Predicting Covid-19's spread in Africa: rural and relatively young population may limit the spread and severity

Diop, B. Z.; Ngom, M.; Pougue Biyong, C.; Pougue Biyong, J. N.

Introduction: A novel coronavirus disease 2019 (COVID-19) has spread to all regions of the world. There is great uncertainty regarding how countries characteristics will affect the spread of the epidemic; to date, there are few studies that attempt to predict the spread of the epidemic in African countries. In this paper, we investigate the role of demographic patterns, urbanization and co-morbidities on the possible trajectories of COVID-19 in Ghana, Kenya, and Senegal. Methods: We use an augmented deterministic SIR model to predict the true spread of the disease, under the containment measures taken so far. We dis-aggregate the infected compartment into asymptomatic, mildly symptomatic, and severely symptomatic to match observed clinical development of COVID-19. We also account for age structures, urbanization, and co-morbidities (HIV, tuberculosis, anemia). Results: In our baseline model, we project that the peak of active cases will occur in July, subject to the effectiveness of policy measures. When accounting for the urbanization, and factoring-in co-morbidities, the peak may occur between June 2nd and June 17th (Ghana), July 22 and August 29 (Kenya), and finally May 28th and June15th. Successful containment policies could lead to even lower rates of severe infections. While most cases will be mild, we project accounting for rural areas and comorbidities and in the absence of policies further containing the spread that between 0.78 and 1.03%, 0.61 and 1.22%, and 0.60 and 0.84% of individuals in Ghana, Kenya, and Senegal will be actively infected and develop severe symptoms at the peak of the epidemic. Conclusion: Compared to Europe, Africa's younger and rural population may modify the severity of the epidemic. The large youth population may lead to more infections but most of these infections will be asymptomatic or mild, and will probably go undetected. The higher prevalence of underlying conditions must be considered.