Impact factor (WEB OF SCIENCE - Clarivate)

2 year: 7.664 | 5 year: 7.127

COVID-19Ongoing Research Themes

Economic evaluation of COVID-19 vaccination: A systematic review

Auliasari Meita Utami1*, Farida Rendrayani1*, Qisty Aulia Khoiry1*, Dita Noviyanti1, Auliya A Suwantika1,2, Maarten J Postma2,3,4, Neily Zakiyah1,2

1 Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran, Bandung, Indonesia
2 Center of Excellence for Pharmaceutical Care Innovation, Universitas Padjadjaran, Bandung, Indonesia
3 Department of Health Sciences, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
4 Department of Economics, Econometrics & Finance, University of Groningen, Faculty of Economics & Business, Groningen, the Netherlands
* Joint first authorship.

DOI: 10.7189/jogh.13.06001




Safe and effective vaccination is considered to be the most critical strategy to fight coronavirus disease 2019 (COVID-19), leading to individual and herd immunity protection. We aimed to systematically review the economic evaluation of COVID-19 vaccination globally.


We performed a systematic search to identify relevant studies in two major databases (MEDLINE/PubMed and EBSCO) published until September 8, 2022. After deduplication, two researchers independently screened the study titles and abstracts according to pre-determined inclusion and exclusion criteria. The remaining full-text studies were assessed for eligibility. We assessed their quality of reporting using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 checklist and summarized and narratively presented the results.


We identified 25 studies that assessed the economic evaluation of COVID-19 vaccination worldwide by considering several input parameters, including vaccine cost, vaccine efficacy, utility value, and the size of the targeted population. All studies suggested that COVID-19 vaccination was a cost-effective or cost-saving intervention for mitigating coronavirus transmission and its effect in many countries within certain conditions. Most studies reported vaccine efficacy values ranging from 65% to 75%.


Given the favorable cost-effectiveness profile of COVID-19 vaccines and disparities in affordability across countries, considering prioritization has become paramount. This review provides comprehensive insights into the economic evaluation of COVID-19 vaccination that will be useful to policymakers, particularly in highlighting preventive measures and preparedness plans for the next possible pandemic.

Print Friendly, PDF & Email

The pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a significant public health problem that has affected millions of people globally [1,2]. The virus first appeared in a cluster of patients with pneumonia-like symptoms in Wuhan, China, near the end of 2019 [3]. The disease has put public health systems under pressure [3,4] because of its rapid and intense transmission [3,5], while causing immense economic losses due to medical expenditures and decreased productivity. The estimation of global economic costs of COVID-19 are varied, ranging from US$77 billion to US$2.7 trillion [6], with estimated years of life lost (YLLs) as high as 4 072 325 in 30 high-incidence countries in the first year of the pandemic [7]. Preventive control measures have become a priority due to the lack of an effective and clinically proven pharmacological treatment [5,8,9]. They include nonpharmacological interventions such as isolation and quarantine, cleaning and disinfection, proper use of face masks, and physical distancing [8,10]. The most important strategy, however, is safe and effective vaccination, as it helps with achieving better herd immunity faster [3,4,11].

By September 2022, various vaccines have been developed by many countries. According to the World Health Organization (WHO), there were about 369 vaccine candidates in development, with around 40% in clinical trials, and the remaining 60% in pre-clinical development stages [12]. After a series of efficacy and safety assessments almost two years into the pandemic, numerous COVID-19 vaccines have received Emergency Use Listing (EUL) or Emergency Use Authorization (EUA) by regulatory authorities worldwide, and vaccinations have been conducted in many countries [13]. While some COVID-19 vaccines appear safe and effective, providing an adequate number of vaccines is frequently dependent on the countries’ resources [14]. Although the WHO has published guidelines for vaccine prioritization, only a few include economic considerations [15].

A recent study that assessed the duration of effectiveness of COVID-19 vaccines found that, although the COVID-19 vaccine’s immediate effectiveness in preventing severe disease symptoms remained high, its effectiveness may decrease in the six months following full vaccination [16]. These findings highlight that further follow-up on COVID-19 vaccination policies is still required. Given the disease’s health and economic burden, providing information on the effectiveness and cost of health interventions is essential for informing decision-makers in optimizing the scarce healthcare resources, especially in countries with limited resources such as in low- and middle-income countries (LMICs). A previous study showed that nonpharmacological interventions, vaccinations, and treatments can be cost-effective interventions to prevent and control COVID-19 [17]. A most recent review also suggested that COVID-19 vaccination was cost-effective and even cost-saving in LMICs [18]. However, studies that comprehensively assessed the cost-effectiveness of COVID-19 vaccination are currently sparse. To address this, we aimed to conduct a systematic review to assess and provide an up-to-date economic evaluation of COVID-19 vaccination globally.


We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 guidelines in reporting this systematic review. The PRISMA checklists of this study are provided in Table S1 in the Online Supplementary Document.

