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Mathematical model for COVID-19 management in crowded settlements and high-activity areas
This paper develops and analyses a habitat area size dependent mathematical model to study the transmission dynamics of COVID-19 in crowded settlements such as refugee camps, schools, markets and churches. The model quantifies the potential impact of physical/social distancing and population density...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7955223/ https://www.ncbi.nlm.nih.gov/pubmed/33747709 http://dx.doi.org/10.1007/s40435-021-00781-9 |
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author | Ssematimba, A. Nakakawa, J. N. Ssebuliba, J. Mugisha, J. Y. T. |
author_facet | Ssematimba, A. Nakakawa, J. N. Ssebuliba, J. Mugisha, J. Y. T. |
author_sort | Ssematimba, A. |
collection | PubMed |
description | This paper develops and analyses a habitat area size dependent mathematical model to study the transmission dynamics of COVID-19 in crowded settlements such as refugee camps, schools, markets and churches. The model quantifies the potential impact of physical/social distancing and population density on the disease burden. Results reveal that with no fatalities and no infected entrants, the reproduction numbers associated with asymptomatic and symptomatic cases are inversely proportional to; the habitat area size, and the efforts employed in tracing and hospitalising these cases. The critical habitat area below which the disease dies out is directly proportion to the time taken to identify and hospitalise infected individuals. Results also show that disease persistence in the community is guaranteed even with minimal admission of infected individuals. Our results further show that as the level of compliance to standard operating procedures (SOPs) increases, then the disease prevalence peaks are greatly reduced and delayed. Therefore, proper adherence to SOPs such as use of masks, physical distancing measures and effective contact tracing should be highly enforced in crowded settings if COVID-19 is to be mitigated. |
format | Online Article Text |
id | pubmed-7955223 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-79552232021-03-15 Mathematical model for COVID-19 management in crowded settlements and high-activity areas Ssematimba, A. Nakakawa, J. N. Ssebuliba, J. Mugisha, J. Y. T. Int J Dyn Control Article This paper develops and analyses a habitat area size dependent mathematical model to study the transmission dynamics of COVID-19 in crowded settlements such as refugee camps, schools, markets and churches. The model quantifies the potential impact of physical/social distancing and population density on the disease burden. Results reveal that with no fatalities and no infected entrants, the reproduction numbers associated with asymptomatic and symptomatic cases are inversely proportional to; the habitat area size, and the efforts employed in tracing and hospitalising these cases. The critical habitat area below which the disease dies out is directly proportion to the time taken to identify and hospitalise infected individuals. Results also show that disease persistence in the community is guaranteed even with minimal admission of infected individuals. Our results further show that as the level of compliance to standard operating procedures (SOPs) increases, then the disease prevalence peaks are greatly reduced and delayed. Therefore, proper adherence to SOPs such as use of masks, physical distancing measures and effective contact tracing should be highly enforced in crowded settings if COVID-19 is to be mitigated. Springer Berlin Heidelberg 2021-03-13 2021 /pmc/articles/PMC7955223/ /pubmed/33747709 http://dx.doi.org/10.1007/s40435-021-00781-9 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Ssematimba, A. Nakakawa, J. N. Ssebuliba, J. Mugisha, J. Y. T. Mathematical model for COVID-19 management in crowded settlements and high-activity areas |
title | Mathematical model for COVID-19 management in crowded settlements and high-activity areas |
title_full | Mathematical model for COVID-19 management in crowded settlements and high-activity areas |
title_fullStr | Mathematical model for COVID-19 management in crowded settlements and high-activity areas |
title_full_unstemmed | Mathematical model for COVID-19 management in crowded settlements and high-activity areas |
title_short | Mathematical model for COVID-19 management in crowded settlements and high-activity areas |
title_sort | mathematical model for covid-19 management in crowded settlements and high-activity areas |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7955223/ https://www.ncbi.nlm.nih.gov/pubmed/33747709 http://dx.doi.org/10.1007/s40435-021-00781-9 |
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