Machine Learning-Based Prediction of Covid-19 Risk Score for Census Tract-Level Communities

A system including one or more processors coupled to memory, the memory loaded with computer instructions to predict chronic disease outcome for census tract-level communities at risk for COVID-19 related complications, the instructions, when executed on the processors, implement actions comprising:

• accessing satellite image data of built environment for census tract-level communities;
• merging the image data for census tract-level communities with respective chronic disease prevalence data per census tract-level community for a plurality of chronic diseases resulting in merged image data in high-dimensional image space;
• identifying principal components forming a basis of the high-dimensional image space wherein an image in the high-dimensional image space is represented as a linear combination of the principal components;
• selecting a subset of the principal components to project the high-dimensional merged image data to a low-dimensional feature subspace by selecting a subset of the principal components that cumulatively describe at least fifty percent of explained variance wherein the explained variance indicates how much information can be attributed to a principal component;
• calculating a COVID-19 risk score for census tract-level communities as a weighted combination of the selected subset of principal components, wherein the COVID-19 risk score predicts risk for COVID-19 related complications as a function of chronic disease outcome;
• and
• providing the COVID-19 risk score to a public health policy decision maker for use in public health policy decisions for census tract-level communities.