Search strategy

Three investigators (AMU, FR, and QAK) searched the MEDLINE/PubMed and EBSCO databases up to September 8, 2022 to identify relevant studies on economic evaluations of COVID-19 vaccination. The following keywords were used for the search, combining mesh terms and text words: (“Costs and Cost Analysis”[Mesh] OR “economic evaluation” OR “cost minimization” OR “Cost-Effectiveness Analysis”[Mesh] OR “cost utility” OR “Cost-Benefit Analysis”[Mesh] OR “willingness-to-pay”) AND (“COVID-19”[Mesh] OR “Coronavirus”[Mesh] OR “COVID-19 Vaccines”[Mesh]).

Study selection

We exported the records into the Mendeley Reference Manager and checked for duplicates. Two researchers (AMU and QAK) did the manual data extraction and independently performed screening on the articles’ titles and abstracts. We included English-language economic studies of COVID-19 vaccines in countries with COVID-19 vaccination programmes, corresponding to the PICOS eligibility criteria (population – countries providing COVID-19 vaccination, intervention – COVID-19 vaccination, comparison – none, outcome – cost-effectiveness ratio, and study design – full economic evaluation studies, i.e. cost minimization analysis, cost-benefit analysis (CBA), cost-effectiveness analysis (CEA), and cost-utility analysis (CUA)). We excluded review articles, case reports, conference proceedings, non-peer-reviewed papers, opinion pieces, letters to the editor, and commentaries. AMU and QAK retrieved and reviewed the full texts of potentially eligible articles. FR and DN double-checked the results of the study selection. Any disagreements were resolved by discussions with another reviewer (NZ). Figure 1 shows the PRISMA flow diagram for the study selection process.

Figure 1.  PRISMA flow diagram of the study selection process.

Data collection and quality assessments

The data from the included studies were manually extracted in Microsoft Excel (Microsoft Inc, Seattle WA, USA) using a predetermined format. From each included study, information regarding characteristics of the studies, i.e. information on authors, year of publication, title, country, study objectives, type of study, data collection, and outcome measure, including incremental cost-effectiveness ratio (ICER), quality-adjusted life years (QALYs), disability-adjusted life years (DALYs), life years gained (LYG), and other intermediate measures, were extracted. Moreover, we also documented methodological characteristics, i.e. study perspectives, intervention, and comparator, time horizon, discount rate, choice of model, and sensitivity parameters. Vaccine information comprising vaccination strategy, duration of vaccine protection, vaccination coverage, and vaccine effectiveness was also obtained. In addition, the following cost elements and primary results from each study were documented. All costs were converted to reflect 2022 US$ using the Campbell and Cochrane Economics Methods Group-the Evidence for Policy and Practice Information ( Centre Cost Converter Software.

The reporting quality of each included study was assessed using the recent version of the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 statement [19]. The checklist comprised 24 items classified into six categories, namely, title and abstract, introduction, methods, results, discussion, and others. We calculated a percentage score with the underlying assumption that all criteria were weighted equally after excluding the criteria that were not applicable. Studies were assigned 1 point for reporting the item, 0.5 for partially reporting, and 0 for not reporting. Studies were categorized as “high quality” if they met at least 75% of these standards, “moderate” if they met between 50% and 75% of relevant standards, and “low” if less than 50% [20]. Since this assessment only measures the quality of reporting, the fact of unreported items does not imply poor study quality. This process involved a discussion by all researchers to ensure the accuracy of the findings.


Study selection

Through the database search, we retrieved 203 records from MEDLINE/PubMed and 160 records from EBSCO. After eliminating 67 duplicates, we screened 296 records and selected 31 for full-text screening. We further excluded six articles because they were not economic evaluation studies and did not explicitly involve vaccine efficacy. Consequently, we identified 25 articles for the final review (Figure 1).

Study characteristics

Table 1 provides the characteristics of the 25 included studies, 23 of which were single-country studies, 11 were from LMICs [2125,29,35,3840,43,44], and 12 were studies from high-income countries (HICs) [2628,3035,37,41,45]. The two remaining studies were conducted in multiple countries; the first one comprised four analyses from LMICs and two analyses from HICs [36], while the other study comprised 12 analyses in LMICs [42]. Sixteen studies were conducted in 2021 [2128,3033,3537,41], while nine studies were conducted in 2022 [29,34,3840,4245]. Most of the included studies (21/25) aimed to estimating the economic evaluation of different vaccination strategies [2130,32,33,3538,40,4245], while two studies were conducted with the goal of estimating the economic evaluation of vaccination vs no vaccination [34,41]. Only one study assessed the economic impact of booster vaccination [31], while another compared the intradermal vaccine with the intramuscular vaccine [39].

