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Predictive models on COVID 19: What Africans should do?
In this study, predictive models are proposed to accurately estimate the confirmed cases and deaths due to of Corona virus 2019 (COVID-19) in Africa. The study proposed the predictive models to determine the spatial and temporal pattern of COVID 19 in Africa. The result of the study has shown that t...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
KeAi Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7670905/ https://www.ncbi.nlm.nih.gov/pubmed/33225115 http://dx.doi.org/10.1016/j.idm.2020.10.015 |
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author | Likassa, Habte Tadesse Xain, Wen Tang, Xuan Gobebo, Gizachew |
author_facet | Likassa, Habte Tadesse Xain, Wen Tang, Xuan Gobebo, Gizachew |
author_sort | Likassa, Habte Tadesse |
collection | PubMed |
description | In this study, predictive models are proposed to accurately estimate the confirmed cases and deaths due to of Corona virus 2019 (COVID-19) in Africa. The study proposed the predictive models to determine the spatial and temporal pattern of COVID 19 in Africa. The result of the study has shown that the spatial and temporal pattern of the pandemic is varying across in the study area. The result has shown that cubic model is best outperforming compared to the other six families of exponentials ([Formula: see text]. The adopted cubic algorithm is more robust in predicting the confirmed cases and deaths due to COVID 19. The cubic algorithm is more superior to the state of the art of the works based on the world health organization data. This also entails the best way to mitigate the expansion of COVID 19 is through persistent and strict self-isolation. This pandemic will sustain to grow up, and peak to the highest for which a strong care and public health interventions practically implemented. It is highly recommended for Africans must go beyond theory preparations implementations practically through the public interventions. |
format | Online Article Text |
id | pubmed-7670905 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | KeAi Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-76709052020-11-18 Predictive models on COVID 19: What Africans should do? Likassa, Habte Tadesse Xain, Wen Tang, Xuan Gobebo, Gizachew Infect Dis Model Special issue on Modelling and Forecasting the 2019 Novel Coronavirus (2019-nCoV) Transmission; Edited by Prof. Carlos Castillo-Chavez, Prof. Gerardo Chowell-Puente, Prof. Ping Yan, Prof. Jianhong Wu In this study, predictive models are proposed to accurately estimate the confirmed cases and deaths due to of Corona virus 2019 (COVID-19) in Africa. The study proposed the predictive models to determine the spatial and temporal pattern of COVID 19 in Africa. The result of the study has shown that the spatial and temporal pattern of the pandemic is varying across in the study area. The result has shown that cubic model is best outperforming compared to the other six families of exponentials ([Formula: see text]. The adopted cubic algorithm is more robust in predicting the confirmed cases and deaths due to COVID 19. The cubic algorithm is more superior to the state of the art of the works based on the world health organization data. This also entails the best way to mitigate the expansion of COVID 19 is through persistent and strict self-isolation. This pandemic will sustain to grow up, and peak to the highest for which a strong care and public health interventions practically implemented. It is highly recommended for Africans must go beyond theory preparations implementations practically through the public interventions. KeAi Publishing 2020-11-17 /pmc/articles/PMC7670905/ /pubmed/33225115 http://dx.doi.org/10.1016/j.idm.2020.10.015 Text en © 2021 The Authors. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Special issue on Modelling and Forecasting the 2019 Novel Coronavirus (2019-nCoV) Transmission; Edited by Prof. Carlos Castillo-Chavez, Prof. Gerardo Chowell-Puente, Prof. Ping Yan, Prof. Jianhong Wu Likassa, Habte Tadesse Xain, Wen Tang, Xuan Gobebo, Gizachew Predictive models on COVID 19: What Africans should do? |
title | Predictive models on COVID 19: What Africans should do? |
title_full | Predictive models on COVID 19: What Africans should do? |
title_fullStr | Predictive models on COVID 19: What Africans should do? |
title_full_unstemmed | Predictive models on COVID 19: What Africans should do? |
title_short | Predictive models on COVID 19: What Africans should do? |
title_sort | predictive models on covid 19: what africans should do? |
topic | Special issue on Modelling and Forecasting the 2019 Novel Coronavirus (2019-nCoV) Transmission; Edited by Prof. Carlos Castillo-Chavez, Prof. Gerardo Chowell-Puente, Prof. Ping Yan, Prof. Jianhong Wu |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7670905/ https://www.ncbi.nlm.nih.gov/pubmed/33225115 http://dx.doi.org/10.1016/j.idm.2020.10.015 |
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