Peer Reviewed Case Studies Showing Toxicity and Efficacy of Vaccinations

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A systematic review of methodological approaches for evaluating real-earth effectiveness of COVID-19 vaccines: Advising resource-constrained settings

• Yot Teerawattananon,
• Thunyarat Anothaisintawee,
• Chatkamol Pheerapanyawaranun,
• Siobhan Botwright,
• Katika Akksilp,
• Natchalaikorn Sirichumroonwit,
• Nuttakarn Budtarad,
• Wanrudee Isaranuwatchai

x

• Published: January 11, 2022
• https://doi.org/10.1371/journal.pone.0261930

Figures

Abstruse

Real-world effectiveness studies are of import for monitoring functioning of COVID-xix vaccination programmes and informing COVID-19 prevention and command policies. We aimed to synthesise methodological approaches used in COVID-19 vaccine effectiveness studies, in social club to evaluate which approaches are most appropriate to implement in low- and middle-income countries (LMICs). For this rapid systematic review, we searched PubMed and Scopus for articles published from inception to July seven, 2021, without language restrictions. We included any type of peer-reviewed observational study measuring COVID-xix vaccine effectiveness, for any population. We excluded randomised command trials and modelling studies. All data used in the analysis were extracted from included papers. We used a standardised data extraction form, modified from STrengthening the Reporting of OBservational studies in Epidemiology (STROBE). Study quality was assessed using the Existent Life EVidence AssessmeNt Tool (RELEVANT) tool. This written report is registered with PROSPERO, CRD42021264658. Our search identified 3,327 studies, of which 42 were eligible for analysis. Most studies (97.5%) were conducted in loftier-income countries and the bulk assessed mRNA vaccines (78% mRNA only, 17% mRNA and viral vector, 2.5% viral vector, ii.5% inactivated vaccine). Thirty-5 of the studies (83%) used a cohort report design. Beyond studies, short follow-upwards time and limited cess and mitigation of potential confounders, including previous SARS-CoV-2 infection and healthcare seeking behaviour, were major limitations. This review summarises methodological approaches for evaluating existent-globe effectiveness of COVID-nineteen vaccines and highlights the lack of such studies in LMICs, as well as the importance of context-specific vaccine effectiveness data. Further research in LMICs will refine guidance for conducting real-world COVID-xix vaccine effectiveness studies in resource-constrained settings.

Commendation: Teerawattananon Y, Anothaisintawee T, Pheerapanyawaranun C, Botwright S, Akksilp K, Sirichumroonwit N, et al. (2022) A systematic review of methodological approaches for evaluating real-world effectiveness of COVID-19 vaccines: Advising resource-constrained settings. PLoS One 17(1): e0261930. https://doi.org/ten.1371/periodical.pone.0261930

Editor: Chaisiri Angkurawaranon, Chiang Mai University, THAILAND

Received: August 23, 2021; Accepted: December xiii, 2021; Published: January 11, 2022

Copyright: © 2022 Teerawattananon et al. This is an open access article distributed nether the terms of the Creative Commons Attribution License, which permits unrestricted utilize, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All articles included in the review are listed in the manuscript and excluded manufactures are available in supplementary file. The data extraction form has been uploaded.

Funding: This study was funded by the Health Systems Inquiry Establish (https://hsri.or.th/researcher), grant number 64134002RM011L0. The funder of the study had no office in written report blueprint, data collection, data analysis, data interpretation, or writing of the report.

Competing interests: This study was funded by the Health Systems Inquiry Institute (https://hsri.or.th/researcher), grant number 64134002RM011L0. The authors declare that no other competing interests be.