Table 1.  General characteristics of included studies

BIA – budget impact of analysis, CBA – cost-benefit analysis, CEA – cost-effectiveness analysis, CUA – cost-utility analysis, DALYs – disability-adjusted life years, DSA – deterministic sensitivity analysis, ICER – incremental cost-effectiveness ratio, NR – not reported, PSA – probabilistic sensitivity analysis, QALYs – quality-adjusted life years, QALD – quality-adjusted life days, YLS – years of life saved, y – years, mo – months

Methodological characteristics

CUA was conducted in 15 studies, 11 of which used QALYs as an outcome [22,29,30,3234,36,37,41,44,45], while four used DALYs [23,24,38,40]. Four studies conducted CBA, with most using net monetary value as the outcome measure [2628], while only one study used cost-benefit ratio as the outcome measure [43]. For studies using CEA, two articles used year of life saved (YLS) as the outcome [21,42] while another used averted cases and deaths [25]. One study conducted CUA using QALYs as the outcome alongside budget impact analysis (BIA) [31]. SARS-CoV-2 anti-RBD antibody response was chosen as the outcome in a study using CEA, which also conducted a cost analysis [39]. One remaining study used two concurrent economic analyses – CEA with quality-adjusted life days (QALD) as outcomes and CBA with cost-benefit ratios [35] (Table 1).

Ten studies applied the dynamic transmission model [2123,25,26,30,32,40,42,44], eight applied the Markov model [29,31,3335,38,41,45], and four studied the epidemiological model [24,27,28,43] for modeling the evaluation. One study utilized a decision tree [36] and another used simplified mathematical modeling [37]. One study did not report the type of modeling used [39]. The short time horizon was reported in most studies, i.e. two, three, four, six, and nine months [24,2730,32,34,35,43] and one year [21,22,25,31,33,36,38,4042,44,45], although a longer time horizon was also reported in three studies [23,26,37]. However, one study did not report a time horizon [39]. For time horizons of more than one year, a discount rate must be mentioned [46]. More than half of the studies (13/25) did not report the discount rate for costs and effects [21,24,25,28,29,31,35,38,39,4345]. Most studies set similar discount rates for costs and effects at 3.5% [37], 3% [22,23,3234,36,40], 1.5% [27], 3%-5%[26], and 2%-4%[30]. While two studies reported 3% [42] and 3.5% [41] discount rates only for the effects.

Regarding perspectives, 12 studies used a healthcare perspective [25,27,2931,33,34,36,38,41,45,47], four used a societal perspective [36,37,40,44], two used a policymaker perspective [21,24], and one adopted the payer perspective [42]. Additionally, the remaining studies used more than one perspective, i.e. healthcare and societal perspectives or societal and payer perspectives [22,23,28,32,35]. Only one study did not report the perspective adopted [39] (Table 2). At least four studies specified a vaccination coverage of less than 50% [21,27,30,40], eight had a vaccination coverage of 50%-75% [22,26,3437,44,45], and one specified a vaccination coverage of 100% [41]. Moreover, three studies presented a range of two to three categories of vaccination coverage each [25,32,42]. Eight studies, however, did not report on vaccination coverage [23,24,28,29,31,38,39,43].

Table 2.  Cost elements and main findings of included studies

NA – not available, NR – not reported, QALYs – quality-adjusted life years, QALD – quality-adjusted life days, ICER – incremental cost-effectivens ratio, YLS – years of life saved, DALYs – disability-adjusted life years, QALD – quality-adjusted life days, ICU – intensive care unit, CrI – credible interval, GDP – gross domestic product, y – year, mo – months

Regarding the possibilities of uncertainty, five studies did not conduct sensitivity analyses [24,27,28,39,43]. Those that did commonly used deterministic sensitivity analyses, particularly one-way sensitivity analyses [22,23,25,30,32,33,35,37,38,4042]. Four studies performed probabilistic sensitivity analysis (PSA) [26,29,31,34]. The remaining included studies used more than one sensitivity analysis, i.e. PSA and one-way sensitivity analysis [21,36,44,45].

Cost estimation

Regarding cost components, the direct medical costs were mostly vaccination costs and hospitalisation or ICU treatment costs related to COVID-19 infection [2124,2628,3238,40,42]. Three studies considered diagnostic testing costs in direct medical costs [2931]. Only eight studies reported direct non-medical costs, including vaccine wastage, freight, human resources, transportation, social mobilization, contact tracing, quarantine, social distancing, and vaccination campaigns [23,28,35,37,40,4244]. The indirect costs considered were those associated with economic productivity loss because of COVID-19 [22,3032,36,40,45]. Table 2 summarizes the detailed information about the cost elements of the included studies.

Primary results

The value of the willingness-to-pay (WTP) threshold differed depending on the study. Several studies used their own thresholds [26,3335,40,42,43,45,4850]; some referred to one to three times the gross domestic product (GDP) per capita as the threshold value [21,22,24,3638,41] while others did not define it [23,25,28,30,39,41] Overall, all studies suggested that vaccination to prevent the COVID-19 pandemic was a cost-effective strategy. Each analysis used a different evaluation to determine whether the use of vaccinations was considered cost-effective, e.g. by considering the procurement of the vaccine program compared with the absence of a vaccination program [21,26,33,36,39,41,45,48,50], the coverage of the vaccine used [37,40,42,49], the existence of priority vaccines for specific populations [25,30,33,34,38,41], the efficacy of many vaccines on the market [23,24,29,35,41,43], and the provision of boosters following vaccination [34].

