COVID-19 Safe Return Simulator

COVID-19 Safe Return Simulator combines proven epidemiological modeling methodologies with some of today’s most sophisticated forecasting techniques to predict when communities are projected to be low-risk at a county-by-county level.

• Low-Risk Indicator
  Forecasted low-risk dates project when a particular location is likely to meet a series of key metrics that indicate localized risk has been sufficiently reduced for the impacted population.
  
  
• Rapidly Accounts for Changing Circumstances
  The low-risk date for each location can be updated daily based on publicly available health information and can incorporate proprietary telemetric data that anonymously measures changes in local residents’ social distancing behaviors and their movements within and between counties.
  
  
• Test and Compare Different Scenarios
  Safe Return Simulator can further allow leaders and health officials to game out various potential tactics (e.g., different social distancing recommendations, targeted versus widespread testing, various approaches to contact tracing) to test their likely impacts on predicted low-risk dates.

Confirmed COVID-19 cases, population density, and healthcare system capacity are among the many data points that the simulator leverages to inform its predictions.

Integrated data sources include:

• Centers for Disease Control and Prevention’s Behavioral Risk Factor Surveillance System Selected Metropolitan/Micropolitan Area Risk Trends
• Census Bureau’s American Community Survey results
• Centers for Medicare & Medicaid Services’ Healthcare Cost Report Information System (HCRIS)

COVID-19 Safe Return Simulator is intended to save and improve lives and improve social conditions by providing local, state, and national leaders with the statistically-sound projections they need to make confident, data-driven decisions on how and when to ease COVID-19-related restrictions. A special appreciation to our academic advisors Sam Scarpino of Northeastern University, and John Brownstein of Harvard University, as well as our software partner Mapbox for making this project possible.      

For the most highly tailored, hyperlocal applications, the COVID-19 Safe Return Simulator can be augmented with additional real-time data sources, including:

• Real-time, anonymized telemetry and activity data localized below the county level
• Social media data representing public sentiment regarding compliance to lockdown and containment measures

Its customizable applications range from the municipal to the national, up to and including as support for an evidence-based, nationwide strategy for returning to normalized operations and mitigating future waves of COVID-19 and other infectious diseases.