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...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-10-01
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| Series: | Frontiers in Artificial Intelligence |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/frai.2022.1013010/full |
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| author | Thuso Mathaha Mhlambululi Mafu Onkabetse V. Mabikwa Joseph Ndenda Gregory Hillhouse Bruce Mellado Bruce Mellado |
| author_facet | Thuso Mathaha Mhlambululi Mafu Onkabetse V. Mabikwa Joseph Ndenda Gregory Hillhouse Bruce Mellado Bruce Mellado |
| author_sort | Thuso Mathaha |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-11T10:03:07Z |
| format | Article |
| id | doaj.art-967056b6757849f69692a346571d4c0b |
| institution | Directory Open Access Journal |
| issn | 2624-8212 |
| language | English |
| last_indexed | 2024-04-11T10:03:07Z |
| publishDate | 2022-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Artificial Intelligence |
| spelling | doaj.art-967056b6757849f69692a346571d4c0b2022-12-22T04:30:19ZengFrontiers Media S.A.Frontiers in Artificial Intelligence2624-82122022-10-01510.3389/frai.2022.10130101013010Leveraging artificial intelligence to optimize COVID-19 robust spread and vaccination roll-out strategies in Southern AfricaThuso Mathaha0Mhlambululi Mafu1Onkabetse V. Mabikwa2Joseph Ndenda3Gregory Hillhouse4Bruce Mellado5Bruce Mellado6School of Physics and Institute for Collider Particle Physics, University of the Witwatersrand, Johannesburg, South AfricaDepartment of Physics, Case Western Reserve University, Cleveland, OH, United StatesDepartment of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Palapye, BotswanaDepartment of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Palapye, BotswanaDepartment of Physics and Astronomy, Botswana International University of Science and Technology, Palapye, BotswanaSchool of Physics and Institute for Collider Particle Physics, University of the Witwatersrand, Johannesburg, South AfricaiThemba LABS, National Research Foundation, Somerset West, South AfricaThe 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.https://www.frontiersin.org/articles/10.3389/frai.2022.1013010/fullCOVID-19comorbiditiesvaccine rolloutartificial intelligenceBotswana |
| spellingShingle | Thuso Mathaha Mhlambululi Mafu Onkabetse V. Mabikwa Joseph Ndenda Gregory Hillhouse Bruce Mellado Bruce Mellado Leveraging artificial intelligence to optimize COVID-19 robust spread and vaccination roll-out strategies in Southern Africa Frontiers in Artificial Intelligence COVID-19 comorbidities vaccine rollout artificial intelligence Botswana |
| 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 | COVID-19 comorbidities vaccine rollout artificial intelligence Botswana |
| url | https://www.frontiersin.org/articles/10.3389/frai.2022.1013010/full |
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