COVID-19 (Coronavirus Disease) Outbreak Prediction Using a Susceptible-Exposed-Symptomatic Infected-Recovered-Super Spreaders-Asymptomatic Infected-Deceased-Critical (SEIR-PADC) Dynamic Model

Extension of SIR type models has been reported ina number of publications in the mathematics community. But little is done on validation of these models to fit adequately with multiple clinical data of an infectious disease. In this paper, we introduceSEIR-PAD model to assess susceptible, exposed, infected,recovered, super-spreader, asymptomatic infected, and deceased populations. SEIR-PAD model consists of 7-set of ordinary differential equations with 8 unknown coefficients which aresolved numerically in MATLAB using an optimization algorithm to fit 4-set of COVID-19 clinical data consist of cumulative populations of infected, deceased, recovered, and susceptible.Trends of COVID-19 in Trends in Gulf Cooperation Council(GCC) countries are successfully predicted using available data from the outbreak until 23rd June 2020. Promising results of the SEIRPAD model provide insight into better management of COVID-19pandemic in GCC countries