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Open Access

Peer-reviewed

Research Article

Costs and cost-effectiveness of influenza illness and vaccination in low- and middle-income countries: A systematic review from 2012 to 2022

  • Radhika Gharpure ,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Visualization, Writing – original draft, Writing – review & editing

    krr4@cdc.gov

    Affiliation U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

    ⨯
  • Anna N. Chard,

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

    Affiliation U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

    ⨯
  • Maria Cabrera Escobar,

    Roles Data curation, Investigation, Methodology, Writing – review & editing

    Affiliation Task Force for Global Health, Atlanta, Georgia, United States of America

    ⨯
  • Weigong Zhou,

    Roles Conceptualization, Investigation, Methodology, Writing – review & editing

    Affiliation U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

    ⨯
  • Molly M. Valleau,

    Roles Investigation, Writing – review & editing

    Affiliation U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

    ⨯
  • Tat S. Yau,

    Roles Investigation, Writing – review & editing

    Affiliation U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

    ⨯
  • Joseph S. Bresee,

    Roles Conceptualization, Writing – review & editing

    Affiliation Task Force for Global Health, Atlanta, Georgia, United States of America

    ⨯
  • Eduardo Azziz-Baumgartner,

    Roles Conceptualization, Writing – review & editing

    Affiliation U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

    ⨯
  • Sarah W. Pallas,

    Roles Methodology, Writing – review & editing

    Affiliation U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

    ⨯
  • Kathryn E. Lafond

    Roles Conceptualization, Methodology, Project administration, Writing – review & editing

    Affiliation U.S. Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America

    ⨯

Abstract

Background

Historically, lack of data on cost-effectiveness of influenza vaccination has been identified as a barrier to vaccine use in low- and middle-income countries. We conducted a systematic review of economic evaluations describing (1) costs of influenza illness; (2) costs of influenza vaccination programs; and (3) vaccination cost-effectiveness from low- and middle-income countries to assess if gaps persist that could hinder global implementation of influenza vaccination programs.

Methods and findings

We performed a systematic search in Medline, Embase, Cochrane Library, CINAHL, and Scopus in January 2022 and October 2023 using a combination of the following key words: “influenza” AND “cost” OR “economic.” The search included studies with publication years 2012 through 2022. Studies were eligible if they (1) presented original, peer-reviewed findings on cost of illness, cost of vaccination program, or cost-effectiveness of vaccination for seasonal influenza; and (2) included data for at least 1 low- or middle-income country. We abstracted general study characteristics and data specific to each of the 3 study types. Of 54 included studies, 26 presented data on cost-effectiveness, 24 on cost-of-illness, and 5 on program costs. Represented countries were classified as upper-middle income (UMIC; n = 12), lower-middle income (LMIC; n = 7), and low-income (LIC; n = 3). The most evaluated target groups were children (n = 26 studies), older adults (n = 17), and persons with chronic medical conditions (n = 12); fewer studies evaluated pregnant persons (n = 9), healthcare workers (n = 5), and persons in congregate living settings (n = 1). Costs-of-illness were generally higher in UMICs than in LMICs/LICs; however, the highest national economic burden, as a percent of gross domestic product and national health expenditure, was reported from an LIC. Among studies that evaluated the cost-effectiveness of influenza vaccine introduction, most (88%) interpreted at least 1 scenario per target group as either cost-effective or cost-saving, based on thresholds designated in the study. Key limitations of this work included (1) heterogeneity across included studies; (2) restrictiveness of the inclusion criteria used; and (3) potential for missed influenza burden from use of sentinel surveillance systems.

Conclusions

The 54 studies identified in this review suggest an increased momentum to generate economic evidence about influenza illness and vaccination from low- and middle-income countries during 2012 to 2022. However, given that we observed substantial heterogeneity, continued evaluation of the economic burden of influenza illness and costs/cost-effectiveness of influenza vaccination, particularly in LICs and among underrepresented target groups (e.g., healthcare workers and pregnant persons), is needed. Use of standardized methodology could facilitate pooling across settings and knowledge sharing to strengthen global influenza vaccination programs.

Author summary

Why was this study done?

  • Cost-effectiveness analyses and other economic evaluations can provide important information to guide evidence-based decision-making, resource allocation, and long-term investment in vaccination by demonstrating value-for-money.
  • Cost-effectiveness analyses require accurate input data, including the costs of influenza illness, costs of vaccination, and impact of the vaccination program, to yield relevant and reliable results.

What did the researchers do and find?

  • We conducted a systematic review of studies describing the costs of influenza illness, costs of influenza vaccination programs, and influenza vaccination cost-effectiveness from low- and middle-income country settings during 2012 to 2022, given the availability of updated global tools for economic evaluations.
  • We collated the data from these articles, by study type and vaccination target group, to identify remaining gaps.
  • We identified 54 eligible studies published during 2012 to 2022, representing an increase from prior years, but studies from low-income countries and for specific target groups such as pregnant persons and healthcare workers were limited.

What do these findings mean?

  • Additional studies from low-income countries and underrepresented target groups would strengthen the evidence regarding value-for-money, as robust, global economic data are critical to design and maintain sustainable influenza vaccination programs.
  • Standardization of methodology across future economic evaluations, including considerations to capture the full spectrum of influenza-associated illness, could allow for pooled estimates and meta-analyses.
  • The main limitations of this review were the variability across studies, limiting our ability to generalize and compare findings, as well as restrictiveness of the inclusion criteria and potential for missed influenza burden by sentinel surveillance.

Citation: Gharpure R, Chard AN, Cabrera Escobar M, Zhou W, Valleau MM, Yau TS, et al. (2024) Costs and cost-effectiveness of influenza illness and vaccination in low- and middle-income countries: A systematic review from 2012 to 2022. PLoS Med 21(1): e1004333. https://doi.org/10.1371/journal.pmed.1004333

Academic Editor: Sydney Rosen, Boston University School of Public Health, UNITED STATES

Received: June 1, 2023; Accepted: December 13, 2023; Published: January 5, 2024

This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: This work was supported by the U.S. Centers for Disease Control and Prevention (https://www.cdc.gov/ncird/flu.html) through grant number CDC-RFA-IP21-2103 to the Task Force for Global Health. Coauthors from the funding agency participated in the study design, data collection and analysis, and preparation of the manuscript.

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

Abbreviations: CHEERS, Consolidated Health Economic Evaluation Reporting Standard; COVID-19, Coronavirus Disease 2019; GDP, gross domestic product; HIV, human immunodeficiency virus; ICER, incremental cost-effectiveness ratio; ILI, influenza-like-illness; IQR, interquartile range; LCI, laboratory-confirmed influenza; LIC, low-income country; LMIC, lower-middle income country; SAGE, Strategic Advisory Group of Experts on Immunization; SARI, severe acute respiratory infection; SIICT, Seasonal Influenza Immunization Costing Tool; UMIC, upper-middle income country; WHO, World Health Organization

Introduction

Seasonal influenza vaccination is a key intervention to prevent morbidity and mortality from influenza virus infections. The World Health Organization (WHO) Strategic Advisory Group of Experts on Immunization (SAGE) recommends that countries starting or expanding influenza vaccination programs prioritize specific target groups at high risk for transmission or severe disease, including healthcare workers, individuals with chronic medical conditions, older adults, and pregnant persons [1]. Additionally, depending on priorities, available resources, and feasibility, countries might consider additional target groups for vaccination, including young children, persons in congregate living settings, systematically disadvantaged populations, and indigenous populations [1]. As of 2018, 118 of 194 (61%) WHO member states had an influenza vaccination policy [2], while low- and middle-income countries represent 40% of the world’s population and have a high burden of influenza illness [3–5]; they constituted 85% of countries without a policy [2].

A 2019 survey indicated that lack of data on cost-effectiveness of influenza vaccination programs was a key barrier to initiating and expanding influenza vaccination programs in low- and middle-income countries [6]. Cost-effectiveness analyses and other economic evaluations can provide important information to guide evidence-based decision-making, resource allocation, and long-term investment in vaccination by demonstrating value-for-money; however, these evaluations require accurate input data, including the costs of influenza illness, costs of vaccination, and impact of the vaccination program, in order to yield relevant and reliable results [7].

To help countries better assess the value of influenza vaccination, the WHO and partners have developed standardized tools and updated guidance in recent years for economic evaluations regarding influenza illness and vaccination. These include 2016 guidance on estimating influenza economic burden [8,9], 2016 guidance on economic evaluations for influenza vaccination, including cost-effectiveness analyses [10,11], and a 2020 update to the Seasonal Influenza Immunization Costing Tool (SIICT) [12]. While previous systematic reviews have described economic data for influenza from low- and middle-income countries [13–17], these were generally conducted prior to the availability of these tools; more recent reviews have described data from high-income settings [16,18,19], focused on specific target groups [20–22], or addressed questions such as the comparative cost-effectiveness of quadrivalent and trivalent vaccines [23]. To summarize recent data and assess remaining gaps, we conducted an updated systematic review of studies describing the costs of influenza illness, costs of influenza vaccination programs, and influenza vaccination cost-effectiveness from low- and middle-income country settings published during 2012 to 2022.

Methods

This review followed the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines for systematic reviews (S1 PRISMA Checklist) and was registered at PROSPERO (international prospective register of systematic reviews) under protocol number CRD42022304803.

Search strategy and study selection

We performed a systematic search using Medline, Embase, Cochrane Library, CINAHL, and Scopus in January 2022 for studies with a publication year of 2012 through 2021. The search was updated in October 2023 to include studies published in 2022. Search terms were a combination of the following key words: “influenza” AND “cost” OR “economic;” specific search syntax for each database is provided in S1 Table.