Introduction

The COVID-xix pandemic has placed a pregnant cost on health systems and economies. With the development and scroll-out of COVID-19 vaccines, policymakers in low- and middle-income countries (LMICs) now have an additional tool to control the pandemic, with the potential to ease lockdowns and other non-pharmaceutical interventions. Yet there is increasing evidence to propose that vaccines are not a magic bullet, and policymakers will take to identify how to best employ vaccines as part of a comprehensive prepare of interventions [1]. In the immediate term, vaccination programme constraints, both in terms of vaccine supply as well as the capacity of health programmes to evangelize vaccine at an unprecedented scale, mean that policymakers must place how best to target vaccines for greatest impact. In the longer-term, financial sustainability is likely to go an ever more pressing issue. Policymakers take been able to allocate emergency funding to finance COVID-19 prevention and command measures, and many fiscal institutions have unlocked access to grants and concessional loans to tackle the pandemic [2]. However, as more data become available on vaccine duration of protection, protection confronting transmission, and protection against COVID-19 variants, policymakers will have to decide which vaccination strategies are sustainable and most appropriate to implement in their context [3]. Already in that location are stark differences in COVID-19 vaccination coverage targets between countries, ranging from those aiming to vaccinate xxx% of the population to those aiming for full population coverage [4].

To inform prove-based policies on the rational utilise of COVID-nineteen vaccines, LMICs require existent-world data on the effectiveness of vaccines in their context. Efficacy information from clinical trials are important for regulatory authorities to identify if a vaccine works and if information technology is safe. However, there are a number of limitations in using efficacy data for policy. Firstly, clinical trials use strict inclusion and exclusion criteria, which are not necessarily representative of all eligible populations for vaccination [5–seven]. For COVID-19, a number of vaccines have been recommended for utilize with limited data on effectiveness in the elderly, pregnant women, and populations with comorbidities, despite these being priority target groups in many countries [8–11]. Second, the setting of clinical trials may not reflect local epidemiology. COVID-19 vaccine clinical trials take been conducted in settings with different circulating strains, diverse underlying population health, varying transmission dynamics and not-pharmaceutical interventions (NPIs), and measuring unlike outcomes [12]. Finally, due to their nature, efficacy studies are unable to accost programmatic issues around health service utilization or off-label use [5]. For COVID-19 vaccines, this includes issues such as timely receipt of the second dose, modified vaccine schedules to address supply shortages or to align timing across vaccine products, vaccine acceptance and hesitancy (especially among specific population groups), interchangeability for mixed production schedules, cold chain excursions and other logistics problems, among others [13].

Real-world effectiveness studies are important for informing policy decisions, as an gauge of the context-specific operation of vaccines [13–15]. The results from real-world effectiveness studies not only monitor impact, merely also give state-specific inputs for modelling future strategies for vaccination and relaxation of NPIs, equally well every bit justifying budget allotment into, or away from, the COVID-19 vaccination programme. Due to the nature of real-globe effectiveness studies, they can exist subject to selection bias, confounding factors, and missing data, therefore requiring careful study design [5, sixteen, 17]. Of import considerations for observational studies include sample size; methods to minimise selection bias; accurate measurement of exposures and outcomes; planning for, managing, and reporting on potential confounders and missing data; and planning appropriate analysis [xvi, 17].

The World Health Organization (WHO) has published an interim guidance for conducting vaccine effectiveness studies in LMICs, and is maintaining a landscape of observational study designs for COVID-19 vaccination effectiveness [13, 18]. Whilst many studies take synthesised COVID-19 vaccine effectiveness estimates from observational studies [19–24], to our cognition, there is no systematic review of published real-world effectiveness study designs for COVID-19 vaccination, to support LMICs to understand which report designs are nigh viable to implement in their settings, and the advantages and drawbacks of different approaches. This review was commissioned by the Thai regime to summarise methodological approaches beingness used to written report real-globe COVID-19 vaccine effectiveness, to assess the quality of published literature, and to consider which best-exercise approaches are most suitable for implementation in Thailand and other LMICs.

Methods

Search strategy and choice criteria

Nosotros conducted a systematic review of the literature to place peer-reviewed research studies on COVID-19 vaccine effectiveness, in guild to analyse the study blueprint and methods for applicability to LMICs. We chose a rapid review methodology every bit a streamlined arroyo to quickly inform policymakers and researchers in Thailand and other LMICs that are in the procedure of developing vaccine effectiveness studies. Since the objective of the review was to analyse methodological approaches, we did not deport meta-assay to summarise the results.