Several studies did not conduct sensitivity analysis to determine the uncertainty of the analysis [24,28,39,41,43], but most did. Reproduction number [21,25,49], vaccine price/cost [22,23,33,41,48], vaccination program [26,42,45], vaccine efficacy [29,30,33,36,40,41,4850], population/infection incidence [33,34,38], hospitalisation fee [35], and discount rate and mortality [37] were the most reported sensitive parameters in the sensitivity analysis. Vaccine cost was one of the most essential factors in determining cost-effectiveness. All the included studies reported vaccine prices, and most of them calculated the average price to obtain the effectiveness of vaccination. Additionally, the vaccine administration cost was also considered, varying from US$0.50 to US$20.16 [25,30,3336,47]. According to the CHEERS 2022 checklist, 14 studies were classified as high quality [2123,2528,30,31,36,38,40,42], while 10 were classified as moderate quality [24,29,32,34,35,37,41,4345]. Only one study was categorized as low in quality of reporting [39]. The abstract and results sections were almost entirely reported in all studies. Most studies have discussed vaccination perspectives and time horizons, but justifications have rarely been mentioned. All studies provided the currency used, but the years of costing and conversion were not fully reported. Regarding heterogeneity, only a few studies described techniques for estimating how the study’s results differ for subgroups. The role of the study’s funder was also underreported, even though almost all studies reported the source of funding.


We identified 25 studies on the economic evaluation studies of COVID-19 vaccination globally. The results showed that the vaccination programs would be cost-effective and even cost-saving compared to no vaccination at all, even when the efficacy of vaccines largely varied, was assumed to be relatively low, and when only a specific age cohort was targeted. Moreover, vaccine effectiveness, costs, and coverage were among the most influential parameters for estimating the cost-effectiveness. We also found variability regarding input parameters in all included studies, eg, the choice of modeling, perspectives, cost components, vaccine coverage, target population, and discount rate.

Vaccination is considered the most cost-effective intervention to fight the COVID-19 pandemic. Most economic evaluation studies on COVID-19 vaccination were from HICs and middle-income countries (MICs), while studies in low-income countries (LICs) were very limited. Most evaluation studies used a decision analytic modeling approach to predict the cost-effectiveness of COVID-19 vaccination. Approximately half of the studies using modeling used dynamic models in the evaluation, which may consider herd immunity and dynamic shifts in the age distribution of the population, thus providing a representation of infectious disease transmission. The models’ assumptions and parameters relating to the direct and indirect costs and vaccine efficacy varied. COVID-19-related costs were determined by the perspectives used in the studies. Societal perspectives could give more comprehensive data in the decision-making process because both direct and indirect costs, such as productivity loss, were considered in the analysis. In contrast, the healthcare perspective only considers direct costs. However, as the data were limited during the COVID-19 pandemic, the healthcare perspective was mostly used, as indicated in most included studies. Most studies used a one-year time horizon or less, considering the viral infection’s nature and the expected effects of vaccination. Vaccination is supposed to be more cost-effective in a shorter time horizon than other interventions such as social distancing [51]. A study that used a short time horizon (≤1 year) did not have to consider a discount rate in the analysis [46]. A longer time horizon was used to determine a longer effect, as done, for example, in the study by Pearson et al. [23], which considered campaign duration and duration of natural immunity for 10 years. Thus, discounting the costs and effects became necessary [46].

Most studies reported vaccine efficacy to be around 60%-95%. These findings are correlated with the fact that vaccination could decrease hospitalisation rate, disease severity, and mortality [13,52]. A previous study also reported that a COVID-19 vaccination could minimize adverse outcomes [52]. Although vaccination could prevent coronavirus transmission, not all countries can afford the same type of vaccines (different types may result in different efficacy) and the number of rounds or doses to be administered. Thus, the economic evaluation becomes important for policymakers to decide on the implementation strategies. Our results indicated that COVID-19 vaccination can be considered a cost-effective or cost-saving intervention, even in LMICs. Combined with lockdown and physical distancing, vaccination is estimated to have decreased 148 million cases and 3.1 million deaths [26]. Vaccines can reduce community transmission without doing physical distancing in the future [26]. The analysis also summarized that mass vaccination campaigns against COVID-19 are cost-saving [28]. From an economic perspective, vaccination campaigns have high social returns [28]. Regarding benefits, the speeding up of vaccination coverage could decrease the number of cases and deaths [32].

Many aspects can influence the priority of conducting COVID-19 vaccination during the beginning of pandemic eg, prioritization criteria, vaccine effectiveness and coverage, and implemented policies [27]. For instance, in Thailand, prioritizing persons at risk of contracting COVID-19 exhibited a more cost-effective effect [25]. In the USA, if the analysis did not consider the productivity loss, prioritizing vaccines for people older than 60 years was more cost-effective [33]. However, the analysis in Denmark suggested that even when the loss of productivity is considered, the scenario to prioritize vaccination for people younger than 60 years can still be considered cost-effective [30].

