Early epidemiological studies of the coronavirus outbreak in Hubei Province, China, where it originated, demonstrated the overwhelming importance of slowing the rate of transmission in the overall success of reducing the spread of COVID-19. Slowing the rate of transmission, however, requires information about who is infected and where they are on a daily basis, and in high geographical resolution.
While efforts are underway around the world to ramp up testing capacity for the novel coronavirus, technology-driven approaches to collect self-reported information can fill an immediate need and complement official diagnostic results.
The anonymous, voluntary collection of information concerning individuals’ health status over time—which can be integrated with other relevant real-time data resources, such as meteorological data, population density at a given time and place, and other dynamic data sources—can provide crucial information that can be immediately leveraged for early identification of disease clusters and will enable researchers to predict, respond to, and learn about the spread of coronavirus.
The Coronavirus Census Collective is an international consortium that will serve as a hub for aggregating this type of data and will provide a unified platform for global epidemiological data collection and analysis.