Modelling spatial variations of coronavirus disease (COVID-19) in Africa

Abstract

Clinical and epidemiological evidence has been advanced for human-to-human transmission of the novel coronavirus rampaging the world since late 2019. Outliers in the human-to-human transmission are yet to be explored. In this study, we examined the spatial density and leaned statistical credence to the global debate. We constructed spatial variations of clusters that examined the nexus between COVID-19 attributable deaths and confirmed cases. We rely on publicly available data on confirmed cases and death across Africa to unravel the unobserved factors, that could be responsible for the spread of COVID-19. We relied on the dynamic system generalised method of moment estimation procedure and found a ~0.045 Covid19 deaths as a result of confirmed cases in Africa. We accounted for cross-sectional dependence and found a basis for the strict orthogonal relationship. Policy measures were discussed.