Because of limited resources, cost is an essential aspect of estimation in any economic evaluation study. Costs are calculated to estimate resource scarcity, which occurs when resources used for one purpose are no longer available for use in another. Decision-makers must choose appropriate WTP thresholds in economic evaluations. Making accurate estimations in WTP would assist policymakers in making informed decisions regarding the healthcare allocation [53]. If a specific WTP is not available, a threshold of less than three times the country’s annual GDP per capita is recommended by the World Health Organization’s Choosing Interventions that are Cost-effective (WHO-CHOICE) project, with interventions that cost less than one time the country’s annual GDP per capita being considered highly cost-effective [54]. The WTP research is predicated on the notion that societal preferences should be considered when making choices on how to distribute resources in the health system [55].

Previous studies also suggested that vaccination against COVID-19 was more cost-effective than no vaccination at all. The COVID-19 vaccine is superior in LMICs in terms of clinical effectiveness and economic value. Vaccination programs have shown to be the most cost-effective strategy to stop the COVID-19 pandemic under any circumstances or situation. The efficacy of the vaccine, the priority of administration in a certain group, and vaccination coverage are the three primary factors for deciding whether a vaccine is cost-effective or not. Herd immunity, which lowers mortality in COVID-19 patients, is influenced by vaccine efficacy and vaccination coverage, whereas population priorities have an effect, since vaccines might be useless if not administered to the correct populations [2225,29,30,33,35,38,40,41,43,49].

Knowing the most influential parameter in sensitivity analyses enables us to identify the factors that have a significant effect on the ICER values. If the results of the sensitivity analyses are consistent with the base-case analysis’ results and lead to similar conclusions on the cost-effectiveness of various strategies, one can be confident that any uncertainty about the model input has been minimized [56].

Despite its limitation, such as the included studies’ heterogeneity, policymakers could use our study to review evidence from all published research on economic evaluations of COVID-19 vaccination to conduct vaccination programs or to use it as a basis for a possible future pandemic. Nonetheless, COVID-19 vaccination has been deemed a cost-effective intervention in many countries. Our findings suggest that optimal vaccine allocation will be determined by current public health policies and their effects on a given population.


COVID-19 vaccination is considered one of the most cost-effective interventions to fight COVID-19 globally. Most studies reported the values of vaccine efficacy to be 65%-75%. The results of economic evaluation in the included studies indicate that COVID-19 vaccination could be considered a cost-effective or cost-saving intervention, even in LMICs. Given the disparities in affordability across countries, prioritization has become crucial to consider. Our study provides insights for conducting effective vaccination that will be helpful to policymakers, particularly as the next possible pandemic approaches.

Additional material

Online Supplementary Document

[1] Funding: This study is supported by a grant from Universitas Padjadjaran.

[2] Authorship contributions: AMU, FR, QAK, DN and NZ designed the study. AMU, FR, and QAK searched the literature. AMU, FR, QAK, DN contributed to data collection and data analysis. AMU and QAK contributed to screening process. FR and DN rechecked the screening results. AMU, FR, and QAK drafted the manuscript. NZ, AAS and MJP reviewed and edited the manuscript. All authors reviewed and approved the final draft of the manuscript.

[3] Disclosure of interest: The authors completed the ICMJE Disclosure of Interest Form (available upon request from the corresponding author) and declare the following activities and relationships: MJP reports grants and honoraria from various pharmaceutical companies, also those involved in developing, producing, and marketing COVID-19 vaccines. Also, MJP is a member of the UK’s Joint Committee of Vaccination & Immunization. Other author reports no conflicts of interest in this work.


[1] S Muralidar, S Visaga, S Sekaran, and UM Krishnan. The emergence of COVID-19 as a global pandemic: Understanding the epidemiology, immune response and potential therapeutic targets of SARS-CoV-2. Biochimie. 2020;179:85-100. DOI: 10.1016/j.biochi.2020.09.018. [PMID:32971147]

[2] WHO. WHO Director-General’s opening remarks at the media briefing on COVID-19 – 11 March 2020. 2020. Available:—11-march-2020. Accessed: 26 Jun 2022

[3] S Su, L Du, and S Jiang. Learning from the past: development of safe and effective COVID-19 vaccines. Nat Rev Microbiol. 2021;19:211-9. DOI: 10.1038/s41579-020-00462-y. [PMID:33067570]

[4] I Ali. Impact of COVID-19 on vaccination programs: adverse or positive? Hum Vaccin Immunother. 2020;16:2594-600. DOI: 10.1080/21645515.2020.1787065. [PMID:32961081]

[5] C Huang, Y Wang, X Li, L Ren, J Zhao, and Y Hu. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:497-506. DOI: 10.1016/S0140-6736(20)30183-5. [PMID:31986264]

[6] S Forsythe, J Cohen, P Neumann, SM Bertozzi, and A Kinghorn. The Economic and Public Health Imperatives Around Making Potential Coronavirus Disease–2019 Treatments Available and Affordable. Value Health. 2020;23:1427-31. DOI: 10.1016/j.jval.2020.04.1824. [PMID:33127012]

[7] IH Oh, M Ock, SY Jang, DS Go, YE Kim, and YS Jung. Years of life lost attributable to COVID-19 in high-incidence countries. J Korean Med Sci. 2020;35:e300. DOI: 10.3346/jkms.2020.35.e300. [PMID:32808515]

