Consumer Spending as a Predictor for COVID-19

Abstract

We conducted this research study in hopes of finding a correlation between consumer spending in various retail sectors and the sum of new COVID-19 cases in the United States. We used the random decision tree model, a data mining tool that compares different factors and determines the importance they have in predicting an outcome (or target), to find connections in our data. The results of this study can be used by businesses or governments to see where consumer sentiment is shifting and how they can adapt their business or political strategies in the case of future pandemics or other extraordinary worldwide events.