Studies were eligible if they met the following inclusion criteria: (1) presented original, peer-reviewed findings on at least one of the following: (a) cost of illness, (b) cost of vaccination program, or (c) cost-effectiveness, cost-utility, or cost-benefit of vaccination (hereafter referred to as “cost-effectiveness studies”) for seasonal influenza; and (2) included data for at least 1 low- or middle-income country based on World Bank income group classification during the study period of each publication [24]. We excluded studies that: (1) did not present original or peer-reviewed findings (e.g., literature reviews, conference abstracts, and editorials); (2) only presented data about infection with or vaccination for pandemic or novel influenza viruses (e.g., influenza A(H1N1)2009 pandemic strain), as these were not considered representative of seasonal influenza infection and/or vaccination; (3) included data from mid-2009 through mid-2010 that could not be disaggregated from other results, as these months were considered to represent the global influenza A(H1N1)2009 pandemic period [25]; or (4) presented data only from March 2020 through the end of 2022, as these years represented the global Coronavirus Disease 2019 (COVID-19) pandemic. Studies in any language were eligible for inclusion.

Specifically, cost-of-illness studies were required to use a case definition of laboratory-confirmed influenza (LCI) or syndromic definitions of influenza-like-illness (ILI) and/or severe acute respiratory infection (SARI), though estimates could then be extrapolated to include other disease presentations (e.g., non-medically attended illnesses). Program cost studies were required to present the monetary value of resources required for an influenza vaccination program; studies that described only the cost of vaccine purchase were excluded. Cost-effectiveness studies were required to include a comparison of influenza vaccination versus no vaccination or modifications to current vaccination program (e.g., increase in vaccination coverage); studies that only compared the cost-effectiveness of different influenza vaccine products (e.g., quadrivalent versus trivalent, adjuvanted versus non-adjuvanted, or live attenuated versus inactivated) were not included.

Titles and abstracts identified by the search strategy were independently screened by 2 reviewers (RG, ANC, MCE, WZ, or KEL) for eligibility; a publication was included for full-text review if either reviewer flagged it as potentially eligible. English-language full texts were again reviewed by 2 reviewers (RG, ANC, MCE, WZ, or MMV) for eligibility, with a third reviewer resolving any conflicting decisions. Identified publications in other languages were reviewed by a single native-language speaker (Mandarin Chinese, Russian, Spanish, and Bulgarian). All screening procedures were performed using Covidence, a web-based collaboration software platform for systematic reviews [26]. We also reviewed references from included studies to identify additional relevant literature for inclusion.

Data extraction and quality assessment

Data from English-language publications were independently extracted by 2 reviewers (RG, ANC, MCE, WZ, or MMV), and disagreement was resolved by a discussion between the reviewers and consultation with a third reviewer if necessary. Data from publications in Mandarin Chinese were abstracted by a single native-language speaker (WZ or TSY); no other non-English publications met inclusion criteria.

A standardized Microsoft Excel-based data extraction form was developed to include the following information for all studies: country, study period, study methods, SAGE target group(s) represented, economic evaluation perspective, and funding source. Additionally, for cost-of-illness studies, we abstracted direct and indirect costs of outpatient visits and hospitalizations, as well as national economic burden if reported. For program cost studies, we abstracted financial and economic costs both including and excluding vaccine procurement. Financial costs were incremental monetary expenditures made for the influenza vaccination program; economic costs included all financial costs as well as the value of existing resources and donations (as categorized by study authors). For cost-effectiveness studies, we abstracted the study intervention(s), comparator(s), incremental cost-effectiveness ratio (ICER), ICER interpretation, and cost-effectiveness threshold. If reported, we preferentially abstracted median values for economic variables; if medians were not reported, we abstracted mean values or ranges. We did not contact study authors to request additional data.

We used World Bank data to classify the income group of countries during the study period [24]; if countries changed income group classification during the study period for a single publication, the higher classification was used. If multiple studies were published before and after a change in income group classification, the country was classified into multiple income groups corresponding to the classification during each study period. Additionally, we used World Bank data to obtain the gross domestic product (GDP) of countries during the study period [24]; for multiyear studies, the final year of the study period was used. For cost-of-illness and program cost studies, we also used WHO data to obtain the Current Health Expenditure and Domestic General Government Health Expenditure, respectively, of countries during the study period [27]. If no study period was specified, we used 3 years prior to the publication year for all relevant inputs as in prior systematic reviews [23].

For each English-language publication, 2 reviewers (RG, ANC, MCE, WZ, or MMV) assessed study quality and risk of bias using the Consolidated Health Economic Evaluation Reporting Standard (CHEERS) checklist [28]; for non-English publications, 1 native speaker (WZ or TSY) completed the CHEERS checklist. The checklist includes 24 criteria developed to ensure standardized reporting across economic studies; all 24 were assessed for cost-effectiveness studies, and modified sets of 13 and 15 criteria were used for cost-of-illness and program cost studies, respectively (S2 Table).

Data conversion and analysis

We converted all currencies to US dollars (US$) using the International Monetary Fund official exchange rate for the nominal year [24] and then inflated all results to 2022 US$ using the US Bureau of Economic Analysis GDP implicit price deflator [29,30]. If a nominal currency year was not presented in the study, we used the final year of the study period or, if the study period was not stated, 3 years prior to the publication year. We calculated the gross national economic burden and program cost, when reported, as a proportion of the national GDP and the national health expenditure. Additionally, we collated direct and indirect costs by SAGE target group and income group and reported ranges across strata. Similarly, we also collated ICER results by SAGE target group and income group and calculated the proportion of studies that interpreted findings as “cost-saving” (ICER<0), “cost-effective” (dependent on cost-effectiveness threshold specified in the study), or “not cost-effective.” All analyses were performed using SAS (version 9.4) and Microsoft Excel.

Patient and public involvement

As this was a systematic review of published literature, patients and the public were not involved in the design, conduct, reporting, or dissemination plans of this work.

Results

Study characteristics and quality assessment

Of 7,547 total studies identified, 54 met eligibility criteria and were included in this review, including 46 English-language and 8 Chinese-language studies (Fig 1 and S3 Table). Study characteristics are presented in Table 1; a total of 26 studies presented cost-effectiveness findings, 24 presented cost-of-illness, and 5 presented program costs. Studies included data from 21 country settings, which were classified as upper-middle income countries (UMICs; n = 12), lower-middle income countries (LMICs; n = 7), and low-income countries (LICs; n = 3); 1 country, China, was classified as both UMIC and LMIC corresponding to multiple studies before and after an upward change in World Bank classification in 2010. These 21 countries represented 13% of 157 countries/territories classified as low- or middle-income countries in any year during 2005 (earliest year of data presented in included studies) through 2022. The most frequently evaluated SAGE target groups were children (n = 26 studies, inclusive of children aged <18 years), older adults (n = 17, inclusive of adults aged ≥60 years), and persons with chronic medical conditions (n = 12); fewer studies evaluated pregnant persons (n = 9), healthcare workers (n = 5), and persons in congregate living settings (n = 1).

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Fig 1. PRISMA flow diagram of study selection process.

ILI, influenza-like illness; SARI, severe acute respiratory infection.

https://doi.org/10.1371/journal.pmed.1004333.g001

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Table 1. Number of included studies by income group classification, region, Strategic Advisory Committee of Experts on Immunization (SAGE) target group, and study type.

https://doi.org/10.1371/journal.pmed.1004333.t001

Quality assessment scores indicated that the quality of included studies was acceptable; median scores by study type were 12 out of 13 (92%; interquartile range [IQR] 92% to 100%) for cost-of-illness, 14 out of 15 (93%; IQR 93% to 100%) for program costs, and 23 out of 24 (96%; IQR 84% to 100%) for cost-effectiveness studies (S1 Fig); only 3 of all 54 studies (6%) scored <75%. Of 48 studies that reported a funding source, 8 (18%) were supported by pharmaceutical industry and 22 (46%) by the WHO or the US Centers for Disease Control and Prevention (CDC).

Cost-of-illness studies

The cost-per-episode of influenza illness ranged widely across studies (Fig 2). Twenty-four studies presented data about cost-per-episode, representing 8 UMICs (China [31–39], Colombia [40,41], Kazakhstan [42], Mexico [43], Panama [44], Romania [42], South Africa [45,46], and Thailand [47]), 6 LMICs (China [based on classification during study period] [48], El Salvador [44], India [49], Kenya [50], Ukraine [42], and Vietnam [51,52]), and 2 LICs (Bangladesh [53] and Mali [54]) (S4 Table). Among the general population, the total cost-per-episode for outpatient visits, inclusive of direct and indirect costs, ranged from $6.24 to 155.92 (2022 US$); the total cost-per-episode for hospitalizations ranged from $106.85 to 1,617.14. Among SAGE target groups, total cost-per-episode of outpatient visits and hospitalizations was $25.92 to 198.13 and $95.15 to 2,202.74 for children, $38.17 to 164.52 and $282.37 to 2,729.25 for older adults, $44.13 to 176.79 and $847.60 to 1,578.86 for persons with chronic medical conditions, and $5.45 to 36.97 and $189.98 to 1,088.92 for pregnant persons. Costs across all target groups were generally higher in UMICs than in LMICs/LICs (Fig 2). Indirect costs comprised a greater proportion of the total costs of outpatient visits compared with hospitalizations and a greater proportion of total costs in LMICs/LICs compared with UMICs (S2 Fig). Details on costs abstracted from each study are described in S4 Table.

