The pandemic has shed light on societal disparities and economic inequalities. We are undertaking extensive analysis and drawing data-driven insights on how the pandemic is disproportionately affecting marginalized and underserved communities. We are assessing the relationship between socioeconomic variables and the epidemiological profiling of COVID-19 including case, death, and recovery rates on zip-code, county, state, and nation-wide level through statistical testing and modelling. This has enabled us to understand the distribution of spread and impact across geographies on a local district level to a country wide level. Through methodologies such as feature extraction and cluster analyses we are able to understand the inherent correlations between socioeconomic variables so we can model appropriately.

Our team has also computed and visualized aggregate risk scores for specific counties based on the socioeconomic variables, population density, and testing rate so we can inform, or rather, assist policy makers and higher officials in their prioritization and allocation of resources.