Abstract: The technology disclosed relates to a system and method for predicting chronic disease outcome for census tract-level communities at risk for COVID-19 related complications. The system can access satellite image data of built environment for census tract-level communities and merge the image data with respective chronic disease prevalence data per census tract-level community. This merging of image data with chronic disease prevalence data results in a high-dimensional image space. The system includes logic to identify principal components forming a basis of the high-dimensional image space. A subset of the principal components is selected that cumulatively explain at least fifty percent of the explained variance. The system includes logic to calculate COVID-19 risk score as a weighted combination of the selected principal components. The COVID-19 risk score is provided to public health policy decision makers for use in public health policy decisions.