Abstract

Globally, excess deaths during 2020–21 outnumbered documented COVID-19 deaths by 9.5 million, primarily driven by deaths in low- and middle-income countries (LMICs) with limited vital surveillance. Here we unravel the contributions of probable COVID-19 deaths from other changes in mortality related to pandemic control measures using medically-certified death registrations from Madurai, India—an urban center with well-functioning vital surveillance. Between March, 2020 and July, 2021, all-cause deaths in Madurai exceeded expected levels by 30% (95% confidence interval: 27–33%). Although driven by deaths attributed to cardiovascular or cerebrovascular conditions, diabetes, senility, and other uncategorized causes, increases in these attributions were restricted to medically-unsupervised deaths, and aligned with surges in confirmed or attributed COVID-19 mortality, likely reflecting mortality among unconfirmed COVID-19 cases. Implementation of lockdown measures was associated with a 7% (0–13%) reduction in all-cause mortality, driven by reductions in deaths attributed to injuries, infectious diseases and maternal conditions, and cirrhosis and other liver conditions, respectively, but offset by a doubling in cancer deaths. Our findings help to account for gaps between documented COVID-19 mortality and excess all-cause mortality during the pandemic in an LMIC setting.

Millions of excess deaths are estimated to have occurred in India during the COVID-19 pandemic, but their causes are not well documented at the national level. In this study, the authors use death registration records to describe the extent and causes of excess deaths in the large urban municipality of Madurai.

Details

Title
Attributed causes of excess mortality during the COVID-19 pandemic in a south Indian city
Author
Lewnard, Joseph A. 1   VIAFID ORCID Logo  ; B, Chandra Mohan 2 ; Kang, Gagandeep 3   VIAFID ORCID Logo  ; Laxminarayan, Ramanan 4 

 University of California, Berkeley, Division of Epidemiology, School of Public Health, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); University of California, Berkeley, Division of Infectious Diseases & Vaccinology, School of Public Health, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878); College of Engineering, University of California, Berkeley, Center for Computational Biology, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878) 
 Indian Administrative Service, Chennai, India (GRID:grid.47840.3f) 
 Christian Medical College, Vellore, India (GRID:grid.11586.3b) (ISNI:0000 0004 1767 8969) 
 One Health Trust, Bangalore, India (GRID:grid.11586.3b); Princeton University, Princeton, USA (GRID:grid.16750.35) (ISNI:0000 0001 2097 5006) 
Pages
3563
Publication year
2023
Publication date
2023
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2826998280
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.