We included research studies published in bookish journals in any language, which reported on the effectiveness of COVID-19 vaccination in real-world settings. We therefore included any type of observational written report, including cohort studies (prospective and retrospective), case control studies, examination-negative design case-command studies, and screening studies, but excluded randomised command trials (RCTs) and modelling studies. We also excluded regression aperture blueprint as it is currently recommended for vaccine effectiveness studies in diseases with low incidence, or for which there is a long time lag until the outcome [25]. Primary enquiry articles were eligible, as were letters to the editor, correspondence, reports, or rapid communications, provided that the methods were fairly described for data extraction and quality assessment of written report design. Due to our focus on methodological approaches, we simply included peer-reviewed literature, as quality assurance for study design and reporting. We did not exclude studies based on population of interest, but restricted inclusion to studies measuring the post-obit outcomes: asymptomatic SARS-CoV-ii infection, symptomatic SARS-CoV-ii infection, astringent SARS-CoV-ii infection (as measured by hospital admission, ICU access, or clinical diagnosis), or expiry from SARS-CoV-2 infection.

Nosotros executed a search strategy (S1 Appendix) of articles published from inception to July 7, 2021, in the MEDLINE (via PubMed) and Scopus databases. Search terms were constructed co-ordinate to intervention of involvement (COVID-19 vaccine) and report design (e.one thousand. cohort study, postal service-marketing study, effectiveness analysis). Searching the reference lists of the included studies and consultation with experts identified boosted relevant studies. In the first phase, titles and abstracts were screened independently by two reviewers, each from one of 2 separate teams. Whatever disagreement was resolved past one of 2 reviewers (YT or TA). In the second stage, total text was reviewed for inclusion/exclusion by a single reviewer.

Data analysis

All authors extracted information using a structured form modified from STrengthening the Reporting of OBservational studies in Epidemiology (STROBE), the reporting standard for observational studies [26]. Data were abstracted on written report characteristics (objectives, type of study design, country, study duration, funding source); study sample (population, sample size, presence of variants of concern); intervention (partial or full vaccination, vaccine product received); study outcomes; data collection and measurement methods (including utilisation of existing database); data analysis methods (subgroup analysis, statistical model, sensitivity analysis, direction of missing data and potential confounders); results (past outcome of interest); study limitations; and upstanding approving and/or consent requirements. Type of written report pattern was classified by the authors based on definitions from the WHO interim guidance on evaluation of COVID-nineteen vaccine effectiveness [13]. For the results, vaccine effectiveness (%) by issue was recorded. For studies reporting incidence charge per unit ratio (IRR), the formula (one-IRR)*100 was used to calculate vaccine effectiveness. The quality of studies was assessed by two contained reviewers using the REal Life Show AssessmeNt Tool (RELEVANT) tool [27]. Each principal and secondary sub-item was scored as 1 (yes) if performed or reported in the study, otherwise a score of 0 (no) was assigned. Two reviewers (YT and TA) resolved any discrepancy in scoring. Qualitative analysis of results from using the RELEVANT tool identified areas of limited evidence and highlighted opportunities to strengthen COVID-xix vaccine effectiveness study methodology.

Figures were produced using R, version 4.1.0 (Camp Pontanezen). The review protocol is registered at PROSPERO, CRD42021264658.

Results

We identified 5,933 manufactures through the database search. No additional articles were identified from searching reference lists. After removal of duplicates (ii,606) and exclusion of studies based on screening the abstract (iii,249) or the full text (42), 36 studies were identified. We included an additional 6 studies identified during skillful consultation, resulting in 42 papers for inclusion (Fig one). Of the 42 studies excluded during total text screening, 31 reported on an excluded event (not effectiveness) and 11 were an excluded study type (randomised control trial or modelling study). All studies were in English language, except one study in Spanish.