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Fig 2. Total costs-per-episode1 of influenza illness, by disease severity (outpatient vs. hospitalized)2, income group, and Strategic Advisory Committee of Experts on Immunization (SAGE) target group3, in low- and middle-income countries.

Plot representation: The horizontal line inside the box represents the median. The lower and upper borders of the box represent the 25th and 75th percentiles, respectively. The whiskers indicate 1.5 times the interquartile range from the lower and upper borders of the box. The cost-per-episode1 reported in each study is depicted as a filled dot. Costs from low-income and lower-middle income countries are combined as 1 group (“LMIC/LIC”) and shown in magenta; costs from upper-middle income countries are in blue. The group “Children” is inclusive of children aged <18 years; “Older adults” is inclusive of adults aged ≥60 years. All costs are presented in 2022 US$. LIC, low-income country; LMIC, lower-middle income country; UMIC, upper-middle income country; US$, US Dollars. 1Total costs inclusive of direct and indirect costs; direct costs were all medical and non-medical costs directly attributable to patient care. Indirect costs were all costs not directly attributable to patient care (e.g., lost earnings or lost productivity). Median costs were preferentially abstracted from source publications; if unavailable, mean costs were abstracted. 2No included papers reported hospitalization costs for older adults or persons with chronic medical conditions in LMIC/LIC. 3No cost-of-illness papers were identified for healthcare workers or individuals in congregate living settings in low- and middle-income countries.

https://doi.org/10.1371/journal.pmed.1004333.g002

Four studies evaluated the cost-per-episode for multiple SAGE target groups [33,37,46,51]. Studies from China and Vietnam found higher hospitalization costs among older adults compared with children [33,37,51], as well as higher costs associated with chronic medical conditions across age groups [33,37]. In South Africa, total economic burden after incorporating rates of illness was highest for persons with chronic medical conditions, followed by children, older adults, and pregnant persons [46]. Across all studies, characteristics that impacted cost-of-illness included urbanicity (rural versus urban) [33,37,48], facility type (public versus private or level of care provision) [33,53], and influenza season or circulating virus type [35,38].

Seven of the 23 studies reported a national economic burden of influenza illness for either the general population or specific SAGE target groups (Table 2), representing 3 UMICs (China [39], Romania [42], and South Africa [45,46]), 2 LMICs (Kenya [50] and Ukraine [42]), and 1 LIC (Bangladesh [53]). Total annual costs of influenza illness in studies evaluating the general population (no specified SAGE target group) were equivalent to 0.02% to 0.19% of the national GDP and 0.32% to 7.16% of the national health expenditure; costs for any single target group were <0.01% to 0.02% of the national GDP and 0.01% to 0.42% of the national health expenditure. The highest total costs, as a percent of GDP and national health expenditure, were reported from Bangladesh [53]. Three studies accounted for non-medically attended illnesses in the estimation of national economic burden [42,45,46].

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Table 2. National economic burden of influenza illness, by Strategic Advisory Committee of Experts on Immunization (SAGE) target group1, in low- and middle-income countries.

https://doi.org/10.1371/journal.pmed.1004333.t002

Program cost studies

Five studies evaluated the cost of influenza vaccination programs (Table 3): 4 with findings from UMICs (Albania [55], China [56], South Africa [57], and Thailand [58]) and 1 from an LIC (Malawi [59]). Of these, 2 evaluated the cost of a program targeting pregnant persons [58,59], 1 evaluated a program targeting healthcare workers [55], and 2 evaluated programs targeting multiple SAGE target groups (older adults, persons with chronic medical conditions, children aged <5 years, pregnant persons, and healthcare workers in China [56] and older adults, pregnant persons, and persons with chronic medical conditions and human immunodeficiency virus (HIV) in South Africa [57]). Three studies used the WHO SIICT [12,55,57,59]. The total annual cost of program was equivalent to <0.01% to 0.02% of the national GDP and 0.06% to 4.78% of the national health expenditure; the highest proportion of health expenditure was reported in the study vaccinating the greatest number of target groups [56]. Vaccine procurement, when vaccine was purchased by the government, represented a large proportion of total costs in both Albania (89% financial and 44% economic) [55] and South Africa (99% financial and 37% economic) [57]. Additionally, when vaccine was donated, the value of vaccine procurement represented 82% of economic costs in Malawi [59]. Across studies, the total cost per dose administered ranged from $0.62 to 5.20 (financial) and $0.81 to 13.72 (economic), inclusive of vaccine purchase or donation.

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Table 3. Costs of national influenza vaccination programs in low- and middle-income countries.

https://doi.org/10.1371/journal.pmed.1004333.t003

Cost-effectiveness studies

Twenty-six studies presented data on cost-effectiveness of influenza vaccination (S5 Table), representing 8 UMICs (Argentina [60], China [61–67], Colombia [68], Malaysia [69], Mexico [70–72], South Africa [73–75], Thailand [76–80], and Turkiye [81]), 4 LMICs (Kenya [82], Lao PDR [83], Ukraine [84], and Vietnam [73]), and 1 LIC (Mali [54]). Twenty-two (85%) studies evaluated influenza vaccine introduction (i.e., vaccination compared with no vaccination), 2 evaluated the effect of increased vaccination coverage on an existing program, and 2 evaluated combinations of new introduction and increased coverage for different target groups. Cost-effectiveness thresholds varied greatly across studies; most (n = 16/26; 62%) used a threshold within 1 to 3 times the GDP per capita, 3 (12%) used other country-specific thresholds, 1 (4%) intentionally did not report a threshold (instead, cost-effectiveness acceptability curves were presented over a range of willingness-to-pay thresholds [73]), and the remaining 6 (23%) did not provide any details about thresholds.

Among the 22 studies that evaluated the cost-effectiveness of vaccine introduction, 8 provided results for children, 6 for older adults, 4 for persons with chronic conditions, 4 for pregnant persons, 3 for healthcare workers, and 1 for persons in congregate living settings, summing to 26 target-group-specific scenarios modeled. Most (23/26; 88%) interpreted at least 1 modeled scenario for each SAGE target group as either cost-effective (based on designated cost-effectiveness threshold) or cost-saving (ICER<0) (Fig 3). The number of studies that identified results as cost-saving were 3/8 (38%) for children, 2/6 (33%) for older adults, 2/4 (50%) for persons with chronic medical conditions, 1/4 (25%) for pregnant persons, and 3/3 (100%) for healthcare workers. Similarly, the number of studies that identified results as cost-effective were 3/8 (38%) for children, 3/6 (50%) for older adults, 2/4 (50%) for persons with chronic medical conditions, 3/4 (75%) for pregnant persons, and 1/1 (100%) for persons in congregate living settings. Only 3 studies interpreted all modeled scenarios for a particular target group as not cost-effective: 2/8 (25%) evaluating cost-effectiveness among children [75,82] and 1/6 (17%) among older adults [66].

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Fig 3. Cost-effectiveness results of studies evaluating influenza vaccination1, by Strategic Advisory Committee of Experts on Immunization (SAGE) target group, in low- and middle-income countries.

Plot representation: Bars represent the number of studies identified by target group and income group. Results from low-income and lower-middle income countries are combined and analyzed as 1 group, designated “LMIC/LIC.” Dark blue bars depict the number of studies that interpreted a result as “cost-saving,” light blue bars depict the number of studies that interpreted a result as “cost-effective,” and magenta bars depict the number of studies that interpreted a result as not cost-effective. Categorization is based on the interpretation provided in the original study; if any modeled intervention was interpreted as cost-saving (ICER<0), the study was characterized as “cost-saving” and if any modeled intervention was interpreted as cost-effective, the study was characterized as “cost-effective.” Interpretations of highly cost-effective and cost-effective were both combined as “cost-effective.” Details on each modeled scenario are provided in S5 Table. The group “Children” is inclusive of children aged <18 years; “Older adults” is inclusive of adults aged ≥60 years. LIC, low-income country; LMIC, lower-middle income country; UMIC, upper-middle income country. 1Only includes studies comparing cost-effectiveness of influenza vaccination vs. no vaccination. Additional studies examining cost-effectiveness of modifications to a current vaccination program (e.g., increased coverage) are described in S5 Table.

https://doi.org/10.1371/journal.pmed.1004333.g003

Two studies assessed the cost-effectiveness of influenza vaccine introduction for multiple target groups; of these, the target groups with the greatest value-for-money were healthcare workers in Laos (cost-saving; other groups evaluated were pregnant persons and older adults, found to be cost-effective) [83], and pregnant persons and persons with chronic medical conditions in South Africa (cost saving; other groups evaluated were older adults, found to be cost-effective, and children, not found to be cost-effective) [75]. Across all studies, the 3 variables most commonly identified to influence the ICER in sensitivity analyses were annual incidence of influenza (n = 10 studies) [54,60,61,67,73–75,78,81,83], vaccine effectiveness (n = 10 studies) [60,65,67,68,74–77,81,83], and cost of vaccine (n = 6 studies) [54,74,75,77,78,82]; some studies demonstrated that variation in the attack rate [61,73,75,78] or vaccine effectiveness [75] could change the interpretation of cost-effectiveness results (cost-saving, cost-effective, or not-cost-effective).

