place of residence. Unlike the study by Zhou et al. [19], which found that urban residents were 57% more likely (95% confidence interval 1.11–2.22) to pay for a high-priced vaccine than rural residents, our study indicates that urban residents are less likely to fully finance vaccines. However, we observed that more educated individuals have a higher probability of completely financing high-priced vaccines, i.e. Russian and FDA-approved, as confirmed by Harapan et al. [25] Specifically, individuals who perceive COVID-19 as dangerous and are exposed to the virus are less likely to be willing to pay higher amounts for its vaccine. This may be caused by a lack of trust in vaccine efficiency, fear of adverse effects, or overconfidence derived from being exposed and healthy with no record of infection to COVID-19, as confirmed by Zhou et al. [19] However, for individuals who have lost a family member to COVID-19, the results differ, with a higher WTP observed in this case.

We believe that information on Iranians’ preferences for vaccine financing is the main finding of this current study, because the absolute value of WTP for COVID-19 vaccines in studies conducted in Iran [13,14,15] varies due to differences in question framing and the presentation of different scenarios and bidding values to respondents. Therefore, it is strongly recommended that policymakers consider people willing to contribute to vaccination programs regardless of the country of origin of vaccines, to achieve higher protection in society.

4.1 Study Limitations and Strengths

This study has several limitations. First, 60% of participants, constituting the in-person data, were exclusively from the Fars province, Shiraz City, potentially limiting the generalizability of the findings to a national level. Second, the remaining 40% of the sample was collected through an online survey, which inherently carries specific limitations, such as unequal access and knowledge among populations, which can lead to non-representative results. Third, our cross-sectional data did not provide causal information and only reported associations. Fourth, the prices presented to the respondents were sourced from websites and may not reflect the actual selling price, which could be lower due to negotiations. Nevertheless, this study contributes significantly to the existing literature by being the first to report Iranians' preferences for financing COVID-19 vaccines, utilizing a large sample size

5 Conclusion

Vaccination holds significant importance for the Iranian people, regardless of the vaccines’ country of origin. In this study, the majority of the public revealed their willingness to support vaccine financing during health crises, ranging from partial contribution to fully covering user fees, in order to enhance protection against COVID-19. Ensuring timely access to vaccines during health crises such as pandemics is vital to save more lives and mitigate the economic burden of disease. Therefore, policymakers are strongly advised to take into account the preferences of the public in vaccine procurement policies, as well as their willingness to support the health system through financial contributions, to achieve more effective control of health crises.