Optimising health and economic impacts of COVID-19 vaccine prioritisation strategies in the WHO European Region: a mathematical modelling study.
| Title: | Optimising health and economic impacts of COVID-19 vaccine prioritisation strategies in the WHO European Region: a mathematical modelling study. |
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| Authors: | Liu Y; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Keppel St, London, United Kingdom WC1E 7HT.; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine; Keppel St, London, United Kingdom WC1E 7HT.; Sandmann FG; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Keppel St, London, United Kingdom WC1E 7HT.; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine; Keppel St, London, United Kingdom WC1E 7HT.; Statistics, Modelling and Economics Department, National Infection Service, Public Health England; 61 Colindale Ave, London, United Kingdom NW9 5EQ.; Barnard RC; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Keppel St, London, United Kingdom WC1E 7HT.; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine; Keppel St, London, United Kingdom WC1E 7HT.; Pearson CAB; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Keppel St, London, United Kingdom WC1E 7HT.; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine; Keppel St, London, United Kingdom WC1E 7HT.; Pastore R; World Health Organization (WHO) Regional Office for Europe; UN City, Marmorvej 51, 2100, Copenhagen, Denmark.; Pebody R; World Health Organization (WHO) Regional Office for Europe; UN City, Marmorvej 51, 2100, Copenhagen, Denmark.; Flasche S; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Keppel St, London, United Kingdom WC1E 7HT.; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine; Keppel St, London, United Kingdom WC1E 7HT.; Jit M; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine; Keppel St, London, United Kingdom WC1E 7HT.; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine; Keppel St, London, United Kingdom WC1E 7HT. |
| Source: | The Lancet regional health. Europe [Lancet Reg Health Eur] 2022 Jan; Vol. 12, pp. 100267. Date of Electronic Publication: 2021 Nov 30. |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: [Oxford] Country of Publication: England NLM ID: 101777707 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2666-7762 (Electronic) Linking ISSN: 26667762 NLM ISO Abbreviation: Lancet Reg Health Eur Subsets: PubMed not MEDLINE |
| Imprint Name(s): | Original Publication: [Oxford] : Elsevier Ltd., [2020]- |
| Abstract: | Background: Countries in the World Health Organization (WHO) European Region differ in terms of the COVID-19 vaccine supply conditions. We evaluated the health and economic impact of different age-based vaccine prioritisation strategies across this demographically and socio-economically diverse region.; Methods: We fitted age-specific compartmental models to the reported daily COVID-19 mortality in 2020 to inform the immunity level before vaccine roll-out. Models capture country-specific differences in population structures, contact patterns, epidemic history, life expectancy, and GDP per capita.We examined four strategies that prioritise: all adults (V+), younger (20-59 year-olds) followed by older adults (60+) (V20), older followed by younger adults (V60), and the oldest adults (75+) (V75) followed by incrementally younger age groups. We explored four roll-out scenarios (R1-4) - the slowest scenario (R1) reached 30% coverage by December 2022 and the fastest (R4) 80% by December 2021. Five decision-making metrics were summarised over 2021-22: mortality, morbidity, and losses in comorbidity-adjusted life expectancy, comorbidity- and quality-adjusted life years, and human capital. Six vaccine profiles were tested - the highest performing vaccine has 95% efficacy against both infection and disease, and the lowest 50% against diseases and 0% against infection.; Findings: Of the 20 decision-making metrics and roll-out scenario combinations, the same optimal strategy applied to all countries in only one combination; V60 was more or similarly desirable than V75 in 19 combinations. Of the 38 countries with fitted models, 11-37 countries had variable optimal strategies by decision-making metrics or roll-out scenarios. There are greater benefits in prioritising older adults when roll-out is slow and when vaccine profiles are less favourable.; Interpretation: The optimal age-based vaccine prioritisation strategies were sensitive to country characteristics, decision-making metrics, and roll-out speeds. A prioritisation strategy involving more age-based stages (V75) does not necessarily lead to better health and economic outcomes than targeting broad age groups (V60). Countries expecting a slow vaccine roll-out may particularly benefit from prioritising older adults.; Funding: World Health Organization, Bill and Melinda Gates Foundation, the Medical Research Council (United Kingdom), the National Institute of Health Research (United Kingdom), the European Commission, the Foreign, Commonwealth and Development Office (United Kingdom), Wellcome Trust.; (© 2021 The Author(s).) |
| Competing Interests: | YL and MJ report grants from the National Institute of Health Research outside the submitted work (16/137/109). RCB and MJ are participants of the Scientific Pandemic Influenza Group on Modelling. The views expressed in this publication are those of the author(s) and not necessarily those of the European Commission, National Institute of Health Research (NIHR) (UK), Public Health England (PHE) or the Department of Health and Social Care (UK). The authors alone are responsible for the views expressed in this publication, and they do not necessarily represent the decisions or policies of the World Health Organization. |
| Comments: | Update of: medRxiv. 2021 Jul 14:2021.07.09.21260272. doi: 10.1101/2021.07.09.21260272.. (PMID: 34282421) |
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| Grant Information: | MR/P014658/1 United Kingdom MRC_ Medical Research Council; MR/S003975/1 United Kingdom MRC_ Medical Research Council; R01 AI141534 United States AI NIAID NIH HHS; MC_PC_19065 United Kingdom MRC_ Medical Research Council; United Kingdom WT_ Wellcome Trust; 001 International WHO_ World Health Organization |
| Contributed Indexing: | Keywords: COVID-19; Europe; Health economics; Mathematical modelling; Multicountry analysis; Policy evaluation; Vaccine policy |
| Entry Date(s): | Date Created: 20211206 Latest Revision: 20250530 |
| Update Code: | 20260130 |
| PubMed Central ID: | PMC8629724 |
| DOI: | 10.1016/j.lanepe.2021.100267 |
| PMID: | 34870256 |
| Database: | MEDLINE |
Journal Article