Rapid implementation of mobile technology for real-time epidemiology of COVID-19

David A. Drew; Long H. Nguyen; Claire J. Steves; Jonathan Wolf; Tim D. Spector; Andrew T. Chan

With additional data collection, we will apply machine learning and other big-data approaches to identify novel patterns that emerge in dynamic settings of exposure, onset of 5 symptoms, disease trajectory, and clinical outcomes. Our launch of the app within several large epidemiology cohorts that have previously gathered longitudinal data on lifestyle, diet and health factors and genetic information will allow investigation of a much broader range of putative risk factors to COVID-19 outcomes. With additional follow-up, we will also be uniquely positioned to investigate long-term outcomes of COVID-19, including mental health, disability, mortality, COVID-19's effects beyond infection, including work hazards from PPE shortages, emotional stress, and absenteeism. Real-time data generation focused within these populations will be critical to optimally allocate resources to protect our healthcare workforce and assess their efficacy.