The goal of this proposal is to develop a COVID-19 detection algorithm based on self-report survey data and wearable sensor data. Data from 25K COVID-19 Experiences participants and 25K Large-scale Flu Surveillance (COVID-19 Questions added March 2020) will be used with an existing machine learning model to develop this new detection algorithm, which will be validated in a large-scale pilot population to identify individuals with undiagnosed COVID-19. Evidation will incorporate the model into an established web and multi-platform (Android, iOS) smartphone platform called Achieve which allows users to share person-generated health data (PGD) from their everyday lives. Data collected under this project will be deidentified and securely transmitted to an NIH data hub.