The need to return to the basics of predictive modelling for disease outbreak response: lessons from COVID-19

The outbreak of COVID-19 has been unprecedented in speed and effect. Efforts to predict the disease transmission have mostly been done using flagship models developed by the global north. These models have not accurately depicted the true rate of transmission of SARS-CoV-2 in Africa. The models have...

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Autor principal: Okuonzi, Sam Agatre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The African Field Epidemiology Network 2020
Materias:
Commentary
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7664134/
https://www.ncbi.nlm.nih.gov/pubmed/33224421
http://dx.doi.org/10.11604/pamj.2020.36.355.24101
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author Okuonzi, Sam Agatre
author_facet Okuonzi, Sam Agatre
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description The outbreak of COVID-19 has been unprecedented in speed and effect. Efforts to predict the disease transmission have mostly been done using flagship models developed by the global north. These models have not accurately depicted the true rate of transmission of SARS-CoV-2 in Africa. The models have ignored Africa’s unique socio-ecological makeup (demographic, social, environmental and biological) that has aided a slower and less severe spread of the virus. This paper opines on how the science of infectious disease modelling needs to evolve to accommodate contextual factors. Country-owned and tailored modelling needs to be urgently supported.
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spelling pubmed-76641342020-11-20 The need to return to the basics of predictive modelling for disease outbreak response: lessons from COVID-19 Okuonzi, Sam Agatre Pan Afr Med J Commentary The outbreak of COVID-19 has been unprecedented in speed and effect. Efforts to predict the disease transmission have mostly been done using flagship models developed by the global north. These models have not accurately depicted the true rate of transmission of SARS-CoV-2 in Africa. The models have ignored Africa’s unique socio-ecological makeup (demographic, social, environmental and biological) that has aided a slower and less severe spread of the virus. This paper opines on how the science of infectious disease modelling needs to evolve to accommodate contextual factors. Country-owned and tailored modelling needs to be urgently supported. The African Field Epidemiology Network 2020-08-27 /pmc/articles/PMC7664134/ /pubmed/33224421 http://dx.doi.org/10.11604/pamj.2020.36.355.24101 Text en Copyright: Sam Agatre Okuonzi et al. https://creativecommons.org/licenses/by/4.0 The Pan African Medical Journal (ISSN: 1937-8688). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Commentary
Okuonzi, Sam Agatre
The need to return to the basics of predictive modelling for disease outbreak response: lessons from COVID-19
title The need to return to the basics of predictive modelling for disease outbreak response: lessons from COVID-19
title_full The need to return to the basics of predictive modelling for disease outbreak response: lessons from COVID-19
title_fullStr The need to return to the basics of predictive modelling for disease outbreak response: lessons from COVID-19
title_full_unstemmed The need to return to the basics of predictive modelling for disease outbreak response: lessons from COVID-19
title_short The need to return to the basics of predictive modelling for disease outbreak response: lessons from COVID-19
title_sort need to return to the basics of predictive modelling for disease outbreak response: lessons from covid-19
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7664134/
https://www.ncbi.nlm.nih.gov/pubmed/33224421
http://dx.doi.org/10.11604/pamj.2020.36.355.24101
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