[8] R Güner, İ Hasanoğlu, and F Aktaş. Covid-19: Prevention and control measures in community. Turk J Med Sci. 2020;50:571-7. DOI: 10.3906/sag-2004-146. [PMID:32293835]

[9] WF Qomara, DN Primanissa, SH Amalia, FV Purwadi, and N Zakiyah. Effectiveness of remdesivir, lopinavir/ritonavir, and favipiravir for COVID-19 treatment: A systematic review. Int J Gen Med. 2021;14:8557-71. DOI: 10.2147/IJGM.S332458. [PMID:34849001]

[10] AA Suwantika, N Zakiyah, A Diantini, R Abdulah, and MJ Postma. The Role of Administrative and Secondary Data in Estimating the Costs and Effects of School and Workplace Closures due to the COVID-19 Pandemic Auliya. Data (Basel). 2020;5:98-109. DOI: 10.3390/data5040098

[11] HE Randolph and LB Barreiro. Herd Immunity: Understanding COVID-19. Immunity. 2020;52:737-41. DOI: 10.1016/j.immuni.2020.04.012. [PMID:32433946]

[12] WHO. COVID-19 vaccine tracker and landscape. 2022 Accessed: June 29, 2022. Available:

[13] YZ Huang and CC Kuan. Vaccination to reduce severe COVID-19 and mortality in COVID-19 patients: a systematic review and meta-analysis. Eur Rev Med Pharmacol Sci. 2022;26:1770-6. [PMID:35302230]

[14] M Massinga Loembé and JN Nkengasong. COVID-19 vaccine access in Africa: Global distribution, vaccine platforms, and challenges ahead. Immunity. 2021;54:1353-62. DOI: 10.1016/j.immuni.2021.06.017. [PMID:34260880]

[15] L Matrajt, J Eaton, T Leung, and ER Brown. Vaccine optimization for COVID-19: Who to vaccinate first? Sci Adv. 2021;7:DOI: 10.1126/sciadv.abf1374. [PMID:33536223]

[16] DR Feikin, MM Higdon, LJ Abu-Raddad, N Andrews, R Araos, and Y Goldberg. Duration of effectiveness of vaccines against SARS-CoV-2 infection and COVID-19 disease: results of a systematic review and meta-regression. Lancet. 2022;399:924-44. DOI: 10.1016/S0140-6736(22)00152-0. [PMID:35202601]

[17] L Zhou, W Yan, S Li, H Yang, X Zhang, and W Lu. Cost-effectiveness of interventions for the prevention and control of COVID-19: Systematic review of 85 modelling studies. J Glob Health. 2022;12:05022 DOI: 10.7189/jogh.12.05022. [PMID:35712857]

[18] AM Utami, F Rendrayani, QA Khoiry, F Alfiani, ASW Kusuma, and AA Suwantika. Cost-Effectiveness Analysis of COVID-19 Vaccination in Low-and Middle-Income Countries. J Multidiscip Healthc. 2022;15:2067-76. DOI: 10.2147/JMDH.S372000. [PMID:36124175]

[19] D Husereau, M Drummond, F Augustovski, E de Bekker-Grob, AH Briggs, and C Carswell. Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) Statement: Updated Reporting Guidance for Health Economic Evaluations. Clin Ther. 2022;44:158-68. DOI: 10.1016/j.clinthera.2022.01.011. [PMID:35168801]

[20] N Zakiyah, ADI Van Asselt, F Roijmans, and MJ Postma. Economic evaluation of family planning interventions in low and middle income countries; A systematic review. PLoS One. 2016;11:e0168447. DOI: 10.1371/journal.pone.0168447. [PMID:27992552]

[21] KP Reddy, KP Fitzmaurice, JA Scott, G Harling, RJ Lessells, and C Panella. Clinical outcomes and cost-effectiveness of COVID-19 vaccination in South Africa. Nat Commun. 2021;12:6238 DOI: 10.1038/s41467-021-26557-5. [PMID:34716349]

[22] A Hagens, AÇ İnkaya, K Yildirak, M Sancar, J van der Schans, and A Acar Sancar. COVID-19 Vaccination Scenarios: A Cost-Effectiveness Analysis for Turkey. Vaccines (Basel). 2021;9:DOI: 10.3390/vaccines9040399. [PMID:33919586]

[23] CAB Pearson, F Bozzani, SR Procter, NG Davies, M Huda, and HT Jensen. COVID-19 vaccination in Sindh Province, Pakistan: A modelling study of health impact and cost-effectiveness. PLoS Med. 2021;18:e1003815. DOI: 10.1371/journal.pmed.1003815. [PMID:34606520]

[24] A Vaezi and A Meysamie. COVID-19 Vaccines Cost-Effectiveness Analysis: A Scenario for Iran. Vaccines (Basel). 2021;10:DOI: 10.3390/vaccines10010037. [PMID:35062698]