All 42 studies identified were published in 2022 and all but 1 study [28] were conducted in high-income countries (HICs) (Table 1). No studies were identified from Africa and only one from Asia [28]. Presence of circulating variants were reported in 12 (29%) studies [eleven, 29–39]. Most studies assessed effectiveness of mRNA vaccines (33 studies), followed past an mRNA and a viral vector vaccine (vii studies), and 1 written report each for viral vector and inactivated vaccine. Upstanding approval was required in 27 studies (64%), with 13 studies (31%) not reporting on ethical approval. Many studies (eighteen, 43%) did non report on funding source; for the other studies, eleven (26%) were publicly funded, ii (5%) funded through public and private funds, three (7%) through non-for-profit private funding, and 8 (19%) did not receive funding.

Table 2 summarises study characteristics. About studies (32 of 42, 76%) reported on vaccine effectiveness against either COVID-xix infection, hospitalisation, or death, whereas 3 studies reported ii outcomes (hospitalisation and infection [37, 66], hospitalisation and decease [51]) and 7 studies reported on all 3 outcomes [31, 33, 35, 42, 54, 58, 59]. Of the 37 studies measuring vaccine effectiveness against infection, 31 are cohort studies, 4 test-negative design example control studies, and 2 screening method (Fig 2). The most common study type is retrospective cohort study, (22 studies), often employing immunisation registries and medical databases. Only five studies considered asymptomatic infection among patients under investigation, frontline workers and randomly selected individuals in the community [eleven, 37, 39, 61, 62]. Virtually cohort studies were conducted among healthcare workers undergoing routine RT-PCR testing as part of the infirmary surveillance system. Sample size ranged from 189 to 10,187,720 (hateful 443,697; median vi,904). For vaccine effectiveness against hospitalisation and/or death, we identified 12 cohort and two test negative pattern instance control studies. Contrary to infection studies, none had healthcare workers as the population. All studies in the general population used national level surveillance information. Sample size ranged from 189 to 10,187,720 (mean 1,890,171; median 338,145). The examination negative designs had small sample sizes compared to cohort studies.

Tabular array three summarises methodology employed beyond included studies. Most studies assessed vaccination condition by registry (31), with 2 studies using self- report [nine, 41], 3 using a mixture of registry and self-report [35, 44, lx], and six studies not reporting on methods to define vaccination status [28, 32, 47, 61, 64, 65]. For confirmation of COVID-19 infection, 39 studies confirmed diagnosis with reverse transcription polymerase chain reaction (RT-PCR); ii studies used RT-PCR as the primary method of confirming diagnosis, but either allowed rapid antigen test for symptomatic cases [37] or if RT-PCR was not available [54]; and 1 study did not mention method of confirmation of COVID-nineteen [28]. Of the studies reporting methods to reduce misclassification error, well-nigh restricted analysis to samples collected within a sure number of days from symptom onset, ranging upwardly to vii days before symptom onset and 7–14 days after symptom onset [9, ten, 33, 35, 37, 46, 50]. Other studies reported reducing misclassification error by restricting analysis to symptomatic cases [9, 42, 46], censoring the date of unreliable vaccination dates [11], and conducting sensitivity assay removing days for possible misclassification [lx]. Although not reported as a method to reduce misclassification fault, an additional 12 studies just included symptomatic cases [10, 32, 34, 35, 39, 47, 50, 53, 54, 58]. At that place was considerable departure across studies in terms of when outcomes were assessed in vaccinated individuals: 10 studies just included outcomes more than than 14 days after vaccination [31–33, 37, 39, 44, 49, 54, 57, 60]; 10 studies more than than seven days afterwards vaccination [10, 34, 35, 42, 46, 47, 53, 55, 63, 66]; nine studies included outcomes more 14 days after vaccination for one of the two vaccine doses, and more than than 7 days after the other vaccine dose [9, 11, 30, 38, 45, 50, 51, 56, 62]; 2 studies included outcomes either 14 days or vii days after vaccination depending on vaccine blazon [48, 59]; seven studies included outcomes any time later vaccination, but stratified outcomes by number of days after vaccination [36, 40, 41, 43, 52, 58, 64]; 2 studies included outcomes whatever time later on vaccination [29, 65]; and 2 studies did not report on time between vaccination and upshot inclusion [28, 61]. 3 studies conducted sensitivity or sub-group analysis by days after vaccination [46, 49, 65].

