Toward on Develop a Framework for Diagnosing Novel-COVID-19 Symptoms Using Decision Support Methods

A novel coronavirus disease is considered the most dangerous epidemic spread in the world recently. The world health organization (WHO) has named this epidemic a novel COVID-19. According to the literature review, the most important symptoms that confirm the infection with this epidemic are high temperature, coughing, shortness of breath, and chest pain. In general, these symptoms have become the actual cause of most deaths for people who have the novel COVID-19 epidemic. These symptoms adopted in this study as essential criteria. The conflict between criteria formatted a challenge in this study. This paper aims to propose a framework for diagnosing the disease symptoms based on multiple criteria using an analytical hierarchy process (AHP) method. Therefore, decision support methods most suitable to solve various criteria problems. The results reported the most important criterion at the mean (0.407) and +/- SD (0.166) for the fever. The least important criterion of the chest pain at the mean (0.116) and +/- SD (0.070). While the cough criterion at the mean (0.254) and +/- SD (0.099) and the shortness of breath criterion at the mean (0.223) and +/- SD (0.127), respectively. This study presented an optimal framework for physicians to immediately diagnose coronavirus symptoms for the person with this disease.