Abstract
The study develops and examines the spatial distribution of the Corona Virus Disease (COVID) on mortality outcomes using a global panel dataset of 79 countries. The empirical evidence is based on Fixed Effect (FE) and System Generalized Method of Moment (SGMM) estimator. The predicted variable is proxy with daily mortality outcomes, while the predictor variable is proxy with spatial COVID spread while controlling for social tension and average temperature. The global and regional findings of the study established that spatial variation in COVID spread had positive and significant relationships with mortality outcomes. Further results also indicate that social tension is a contributing factor to the rising daily mortality outcome from the COVD outbreak, whereas temperature variation reduces mortality outcome. Thus, the study recommends the use of statistical modelling to predict and manage the epidemic. Also, there is an urgent demand to deploy essential social need to the vulnerable proportion of the population to reduce the level of social unrest, while strengthening collaborative research among scientists to develop, produce and distribute vaccines that will put an end to the pandemic.