For the quality assessment using RELEVANT, 9 of the 42 studies (of which all were accomplice studies) met less than half of the criteria [28, 34, 43, 47, 48, 53, 61, 63, 64]. But 10 of the 43 studies reported registration or publication of the study protocol and 17 reported on potential conflicts of interest (Fig three). Regarding study methods, there were a number of limitations across studies. Firstly, due to the brusk time since vaccine gyre-out, follow-up time for all studies was very short (mean half dozen.3 weeks for studies with infection outcomes, nine.vii weeks for hospitalisation or death outcomes). Secondly, simply x studies reported computing a sample size a priori (Fig three). Although studies with large national datasets do not need to calculate a minimum sample size, iii out of 4 (75%) of the examination negative case control designs with fewer than v,000 participants did not report calculating a minimum sample size [nine, 10, 41], and this was too the case for 6 out of 10 of the accomplice studies with fewer than v,000 participants [30, 47, 55, 57, 64, 65]. Thirdly, most studies did non clearly delineate inclusion/exclusion of study participants as a flowchart, although all studies were judged to be in a relevant population and setting. For the test-negative pattern instance control studies, ii studies were conducted in older adults [33, 41], whilst ii studies were conducted in wellness workers ([9, x]. However, 1 test-negative blueprint instance control study was in the full general population [32], which may be subject to collider bias. Fourthly, due to the observational study blueprint, selection bias and misreckoning furnishings were inevitable limitations. Nevertheless, 22 studies did not report on assessment and mitigation of potential confounders (Fig three). The about commonly reported confounders were age [nine–11, 29–33, 37, 39–42, 44–46, 50, 51, 54–57, 59–62, 66], sex [9, 10, 29–33, 37, 39–42, 44–46, l, 51, 54–57, 60–62, 66], socio-demographic factors (ethnicity/faith) [11, 33, 39, 41, 44, 50–52, 55, 60, 61, 66], geographical location [10, xi, 30, 33, 39, 41, 44, 51, 52, 54, 57, 62], chronic affliction and/or comorbidities [9, eleven, 31, 32, 37, 39, forty, fifty, 51, 54, 60, 66], time [10, 33, 36, 37, 40–42, l, 52, 57], occupation [10, 11, 39, 44, 45, 55, 56, 60], and socio-economic condition [33, 39, twoscore, 54, 57, 66]. Methods reported to manage confounders include adjusted logistic regression model [10, 11, 29, 30, 38, 45, 57, 60], stratified analysis [42, 54], matching cases and controls [51], and excluding population groups with high variability in the probability of vaccination or outcome [51]. iv studies reported adjusting for or conducting sensitivity analysis by different exposure or infection rates [forty, 49, 55, 62]. No study in our review measured adherence to NPIs and none of the test-negative pattern studies measured respiratory viral infection, which could bias likelihood of individuals seeking COVID-19 tests. Previous SARS-CoV-2 infection was not measured (or non reported) in the majority of studies, participants with prior infection were excluded in 16 studies, and 2 studies included prior infection in sensitivity analysis [ten, 33]. Finally, merely 14 of 26 studies reported on the extent of missing information (Fig 3). Studies reported dealing with missing data by creating a separate group for individuals with missing data [40], not including missing variables in the analysis [50, 60], or past mean imputation [32].

