Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria

Imperial College COVID-19 Response Team (2021) Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria. Nature Communications, 12 (1). ISSN 2041-1723

Text (s41467-021-22474-9) - Published Version Available under License Creative Commons Attribution. Download (1MB)

Abstract

The COVID-19 pandemic has resulted in substantial mortality worldwide. However, to date, countries in the Middle East and Africa have reported considerably lower mortality rates than in Europe and the Americas. Motivated by reports of an overwhelmed health system, we estimate the likely under-ascertainment of COVID-19 mortality in Damascus, Syria. Using all-cause mortality data, we fit a mathematical model of COVID-19 transmission to reported mortality, estimating that 1.25% of COVID-19 deaths (sensitivity range 1.00% – 3.00%) have been reported as of 2 September 2020. By 2 September, we estimate that 4,380 (95% CI: 3,250 – 5,550) COVID-19 deaths in Damascus may have been missed, with 39.0% (95% CI: 32.5% – 45.0%) of the population in Damascus estimated to have been infected. Accounting for under-ascertainment corroborates reports of exceeded hospital bed capacity and is validated by community-uploaded obituary notifications, which confirm extensive unreported mortality in Damascus.

Item Type:	Article
Official URL:	https://www.nature.com/ncomms/
Additional Information:	© 2021 The Authors
Divisions:	Conflict and Civil Society
Subjects:	R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine H Social Sciences > HV Social pathology. Social and public welfare. Criminology
Date Deposited:	12 Oct 2021 10:42
Last Modified:	16 Nov 2024 05:57
URI:	http://eprints.lse.ac.uk/id/eprint/112229

Actions (login required)

View Item