This report by Mollalo, Vahedi, and Rivera uses GIS-based modeling to create figures that map the disease incidence of COVID-19. The modeling accounted for 35 demographic variables including income levels, environmental conditions, and comorbidities to visually depict the virus’ incidence since 2020. Some important environmental factors that affect the likelihood of contracting COVID are a location’s air quality, temperature and particulate matter. However, the results state that 87.3% of COVID incidence rates are due to factors not accounted for in the given model. Despite this finding, the report offers an important visual model for disease rates in a time of crisis and to better understand the complexity of the virus that involves many facets.