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Early estimates of COVID-19 infections in small, medium and large population clusters
INTRODUCTION: Since its emergence in late December 2019, COVID-19 has rapidly developed into a pandemic in mid of March with many countries suffering heavy human loss and declaring emergency conditions to contain its spread. The impact of the disease, while it has been relatively low in the sub-Saha...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BMJ Publishing Group
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7503195/ https://www.ncbi.nlm.nih.gov/pubmed/32948617 http://dx.doi.org/10.1136/bmjgh-2020-003055 |
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author | Siraj, Amir Worku, Alemayehu Berhane, Kiros Aregawi, Maru Eshetu, Munir Mirkuzie, Alemnesh Berhane, Yemane Siraj, Dawd |
author_facet | Siraj, Amir Worku, Alemayehu Berhane, Kiros Aregawi, Maru Eshetu, Munir Mirkuzie, Alemnesh Berhane, Yemane Siraj, Dawd |
author_sort | Siraj, Amir |
collection | PubMed |
description | INTRODUCTION: Since its emergence in late December 2019, COVID-19 has rapidly developed into a pandemic in mid of March with many countries suffering heavy human loss and declaring emergency conditions to contain its spread. The impact of the disease, while it has been relatively low in the sub-Saharan Africa (SSA) as of May 2020, is feared to be potentially devastating given the less developed and fragmented healthcare system in the continent. In addition, most emergency measures practised may not be effective due to their limited affordability as well as the communal way people in SSA live in relative isolation in clusters of large as well as smaller population centres. METHODS: To address the acute need for estimates of the potential impacts of the disease once it sweeps through the African region, we developed a process-based model with key parameters obtained from recent studies, taking local context into consideration. We further used the model to estimate the number of infections within a year of sustained local transmissions under scenarios that cover different population sizes, urban status, effectiveness and coverage of social distancing, contact tracing and usage of cloth face mask. RESULTS: We showed that when implemented early, 50% coverage of contact tracing and face mask, with 33% effective social distancing policies can bringing the epidemic to a manageable level for all population sizes and settings we assessed. Relaxing of social distancing in urban settings from 33% to 25% could be matched by introduction and maintenance of face mask use at 43%. CONCLUSIONS: In SSA countries with limited healthcare workforce, hospital resources and intensive care units, a robust system of social distancing, contact tracing and face mask use could yield in outcomes that prevent several millions of infections and thousands of deaths across the continent. |
format | Online Article Text |
id | pubmed-7503195 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-75031952020-09-21 Early estimates of COVID-19 infections in small, medium and large population clusters Siraj, Amir Worku, Alemayehu Berhane, Kiros Aregawi, Maru Eshetu, Munir Mirkuzie, Alemnesh Berhane, Yemane Siraj, Dawd BMJ Glob Health Original Research INTRODUCTION: Since its emergence in late December 2019, COVID-19 has rapidly developed into a pandemic in mid of March with many countries suffering heavy human loss and declaring emergency conditions to contain its spread. The impact of the disease, while it has been relatively low in the sub-Saharan Africa (SSA) as of May 2020, is feared to be potentially devastating given the less developed and fragmented healthcare system in the continent. In addition, most emergency measures practised may not be effective due to their limited affordability as well as the communal way people in SSA live in relative isolation in clusters of large as well as smaller population centres. METHODS: To address the acute need for estimates of the potential impacts of the disease once it sweeps through the African region, we developed a process-based model with key parameters obtained from recent studies, taking local context into consideration. We further used the model to estimate the number of infections within a year of sustained local transmissions under scenarios that cover different population sizes, urban status, effectiveness and coverage of social distancing, contact tracing and usage of cloth face mask. RESULTS: We showed that when implemented early, 50% coverage of contact tracing and face mask, with 33% effective social distancing policies can bringing the epidemic to a manageable level for all population sizes and settings we assessed. Relaxing of social distancing in urban settings from 33% to 25% could be matched by introduction and maintenance of face mask use at 43%. CONCLUSIONS: In SSA countries with limited healthcare workforce, hospital resources and intensive care units, a robust system of social distancing, contact tracing and face mask use could yield in outcomes that prevent several millions of infections and thousands of deaths across the continent. BMJ Publishing Group 2020-09-18 /pmc/articles/PMC7503195/ /pubmed/32948617 http://dx.doi.org/10.1136/bmjgh-2020-003055 Text en © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. http://creativecommons.org/licenses/by-nc/4.0/ http://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Original Research Siraj, Amir Worku, Alemayehu Berhane, Kiros Aregawi, Maru Eshetu, Munir Mirkuzie, Alemnesh Berhane, Yemane Siraj, Dawd Early estimates of COVID-19 infections in small, medium and large population clusters |
title | Early estimates of COVID-19 infections in small, medium and large population clusters |
title_full | Early estimates of COVID-19 infections in small, medium and large population clusters |
title_fullStr | Early estimates of COVID-19 infections in small, medium and large population clusters |
title_full_unstemmed | Early estimates of COVID-19 infections in small, medium and large population clusters |
title_short | Early estimates of COVID-19 infections in small, medium and large population clusters |
title_sort | early estimates of covid-19 infections in small, medium and large population clusters |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7503195/ https://www.ncbi.nlm.nih.gov/pubmed/32948617 http://dx.doi.org/10.1136/bmjgh-2020-003055 |
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