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Modelling spatial variations of coronavirus disease (COVID-19) in Africa

Clinical and epidemiological evidence has been advanced for human-to-human transmission of the novel coronavirus rampaging the world since late 2019. Outliers in the human-to-human transmission are yet to be explored. In this study, we examined the spatial density and leaned statistical credence to...

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Autores principales: Adekunle, Ibrahim Ayoade, Onanuga, Abayomi Toyin, Akinola, Olanrewaju Olugbenga, Ogunbanjo, Olakitan Wahab
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7195380/
https://www.ncbi.nlm.nih.gov/pubmed/32361455
http://dx.doi.org/10.1016/j.scitotenv.2020.138998
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author Adekunle, Ibrahim Ayoade
Onanuga, Abayomi Toyin
Akinola, Olanrewaju Olugbenga
Ogunbanjo, Olakitan Wahab
author_facet Adekunle, Ibrahim Ayoade
Onanuga, Abayomi Toyin
Akinola, Olanrewaju Olugbenga
Ogunbanjo, Olakitan Wahab
author_sort Adekunle, Ibrahim Ayoade
collection PubMed
description Clinical and epidemiological evidence has been advanced for human-to-human transmission of the novel coronavirus rampaging the world since late 2019. Outliers in the human-to-human transmission are yet to be explored. In this study, we examined the spatial density and leaned statistical credence to the global debate. We constructed spatial variations of clusters that examined the nexus between COVID-19 attributable deaths and confirmed cases. We rely on publicly available data on confirmed cases and death across Africa to unravel the unobserved factors, that could be responsible for the spread of COVID-19. We relied on the dynamic system generalised method of moment estimation procedure and found a ~0.045 Covid19 deaths as a result of confirmed cases in Africa. We accounted for cross-sectional dependence and found a basis for the strict orthogonal relationship. Policy measures were discussed.
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spelling pubmed-71953802020-05-02 Modelling spatial variations of coronavirus disease (COVID-19) in Africa Adekunle, Ibrahim Ayoade Onanuga, Abayomi Toyin Akinola, Olanrewaju Olugbenga Ogunbanjo, Olakitan Wahab Sci Total Environ Article Clinical and epidemiological evidence has been advanced for human-to-human transmission of the novel coronavirus rampaging the world since late 2019. Outliers in the human-to-human transmission are yet to be explored. In this study, we examined the spatial density and leaned statistical credence to the global debate. We constructed spatial variations of clusters that examined the nexus between COVID-19 attributable deaths and confirmed cases. We rely on publicly available data on confirmed cases and death across Africa to unravel the unobserved factors, that could be responsible for the spread of COVID-19. We relied on the dynamic system generalised method of moment estimation procedure and found a ~0.045 Covid19 deaths as a result of confirmed cases in Africa. We accounted for cross-sectional dependence and found a basis for the strict orthogonal relationship. Policy measures were discussed. Elsevier B.V. 2020-08-10 2020-04-26 /pmc/articles/PMC7195380/ /pubmed/32361455 http://dx.doi.org/10.1016/j.scitotenv.2020.138998 Text en © 2020 Elsevier B.V. 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
Adekunle, Ibrahim Ayoade
Onanuga, Abayomi Toyin
Akinola, Olanrewaju Olugbenga
Ogunbanjo, Olakitan Wahab
Modelling spatial variations of coronavirus disease (COVID-19) in Africa
title Modelling spatial variations of coronavirus disease (COVID-19) in Africa
title_full Modelling spatial variations of coronavirus disease (COVID-19) in Africa
title_fullStr Modelling spatial variations of coronavirus disease (COVID-19) in Africa
title_full_unstemmed Modelling spatial variations of coronavirus disease (COVID-19) in Africa
title_short Modelling spatial variations of coronavirus disease (COVID-19) in Africa
title_sort modelling spatial variations of coronavirus disease (covid-19) in africa
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7195380/
https://www.ncbi.nlm.nih.gov/pubmed/32361455
http://dx.doi.org/10.1016/j.scitotenv.2020.138998
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