Title: Dealing with uncertainty; Systems dynamics approach for modelling South Africa response to COVID-19

Abstract

Many countries in the world are still struggling to control the COVID-19 pandemic. In Sub-Sahara Africa, South Africa has reported the highest number of COVID-19 infections. The country took aggressive steps to control the spread of virus including setting a national command team for COVID-19 and putting the country on a complete lockdown for more than 100 days. Evidence across most countries have shown that, it is vital to monitor the progression pandemics and assess the effects of various public health measures, such as lockdown on mass gatherings. Countries need to have scientific tools to assist in the monitoring and assessment of effectiveness of mitigation interventions. This study presents a systems dynamic model of the COVID-19 infection in South Africa, as one of such tools. The key purpose of developing the model was to assess the extent a system dynamics model can forecast the COVID-19 infections in South Africa and be a useful tool in evaluating government interventions to manage the epidemics through ‘what if’ simulations. Our model simulation shows progression and upsurge in infections with the peak being anticipated to be in the last quarter of the Year 2020. The model satisfactorily depict the general trend of COVID infections and recovery for South Africa which is in sync with the actual recorded data within the first 100 Days since the recorded first case of infection. The current presented model provides evidence to suggest that systems dynamics can be a useful tool in monitoring pandemics such as COVID-19 despite the limitation of predicting these with a lower margin of error. It provides a foundation for further development taking into account more factors or parameters that emerge for the volatile and uncertain spread of pandemics such as the first ever COVID-19 epidemic.