Cargando…

A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data

The transmission dynamics and burden of SARS-CoV-2 in many regions of the world is still largely unknown due to the scarcity of epidemiological analyses and lack of testing to assess the prevalence of disease. In this work, we develop a quantitative framework based on excess mortality data to recons...

Descripción completa

Detalles Bibliográficos
Autores principales: Ghafari, Mahan, Watson, Oliver J., Karlinsky, Ariel, Ferretti, Luca, Katzourakis, Aris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9156676/
https://www.ncbi.nlm.nih.gov/pubmed/35641529
http://dx.doi.org/10.1038/s41467-022-30711-y
_version_ 1784718485728788480
author Ghafari, Mahan
Watson, Oliver J.
Karlinsky, Ariel
Ferretti, Luca
Katzourakis, Aris
author_facet Ghafari, Mahan
Watson, Oliver J.
Karlinsky, Ariel
Ferretti, Luca
Katzourakis, Aris
author_sort Ghafari, Mahan
collection PubMed
description The transmission dynamics and burden of SARS-CoV-2 in many regions of the world is still largely unknown due to the scarcity of epidemiological analyses and lack of testing to assess the prevalence of disease. In this work, we develop a quantitative framework based on excess mortality data to reconstruct SARS-CoV-2 transmission dynamics and assess the level of underreporting in infections and deaths. Using weekly all-cause mortality data from Iran, we are able to show a strong agreement between our attack rate estimates and seroprevalence measurements in each province and find significant heterogeneity in the level of exposure across the country with 11 provinces reaching near 100% attack rates. Despite having a young population, our analysis reveals that incorporating limited access to medical services in our model, coupled with undercounting of COVID-19-related deaths, leads to estimates of infection fatality rate in most provinces of Iran that are comparable to high-income countries.
format Online
Article
Text
id pubmed-9156676
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-91566762022-06-02 A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data Ghafari, Mahan Watson, Oliver J. Karlinsky, Ariel Ferretti, Luca Katzourakis, Aris Nat Commun Article The transmission dynamics and burden of SARS-CoV-2 in many regions of the world is still largely unknown due to the scarcity of epidemiological analyses and lack of testing to assess the prevalence of disease. In this work, we develop a quantitative framework based on excess mortality data to reconstruct SARS-CoV-2 transmission dynamics and assess the level of underreporting in infections and deaths. Using weekly all-cause mortality data from Iran, we are able to show a strong agreement between our attack rate estimates and seroprevalence measurements in each province and find significant heterogeneity in the level of exposure across the country with 11 provinces reaching near 100% attack rates. Despite having a young population, our analysis reveals that incorporating limited access to medical services in our model, coupled with undercounting of COVID-19-related deaths, leads to estimates of infection fatality rate in most provinces of Iran that are comparable to high-income countries. Nature Publishing Group UK 2022-05-31 /pmc/articles/PMC9156676/ /pubmed/35641529 http://dx.doi.org/10.1038/s41467-022-30711-y Text en © The Author(s) 2022 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
Ghafari, Mahan
Watson, Oliver J.
Karlinsky, Ariel
Ferretti, Luca
Katzourakis, Aris
A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data
title A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data
title_full A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data
title_fullStr A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data
title_full_unstemmed A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data
title_short A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data
title_sort framework for reconstructing sars-cov-2 transmission dynamics using excess mortality data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9156676/
https://www.ncbi.nlm.nih.gov/pubmed/35641529
http://dx.doi.org/10.1038/s41467-022-30711-y
work_keys_str_mv AT ghafarimahan aframeworkforreconstructingsarscov2transmissiondynamicsusingexcessmortalitydata
AT watsonoliverj aframeworkforreconstructingsarscov2transmissiondynamicsusingexcessmortalitydata
AT karlinskyariel aframeworkforreconstructingsarscov2transmissiondynamicsusingexcessmortalitydata
AT ferrettiluca aframeworkforreconstructingsarscov2transmissiondynamicsusingexcessmortalitydata
AT katzourakisaris aframeworkforreconstructingsarscov2transmissiondynamicsusingexcessmortalitydata
AT ghafarimahan frameworkforreconstructingsarscov2transmissiondynamicsusingexcessmortalitydata
AT watsonoliverj frameworkforreconstructingsarscov2transmissiondynamicsusingexcessmortalitydata
AT karlinskyariel frameworkforreconstructingsarscov2transmissiondynamicsusingexcessmortalitydata
AT ferrettiluca frameworkforreconstructingsarscov2transmissiondynamicsusingexcessmortalitydata
AT katzourakisaris frameworkforreconstructingsarscov2transmissiondynamicsusingexcessmortalitydata