Additionally, 7 papers looked at different prioritization strategies within SAGE target groups by underlying health conditions [74,76] or age [60,61,77,79,82]; among pregnant persons in South Africa, prioritization of people living with HIV reduced the ICER (though not statistically significant) [74], and among persons with underlying coronary heart disease in Thailand, restricting to only persons with angina reduced the ICER, whereas restricting to persons with cardiac arrest/myocardial infarction increased the ICER (no longer cost-effective) [76]. Results by age were also mixed; 2 studies among children found lower ICERs for vaccinating younger children (6 to 23 months versus 2 to 5 years or 6 to 14 years in Kenya [82] and 6 to 59 months versus 5 to 14 years in China [61]), 2 studies among children found lower ICERs for vaccinating wider age ranges (6 months to 5 years versus 6 to 23 months or 6 to 36 months in Argentina [60]) or older children (12 to 17 years versus 2 to 5 years or 6 to 11 years in Thailand [77]), and a study among persons with underlying heart disease in Thailand found a lower ICER for persons aged ≥50 years compared with ≥40 years or ≥60 years [79].

Discussion

The 54 studies identified in this review suggest an increased momentum to generate economic evidence about influenza illness and vaccination from low- and middle-income countries during 2012 to 2022; a previous review using a similar search strategy identified only 22 cost-of-illness or cost-effectiveness studies from low- and middle-income countries published as of 2012 [15], and another identified 9 cost-effectiveness/cost-benefit/cost-utility studies published as of 2011 [13]. The release of updated tools and guidance by the WHO, as well as technical and financial support by the WHO, CDC, and other international partners, has facilitated this expansion of the evidence base, emphasizing the utility of global and multinational collaborations in strengthening influenza vaccination programs worldwide. Studies included in this review were generally of good quality based on their quality assessment scores; however, we identified substantial variability in methodologies and approaches. Although methods for meta-analysis of economic data are available [85] and have been used in other reviews that focus predominantly on high-income settings [17], we did not conduct these analyses because of study heterogeneity.

Recent additions to the literature since 2012 include studies from LMIC/LICs, studies representing sub-Saharan Africa, South Asia, and middle-income European countries, and studies focused on pregnant persons; none of these were represented in the previous reviews, which only identified data from UMICs in East Asia, Latin America, and Europe [13,15]. However, there are still disparities in available data by income group and region; LICs are still very underrepresented, and no studies from low- and middle-income countries in the Middle East and North Africa region were identified in our review. As of a global survey in 2018, very few LICs (2/31; 6%) reported having a national influenza vaccine policy in place [2]; absence of a vaccination program could in part explain their underrepresentation in the literature, but also underscores the importance of generating policy-relevant data on cost-of-illness and projected costs and cost-effectiveness of vaccination. By comparison, 78% (45/58) of UMICs and 39% (18/46) LMICS had an influenza vaccine policy in 2018 [2].

Additionally, pregnant persons, healthcare workers, and persons in congregate living settings remain especially underrepresented in economic evaluations. Healthcare workers are of particular interest because of the potential benefit of vaccination to themselves and the greater health system [86]. To date, global literature about cost-effectiveness and other evidence for influenza vaccination among healthcare workers remains limited [86,87], but notably, we identified cost-saving results for healthcare worker vaccination in Lao PDR [83], Malaysia [69], and Ukraine [84], suggesting high value-for-money. Additional data are needed to strengthen the evidence to optimize influenza vaccination in this target group.

Among all cost-of-illness studies, we found that the cost-per-episode estimates for influenza outpatient visits and hospitalizations varied widely. Per-episode costs were generally greater in higher income settings (i.e., UMICs compared with LMICs/LICs), likely reflecting higher costs of care, but the national economic burden among the general population, which ranged from 0.01% to 7% of the national health expenditure, was highest in an LIC (Bangladesh; 7% [53]). For comparison, a prior review indicated that the economic burden as a percentage of national GDP, in high-income countries and UMICs in North America, Europe, Asia, and Australia, ranged from 0.01% to 0.14% [15]. More studies from LICs are needed to further evaluate disparities among income groups.

Many studies used data from ILI/SARI sentinel surveillance sites for estimating economic burden; these surveillance systems can serve as a valuable data source but are not typically designed to capture non-medically attended illnesses [88] or non-respiratory disease outcomes [89], thereby underestimating the true economic burden of influenza. In South Africa for example, estimates obtained among patients meeting a SARI/ILI case definition underestimated the total economic burden by approximately 65% [45]; thus, comprehensive strategies and innovative strategies are needed to better characterize economic burden. Finally, characteristics of the underlying population in a particular setting, such as age structure and prevalence of underlying medical conditions, might affect costs across target groups; for example, in South Africa, where the highest burden was in individuals with chronic medical conditions, this was impacted by HIV and tuberculosis prevalence in the population [45,46]. Thus, economic evaluations that address multiple target groups in a particular setting, rather than a single target group, can provide valuable evidence to inform local vaccination policy; given limited resources for vaccination programs, such comparisons could assist with target group prioritization.

We identified only 5 program cost studies, indicating a need for more evaluations in low- and middle-income countries. Vaccine delivery cost studies can provide direct evidence to policymakers to make decisions on vaccine introduction, plan budgets and financing strategies for rollout, and identify efficiencies in service delivery [90]. In fact, the WHO SIICT [12] and other costing methods can be used even in the absence of an existing program, as performed in Malawi [59]. The 5 studies that we identified indicated that influenza vaccination programs generally cost a small fraction compared to the national GDP (≤0.02% in these studies) or national health expenditure (≤1% per each individual target group covered in these studies) [55–59]. Vaccine procurement was a major driver of program costs in all 3 studies that disaggregated this component, representing 82% of economic costs (including the value of donated resources) of the hypothetical maternal vaccination program using donated vaccine in Malawi [59], 99% of financial and 37% of economic costs of a vaccination program utilizing government-procured vaccines for multiple target groups in South Africa [57], and 89% of financial and 44% of economic costs of a healthcare worker vaccination program utilizing a combination of government-procured and donated vaccines in Albania [55]. This underscores the importance of sustainable financing and procurement strategies to support access to influenza vaccines and enable successful program implementation, consistent with lessons learned from other vaccine introductions [91]. In the 2 studies that presented costs exclusive of vaccine procurement ($7.68 economic cost-per-dose for healthcare workers in Albania [55] and $6.45 economic cost-per-dose for multiple target groups in South Africa [57]), the costs for influenza vaccination were generally higher than the estimated incremental cost to deliver a single, newly introduced vaccine (e.g., pneumococcal conjugate vaccine or rotavirus vaccine) in low-income countries ($0.57 to 1.63 in 2022 US$) [92], likely because the costs for delivering vaccine to influenza target groups rely on different systems and infrastructure than routine immunization delivery for children. Again, as costs may vary across target groups, evaluating program costs in multiple groups within a given country context could provide useful data for resource prioritization.

Among cost-effectiveness studies identified in this review, most reported at least 1 cost-saving or cost-effective vaccination scenario per target group assessed; however, results were significantly impacted by variables such as influenza incidence, vaccine effectiveness, cost of vaccine, and vaccine coverage, as well as by prioritization within target groups (e.g., by age or specific underlying health conditions). Strategies to address this variability include use of at least 5 years of data to assess disease burden, if available, and use of sensitivity analyses among ranges of plausible values, for example, including vaccine effectiveness estimates from years with high and low antigenic match of vaccine with circulating viruses [11]. Future studies could use innovative approaches to more completely characterize the total disease and economic burden of influenza, as well as additional endpoints for vaccine effectiveness (illness attenuation) and indirect protection from vaccination [7]. Finally, the use of appropriate cost-effectiveness thresholds in low- and middle-income settings warrants further discussion [93,94]. In our review, among only 3 studies that did not identify any cost-effective scenarios, 2 used a cost-effectiveness threshold less than GDP per capita [75,82]; however, using the GDP per capita would have resulted in a cost-effective result in both. Use of context-specific thresholds reflecting local preferences [95], such as local health opportunity costs [96], might provide more valuable information to guide investment decisions than thresholds of 1 to 3 times GDP per capita [93,94,97,98]. As indicated in the WHO guidance for economic evaluations for immunization programs, if willingness-to-pay values are not available for a given country, cost-effectiveness results should be shown for a range of willingness-to-pay values, along with the vaccine price on which they are based [99].

This review is subject to several notable limitations. First, the inclusion/exclusion criteria used (e.g., estimates derived from LCI or ILI/SARI case definition; no comparison of vaccine formulations) undercount the total number of economic studies from low- and middle-income countries within the past 10 years. Multiple other studies have evaluated costs of acute respiratory illness, of which influenza is an important etiology, or addressed other economic questions, such as the cost-effectiveness of quadrivalent versus trivalent vaccine [23,100], and were not captured here. Influenza illness might also present as non-respiratory outcomes [89], and thus the economic burden of influenza is underestimated in most studies that restrict to syndromic surveillance for ILI/SARI [88]. Second, although we conducted the search using multiple databases and considered publications in any language eligible for inclusion, we might have missed studies published in national or regional journals. Third, target group definitions vary across countries, with variation in age cut-offs for children and older adults and prioritization of specific chronic medical conditions, but all results per target group were summarized together in this review because of the small numbers of publications, potentially missing nuances of within-group differences. Relatedly, although SAGE recommendations specifically reference children aged <5 years [1], all publications with data for children and adolescents aged <18 years were included. Finally, we found substantial heterogeneity in the methodology and data inputs used across studies; in addition, influenza itself intrinsically varies in annual incidence, disease severity, and vaccine effectiveness across seasons. As previously discussed, we did not conduct meta-analyses because of this variability, though methods for meta-analysis of economic data are available [85] and have been used in other reviews that focus predominantly on high-income settings [21].

