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Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context
Reported COVID-19 cases and associated mortality remain low in many sub-Saharan countries relative to global averages, but true impact is difficult to estimate given limitations around surveillance and mortality registration. In Lusaka, Zambia, burial registration and SARS-CoV-2 prevalence data duri...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10307769/ https://www.ncbi.nlm.nih.gov/pubmed/37380650 http://dx.doi.org/10.1038/s41467-023-39288-6 |
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author | Sheppard, Richard J. Watson, Oliver J. Pieciak, Rachel Lungu, James Kwenda, Geoffrey Moyo, Crispin Chanda, Stephen Longa Barnsley, Gregory Brazeau, Nicholas F. Gerard-Ursin, Ines C. G. Olivera Mesa, Daniela Whittaker, Charles Gregson, Simon Okell, Lucy C. Ghani, Azra C. MacLeod, William B. Del Fava, Emanuele Melegaro, Alessia Hines, Jonas Z. Mulenga, Lloyd B. Walker, Patrick G. T. Mwananyanda, Lawrence Gill, Christopher J. |
author_facet | Sheppard, Richard J. Watson, Oliver J. Pieciak, Rachel Lungu, James Kwenda, Geoffrey Moyo, Crispin Chanda, Stephen Longa Barnsley, Gregory Brazeau, Nicholas F. Gerard-Ursin, Ines C. G. Olivera Mesa, Daniela Whittaker, Charles Gregson, Simon Okell, Lucy C. Ghani, Azra C. MacLeod, William B. Del Fava, Emanuele Melegaro, Alessia Hines, Jonas Z. Mulenga, Lloyd B. Walker, Patrick G. T. Mwananyanda, Lawrence Gill, Christopher J. |
author_sort | Sheppard, Richard J. |
collection | PubMed |
description | Reported COVID-19 cases and associated mortality remain low in many sub-Saharan countries relative to global averages, but true impact is difficult to estimate given limitations around surveillance and mortality registration. In Lusaka, Zambia, burial registration and SARS-CoV-2 prevalence data during 2020 allow estimation of excess mortality and transmission. Relative to pre-pandemic patterns, we estimate age-dependent mortality increases, totalling 3212 excess deaths (95% CrI: 2104–4591), representing an 18.5% (95% CrI: 13.0–25.2%) increase relative to pre-pandemic levels. Using a dynamical model-based inferential framework, we find that these mortality patterns and SARS-CoV-2 prevalence data are in agreement with established COVID-19 severity estimates. Our results support hypotheses that COVID-19 impact in Lusaka during 2020 was consistent with COVID-19 epidemics elsewhere, without requiring exceptional explanations for low reported figures. For more equitable decision-making during future pandemics, barriers to ascertaining attributable mortality in low-income settings must be addressed and factored into discourse around reported impact differences. |
format | Online Article Text |
id | pubmed-10307769 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103077692023-06-30 Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context Sheppard, Richard J. Watson, Oliver J. Pieciak, Rachel Lungu, James Kwenda, Geoffrey Moyo, Crispin Chanda, Stephen Longa Barnsley, Gregory Brazeau, Nicholas F. Gerard-Ursin, Ines C. G. Olivera Mesa, Daniela Whittaker, Charles Gregson, Simon Okell, Lucy C. Ghani, Azra C. MacLeod, William B. Del Fava, Emanuele Melegaro, Alessia Hines, Jonas Z. Mulenga, Lloyd B. Walker, Patrick G. T. Mwananyanda, Lawrence Gill, Christopher J. Nat Commun Article Reported COVID-19 cases and associated mortality remain low in many sub-Saharan countries relative to global averages, but true impact is difficult to estimate given limitations around surveillance and mortality registration. In Lusaka, Zambia, burial registration and SARS-CoV-2 prevalence data during 2020 allow estimation of excess mortality and transmission. Relative to pre-pandemic patterns, we estimate age-dependent mortality increases, totalling 3212 excess deaths (95% CrI: 2104–4591), representing an 18.5% (95% CrI: 13.0–25.2%) increase relative to pre-pandemic levels. Using a dynamical model-based inferential framework, we find that these mortality patterns and SARS-CoV-2 prevalence data are in agreement with established COVID-19 severity estimates. Our results support hypotheses that COVID-19 impact in Lusaka during 2020 was consistent with COVID-19 epidemics elsewhere, without requiring exceptional explanations for low reported figures. For more equitable decision-making during future pandemics, barriers to ascertaining attributable mortality in low-income settings must be addressed and factored into discourse around reported impact differences. Nature Publishing Group UK 2023-06-29 /pmc/articles/PMC10307769/ /pubmed/37380650 http://dx.doi.org/10.1038/s41467-023-39288-6 Text en © The Author(s) 2023 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Sheppard, Richard J. Watson, Oliver J. Pieciak, Rachel Lungu, James Kwenda, Geoffrey Moyo, Crispin Chanda, Stephen Longa Barnsley, Gregory Brazeau, Nicholas F. Gerard-Ursin, Ines C. G. Olivera Mesa, Daniela Whittaker, Charles Gregson, Simon Okell, Lucy C. Ghani, Azra C. MacLeod, William B. Del Fava, Emanuele Melegaro, Alessia Hines, Jonas Z. Mulenga, Lloyd B. Walker, Patrick G. T. Mwananyanda, Lawrence Gill, Christopher J. Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context |
title | Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context |
title_full | Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context |
title_fullStr | Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context |
title_full_unstemmed | Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context |
title_short | Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context |
title_sort | using mortuary and burial data to place covid-19 in lusaka, zambia within a global context |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10307769/ https://www.ncbi.nlm.nih.gov/pubmed/37380650 http://dx.doi.org/10.1038/s41467-023-39288-6 |
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