Representative estimates of COVID-19 infection fatality rates from four locations in India: cross-sectional study
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Author(s)
Cai, Rebecca
Novosad, Paul
Tandel, Vaidehi
Asher, Sam
Malani, Anup
Type
Journal Article
Abstract
Strengths and limitations of this study
This study provides representative estimates of the age-specific COVID-19 infection fatality rate (IFR) in four socioeconomically diverse regions of India, a major lower-middle-income country, using the standard method for estimating IFR.
Due to high measurement cost, there are very few age-specific IFR estimates in low-income and middle-income countries (LMICs), despite concerns that LMICs are more vulnerable and plausibly have different mortality patterns.
This study uses the primary method of estimating IFR in settings around the world, combining population-representative prevalence/seroprevalence surveys with official death reports, allowing direct methodological comparison with dozens of similar estimates from high-income countries.
We provide population-representative estimates for over 150 million people using the largest sample to date in an LMIC, and the first documentation of IFR among the large, highly vulnerable population of migrant workers.
The main limitation is our reliance on official reports of confirmed COVID-19 deaths, which, due to under-reporting and undertesting, likely underestimate the true number of deaths.
This study provides representative estimates of the age-specific COVID-19 infection fatality rate (IFR) in four socioeconomically diverse regions of India, a major lower-middle-income country, using the standard method for estimating IFR.
Due to high measurement cost, there are very few age-specific IFR estimates in low-income and middle-income countries (LMICs), despite concerns that LMICs are more vulnerable and plausibly have different mortality patterns.
This study uses the primary method of estimating IFR in settings around the world, combining population-representative prevalence/seroprevalence surveys with official death reports, allowing direct methodological comparison with dozens of similar estimates from high-income countries.
We provide population-representative estimates for over 150 million people using the largest sample to date in an LMIC, and the first documentation of IFR among the large, highly vulnerable population of migrant workers.
The main limitation is our reliance on official reports of confirmed COVID-19 deaths, which, due to under-reporting and undertesting, likely underestimate the true number of deaths.
Date Issued
2021-10-05
Date Acceptance
2021-08-19
Citation
BMJ Open, 2021, 11 (10)
ISSN
2044-6055
Publisher
BMJ Publishing Group
Start Page
e050920
End Page
e050920
Journal / Book Title
BMJ Open
Volume
11
Issue
10
Copyright Statement
© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Identifier
10.1136/bmjopen-2021-050920
Publication Status
Published
Article Number
e050920
Date Publish Online
2021-10-05