[25] R Suphanchaimat, T Tuangratananon, N Rajatanavin, M Phaiyarom, W Jaruwanno, and S Uansri. Prioritization of the Target Population for Coronavirus Disease 2019 (COVID-19) Vaccination Program in Thailand. Int J Environ Res Public Health. 2021;18:DOI: 10.3390/ijerph182010803. [PMID:34682548]

[26] FG Sandmann, NG Davies, A Vassall, WJ Edmunds, and M Jit. The potential health and economic value of SARS-CoV-2 vaccination alongside physical distancing in the UK: a transmission model-based future scenario analysis and economic evaluation. Lancet Infect Dis. 2021;21:962-74. DOI: 10.1016/S1473-3099(21)00079-7. [PMID:33743846]

[27] E Kirwin, E Rafferty, K Harback, J Round, and C McCabe. A Net Benefit Approach for the Optimal Allocation of a COVID-19 Vaccine. PharmacoEconomics. 2021;39:1059-73. DOI: 10.1007/s40273-021-01037-2. [PMID:34138458]

[28] F López, M Català, C Prats, O Estrada, I Oliva, and N Prat. A Cost-Benefit Analysis of COVID-19 Vaccination in Catalonia. Vaccines (Basel). 2021;10:DOI: 10.3390/vaccines10010059. [PMID:35062719]

[29] RRA Fernandes, M da S Santos, CA da S Magliano, BR Tura, LSDN Macedo, and MP Padila. Cost Utility of Vaccination Against COVID-19 in Brazil. Value Health Reg Issues. 2022;31:18-24. DOI: 10.1016/j.vhri.2022.01.009. [PMID:35325693]

[30] K Debrabant, L Grønbæk, and C Kronborg. The Cost-Effectiveness of a COVID-19 Vaccine in a Danish Context. Clin Drug Investig. 2021;41:975-88. DOI: 10.1007/s40261-021-01085-8. [PMID:34623627]

[31] WV Padula, S Malaviya, NM Reid, BG Cohen, F Chingcuanco, and J Ballreich. Economic value of vaccines to address the COVID-19 pandemic: a U.S. cost-effectiveness and budget impact analysis. J Med Econ. 2021;24:1060-9. DOI: 10.1080/13696998.2021.1965732. [PMID:34357843]

[32] SM Bartsch, PT Wedlock, KJ O’Shea, SN Cox, U Strych, and JB Nuzzo. Lives and Costs Saved by Expanding and Expediting Coronavirus Disease 2019 Vaccination. J Infect Dis. 2021;224:938-48. DOI: 10.1093/infdis/jiab233. [PMID:33954775]

[33] M Kohli, M Maschio, D Becker, and MC Weinstein. The potential public health and economic value of a hypothetical COVID-19 vaccine in the United States: Use of cost-effectiveness modeling to inform vaccination prioritization. Vaccine. 2021;39:1157-64. DOI: 10.1016/j.vaccine.2020.12.078. [PMID:33483216]

[34] R Li, H Liu, CK Fairley, Z Zou, L Xie, and X Li. Cost-effectiveness analysis of BNT162b2 COVID-19 booster vaccination in the United States. Int J Infect Dis. 2022;119:87-94. DOI: 10.1016/j.ijid.2022.03.029. [PMID:35338008]

[35] W-C Wang, JC-Y Fann, R-E Chang, Y-C Jeng, C-Y Hsu, and H-H Chen. Economic evaluation for mass vaccination against COVID-19. J Formos Med Assoc. 2021;120:Suppl 1S95-105. DOI: 10.1016/j.jfma.2021.05.020. [PMID:34108119]

[36] Y Jiang, D Cai, and S Shi. Economic evaluations of inactivated COVID-19 vaccines in six Western Pacific and South East Asian countries and regions: A modeling study. Infect Dis Model. 2022;7:109-21. DOI: 10.1016/j.idm.2021.12.002. [PMID:34909514]

[37] JE Marco-Franco, P Pita-barros, S Gonz, I Sabat, and D Vivas-consuelo. Simplified Mathematical Modelling of Uncertainty: Cost-Effectiveness of COVID-19 Vaccines in Spain. Mathematics. 2021;9:566 DOI: 10.3390/math9050566

[38] G Morales-Zamora, O Espinosa, E Puertas, JC Fernandes, J Hernández, and V Zakzuk. Cost-Effectiveness Analysis of Strategies of COVID-19 Vaccination in Colombia: Comparison of High-Risk Prioritization and No Prioritization Strategies With the Absence of a Vaccination Plan. Value Health Reg Issues. 2022;31:101-10. DOI: 10.1016/j.vhri.2022.04.004. [PMID:35640462]

[39] R Mungmunpuntipantip and V Wiwanitkit. Cost-utility-safety analysis of alternative intradermal versus classical intramuscular COVID-19 vaccination. Int J Physiol Pathophysiol Pharmacol. 2022;14:129-33. [PMID:35619662]

[40] S Orangi, J Ojal, SPC Brand, C Orlendo, A Kairu, and R Aziza. Epidemiological impact and cost- effectiveness analysis of COVID- vaccination in Kenya. BMJ Glob Health. 2022;7:e009430. DOI: 10.1136/bmjgh-2022-009430. [PMID:35914832]

