Clinical decision support system for the early diagnosis and management of COVID-19

Having a tool that can figure out the likelihood of contracted severe acute respiratory syndrome (SARS-CoV-2) COVID-19 to combat its spread will be a considerable step to slow the speed of the virus. Therefore, we describe a series of steps to analyse data from the New York State Government Health and New Jersey using SAS and Python. First, focusing on counties bordering each state using variables such as individual social-economic, gender, age group to determine the likelihood of getting the SARS-CoV-2 COVID-19. Furthermore, we created a clinical decision support system (CDSS) interface to collect data and analyse them better to understand this virus.