The aim of this study is to develop a proof-of-concept framework for predicting changes in employment and income based on data-driven models of daily consumer product sales. For this purpose, we develop a data-driven approach for extracting spatial and temporal patterns of consumer demand changes, based on historic Nielsen product sales data. Although the available database is limited to data through 2018, the assessment of previous disaster events in Florida, such as tropical cyclones or the Deepwater Horizon oil spill, will provide a “proof-of-concept” for applying such methods to assess the impacts of the COVID-19 pandemic or future disaster events. The ability to produce more accurate predictions of near-term changes in demand for specific classes of products will allow for better estimation of sector level employment and income changes resulting from disaster events, which can inform disaster response efforts. To learn more, click here to read story.