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Spread of COVID-19 in Zambia: An assessment of environmental and socioeconomic factors using a classification tree approach

The global pandemic emergent from SARS-COV-2 (COVID-19) has continued to cause both health and socio-economic challenges worldwide. However, there is limited information on the factors affecting the dynamics of COVID-19, especially in developing countries, including African countries. In this study,...

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Autores principales: Phiri, Darius, Salekin, Serajis, Nyirenda, Vincent R., Simwanda, Matamyo, Ranagalage, Manjula, Murayama, Yuji
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. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8256674/
https://www.ncbi.nlm.nih.gov/pubmed/34250321
http://dx.doi.org/10.1016/j.sciaf.2021.e00827
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author Phiri, Darius
Salekin, Serajis
Nyirenda, Vincent R.
Simwanda, Matamyo
Ranagalage, Manjula
Murayama, Yuji
author_facet Phiri, Darius
Salekin, Serajis
Nyirenda, Vincent R.
Simwanda, Matamyo
Ranagalage, Manjula
Murayama, Yuji
author_sort Phiri, Darius
collection PubMed
description The global pandemic emergent from SARS-COV-2 (COVID-19) has continued to cause both health and socio-economic challenges worldwide. However, there is limited information on the factors affecting the dynamics of COVID-19, especially in developing countries, including African countries. In this study, we have focused on understanding the association of COVID-19 cases with environmental and socioeconomic factors in Zambia - a sub-Saharan African country. We used Zambia's district-level COVID-19 data, covering 18 March 2020 (i.e., from first reported cases) to 17 July 2020. Geospatial approaches were used to organize, extract and establish the dataset, while a classification tree (CT) technique was employed to analyze the factors associated with the COVID-19 cases. The analyses were conducted in two stages: (1) the binary analysis of occurrences of COVID-19 (i.e., COVID-19 or No COVID-19), and (2) a risk level analysis which grouped the number of cases into four risk levels (high, moderate, low and very low). The results showed that the distribution of COVID-19 cases in Zambia was significantly influenced by the socioeconomic factors compared to environmental factors. More specifically, the binary model showed that distance to the airport, population density and distance to the town centres were the most combination influential factors, while the risk level analysis indicated that areas with high rates of human immuno-deficient virus (HIV) infection had relatively high chances of having many COVID-19 cases compared to areas with low HIV rates. The districts that are far from major urban establishments and that experience higher temperatures have lower chances of having COVID-19 cases. This study makes two major contributions towards the understanding of COVID-19 dynamics: (1) the methodology presented here can be effectively applied in other areas to understand the association of environmental and socioeconomic factors with COVID-19 cases, and (2), the findings from this study present the empirical evidence of the relationship between COVID-19 cases and their associated environmental and socioeconomic factors. Further studies are needed to understand the relationship of this disease and the associated factors in different cultural settings, seasons and age groups, especially as the COVID-19 cases increase and spread in many countries.
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spelling pubmed-82566742021-07-06 Spread of COVID-19 in Zambia: An assessment of environmental and socioeconomic factors using a classification tree approach Phiri, Darius Salekin, Serajis Nyirenda, Vincent R. Simwanda, Matamyo Ranagalage, Manjula Murayama, Yuji Sci Afr Article The global pandemic emergent from SARS-COV-2 (COVID-19) has continued to cause both health and socio-economic challenges worldwide. However, there is limited information on the factors affecting the dynamics of COVID-19, especially in developing countries, including African countries. In this study, we have focused on understanding the association of COVID-19 cases with environmental and socioeconomic factors in Zambia - a sub-Saharan African country. We used Zambia's district-level COVID-19 data, covering 18 March 2020 (i.e., from first reported cases) to 17 July 2020. Geospatial approaches were used to organize, extract and establish the dataset, while a classification tree (CT) technique was employed to analyze the factors associated with the COVID-19 cases. The analyses were conducted in two stages: (1) the binary analysis of occurrences of COVID-19 (i.e., COVID-19 or No COVID-19), and (2) a risk level analysis which grouped the number of cases into four risk levels (high, moderate, low and very low). The results showed that the distribution of COVID-19 cases in Zambia was significantly influenced by the socioeconomic factors compared to environmental factors. More specifically, the binary model showed that distance to the airport, population density and distance to the town centres were the most combination influential factors, while the risk level analysis indicated that areas with high rates of human immuno-deficient virus (HIV) infection had relatively high chances of having many COVID-19 cases compared to areas with low HIV rates. The districts that are far from major urban establishments and that experience higher temperatures have lower chances of having COVID-19 cases. This study makes two major contributions towards the understanding of COVID-19 dynamics: (1) the methodology presented here can be effectively applied in other areas to understand the association of environmental and socioeconomic factors with COVID-19 cases, and (2), the findings from this study present the empirical evidence of the relationship between COVID-19 cases and their associated environmental and socioeconomic factors. Further studies are needed to understand the relationship of this disease and the associated factors in different cultural settings, seasons and age groups, especially as the COVID-19 cases increase and spread in many countries. The Author(s). Published by Elsevier B.V. on behalf of African Institute of Mathematical Sciences / Next Einstein Initiative. 2021-07 2021-07-05 /pmc/articles/PMC8256674/ /pubmed/34250321 http://dx.doi.org/10.1016/j.sciaf.2021.e00827 Text en © 2021 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
Phiri, Darius
Salekin, Serajis
Nyirenda, Vincent R.
Simwanda, Matamyo
Ranagalage, Manjula
Murayama, Yuji
Spread of COVID-19 in Zambia: An assessment of environmental and socioeconomic factors using a classification tree approach
title Spread of COVID-19 in Zambia: An assessment of environmental and socioeconomic factors using a classification tree approach
title_full Spread of COVID-19 in Zambia: An assessment of environmental and socioeconomic factors using a classification tree approach
title_fullStr Spread of COVID-19 in Zambia: An assessment of environmental and socioeconomic factors using a classification tree approach
title_full_unstemmed Spread of COVID-19 in Zambia: An assessment of environmental and socioeconomic factors using a classification tree approach
title_short Spread of COVID-19 in Zambia: An assessment of environmental and socioeconomic factors using a classification tree approach
title_sort spread of covid-19 in zambia: an assessment of environmental and socioeconomic factors using a classification tree approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8256674/
https://www.ncbi.nlm.nih.gov/pubmed/34250321
http://dx.doi.org/10.1016/j.sciaf.2021.e00827
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