The goal of this project is to develop mobile applications, data integrations, and validated machine learning algorithms to identify COVID-19 and differentiate it from the flu, and to perform contact tracing using Wi-Fi technologies. Vibrent Health will accomplish this goal by enhancing their Vibrent Digital Health Solutions Platform (DHSP) implementation to large-scale pilot populations among diverse user groups. The project will focus on validating the technology’s performance, usability, and reliability in refinement of analytics to generate predictive algorithms for infection. The platform is intended to support individual, organizational, community, and societal-level decision-making in the COVID-19 pandemic response. The first objective involves innovation to develop a technology that can differentiate between COVID-19 and flu (or other respiratory illness). The second objective involves the development and testing of a Wi-Fi-based contact tracing tool using George Mason University’s enterprise Wi-Fi system. The third objective involves the development of a full technical integration approach and strategy to support data exchange. Data collected under this project will be deidentified and securely transmitted to an NIH data hub.