Led by PISC Senior Scholar Mary Regina Boland, MA, PhD, this study used informatics approaches to better understand the role of individual and community risk factors for COVID-19. In particular, it developed a method to integrate COVID-19 data with multiple neighborhood-level factors from the American Community Survey and opendataphilly.org, after which it assessed the spatial association between neighborhood-level factors and the frequency of COVID-19 positivity. The study found that more Hispanic/Latinx neighborhoods and neighborhoods with a higher percentage of high school graduates were more likely to have higher COVID-19 rates, while more White neighborhoods were less likely. With these results, the study was able to demonstrate the effectiveness of informatics-based approaches in informing future public health efforts.