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Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria
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-ascert...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062464/ https://www.ncbi.nlm.nih.gov/pubmed/33888698 http://dx.doi.org/10.1038/s41467-021-22474-9 |
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author | Watson, Oliver J. Alhaffar, Mervat Mehchy, Zaki Whittaker, Charles Akil, Zack Brazeau, Nicholas F. Cuomo-Dannenburg, Gina Hamlet, Arran Thompson, Hayley A. Baguelin, Marc FitzJohn, Richard G. Knock, Edward Lees, John A. Whittles, Lilith K. Mellan, Thomas Winskill, Peter Howard, Natasha Clapham, Hannah Checchi, Francesco Ferguson, Neil Ghani, Azra Beals, Emma Walker, Patrick |
author_facet | Watson, Oliver J. Alhaffar, Mervat Mehchy, Zaki Whittaker, Charles Akil, Zack Brazeau, Nicholas F. Cuomo-Dannenburg, Gina Hamlet, Arran Thompson, Hayley A. Baguelin, Marc FitzJohn, Richard G. Knock, Edward Lees, John A. Whittles, Lilith K. Mellan, Thomas Winskill, Peter Howard, Natasha Clapham, Hannah Checchi, Francesco Ferguson, Neil Ghani, Azra Beals, Emma Walker, Patrick |
author_sort | Watson, Oliver J. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8062464 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-80624642021-05-11 Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria Watson, Oliver J. Alhaffar, Mervat Mehchy, Zaki Whittaker, Charles Akil, Zack Brazeau, Nicholas F. Cuomo-Dannenburg, Gina Hamlet, Arran Thompson, Hayley A. Baguelin, Marc FitzJohn, Richard G. Knock, Edward Lees, John A. Whittles, Lilith K. Mellan, Thomas Winskill, Peter Howard, Natasha Clapham, Hannah Checchi, Francesco Ferguson, Neil Ghani, Azra Beals, Emma Walker, Patrick Nat Commun Article 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. Nature Publishing Group UK 2021-04-22 /pmc/articles/PMC8062464/ /pubmed/33888698 http://dx.doi.org/10.1038/s41467-021-22474-9 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Watson, Oliver J. Alhaffar, Mervat Mehchy, Zaki Whittaker, Charles Akil, Zack Brazeau, Nicholas F. Cuomo-Dannenburg, Gina Hamlet, Arran Thompson, Hayley A. Baguelin, Marc FitzJohn, Richard G. Knock, Edward Lees, John A. Whittles, Lilith K. Mellan, Thomas Winskill, Peter Howard, Natasha Clapham, Hannah Checchi, Francesco Ferguson, Neil Ghani, Azra Beals, Emma Walker, Patrick Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria |
title | Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria |
title_full | Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria |
title_fullStr | Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria |
title_full_unstemmed | Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria |
title_short | Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria |
title_sort | leveraging community mortality indicators to infer covid-19 mortality and transmission dynamics in damascus, syria |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8062464/ https://www.ncbi.nlm.nih.gov/pubmed/33888698 http://dx.doi.org/10.1038/s41467-021-22474-9 |
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