This review also uncovered opportunities to provide evidence about policy-relevant questions that currently have limited evidence. First, we only identified 1 study taking an employer payer’s perspective [69]; additional studies utilizing this approach could provide valuable policy-relevant information to encourage vaccination among employees or to encourage employer-supported vaccination programs [101] as a pathway to broader influenza vaccine availability. Second, we only identified 1 included study that evaluated cost-effectiveness of influenza vaccination coadministered with another vaccine (pneumococcal vaccine) [68]; a few additional studies addressing coadministration were excluded because they did not provide results for influenza vaccination alone. Given opportunities to coadminister influenza vaccine with other vaccines across the life course, including COVID-19 vaccine [102], evaluation of shared costs in program cost or cost-effectiveness studies might incentivize integrated vaccine implementation. Third, we found only 2 studies that considered non-respiratory disease outcomes (cardiovascular disease events) in cost-effectiveness analyses, both among persons with underlying heart disease in Thailand [76,79]; as previously discussed, inclusion of non-respiratory disease outcomes could better characterize the full impact of influenza vaccination [89]. Finally, innovative strategies might address the broader impact of vaccines, such as impact on childhood development, household behavior, economic growth, political stability, and health equity [103,104].

Continued evaluation of costs and cost-effectiveness is useful to drive evidence-based vaccine policy development, implementation, refinement, and global investment in influenza vaccination. In this review, we documented an increased number of economic evaluations on influenza illness and vaccination from low- and middle-income countries during 2012 to 2022 compared with prior years. Additional studies from low-income countries and underrepresented target groups (e.g., pregnant persons, healthcare workers, and persons in congregate living settings) would strengthen the evidence regarding value-for-money. Standardization of research agenda [1] and methodology across future evaluations, including considerations to capture the full spectrum of influenza-associated illness, could allow for pooled estimates and meta-analyses. Global, regional, and country-specific data on the economics of vaccination, including costs of vaccination programs, costs of avertable illnesses, and cost-effectiveness, are instrumental for policymaking and resource allocation for expanded and sustainable influenza vaccination programs.

Supporting information

S1 PRISMA Checklist. PRISMA 2020 Main Checklist.

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S1 Fig. Distribution of modified Consolidated Health Economic Evaluation Reporting Standard (CHEERS) quality assessment scores.

Plot representation: The horizontal line inside the box represents the median. The lower and upper borders of the box represent the 25th and 75th percentiles, respectively. The whiskers indicate 1.5 times the interquartile range from the lower and upper borders of the box. All CHEERS scores are presented as a percent of total possible score; the full CHEERS criteria assessment [28] was performed for cost-effectiveness studies and a modified set of relevant criteria were assessed for cost-of-illness and cost-of-program studies, as explained in S2 Table. CHEERS, Consolidated Health Economic Evaluation Reporting Standard.

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S2 Fig. Contribution of direct and indirect costs to costs of influenza outpatient visits and hospitalizations, by target group, in low- and middle-income countries.

Plot representation: Vertical bars represent the contribution (as percent of total) of direct costs (blue) and indirect costs (gray) to total outpatient visit costs (left column) and hospitalization costs (right column), by target group. Direct costs were all medical and non-medical costs directly attributable to patient care, as reported in the study. Indirect costs were all costs not directly attributable to patient care (e.g., lost earnings or lost productivity). The group “Children” is inclusive of children aged <18 years; “Older adults” is inclusive of adults aged ≥60 years. LIC, low-income country; LMIC, lower-middle income country; UMIC, upper-middle income country.

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S1 Table. Search terms for systematic review, by database.

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S2 Table. Modified Consolidated Health Economic Evaluation Reporting Standard (CHEERS) criteria1 used for quality assessment.

DALY, disability-adjusted life years; QALY, quality-adjusted life years. 1The full CHEERS criteria assessment [28] was performed for cost-effectiveness studies; a modified set of relevant criteria were assessed for cost-of-illness and cost-of-program studies.

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S3 Table. Description of included studies, by country.

LIC, low-income country; LMIC, lower-middle income country; SAGE, Strategic Advisory Committee of Experts on Immunization; UMIC, upper-middle income country; US$, US Dollars. 1Although SAGE recommendations specifically reference children aged <5 years [1], publications with data for children aged <18 years were included. 2Publications with data for adults aged ≥60 years. 3Bangladesh changed classification from LIC to LMIC in 2014 [24], after the study period [53], and was thus classified as LIC. 4China was classified as both UMIC and LMIC corresponding to studies before and after an upward change in World Bank classification in 2010. 5Kenya changed classification from LIC to LMIC in 2014 [24], during the study period for 1 study [50], and was thus classified as LMIC for both studies.

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S4 Table. Costs of influenza illness1, by Strategic Advisory Committee of Experts on Immunization (SAGE) target group2 and disease severity (outpatient vs. hospitalized), in low- and middle-income countries.

HIV, human immunodeficiency virus; ILI, influenza-like illness; LCI, laboratory-confirmed influenza; LIC, low-income country; LMIC, lower-middle income country; NA, not applicable; NR, not reported; P&I, pneumonia and influenza hospitalization; SARI, severe acute respiratory infection; TB, tuberculosis; UMC, underlying medical condition; UMIC, upper-middle income country; US$, US Dollars. 1Median costs were preferentially abstracted from source publications; if unavailable, mean costs were abstracted. 2No cost-of-illness papers were identified for healthcare workers or individuals in congregate living settings in low- and middle-income countries. 3For source publications presenting results for both LCI and syndromic illness, the results for LCI were used. 4Direct costs were all medical and non-medical costs directly attributable to patient care. 5Calculated or converted value; not presented in source publication. 6Indirect costs were all costs not directly attributable to patient care (e.g., lost earnings or lost productivity). 7Direct medical and non-medical costs were summarized separately in the source publication; medians were summed to obtain a total median direct cost. 8China changed classification from LMIC to UMIC in 2010 [24], after the study period, and was thus classified as LMIC for this study. 9No indirect costs were included in the total estimate because of study perspective. The specific payer was not specified in the source publication. 10Kenya changed classification from LIC to LMIC in 2014 [24], during the study period, and was thus classified as LMIC. 11Bangladesh changed classification from LIC to LMIC in 2014 [24], after the study period, and was thus classified as LIC. 12Included only direct medical costs (no non-medical costs). 13Although SAGE recommendations specifically reference children aged <5 years [1], publications with data for children aged <18 years were included. 14The full publication study period was 2005–2011; however, 2009–2010 and 2010–2011 were excluded because of H1N1 pandemic activity. Abstracted values represent the median of 2005–2009 annual values. 15Cost data were only available for 1 hospitalized LCI case; thus, ILI hospitalization costs were abstracted.

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S5 Table. Cost-effectiveness of influenza vaccination1, by Strategic Advisory Committee of Experts on Immunization (SAGE) target group, in low- and middle-income countries.

DALY, disability-adjusted life year; ICER, incremental cost-effectiveness ratio; Govt, government; HIV, human immunodeficiency virus; LAIV, live attenuated influenza vaccine; LIC, low-income country; LMIC, lower-middle income country; NA, not applicable; NR, not reported; QALY, quality-adjusted life year; QIV, quadrivalent influenza vaccine; TIV, trivalent influenza vaccine; UMIC, upper-middle income country; US$, US Dollars; WTP, willingness-to-pay. 1Cost-effectiveness, cost-utility, and cost-benefit analyses were eligible for inclusion if they included a comparison of influenza vaccination vs. either no vaccination or modifications to current vaccination program. Studies that only compared the cost-effectiveness of different influenza vaccine products were not included. 2Data for each base-scenario intervention or each perspective assessed are presented in individual rows. Sensitivity analyses are not presented. Vaccine coverage was rounded to the nearest integer. 3Calculated or converted value; not presented in source publication. Ranges represent annual seasonal estimates or varying illness attack rate. 4Interpretation per source publication. Interpretations of highly cost-effective and cost-effective were both combined as “cost-effective.” 5The study authors intentionally did not specify a cost-effectiveness threshold or interpretation because a country-specific threshold was not available. Instead, cost-effectiveness acceptability curves were presented over a range of willingness-to-pay thresholds. 6Similar data sources and analysis methods used in both publications; these were counted collectively as one study for Fig 3. 7Interpretation of net costs of vaccination (including illness averted) vs. no vaccination. 8Although SAGE recommendations specifically reference children aged <5 years [1], publications with data for children aged <18 years were included. 9This study also modeled alternative strategies to increase vaccination rates. 10This study used a cost-effectiveness threshold for South Africa that reflects the health opportunity cost of health spending. 11The age of the hypothetical cohort was based on the mean age of the target population in China (69 years). 12Age groups of ≥50 years and ≥60 years were also modeled; only results for ≥40 years are shown as this was inclusive of all other groups. All scenarios were cost-effective. 13Medical conditions included diabetes, high blood pressure, morbid obesity, chronic renal failure, asthma, and pregnancy. 14Included patients with angina and cardiac arrest/myocardial infarction. 15A country-specific threshold of 100,000 Thai Baht was used (rationale not reported). 16The 90% uncertainty intervals for the ICER overlapped the cost-effectiveness threshold. 17Additional scenarios adjusted for poor access to care and increased severity of disease; all scenarios were cost-effective. 18Results were interpreted as cost-effective when the cost per pregnant woman vaccinated was $1.00 or less. 19Additional scenarios modeled higher coverage of 30% and 100%; all scenarios were cost-effective.

