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Analysis of a mathematical model for COVID-19 population dynamics in Lagos, Nigeria

This work examines the impact of various non-pharmaceutical control measures (government and personal) on the population dynamics of the novel coronavirus disease 2019 (COVID-19) in Lagos, Nigeria, using an appropriately formulated mathematical model. Using the available data, since its first report...

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Autores principales: Okuonghae, D., Omame, A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305939/
https://www.ncbi.nlm.nih.gov/pubmed/32834593
http://dx.doi.org/10.1016/j.chaos.2020.110032
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author Okuonghae, D.
Omame, A.
author_facet Okuonghae, D.
Omame, A.
author_sort Okuonghae, D.
collection PubMed
description This work examines the impact of various non-pharmaceutical control measures (government and personal) on the population dynamics of the novel coronavirus disease 2019 (COVID-19) in Lagos, Nigeria, using an appropriately formulated mathematical model. Using the available data, since its first reported case on 16 March 2020, we seek to develop a predicative tool for the cumulative number of reported cases and the number of active cases in Lagos; we also estimate the basic reproduction number of the disease outbreak in the aforementioned State in Nigeria. Using numerical simulations, we show the effect of control measures, specifically the common social distancing, use of face mask and case detection (via contact tracing and subsequent testings) on the dynamics of COVID-19. We also provide forecasts for the cumulative number of reported cases and active cases for different levels of the control measures being implemented. Numerical simulations of the model show that if at least 55% of the population comply with the social distancing regulation with about 55% of the population effectively making use of face masks while in public, the disease will eventually die out in the population and that, if we can step up the case detection rate for symptomatic individuals to about 0.8 per day, with about 55% of the population complying with the social distancing regulations, it will lead to a great decrease in the incidence (and prevalence) of COVID-19.
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spelling pubmed-73059392020-06-22 Analysis of a mathematical model for COVID-19 population dynamics in Lagos, Nigeria Okuonghae, D. Omame, A. Chaos Solitons Fractals Article This work examines the impact of various non-pharmaceutical control measures (government and personal) on the population dynamics of the novel coronavirus disease 2019 (COVID-19) in Lagos, Nigeria, using an appropriately formulated mathematical model. Using the available data, since its first reported case on 16 March 2020, we seek to develop a predicative tool for the cumulative number of reported cases and the number of active cases in Lagos; we also estimate the basic reproduction number of the disease outbreak in the aforementioned State in Nigeria. Using numerical simulations, we show the effect of control measures, specifically the common social distancing, use of face mask and case detection (via contact tracing and subsequent testings) on the dynamics of COVID-19. We also provide forecasts for the cumulative number of reported cases and active cases for different levels of the control measures being implemented. Numerical simulations of the model show that if at least 55% of the population comply with the social distancing regulation with about 55% of the population effectively making use of face masks while in public, the disease will eventually die out in the population and that, if we can step up the case detection rate for symptomatic individuals to about 0.8 per day, with about 55% of the population complying with the social distancing regulations, it will lead to a great decrease in the incidence (and prevalence) of COVID-19. Elsevier Ltd. 2020-10 2020-06-20 /pmc/articles/PMC7305939/ /pubmed/32834593 http://dx.doi.org/10.1016/j.chaos.2020.110032 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Okuonghae, D.
Omame, A.
Analysis of a mathematical model for COVID-19 population dynamics in Lagos, Nigeria
title Analysis of a mathematical model for COVID-19 population dynamics in Lagos, Nigeria
title_full Analysis of a mathematical model for COVID-19 population dynamics in Lagos, Nigeria
title_fullStr Analysis of a mathematical model for COVID-19 population dynamics in Lagos, Nigeria
title_full_unstemmed Analysis of a mathematical model for COVID-19 population dynamics in Lagos, Nigeria
title_short Analysis of a mathematical model for COVID-19 population dynamics in Lagos, Nigeria
title_sort analysis of a mathematical model for covid-19 population dynamics in lagos, nigeria
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7305939/
https://www.ncbi.nlm.nih.gov/pubmed/32834593
http://dx.doi.org/10.1016/j.chaos.2020.110032
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