[41] K Orlewska, W Wierzba, and A Sliwczynski. Cost-effectiveness analysis of COVID-19 vaccination in Poland. Arch Med Sci. 2021;18:1021-30. DOI: 10.5114/aoms/144626. [PMID:35832692]

[42] MJ Siedner, C Alba, KP Fitzmaurice, RF Gilbert, JA Scott, and FM Shebl. Cost-effectiveness of COVID-19 vaccination in low- and middle-income countries. J Infect Dis. 2022;226:1887-1896. DOI: 10.1093/infdis/jiac243. [PMID:35696544]

[43] PG Siqueira and HO Duarte. Moura M das C. Risk-based cost-benefit analysis of alternative vaccines against COVID-19 in Brazil: Coronavac vs. Astrazeneca vs. Pfizer. Vaccine. 2022;40:3851-60. DOI: 10.1016/j.vaccine.2022.05.038. [PMID:35610105]

[44] Y Wang, N Luangasanatip, W Pan-ngum, W Isaranuwathcai, J Prawjaeng, and S Saralamba. Assessing the cost-efectiveness of COVID-19 vaccines in a low incidence and low mortality setting in Thailand. Eur J Health Econ. 2022;11:1-14. [PMID:35951243]

[45] X Xiong, J Li, B Huang, T Tam, Y Hong, and K Chong. Economic Value of Vaccines to Address the COVID-19 Pandemic in Hong Kong: A Cost-Effectiveness Analysis. Vaccines (Basel). 2022;10:495 DOI: 10.3390/vaccines10040495. [PMID:35455244]

[46] W Supadmi, AA Suwantika, DA Perwitasari, and R Abdulah. Economic Evaluations of Dengue Vaccination in Southeast Asia Region: Evidence From a Systematic Review. Value Health Reg Issues. 2019;18:132-44. DOI: 10.1016/j.vhri.2019.02.004. [PMID:31082793]

[47] S Orangi, A Kairu, A Ngatia, J Ojal, and E Barasa. Examining the unit costs of COVID-19 vaccine delivery in Kenya. BMC Health Serv Res. 2022;22:439 DOI: 10.1186/s12913-022-07864-z. [PMID:35379227]

[48] WV Padula, S Malaviya, NM Reid, BG Cohen, F Chingcuanco, and J Ballreich. Economic value of vaccines to address the COVID-19 pandemic: a U.S. cost-effectiveness and budget impact analysis. J Med Econ. 2021;24:1060-9. DOI: 10.1080/13696998.2021.1965732. [PMID:34357843]

[49] SM Bartsch, KJ O’Shea, KL Chin, U Strych, MC Ferguson, and ME Bottazzi. Maintaining face mask use before and after achieving different COVID-19 vaccination coverage levels: a modelling study. Lancet Public Health. 2022;7:e356-65. DOI: 10.1016/S2468-2667(22)00040-8. [PMID:35276093]

[50] Y Wang, N Luangasanatip, W Pan–ngum, W Isaranuwatchai, J Prawjaeng, and S Saralamba. Assessing the cost-effectiveness of COVID-19 vaccines in a low incidence and low mortality setting: the case of Thailand at start of the pandemic. Eur J Health Econ. 2022;11:1-14. DOI: 10.1007/s10198-022-01505-2. [PMID:35951243]

[51] A Rezapour, A Souresrafil, MM Peighambari, M Heidarali, and M Tashakori-Miyanroudi. Economic evaluation of programs against COVID-19: A systematic review. Int J Surg. 2021;85:10-8. DOI: 10.1016/j.ijsu.2020.11.015. [PMID:33227532]

[52] SM Moghadas, TN Vilches, K Zhang, CR Wells, A Shoukat, and BH Singer. The Impact of Vaccination on Coronavirus Disease 2019 (COVID-19) Outbreaks in the United States. Clin Infect Dis. 2021;73:2257-64. DOI: 10.1093/cid/ciab079. [PMID:33515252]

[53] CE Phelps and C Cinatl. Estimating optimal willingness to pay thresholds for cost-effectiveness analysis: A generalized method. Health Econ. 2021;30:1697-702. DOI: 10.1002/hec.4268. [PMID:33884694]

[54] Hutubessy RCW, Baltussen R, Tan Torres-Edejer T, Evans DB. WHO-CHOICE: Choosing interventions that are cost-effective. Health systems performance assessment: debates, methods and empiricism Geneva: WHO Editions. 2003;823–835.

[55] JA McDougall, WE Furnback, BCM Wang, and J Mahlich. Understanding the global measurement of willingness to pay in health. J Mark Access Health Policy. 2020;8:1717030. DOI: 10.1080/20016689.2020.1717030. [PMID:32158523]

[56] R Jain, M Grabner, and E Onukwugha. Sensitivity Analysis in Cost-Effectiveness Studies. Pharmacoeconomics. 2011;29:297 DOI: 10.2165/11584630-000000000-00000. [PMID:21395350]

Correspondence to:
Neily Zakiyah, PhD
Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Padjadjaran, Bandung, Indonesia
[email protected]