Modelling the global prevalence of COVID-19: evidence from multiple wave scenarios

Nearly all economies of the world suffered from the sudden outbreak of the coronavirus pandemic that originated from the Wuhan City of China. In this study, with the aid of the OLS estimator, we uncovered the socio-economic conditions that drove the prevalence of COVID-19 across four continents: Africa, Asia, America and Europe, covering three sub-sample periods of the first wave, second wave and vaccine roll-out. While the only significant and positive driver of the pandemic across continents is life expectancy, higher healthcare spending is prevalence reducing. We also established the prevalence impacts of out-of-pocket spending, net migration, distance and international arrivals for Africa, America, Asia and Europe, respectively. We, finally, obtained forecast graphs for the six predictive models per continent, and our results showed that both the linear and nonlinear specifications are best fit predictive models, particularly for the vaccine roll-out era. We suggest useful policy options.