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 (Frontiers in Artificial Intelligence, 2022)
The unprecedented outbreak of the infectious novel coronavirus 2019 (COVID-19), caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) has prompted widespread illness and death and extended economic devastation worldwide. In response, numerous countries, including Botswana, have instituted various clinical public health (CPH) strategies to mitigate and control the disease. Though different COVID-19 vaccines have become available; however, the emergence of variants of concern (VOC), vaccine hesitancy, morbidity, inadequate and inequitable vaccine supply, ineffective vaccine roll-out strategies have caused the continual disruption of essential services in Botswana. Therefore, based on the hospitalization and mortality data, we identify determinants such as comorbidities and the impact of age and gender on the severity of the COVID-19 pandemic leading to mortality. Notably, we perform a comparative analysis of various epidemiological factors and others such as comorbidities and mortality rates due to the COVID-19 epidemic in Botswana and South Africa as a reference. Thus, we propose and model a vaccination strategy to complement the CPH strategies by leveraging artificial intelligence to classify people who need vaccines based on the health status characteristics, thus allowing us to optimize the roll-out of the vaccine in Botswana. We find that the severity of COVID-19 is associated with several comorbidities; however, hypertension and diabetes are more severe and common in both countries. Notably, those aged 60 years and above need to be prioritized, and unfortunately, more than 70% of them have major comorbidities, thus increasing the severity of COVID-19. However, our results also indicate that young adults below those populations with these comorbidities are also at risk. Moreover, we find that the mortality rates due to the virus are similar in both countries, which suggests that these results apply to the rest of Southern Africa since the countries have similar epidemiological factors.