On Data-Driven Management of the COVID-19 Outbreak in South Africa

Abstract The rapid spread of the novel coronavirus (SARS-CoV-2) has highlighted the need for the development of rapid mitigating responses under conditions of extreme uncertainty. While numerous works have provided projections of the progression of the pandemic, very little work has been focused on its progression in Africa and South Africa, in particular. In this work, we calibrate the susceptible-infected-recovered (SIR) compartmental model to South African data using initial conditions inferred from progression in Hubei, China and Lombardy, Italy. The results suggest two plausible hypotheses - either the COVID-19 pandemic is still at very early stages of progression in South Africa or a combination of prompt mitigating measures, demographics and social factors have resulted in a slowdown in its spread and severity. We further propose pandemic monitoring and health system capacity metrics for assisting decision-makers in evaluating which of the two hypotheses is most probable.