The utility of 2009 H1N1 pandemic data in understanding the transmission potential and estimating the burden of COVID-19 in South Africa to guide mitigation strategies

The coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome coronavirus (SARS-CoV-2) rapidly became a public health emergency of international concern requiring urgent attention. It emerged late in 2019 in China as a respiratory pathogen, with the first epicentres observed in Iran, Spain and northern Italy. At the time of writing there were about 4 525 497 cases and 307 395 deaths worldwide, of which 1 409 452 cases and 85 860 deaths were in the USA, which is the most affected country in absolute terms.[1] The COVID-19 pandemic has been marked by extreme heterogeneity in both geography and population across the world. Consequently, leveraging local data aligned to the unique South African (SA) context is critical. Moreover, comprehensive mathematical models should integrate the full complexity of transmission dynamics observed with COVID-19 in the context of rapidly changing individual, social and structural determinants in S