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

The exponentially increasing number of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections has led to "an urgent need to expand public health activities to elucidate the epidemiology of the novel virus and characterize it's potential impact." (1) Understanding risk factors for infection and predictors of subsequent outcomes is critical to gain 5 control of the coronavirus disease 2019 (COVID-19) pandemic (2). However, the speed at which the pandemic is unfolding poses an unprecedented challenge to collecting exposure data characterizing the full breadth of disease severity, hampering efforts to disseminate accurate information in a timely manner to impact public health planning and clinical management. Thus, there is an urgent need for an adaptable real-time data-capture platform to rapidly and 10 prospectively collect actionable high-quality data that encompasses the spectrum of subclinical and acute presentations while identifying disparities in diagnosis, treatment, and clinical outcomes. Addressing this priority will allow for more accurate estimates of disease incidence, inform risk mitigation strategies, more effectively allocate still-scarce testing resources, and allow for appropriate quarantine and treatment of those afflicted. 15 An evolving body of literature suggests COVID-19 incidence and outcomes vary according to age, sex, race/ethnicity, and underlying health status, with inconsistent evidence suggesting that commonly used medications such as angiotensin-converting enzyme (ACE) inhibitors, thiazolidinediones (TZD), and ibuprofen may alter the natural disease course(3-9).