Discussion

To our cognition, this is the first systematic review of methodologies for COVID-19 vaccine effectiveness studies. Given the scale of COVID-nineteen vaccine roll-out thus far, our review identified relatively few studies assessing real-world vaccine effectiveness. All studies identified are from HICs, often utilising national databases (which may not exist or may be of poorer quality in LMICs), and the great bulk assessed mRNA vaccines, which are more prevalent in HICs but simply represent a third of the vaccines with WHO Emergency Apply List (EUL) [67] and one-fifth of COVAX secured supply from legally binding agreements [68]. Whilst the WHO landscape of observational studies has identified pre-prints and registered studies beingness conducted in six middle income countries (Argentina, Brazil, Bharat, Indonesia, Tunisia, Turkey) [eighteen], between our review and the WHO landscape certificate there are few real-earth effectiveness studies for vaccines that have received WHO EUL and no study in low-income countries. These findings underscore the importance of advocating for real-world effectiveness studies on all approved COVID-19 vaccines and beyond diverse LMIC settings.

Our review has highlighted several of import components to consider at the outset of designing a real-world effectiveness written report of COVID-nineteen vaccines, including the advisable study design, written report population, event, and time for follow-up. The almost mutual study blueprint identified in our review was a cohort arroyo, which may have been facilitated by the presence of large, reliable, and inter-linked databases in report countries. Test negative design case command studies were the second nigh common study design, but we did not place any case-control studies in this review. Nosotros hypothesise that this finding may be because of the challenges in enrolling an unbiased comparing group: the low number of case-control registered studies and pre-prints suggests that we did non select against instance-control studies past restricting our search to peer-reviewed articles [18].

In studies assessing symptomatic or asymptomatic infection every bit an event, healthcare workers were the most common study population. In many studies, healthcare workers were an opportune population due to routine symptomatic or RT-PCR screening activities undertaken within the wellness organization. Conversely, we identified no studies using healthcare workers every bit the study population for the outcomes hospitalisation and decease, which nosotros hypothesise as being due to the depression number of severe outcomes in this grouping [69]. Instead, studies either selected populations at high risk of disease (such as the elderly) or utilised large national databases to appraise outcomes in the general population. If large-calibration studies are not feasible, or rely on poor-quality databases, LMICs may find that exam-negative designs are most feasible to implement, as recommended past the WHO interim guidance [thirteen]. Regarding study population and issue, nosotros propose that health workers may exist the most appropriate population for studies measuring effectiveness against infection, whereas studies on hospitalisation/expiry may best focus on elderly populations or other loftier risk groups.

Given the short timeline since COVID-19 vaccine introduction, the elapsing of all studies was less than 5 months. Every bit would be expected, studies looking at hospitalisation and death tended to have longer duration than those assessing infection. Nonetheless, the short follow-upwards time may have underestimated vaccine effectiveness against severe outcomes, and means that studies were non able to consider duration of protection, which will exist important in informing strategies for delivering booster doses among different populations. Studies of longer duration may also allow assessment of irresolute vaccine effectiveness with the emergence of new VOCs. Despite widespread business organization on protection of COVID-nineteen vaccines confronting VOCs, many studies did not assess prevalence of variants and none reported on the delta strain. The WHO mural of observational studies for vaccine effectiveness suggests that this is likely to remain a significant gap in the literature for future research to consider [18].

Our review highlights several gaps that merit farther written report, alongside opportunities to strengthen the quality of real-world vaccine effectiveness studies. Firstly, we identified a demand for studies in LMICs, especially in Africa and Asia, as well as effectiveness studies with a longer duration and covering all vaccines with WHO EUL. Without information on vaccine effectiveness for all licensed products, governments may face diminishing public confidence towards the vaccines in use in their country. 2d, most studies did not summate (or study) the sample size a priori. Whilst this may be less relevant for retrospective cohort studies based on national databases, which often utilise thousands or millions of records, information technology is an important consideration for prospective study designs or smaller scale retrospective cohort studies. Since many LMICs are unlikely to be able to replicate the large-calibration studies from HICs, computing minimum sample size will exist very of import, and should account for differences in access to healthcare services and health seeking behaviour in LMICs, as compared with HICs. Third, we identified weaknesses beyond studies in identifying and mitigating against potential confounders, and in reporting on missing data. Missing data are likely to be a greater issue in LMICs and differences in healthcare utilisation are probable to be more than pronounced than in many HICs, requiring a well-considered plan for identifying and dealing with confounders and missing data. In particular, we note that many studies either did not measure for previous SARS-CoV-2 infection or used this as an exclusion criterion. If the infrastructure exists, nosotros recommend testing for previous infection and conducting sensitivity analysis including this grouping, to avoid selecting the sample based on exposure risk. Finally, most studies failed to report on the presence of VOCs or on disharmonize of involvement, including funding source. The former is important to answer to changes in vaccine effectiveness with new variants, and the latter is of import for credibility of studies for policymaking. Accordingly, nosotros recommend a number of additions to the WHO interim guidance on evaluation of COVID-nineteen vaccine effectiveness. The document would benefit from further guidance on setting an advisable fourth dimension horizon for studies, alongside guidance on designing studies that can be conducted with express resources. Nosotros also propose the inclusion of practical guidance on identifying important confounders for a given setting and management of missing data. Finally, we suggest the inclusion of managing and reporting disharmonize of interest, as a central part of study design.

