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COVID-19 outbreak, social distancing and mass testing in Kenya-insights from a mathematical model

As reported by the World Health Organization (WHO), the world is currently facing a devastating pandemic of a novel coronavirus (COVID-19), which started as an outbreak of pneumonia of unknown cause in the Wuhan city of China in December 2019. Since then, the respiratory disease has exponentially sp...

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Autores principales: Mbogo, Rachel Waema, Odhiambo, John W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7782570/
http://dx.doi.org/10.1007/s13370-020-00859-1
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author Mbogo, Rachel Waema
Odhiambo, John W.
author_facet Mbogo, Rachel Waema
Odhiambo, John W.
author_sort Mbogo, Rachel Waema
collection PubMed
description As reported by the World Health Organization (WHO), the world is currently facing a devastating pandemic of a novel coronavirus (COVID-19), which started as an outbreak of pneumonia of unknown cause in the Wuhan city of China in December 2019. Since then, the respiratory disease has exponentially spread to over 210 countries. By the end of April, COVID-19 had caused over three million confirmed cases of infections and over 200,000 fatalities globally. The trend poses a huge threat to global public health. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. We employed a SEIHQRD delay differential mathematical transmission model with reported Kenyan data on cases of COVID-19 to estimate how transmission varies over time and which population to target for mass testing. The model is concise in structure, and successfully captures the course of the COVID-19 outbreak, and thus sheds light on understanding the trends of the outbreak and the vulnerable populations. The results show that, the government should target population in the informal settlement for mass testing and provide affordable sanitizers and clean water to this population. The model results also indicate that people with pre-existing non-communicable diseases (NCDs) should be identified and given special medical care. Given the absence of vaccine at the moment, non-pharmaceutical intervention is needed to effectively reduce the final epidemic size.
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spelling pubmed-77825702021-01-05 COVID-19 outbreak, social distancing and mass testing in Kenya-insights from a mathematical model Mbogo, Rachel Waema Odhiambo, John W. Afr. Mat. Article As reported by the World Health Organization (WHO), the world is currently facing a devastating pandemic of a novel coronavirus (COVID-19), which started as an outbreak of pneumonia of unknown cause in the Wuhan city of China in December 2019. Since then, the respiratory disease has exponentially spread to over 210 countries. By the end of April, COVID-19 had caused over three million confirmed cases of infections and over 200,000 fatalities globally. The trend poses a huge threat to global public health. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas. We employed a SEIHQRD delay differential mathematical transmission model with reported Kenyan data on cases of COVID-19 to estimate how transmission varies over time and which population to target for mass testing. The model is concise in structure, and successfully captures the course of the COVID-19 outbreak, and thus sheds light on understanding the trends of the outbreak and the vulnerable populations. The results show that, the government should target population in the informal settlement for mass testing and provide affordable sanitizers and clean water to this population. The model results also indicate that people with pre-existing non-communicable diseases (NCDs) should be identified and given special medical care. Given the absence of vaccine at the moment, non-pharmaceutical intervention is needed to effectively reduce the final epidemic size. Springer Berlin Heidelberg 2021-01-05 2021 /pmc/articles/PMC7782570/ http://dx.doi.org/10.1007/s13370-020-00859-1 Text en © African Mathematical Union and Springer-Verlag GmbH Deutschland, ein Teil von 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
Mbogo, Rachel Waema
Odhiambo, John W.
COVID-19 outbreak, social distancing and mass testing in Kenya-insights from a mathematical model
title COVID-19 outbreak, social distancing and mass testing in Kenya-insights from a mathematical model
title_full COVID-19 outbreak, social distancing and mass testing in Kenya-insights from a mathematical model
title_fullStr COVID-19 outbreak, social distancing and mass testing in Kenya-insights from a mathematical model
title_full_unstemmed COVID-19 outbreak, social distancing and mass testing in Kenya-insights from a mathematical model
title_short COVID-19 outbreak, social distancing and mass testing in Kenya-insights from a mathematical model
title_sort covid-19 outbreak, social distancing and mass testing in kenya-insights from a mathematical model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7782570/
http://dx.doi.org/10.1007/s13370-020-00859-1
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