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Dynamic model of COVID-19 disease with exploratory data analysis
Novel Coronavirus is a highly infectious disease, with over one million confirmed cases and thousands of deaths recorded. The disease has become pandemic, affecting almost all nations of the world, and has caused enormous economic, social and psychological burden on countries. Hygiene and educationa...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V. on behalf of African Institute of Mathematical Sciences / Next Einstein Initiative.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7837064/ https://www.ncbi.nlm.nih.gov/pubmed/33521409 http://dx.doi.org/10.1016/j.sciaf.2020.e00477 |
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author | Adeniyi, Michael O. Ekum, Matthew I. C, Iluno S, Ogunsanya A. A, Akinyemi J. Oke, Segun I. B, Matadi M. |
author_facet | Adeniyi, Michael O. Ekum, Matthew I. C, Iluno S, Ogunsanya A. A, Akinyemi J. Oke, Segun I. B, Matadi M. |
author_sort | Adeniyi, Michael O. |
collection | PubMed |
description | Novel Coronavirus is a highly infectious disease, with over one million confirmed cases and thousands of deaths recorded. The disease has become pandemic, affecting almost all nations of the world, and has caused enormous economic, social and psychological burden on countries. Hygiene and educational campaign programmes have been identified to be potent public health interventions that can curtail the spread of the highly infectious disease. In order to verify this claim quantitatively, we propose and analyze a non-linear mathematical model to investigate the effect of healthy sanitation and awareness on the transmission dynamics of Coronavirus disease (COVID-19) prevalence. Rigorous stability analysis of the model equilibrium points was performed to ascertain the basic reproduction number R(0), a threshold that determines whether or not a disease dies out of the population. Our model assumes that education on the disease transmission and prevention induce behavioral changes in individuals to imbibe good hygiene, thereby reducing the basic reproduction number and disease burden. Numerical simulations are carried out using real life data to support the analytic results. |
format | Online Article Text |
id | pubmed-7837064 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Author(s). Published by Elsevier B.V. on behalf of African Institute of Mathematical Sciences / Next Einstein Initiative. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78370642021-01-26 Dynamic model of COVID-19 disease with exploratory data analysis Adeniyi, Michael O. Ekum, Matthew I. C, Iluno S, Ogunsanya A. A, Akinyemi J. Oke, Segun I. B, Matadi M. Sci Afr Article Novel Coronavirus is a highly infectious disease, with over one million confirmed cases and thousands of deaths recorded. The disease has become pandemic, affecting almost all nations of the world, and has caused enormous economic, social and psychological burden on countries. Hygiene and educational campaign programmes have been identified to be potent public health interventions that can curtail the spread of the highly infectious disease. In order to verify this claim quantitatively, we propose and analyze a non-linear mathematical model to investigate the effect of healthy sanitation and awareness on the transmission dynamics of Coronavirus disease (COVID-19) prevalence. Rigorous stability analysis of the model equilibrium points was performed to ascertain the basic reproduction number R(0), a threshold that determines whether or not a disease dies out of the population. Our model assumes that education on the disease transmission and prevention induce behavioral changes in individuals to imbibe good hygiene, thereby reducing the basic reproduction number and disease burden. Numerical simulations are carried out using real life data to support the analytic results. The Author(s). Published by Elsevier B.V. on behalf of African Institute of Mathematical Sciences / Next Einstein Initiative. 2020-09 2020-07-11 /pmc/articles/PMC7837064/ /pubmed/33521409 http://dx.doi.org/10.1016/j.sciaf.2020.e00477 Text en © 2020 The Author(s) 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 Adeniyi, Michael O. Ekum, Matthew I. C, Iluno S, Ogunsanya A. A, Akinyemi J. Oke, Segun I. B, Matadi M. Dynamic model of COVID-19 disease with exploratory data analysis |
title | Dynamic model of COVID-19 disease with exploratory data analysis |
title_full | Dynamic model of COVID-19 disease with exploratory data analysis |
title_fullStr | Dynamic model of COVID-19 disease with exploratory data analysis |
title_full_unstemmed | Dynamic model of COVID-19 disease with exploratory data analysis |
title_short | Dynamic model of COVID-19 disease with exploratory data analysis |
title_sort | dynamic model of covid-19 disease with exploratory data analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7837064/ https://www.ncbi.nlm.nih.gov/pubmed/33521409 http://dx.doi.org/10.1016/j.sciaf.2020.e00477 |
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