• S P Silal, M J Groome, N Govender, J R C Pulliam, O P Ramadan, A Puren, W Jassat, E Leonard, H Moultrie, K G Meyer-Rath, W Ramkrishna, T Langa, T Furumele, D Moonasar, C Cohen, and S Walaza.
• Modelling and Simulation Hub, Africa (MASHA), Department of Statistical Sciences, University of Cape Town, South Africa.
• S. Afr. Med. J. 2022 May 31; 112 (5b): 361365361-365.

AbstractBy May 2021, South Africa (SA) had experienced two 'waves' of COVID-19 infections, with an initial peak of infections reached in July 2020, followed by a larger peak of infections in January 2021. Public health decisions rely on accurate and timely disease surveillance and epidemiological analyses, and accessibility of data at all levels of government is critical to inform stakeholders to respond effectively. In this paper, we describe the adaptation, development and operation of epidemiological surveillance and modelling systems in SA in response to the COVID-19 epidemic, including data systems for monitoring laboratory-confirmed COVID-19 cases, hospitalisations, mortality and recoveries at a national and provincial level, and how these systems were used to inform modelling projections and public health decisions. Detailed descriptions on the characteristics and completeness of individual datasets are not provided in this paper. Rapid development of robust data systems was necessary to support the response to the SA COVID-19 epidemic. These systems produced data streams that were used in decision-making at all levels of government. While much progress was made in producing epidemiological data, challenges remain to be overcome to address gaps to better prepare for future waves of COVID-19 and other health emergencies.

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