Cargando…

Leveraging artificial intelligence to optimize COVID-19 robust spread and vaccination roll-out strategies in Southern Africa

The outbreak of coronavirus in the year 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prompted widespread illness, death, and extended economic devastation worldwide. In response, numerous countries, including Botswana and South Africa, instituted various cl...

Descripción completa

Detalles Bibliográficos
Autores principales: Mathaha, Thuso, Mafu, Mhlambululi, Mabikwa, Onkabetse V., Ndenda, Joseph, Hillhouse, Gregory, Mellado, Bruce
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9606810/
https://www.ncbi.nlm.nih.gov/pubmed/36311551
http://dx.doi.org/10.3389/frai.2022.1013010
_version_ 1784818382316503040
author Mathaha, Thuso
Mafu, Mhlambululi
Mabikwa, Onkabetse V.
Ndenda, Joseph
Hillhouse, Gregory
Mellado, Bruce
author_facet Mathaha, Thuso
Mafu, Mhlambululi
Mabikwa, Onkabetse V.
Ndenda, Joseph
Hillhouse, Gregory
Mellado, Bruce
author_sort Mathaha, Thuso
collection PubMed
description The outbreak of coronavirus in the year 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prompted widespread illness, death, and extended economic devastation worldwide. In response, numerous countries, including Botswana and South Africa, instituted various clinical public health (CPH) strategies to mitigate and control the disease. However, the emergence of variants of concern (VOC), vaccine hesitancy, morbidity, inadequate and inequitable vaccine supply, and ineffective vaccine roll-out strategies caused continuous disruption of essential services. Based on Botswana and South Africa hospitalization and mortality data, we studied the impact of age and gender on disease severity. Comparative analysis was performed between the two countries to establish a vaccination strategy that could complement the existing CPH strategies. To optimize the vaccination roll-out strategy, artificial intelligence was used to identify the population groups in need of insufficient vaccines. We found that COVID-19 was associated with several comorbidities. However, hypertension and diabetes were more severe and common in both countries. The elderly population aged ≥60 years had 70% of major COVID-19 comorbidities; thus, they should be prioritized for vaccination. Moreover, we found that the Botswana and South Africa populations had similar COVID-19 mortality rates. Hence, our findings should be extended to the rest of Southern African countries since the population in this region have similar demographic and disease characteristics.
format Online
Article
Text
id pubmed-9606810
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-96068102022-10-28 Leveraging artificial intelligence to optimize COVID-19 robust spread and vaccination roll-out strategies in Southern Africa Mathaha, Thuso Mafu, Mhlambululi Mabikwa, Onkabetse V. Ndenda, Joseph Hillhouse, Gregory Mellado, Bruce Front Artif Intell Artificial Intelligence The outbreak of coronavirus in the year 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prompted widespread illness, death, and extended economic devastation worldwide. In response, numerous countries, including Botswana and South Africa, instituted various clinical public health (CPH) strategies to mitigate and control the disease. However, the emergence of variants of concern (VOC), vaccine hesitancy, morbidity, inadequate and inequitable vaccine supply, and ineffective vaccine roll-out strategies caused continuous disruption of essential services. Based on Botswana and South Africa hospitalization and mortality data, we studied the impact of age and gender on disease severity. Comparative analysis was performed between the two countries to establish a vaccination strategy that could complement the existing CPH strategies. To optimize the vaccination roll-out strategy, artificial intelligence was used to identify the population groups in need of insufficient vaccines. We found that COVID-19 was associated with several comorbidities. However, hypertension and diabetes were more severe and common in both countries. The elderly population aged ≥60 years had 70% of major COVID-19 comorbidities; thus, they should be prioritized for vaccination. Moreover, we found that the Botswana and South Africa populations had similar COVID-19 mortality rates. Hence, our findings should be extended to the rest of Southern African countries since the population in this region have similar demographic and disease characteristics. Frontiers Media S.A. 2022-10-13 /pmc/articles/PMC9606810/ /pubmed/36311551 http://dx.doi.org/10.3389/frai.2022.1013010 Text en Copyright © 2022 Mathaha, Mafu, Mabikwa, Ndenda, Hillhouse and Mellado. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Artificial Intelligence
Mathaha, Thuso
Mafu, Mhlambululi
Mabikwa, Onkabetse V.
Ndenda, Joseph
Hillhouse, Gregory
Mellado, Bruce
Leveraging artificial intelligence to optimize COVID-19 robust spread and vaccination roll-out strategies in Southern Africa
title Leveraging artificial intelligence to optimize COVID-19 robust spread and vaccination roll-out strategies in Southern Africa
title_full Leveraging artificial intelligence to optimize COVID-19 robust spread and vaccination roll-out strategies in Southern Africa
title_fullStr Leveraging artificial intelligence to optimize COVID-19 robust spread and vaccination roll-out strategies in Southern Africa
title_full_unstemmed Leveraging artificial intelligence to optimize COVID-19 robust spread and vaccination roll-out strategies in Southern Africa
title_short Leveraging artificial intelligence to optimize COVID-19 robust spread and vaccination roll-out strategies in Southern Africa
title_sort leveraging artificial intelligence to optimize covid-19 robust spread and vaccination roll-out strategies in southern africa
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9606810/
https://www.ncbi.nlm.nih.gov/pubmed/36311551
http://dx.doi.org/10.3389/frai.2022.1013010
work_keys_str_mv AT mathahathuso leveragingartificialintelligencetooptimizecovid19robustspreadandvaccinationrolloutstrategiesinsouthernafrica
AT mafumhlambululi leveragingartificialintelligencetooptimizecovid19robustspreadandvaccinationrolloutstrategiesinsouthernafrica
AT mabikwaonkabetsev leveragingartificialintelligencetooptimizecovid19robustspreadandvaccinationrolloutstrategiesinsouthernafrica
AT ndendajoseph leveragingartificialintelligencetooptimizecovid19robustspreadandvaccinationrolloutstrategiesinsouthernafrica
AT hillhousegregory leveragingartificialintelligencetooptimizecovid19robustspreadandvaccinationrolloutstrategiesinsouthernafrica
AT melladobruce leveragingartificialintelligencetooptimizecovid19robustspreadandvaccinationrolloutstrategiesinsouthernafrica