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Acknowledgments

We thank Rakhat Akmatova and Silvia Bino for screening of non-English publications; Britni Burkhardsmeier for administrative project support; Joanna Taliano for search strategy support; and Chris Chadwick, Stefano Tempia, and members of the Partnership for Influenza Vaccine Introduction (PIVI) technical working group for their insightful review and suggestions.

References

  1. 1. World Health Organization. Vaccines against influenza: WHO position paper—May 2022. Wkly Epidemiol Rec. 2022;19:185–208.
  2. 2. Morales KF, Brown DW, Dumolard L, Steulet C, Vilajeliu A, Ropero Alvarez AM, et al. Seasonal influenza vaccination policies in the 194 WHO Member States: The evolution of global influenza pandemic preparedness and the challenge of sustaining equitable vaccine access. Vaccine X. 2021;8:100097. pmid:34041476
  3. 3. Iuliano AD, Roguski KM, Chang HH, Muscatello DJ, Palekar R, Tempia S, et al. Estimates of global seasonal influenza-associated respiratory mortality: a modelling study. Lancet. 2018;391(10127):1285–1300. pmid:29248255
  4. 4. Lafond KE, Porter RM, Whaley MJ, Suizan Z, Ran Z, Aleem MA, et al. Global burden of influenza-associated lower respiratory tract infections and hospitalizations among adults: A systematic review and meta-analysis. PLoS Med. 2021;18(3):e1003550. pmid:33647033
  5. 5. Lafond KE, Nair H, Rasooly MH, Valente F, Booy R, Rahman M, et al. Global Role and Burden of Influenza in Pediatric Respiratory Hospitalizations, 1982–2012: A Systematic Analysis. PLoS Med. 2016;13(3):e1001977. pmid:27011229
  6. 6. Kraigsley AM, Moore KA, Bolster A, Peters M, Richardson D, Arpey M, et al. Barriers and activities to implementing or expanding influenza vaccination programs in low- and middle-income countries: A global survey. Vaccine. 2021;39(25):3419–3427. pmid:33992439
  7. 7. Jit M, Newall AT, Beutels P. Key issues for estimating the impact and cost-effectiveness of seasonal influenza vaccination strategies. Hum Vaccin Immunother. 2013;9(4):834–840. pmid:23357859
  8. 8. World Health Organization. WHO Manual for estimating the economic burden of seasonal influenza. World Health Organization, 2016 WHO/IVB/16.04.
    • 9. Chaiyakunapruk N, Kotirum S, Newall AT, Lambach P, Hutubessy RCW. Rationale and opportunities in estimating the economic burden of seasonal influenza across countries using a standardized WHO tool and manual. Influenza Other Respir Viruses. 2018;12(1):13–21. pmid:29143498
    • 10. World Health Organization. Guidance on the economic evaluation of influenza vaccination. World Health Organization, 2016 WHO/IVB/16.05.
      • 11. Newall AT, Chaiyakunapruk N, Lambach P, Hutubessy RCW. WHO guide on the economic evaluation of influenza vaccination. Influenza Other Respir Viruses. 2018;12(2):211–219. pmid:29024434
      • 12. World Health Organization. Flutool plus: WHO seasonal influenza immunization costing tool (SIICT), Pilot version 1.0. 2020.
      • 13. Ott JJ, Klein Breteler J, Tam JS, Hutubessy RC, Jit M, de Boer MR. Influenza vaccines in low and middle income countries: a systematic review of economic evaluations. Hum Vaccin Immunother. 2013;9(7):1500–1511. pmid:23732900
      • 14. de Francisco SN, Donadel M, Jit M, Hutubessy R. A systematic review of the social and economic burden of influenza in low- and middle-income countries. Vaccine. 2015;33(48):6537–6544. pmid:26597032
      • 15. Peasah SK, Azziz-Baumgartner E, Breese J, Meltzer MI, Widdowson MA. Influenza cost and cost-effectiveness studies globally—a review. Vaccine. 2013;31(46):5339–48. pmid:24055351
      • 16. D’Angiolella LS, Lafranconi A, Cortesi PA, Rota S, Cesana G, Mantovani LG. Costs and effectiveness of influenza vaccination: a systematic review. Ann Ist Super Sanita. 2018;54(1):49–57. pmid:29616674
      • 17. Valcárcel Nazco C, García Lorenzo B, Del Pino ST, García Pérez L, Brito García N, Linertová R, et al. Cost-effectiveness of vaccines for the prevention of seasonal influenza in different age groups: a systematic review. Rev Esp Salud Publica. 2018;92.
      • 18. Ting EEK, Sander B, Ungar WJ. Systematic review of the cost-effectiveness of influenza immunization programs. Vaccine. 2017;35(15):1828–1843. pmid:28284681
      • 19. de Courville C, Cadarette SM, Wissinger E, Alvarez FP. The economic burden of influenza among adults aged 18 to 64: A systematic literature review. Influenza Other Respir Viruses. 2022;16(3):376–385. pmid:35122389
      • 20. Imai C, Toizumi M, Hall L, Lambert S, Halton K, Merollini K. A systematic review and meta-analysis of the direct epidemiological and economic effects of seasonal influenza vaccination on healthcare workers. PLoS ONE. 2018;13(6):e0198685. pmid:29879206
      • 21. Dilokthornsakul P, Lan LM, Thakkinstian A, Hutubessy R, Lambach P, Chaiyakunapruk N. Economic evaluation of seasonal influenza vaccination in elderly and health workers: A systematic review and meta-analysis. EClinicalMedicine. 2022;47:101410. pmid:35497069
      • 22. Loong D, Pham B, Amiri M, Saunders H, Mishra S, Radhakrishnan A, et al. Systematic Review on the Cost-Effectiveness of Seasonal Influenza Vaccines in Older Adults. Value Health. 2022;25(8):1439–1458. pmid:35659487
      • 23. Warmath CR, Ortega-Sanchez IR, Duca LM, Porter RM, Usher MG, Bresee JS, et al. Comparisons in the Health and Economic Assessments of Using Quadrivalent Versus Trivalent Influenza Vaccines: A Systematic Literature Review. Value Health. 2022. pmid:36436790
      • 24. The World Bank Group. World Bank Open Data. 2023 [accessed 2022 Nov 1]. Available from: https://data.worldbank.org/.
      • 25. World Health Organization. Evolution of a pandemic: A (H1N1) 2009. April 2009–August 2010. 2013 924150305X.
      • 26. Veritas Health Innovation. Covidence systematic review software. Available from: www.covidence.org. Melbourne, Australia.
      • 27. World Health Organization. Global Health Expenditure Database. 2023 [accessed 2022 Nov 1]. Available from: https://apps.who.int/nha/database/Home/Index/en.
      • 28. Husereau D, Drummond M, Petrou S, Carswell C, Moher D, Greenberg D, et al. Consolidated Health Economic Evaluation Reporting Standards (CHEERS)—explanation and elaboration: a report of the ISPOR Health Economic Evaluation Publication Guidelines Good Reporting Practices Task Force. Value Health. 2013;16(2):231–50. pmid:23538175
      • 29. Dunn A, Grosse SD, Zuvekas SH. Adjusting Health Expenditures for Inflation: A Review of Measures for Health Services Research in the United States. Health Serv Res. 2018;53(1):175–196. pmid:27873305
      • 30. Bureau of Economic Analysis. GDP Price Deflator. 2023 [accessed 2022 Nov 1]. Available from: https://www.bea.gov/data/prices-inflation/gdp-price-deflator.
      • 31. Wang D, Zhang T, Wu J, Jiang Y, Ding Y, Hua J, et al. Socio-economic burden of influenza among children younger than 5 years in the outpatient setting in Suzhou, China. PLoS ONE. 2013;8(8):e69035. pmid:23950882
      • 32. Wang X, Cai J, Yao W, Zhu Q, Zeng M. Socio-economic impact of influenza in children: a single-centered hospital study in Shanghai [in Chinese]. Zhonghua Liu Xing Bing Xue Za Zhi. 2015;36(1):27–30.
      • 33. Yang J, Jit M, Leung KS, Zheng YM, Feng LZ, Wang LP, et al. The economic burden of influenza-associated outpatient visits and hospitalizations in China: a retrospective survey. Infect Dis Poverty. 2015;4:44. pmid:26445412
      • 34. Zhang X, Zhang J, Chen L, Feng L, Yu H, Zhao G, et al. Pneumonia and influenza hospitalizations among children under 5 years of age in Suzhou, China, 2005–2011. Influenza Other Respir Viruses. 2017;11(1):15–22. pmid:27383534
      • 35. Yu J, Zhang T, Wang Y, Gao JM, Hua J, Tian JM, et al. Clinical characteristics and economic burden of influenza among children under 5 years old, in Suzhou, 2011–2017 [in Chinese]. Zhonghua Liu Xing Bing Xue Za Zhi. 2018;39(6):847–851. pmid:29936759
      • 36. Wang SY, Gan ZK, Shao YZ, Chen ZP, Lyu HK. Disease burden of influenza in schools and child care settings in rural areas of Hangzhou, 2016–2018 [in Chinese]. Zhonghua Yu Fang Yi Xue Za Zhi. 2019;53(7):713–8. pmid:31288343
