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Levin AT, Owusu-Boaitey N, Pugh S, Fosdick BK, Zwi AB, Malani A, Soman S, Besançon L, Kashnitsky I, Ganesh S, McLaughlin A, Song G, Uhm R, Herrera-Esposito D, de Los Campos G, Peçanha Antonio ACP, Tadese EB, Meyerowitz-Katz G. Assessing the burden of COVID-19 in developing countries: systematic review, meta-analysis and public policy implications. BMJ Glob Health 2022; 7:e008477. [PMID: 35618305 PMCID: PMC9136695 DOI: 10.1136/bmjgh-2022-008477] [Citation(s) in RCA: 80] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Accepted: 05/05/2022] [Indexed: 12/11/2022] Open
Abstract
INTRODUCTION The infection fatality rate (IFR) of COVID-19 has been carefully measured and analysed in high-income countries, whereas there has been no systematic analysis of age-specific seroprevalence or IFR for developing countries. METHODS We systematically reviewed the literature to identify all COVID-19 serology studies in developing countries that were conducted using representative samples collected by February 2021. For each of the antibody assays used in these serology studies, we identified data on assay characteristics, including the extent of seroreversion over time. We analysed the serology data using a Bayesian model that incorporates conventional sampling uncertainty as well as uncertainties about assay sensitivity and specificity. We then calculated IFRs using individual case reports or aggregated public health updates, including age-specific estimates whenever feasible. RESULTS In most locations in developing countries, seroprevalence among older adults was similar to that of younger age cohorts, underscoring the limited capacity that these nations have to protect older age groups.Age-specific IFRs were roughly 2 times higher than in high-income countries. The median value of the population IFR was about 0.5%, similar to that of high-income countries, because disparities in healthcare access were roughly offset by differences in population age structure. CONCLUSION The burden of COVID-19 is far higher in developing countries than in high-income countries, reflecting a combination of elevated transmission to middle-aged and older adults as well as limited access to adequate healthcare. These results underscore the critical need to ensure medical equity to populations in developing countries through provision of vaccine doses and effective medications.
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Affiliation(s)
- Andrew T Levin
- Economics, Dartmouth College, Hanover, New Hampshire, USA
- National Bureau for Economic Research, Cambridge, Massachusetts, USA
| | - Nana Owusu-Boaitey
- School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Sierra Pugh
- Statistics, Colorado State University, Fort Collins, Colorado, USA
| | - Bailey K Fosdick
- Department of Statistics, Colorado State University, Fort Collins, Colorado, USA
| | - Anthony B Zwi
- School of Social Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Anup Malani
- Law School, University of Chicago, Chicago, Illinois, USA
| | - Satej Soman
- Harris School of Public Policy, University of Chicago, Chicago, Illinois, USA
| | - Lonni Besançon
- Faculty of Information and Technology, Monash University, Clayton, Victoria, Australia
| | - Ilya Kashnitsky
- Interdisciplinary Centre on Population Dynamics, University of Southern Denmark, Odense, Denmark
| | - Sachin Ganesh
- Department of Economics, Dartmouth College, Hanover, New Hampshire, USA
| | | | - Gayeong Song
- Department of Economics, Dartmouth College, Hanover, New Hampshire, USA
| | - Rine Uhm
- Department of Economics, Dartmouth College, Hanover, New Hampshire, USA
| | | | - Gustavo de Los Campos
- Department of Epidemiology & Biostatistics, Michigan State University, East Lansing, Michigan, USA
| | | | | | - Gideon Meyerowitz-Katz
- Western Sydney Diabetes, Western Sydney Local Health District, Blacktown, New South Wales, Australia
- School of Health and Society, University of Wollongong, Wollongong, New South Wales, Australia
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Zheng W, Yan X, Zhao Z, Yang J, Yu H. COVID-19 vaccination program in the mainland of China: a subnational descriptive analysis on target population size and current progress. Infect Dis Poverty 2021; 10:124. [PMID: 34654478 PMCID: PMC8517558 DOI: 10.1186/s40249-021-00909-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 09/27/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND China is facing substantial risks of imported coronavirus disease 2019 (COVID-19) cases and a domestic resurgence in the long run, and COVID-19 vaccination is expected to be the long-lasting solution to end the pandemic. We aim to estimate the size of the target population for COVID-19 vaccination at the provincial level in the mainland of China, and summarize the current progress of vaccination programs, which could support local governments in the timely determination and adjustment of vaccination policies and promotional measures. METHODS We conducted a descriptive study of the entire population in the mainland of China, between December 2020 and August 2021. By extracting provincial-stratified data from publicly available sources, we estimated the size of priority target groups for vaccination programs, and further characterized the ongoing vaccination program at the provincial level, including the total doses administered, the coverage rate, and the vaccination capacity needed to achieve the target coverage of 80% by the end of 2021. We used R (version 4.1.0) to complete the descriptive statistics. RESULTS The size of the target population shows large differences among provinces, ranging from 3.4 million to 108.4 million. As of 31 August, 2021, the speed of vaccine roll-out differs considerably as well, with the highest coverage occurring in Beijing and Shanghai, where 88.5% and 79.1% of the population has been fully vaccinated, respectively. In 22 of 31 provincial-level administrative divisions (PLADs), more than 70% of the population was administered at least one dose by August. With the current vaccination capacity, the target of 80% coverage could be achieved by 2021 in 28 PLADs. CONCLUSIONS Disparities exist in the target population size and vaccination progress across provinces in the mainland of China. China has made great strides in the vaccination speed since roll-out, and could basically achieve the targeted vaccine coverage.
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Affiliation(s)
- Wen Zheng
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University, Shanghai, China
| | - Xuemei Yan
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University, Shanghai, China
| | - Zeyao Zhao
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University, Shanghai, China
| | - Juan Yang
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University, Shanghai, China. .,Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China.
| | - Hongjie Yu
- Shanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University, Shanghai, China. .,Key Laboratory of Public Health Safety, Ministry of Education, Fudan University, Shanghai, China. .,Department of Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China.
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