Predictive Models for Mitigating COVID-19 Outbreak

摘要

Reportedly starting in Wuhan, China in 2019, the Corona virus 2019 (Covid-19) is a pandemic that has hit many countries of the world. Globally the number of infections and death cases have been on the rise and Africa is no exception. As of May 2020, South Africa had been the most affected country in Africa with Cape Town being the pandemic's epicentre. Preempting the pandemic rather than attempting to cure infected patients is very crucial to Africa, considering its poorer healthcare system compared to developed countries, which have struggled to curtain the ravaging pandemic despite the advanced state of their healthcare systems. This paper proposes two models that i) validate the proposed protective measures using epidemic modelling; ii) pre-empt the evolution of the pandemic through data analytics. The first model builds around the classic SIR model to simulate the main protective measures suggested by the World Health Organisation; while the second built on regression models to predict future confirmed cases. Real Covid-19 data of the city of Cape Town were used for the simulations and results reveal the accuracy of the models and the relevance of combining simulation modelling and data analytics as relevant tools in the fight against the pandemic.