      • 37. Lai X, Rong H, Ma X, Hou Z, Li S, Jing R, et al. The Economic Burden of Influenza-Like Illness among Children, Chronic Disease Patients, and the Elderly in China: A National Cross-Sectional Survey. Int J Environ Res Public Health. 2021;18(12):10. pmid:34200619
      • 38. Wang Y, Chen L, Cheng F, Biggerstaff M, Situ S, Zhou S, et al. Economic burden of influenza illness among children under 5 years in Suzhou, China: Report from the cost surveys during 2011/12 to 2016/17 influenza seasons. Vaccine. 2021;39(8):1303–9. pmid:33494968
      • 39. Gong H, Shen X, Yan H, Lu W, Zhong G, Dong K, et al. Estimating the disease burden of seasonal influenza in China, 2006–2019 [in Chinese]. Zhonghua Yi Xue Za Zhi. 2021;101(8):560–567. pmid:33663186
      • 40. Salcedo-Mejia F, Alvis-Zakzuk NJ, Carrasquilla-Sotomayor M, Redondo HP, Castaneda-Orjuela C, De la Hoz-Restrepo F, et al. Economic Cost of Severe Acute Respiratory Infection Associated to Influenza in Colombian Children: A Single Setting Analysis. Value Health Reg Issues. 2019;20:159–63. pmid:31563859
      • 41. Castillo-Rodriguez L, Malo-Sanchez D, Diaz-Jimenez D, Garcia-Velasquez I, Pulido P, Castaneda-Orjuela C. Economic costs of severe seasonal influenza in Colombia, 2017–2019: A multi-center analysis. PLoS ONE. 2022;17(6):e0270086. pmid:35714144
      • 42. Kovacs G, Kalo Z, Jahnz-Rozyk K, Kyncl J, Csohan A, Pistol A, et al. Medical and economic burden of influenza in the elderly population in central and eastern European countries. Hum Vaccin Immunother. 2014;10(2):428–40. pmid:24165394
      • 43. Reyes-Lopez A, Moreno-Espinosa S, Hernandez-Olivares YO, Rodolfo Norberto JJ. Economic issues of Severe Acute Respiratory Infections for influenza in Mexican children attended in a tertiary public hospital. PLoS ONE. 2022;17(9):e0273923. pmid:36084073
      • 44. Jara JH, Azziz-Baumgartner E, De Leon T, Luciani K, Brizuela YS, Estripeaut D, et al. Costs associated with acute respiratory illness and select virus infections in hospitalized children, El Salvador and Panama, 2012–2013. J Infect. 2019;79(2):108–114. pmid:31153920
      • 45. Tempia S, Moyes J, Cohen AL, Walaza S, Edoka I, McMorrow ML, et al. Health and economic burden of influenza-associated illness in South Africa, 2013–2015. Influenza Other Respir Viruses. 2019;13(5):484–95. pmid:31187609
      • 46. Tempia S, Moyes J, Cohen AL, Walaza S, McMorrow ML, Edoka I, et al. Influenza economic burden among potential target risk groups for immunization in South Africa, 2013–2015. Vaccine. 2020;38(45):7007–14. pmid:32980198
      • 47. Kittikraisak W, Suntarattiwong P, Kanjanapattanakul W, Ditsungnoen D, Klungthong C, Lindblade KA, et al. Comparison of incidence and cost of influenza between healthy and high-risk children <60 months old in Thailand, 2011–2015. PLoS ONE. 2018;13(5):e0197207. pmid:29771945
      • 48. Guo RN, Zheng HZ, Huang LQ, Zhou Y, Zhang X, Liang CK, et al. Epidemiologic and economic burden of influenza in the outpatient setting: a prospective study in a subtropical area of China. PLoS ONE. 2012;7(7):e41403. pmid:22911789
      • 49. Koul PA, Bhavsar A, Mir H, Simmerman M, Khanna H. Epidemiology and costs of severe acute respiratory infection and influenza hospitalizations in adults with diabetes in India. J Infect Dev Ctries. 2019;13(3):204–11. pmid:32040449
      • 50. Emukule GO, Ndegwa LK, Washington ML, Paget JW, Duque J, Chaves SS, et al. The cost of influenza-associated hospitalizations and outpatient visits in Kenya. BMC Public Health. 2019;19(Suppl 3):471. pmid:32326937
      • 51. Vo TQ, Chaikledkaew U, Hoang MV, Riewpaiboon A. Economic burden of influenza at a tertiary hospital in Vietnam. Asian Pac J Trop Dis. 2017;7(3):144–150.
      • 52. Vo TQ, Chaikledkaew U, Van Hoang M, Riewpaiboon A. Social and economic burden of patients with influenza-like illness and clinically diagnosed flu treated at various health facilities in Vietnam. Clinicoecon Outcomes Res. 2017;9:423–32. pmid:28769577
      • 53. Bhuiyan MU, Luby SP, Alamgir NI, Homaira N, Mamun AA, Khan JA, et al. Economic burden of influenza-associated hospitalizations and outpatient visits in Bangladesh during 2010. Influenza Other Respir Viruses. 2014;8(4):406–13. pmid:24750586
      • 54. Orenstein EW, Orenstein LA, Diarra K, Djiteye M, Sidibe D, Haidara FC, et al. Cost-effectiveness of maternal influenza immunization in Bamako, Mali: A decision analysis. PLoS ONE. 2017;12(2):e0171499. pmid:28170416
      • 55. Pallas SW, Ahmeti A, Morgan W, Preza I, Nelaj E, Ebama M, et al. Program cost analysis of influenza vaccination of health care workers in Albania. Vaccine. 2020;38(2):220–7. pmid:31669063
      • 56. Yang J, Atkins KE, Feng L, Pang M, Zheng Y, Liu X, et al. Seasonal influenza vaccination in China: Landscape of diverse regional reimbursement policy, and budget impact analysis. Vaccine. 2016;34(47):5724–5735. pmid:27745951
      • 57. Fraser H, Tombe-Mdewa W, Kohli-Lynch C, Hofman K, Tempia S, McMorrow M, et al. Costs of seasonal influenza vaccination in South Africa. Influenza Other Respir Viruses. 2022;16(5):873–80. pmid:35355414
      • 58. Riewpaiboon A. Cost analysis of influenza vaccination for pregnant women in Thailand. Pharmaceutical Sciences Asia. 2021;48(2):99–106.
      • 59. Pecenka C, Munthali S, Chunga P, Levin A, Morgan W, Lambach P, et al. Maternal influenza immunization in Malawi: Piloting a maternal influenza immunization program costing tool by examining a prospective program. PLoS ONE. 2017;12(12):e0190006. pmid:29281710
      • 60. Giglio N, Gentile A, Lees L, Micone P, Armoni J, Reygrobellet C, et al. Public health and economic benefits of new pediatric influenza vaccination programs in Argentina. Hum Vaccin Immunother. 2012;8(3):312–22. pmid:22330959
      • 61. Zhou L, Situ S, Feng Z, Atkins CY, Fung IC, Xu Z, et al. Cost-effectiveness of alternative strategies for annual influenza vaccination among children aged 6 months to 14 years in four provinces in China. PLoS ONE. 2014;9(1):e87590. pmid:24498145
      • 62. Chen C, Liu GE, Wang MJ, Gao TF, Jia HP, Yang H, et al. Cost-effective analysis of seasonal influenza vaccine in elderly Chinese population [in Chinese]. Zhonghua Yu Fang Yi Xue Za Zhi. 2019;53(10):993–9. pmid:31607044
      • 63. Yang J, Yan H, Feng LZ, Yu HJ. Cost-effectiveness of potential government fully-funded influenza vaccination in population with diabetes in China [in Chinese]. Zhonghua Yu Fang Yi Xue Za Zhi. 2019;53(10):1000–1006. pmid:31607045
      • 64. Jiang M, Li P, Wang W, Zhao M, Atif N, Zhu S, et al. Cost-effectiveness of quadrivalent versus trivalent influenza vaccine for elderly population in China. Vaccine. 2020;38(5):1057–64. pmid:31787414
      • 65. Yang J, Atkins KE, Feng L, Baguelin M, Wu P, Yan H, et al. Cost-effectiveness of introducing national seasonal influenza vaccination for adults aged 60 years and above in mainland China: a modelling analysis. BMC Med. 2020;18(1):90. pmid:32284056
      • 66. Yan H, Yang J, Chen Z, Gong H, Zhong G, Yu H. Cost-effectiveness analysis of quadrivalent influenza vaccination for older adults aged 60 and above in mainland China [in Chinese]. Zhonghua Yi Xue Za Zhi. 2021;101(30):2405–12. pmid:34404135
      • 67. Wu XL, Ye ZJ, Xie F, Huang DF, Kong TJ, Feng SX, et al. Based on a Markov model, cost-effectiveness analysis of influenza vaccination among people aged 60 years and older in Shenzhen [in Chinese]. Zhonghua Liu Xing Bing Xue Za Zhi. 2022;43(7):1140–6. pmid:35856212
      • 68. Lara C, De Graeve D, Franco F. Cost-Effectiveness Analysis of Pneumococcal and Influenza Vaccines Administered to Children Less Than 5 Years of Age in a Low-Income District of Bogota, Colombia. Value Health Reg Issues. 2018;17:21–31. pmid:29626706
      • 69. Tohiar MAH, Jaafar S, Aizuddin AN, Leong TK, Abdul Rahim AS. Workplace influenza vaccination in private hospital setting: a cost-benefit analysis. Ann Occup Environ Med. 2022;34:e3. pmid:35425620
      • 70. Falcon-Lezama JA, Saucedo-Martinez R, Betancourt-Cravioto M, Alfaro-Cortes MM, Bahena-Gonzalez RI, Tapia-Conyer R. Influenza in the school-aged population in Mexico: burden of disease and cost-effectiveness of vaccination in children. BMC Infect Dis. 2020;20(1):240. pmid:32197591