There are several limitations to our review. We conducted the review only vii months later the first COVID-19 vaccines were licensed, limiting the number of studies and timeframe, also as skewing our search results towards HICs, which were the starting time to innovate COVID-19 vaccination. Restricting our search to peer-reviewed manufactures further express the number of results and favoured earlier studies in HICs with limited outcomes based on bachelor data. Considering of these limitations, our review was unable to objectively compare approaches that may exist more advisable to LMIC settings. Furthermore, considering of an urgent request from the Thai government, we employed rapid review methodology. Consultation with experts identified six boosted papers that were non captured by our search terms, and in that location may be other studies which nosotros missed. However, because the focus of our review is methodology of studies and not an gauge of vaccine effectiveness, we believe that this is acceptable. Particularly for the quality assessment of studies, nosotros had to brand assumptions based on reporting in the commodity, whereas contacting study authors for clarifications may accept yielded further information to enhance our analysis.

Despite the importance of real-globe effectiveness studies for informing national COVID-19 prevention and control policies in LMICs, existing studies tend to focus on settings, available vaccines, and VOCs specific to a handful of HICs. Although WHO recommends against conducting effectiveness studies in each country [xiii], in light of the heterogeneity between studies, we fence that there is benefit to each country designing and conducting effectiveness studies, subject to bachelor resources. Considerable funding has been made available from the public sector for COVID-19 vaccine evolution and deployment. Nosotros therefore argue that it is imperative for the public sector to proceed funding to the end of the product evolution continuum and finance studies on effectiveness and impact, not merely domestically just across countries, given the global nature of the COVID-nineteen pandemic.

In summary, our review highlights the importance of local vaccine effectiveness information, and in providing further guidance on important confounders and methods for managing missing data. Most vaccine effectiveness studies to date have been conducted in HICs with admission to reliable and interlinked databases for COVID-19 vaccination, diagnosis and treatment. Such databases oftentimes practice not exist in LMICs, meaning that countries will be employing prospective study designs, requiring a priori calculation of sample size and a articulate plan to manage and report on confounders and missing information. We highlight the express feel conducting vaccine effectiveness in LMICs, but emphasise the importance of such studies for policymakers in LMICs to develop and monitor vaccination policies, besides as to enhance public confidence in vaccination. Nosotros call on the global community to support LMICs to pb and implement COVID-xix vaccine effectiveness studies in their settings, as a priority inquiry area moving forwards.

Supporting information

Acknowledgments

The authors would like to admit Vice Public Wellness Minister Sopon Mekthon who commissioned this written report. The Health Intervention and Technology Assessment Program (HITAP) is supported past the International Decision Support Initiative (iDSI) to provide technical assist on wellness intervention and technology assessment to governments in depression- and centre-income countries. iDSI is funded by the Neb & Melinda Gates Foundation, the Britain's Section for International Evolution, and the Rockefeller Foundation. HITAP is also supported by the Admission and Commitment Partnership, which is hosted past the United Nations Development Program and funded by the Government of Japan.

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