      • 71. Betancourt-Cravioto M, Falcon-Lezama JA, Saucedo-Martinez R, Alfaro-Cortes MM, Tapia-Conyer R. Public Health and Economic Benefits of Influenza Vaccination of the Population Aged 50 to 59 Years without Risk Factors for Influenza Complications in Mexico: A Cross-Sectional Epidemiological Study. Vaccines (Basel). 2021;9(3):24. pmid:33668199
      • 72. Tapia-Conyer R, Betancourt-Cravioto M, Montoya A, Falcon-Lezama JA, Alfaro-Cortes MM, Saucedo-Martinez R. A Call for a Reform of the Influenza Immunization Program in Mexico: Epidemiologic and Economic Evidence for Decision Making. Vaccines (Basel). 2021;9(3):19. pmid:33808916
      • 73. de Boer PT, Kelso JK, Halder N, Nguyen TP, Moyes J, Cohen C, et al. The cost-effectiveness of trivalent and quadrivalent influenza vaccination in communities in South Africa, Vietnam and Australia. Vaccine. 2018;36(7):997–1007. pmid:29373192
      • 74. Biggerstaff M, Cohen C, Reed C, Tempia S, McMorrow ML, Walaza S, et al. A cost-effectiveness analysis of antenatal influenza vaccination among HIV-infected and HIV-uninfected pregnant women in South Africa. Vaccine. 2019;37(46):6874–84. pmid:31575494
      • 75. Edoka I, Kohli-Lynch C, Fraser H, Hofman K, Tempia S, McMorrow M, et al. A cost-effectiveness analysis of South Africa’s seasonal influenza vaccination programme. Vaccine. 2021;39(2):412–22. pmid:33272702
      • 76. Choosakulchart P, Kittisopee T, Takdhada S, Lubell Y, Robinson J. Cost-utility evaluation of influenza vaccination in patients with existing coronary heart diseases in Thailand. Asian Biomedicine. 2013;7(3):425–435.
      • 77. Meeyai A, Praditsitthikorn N, Kotirum S, Kulpeng W, Putthasri W, Cooper BS, et al. Seasonal influenza vaccination for children in Thailand: a cost-effectiveness analysis. PLoS Med. 2015;12(5):e1001829. pmid:26011712
      • 78. Kittikraisak W, Suntarattiwong P, Ditsungnoen D, Pallas SE, Abimbola TO, Klungthong C, et al. Cost-effectiveness of inactivated seasonal influenza vaccination in a cohort of Thai children 60 months of age. PLoS ONE. 2017;12(8). pmid:28837594
      • 79. Sribhutorn A, Phrommintikul A, Wongcharoen W, Chaikledkaew U, Eakanunkul S, Sukonthasarn A. Influenza vaccination in acute coronary syndromes patients in Thailand: the cost-effectiveness analysis of the prevention for cardiovascular events and pneumonia. J Geriatr Cardiol. 2018;15(6):413–421. pmid:30108613
      • 80. Suphanchaimat R, Doung-Ngern P, Ploddi K, Suthachana S, Phaiyarom M, Pachanee K, et al. Cost Effectiveness and Budget Impact Analyses of Influenza Vaccination for Prisoners in Thailand: An Application of System Dynamic Modelling. Int J Environ Res Public Health. 2020;17(4):14. pmid:32075182
      • 81. Akin L, Macabeo B, Caliskan Z, Altinel S, Satman I. Cost-Effectiveness of Increasing Influenza Vaccination Coverage in Adults with Type 2 Diabetes in Turkey. PLoS ONE. 2016;11(6):e0157657. pmid:27322384
      • 82. Dawa J, Emukule GO, Barasa E, Widdowson MA, Anzala O, van Leeuwen E, et al. Seasonal influenza vaccination in Kenya: an economic evaluation using dynamic transmission modelling. BMC Med. 2020;18(1):223. pmid:32814581
      • 83. Ortega-Sanchez IR, Mott JA, Kittikraisak W, Khanthamaly V, McCarron M, Keokhonenang S, et al. Cost-effectiveness of seasonal influenza vaccination in pregnant women, healthcare workers and adults > = 60 years of age in Lao People’s Democratic Republic. Vaccine. 2021;39(52):7633–45. pmid:34802790
      • 84. Kyi-Kokarieva VG, Padalkо LI, Kriachkova LV. Socio-economic substantiation of expediency of seasonal influenza vaccine prophylaxis among medical workers. Medicni Perspektivi. 2021;26(4):205–212.
      • 85. Crespo C, Monleon A, Díaz W, Ríos M. Comparative efficiency research (COMER): meta-analysis of cost-effectiveness studies. BMC Med Res Methodol. 2014;14:139. pmid:25533141
      • 86. Jenkin DC, Mahgoub H, Morales KF, Lambach P, Nguyen-Van-Tam JS. A rapid evidence appraisal of influenza vaccination in health workers: An important policy in an area of imperfect evidence. Vaccine X. 2019;2:100036. pmid:31384750
      • 87. Cherian T, Morales KF, Mantel C, Lambach P. Factors and considerations for establishing and improving seasonal influenza vaccination of health workers: Report from a WHO meeting, January 16–17, Berlin. Germany. Vaccine. 2019;37(43):6255–6261. pmid:31500965
      • 88. Thompson MG, Levine MZ, Bino S, Hunt DR, Al-Sanouri TM, Simões EAF, et al. Underdetection of laboratory-confirmed influenza-associated hospital admissions among infants: a multicentre, prospective study. Lancet Child Adolesc Health. 2019;3(11):781–794. pmid:31492594
      • 89. Macias AE, McElhaney JE, Chaves SS, Nealon J, Nunes MC, Samson SI, et al. The disease burden of influenza beyond respiratory illness. Vaccine. 2021;39(Suppl 1):A6–a14. pmid:33041103
      • 90. Levin A, Boonstoppel L, Brenzel L, Griffiths U, Hutubessy R, Jit M, et al. WHO-led consensus statement on vaccine delivery costing: process, methods, and findings. BMC Med. 2022;20(1):88. pmid:35255920
      • 91. Levine OS, Hajjeh R, Wecker J, Cherian T, O’Brien KL, Knoll MD, et al. A policy framework for accelerating adoption of new vaccines. Hum Vaccin Immunother. 2010;6(12):1021–1024. pmid:21150269
      • 92. ThinkWell Immunization Costing Action Network (ICAN). Immunization Delivery Cost Catalogue. 2020 [accessed 2023 Aug 7]. Available from: https://immunizationeconomics.org/thinkwell-idcc#anchor-singlenuvi.
      • 93. Turner HC, Archer RA, Downey LE, Isaranuwatchai W, Chalkidou K, Jit M, et al. An Introduction to the Main Types of Economic Evaluations Used for Informing Priority Setting and Resource Allocation in Healthcare: Key Features, Uses, and Limitations. Front Public Health. 2021;9:722927. pmid:34513790
      • 94. Kazibwe J, Gheorghe A, Wilson D, Ruiz F, Chalkidou K, Chi YL. The Use of Cost-Effectiveness Thresholds for Evaluating Health Interventions in Low- and Middle-Income Countries From 2015 to 2020: A Review. Value Health. 2022;25(3):385–389. pmid:35227450
      • 95. Leech AA, Kim DD, Cohen JT, Neumann PJ. Use and Misuse of Cost-Effectiveness Analysis Thresholds in Low- and Middle-Income Countries: Trends in Cost-per-DALY Studies. Value Health. 2018;21(7):759–761. pmid:30005746
      • 96. Ochalek J, Lomas J, Claxton K. Estimating health opportunity costs in low-income and middle-income countries: a novel approach and evidence from cross-country data. BMJ Glob Health. 2018;3(6):e000964. pmid:30483412
      • 97. Bertram MY, Lauer JA, De Joncheere K, Edejer T, Hutubessy R, Kieny MP, et al. Cost-effectiveness thresholds: pros and cons. Bull World Health Organ. 2016;94(12):925–930. pmid:27994285
      • 98. Robinson LA, Hammitt JK, Chang AY, Resch S. Understanding and improving the one and three times GDP per capita cost-effectiveness thresholds. Health Policy Plan. 2017;32(1):141–145. pmid:27452949
      • 99. World Health Organization. WHO guide for standardization of economic evaluations of immunization programmes. 2nd ed. Geneva: World Health Organization, 2019 WHO/IVB/19.10.
        • 100. de Boer PT, van Maanen BM, Damm O, Ultsch B, Dolk FCK, Crépey P, et al. A systematic review of the health economic consequences of quadrivalent influenza vaccination. Expert Rev Pharmacoecon Outcomes Res. 2017;17(3):249–265. pmid:28613092
        • 101. Ofori SK, Hung YW, Schwind JS, Diallo K, Babatunde D, Nwaobi SO, et al. Economic evaluations of interventions against influenza at workplaces: systematic review. Occup Med (Lond). 2022;72(2):70–80. pmid:34931675
        • 102. World Health Organization. Coadministration of seasonal inactivated influenza and COVID-19 vaccines. 2021 WHO/2019-nCoV/SAGE/Vaccines_coadministration/Influenza/2021.1.
        • 103. Jit M, Hutubessy R, Png ME, Sundaram N, Audimulam J, Salim S, et al. The broader economic impact of vaccination: reviewing and appraising the strength of evidence. BMC Med. 2015;13:209. pmid:26335923
        • 104. Jit M, Hutubessy R. Methodological Challenges to Economic Evaluations of Vaccines: Is a Common Approach Still Possible? Appl Health Econ Health Policy. 2016;14(3):245–252. pmid:26832145