Forecasting the Impacts of Weather and Social Distancing on COVID-19 Transmission Across the U.S.

Statement of Problem

As the nation mobilizes to respond to the once-in-a-century challenge of the COVID-19 pandemic, there is an urgent need to project how the virus will spread in the coming months. This information is critical to help local, state, and federal leadership make informed decisions about public policy solutions to manage the crisis.

To respond to the pandemic, society largely shut down through a variety of social distancing interventions that varied in magnitude and timing, and were designed to help slow the rate of infection, or flatten the curve. Flattening the curve was essential to prevent overwhelming health care systems, particularly with increased demands for ICU beds and ventilators, as well as to improve access to rapid and serologic testing for public health surveillance.

As the pandemic spreads in varied ways among our cities, it will be critical to provide more robust and reliable data models to guide decision-making about when and how to relax social distancing interventions in a way that allows Americans to safely transition back to work and school.

Description

Forecasting the Impacts of Weather and Social Distancing on COVID-19 Transmission Across the U.S.

Our interdisciplinary team across Children’s Hospital of Philadelphia and the University of Pennsylvania is using local data to provide short-term forecasts based on current social distancing practices.

Our interdisciplinary team from Children’s Hospital of Philadelphia and the University of Pennsylvania is using actual case data to longitudinally project, in real-time, the epidemic across 747 counties with active outbreaks as it spreads across the United States.

Other COVID-19 models project the disease’s impact across states/large areas, but our model focuses more locally by forecasting the spread of COVID-19 within counties, still capturing 80% of the U.S. population and all 50 states plus Washington D.C. The 747 counties include those with state capitals, populations of 40,000 individuals or more (with a minimum population density of 250 people per square mile), and sustained outbreaks, which we define further in this abstract.

Through this model, we are accounting for the impact of weather, health and demographics of the population and city characteristics in order to: define the influence of temperature and humidity on SARS-CoV-2 transmission; determine the impact of social distancing in modifying the trajectory of SARS-CoV-2 transmission during current and future outbreaks; investigate how city characteristics modify the transmission; and forecast the effects of policy change and social distancing practices on the risk for virus resurgence.

The data and methodology behind this modeling project was informed by a peer-reviewed study, published in JAMA Network Open, confirming social distancing as the most effective intervention against COVID-19. When observing how time-varying factors, such as weather and social distancing, impacted COVID-19 transmission risk at the county level between February 25 and April 23, 2020, we found that spring-like temperatures contributed to some reduction in the spread of the virus, but without strong social distancing practices, the beneficial impact of temperature was not fully realized.

Data from the latest updates to the model, released on July 29, show concerning signals that some of the largest U.S. cities, which have seen relatively low case counts since the spring, could begin seeing dramatic virus resurgence in the absence of further mitigation. Additionally, we updated modeled scenarios the week of July 13 that reflect how varying degrees of tightening distancing and occupancy policies and implementing universal masking in 158 of our largest counties could impact case counts as we head into fall, scenarios originally prepared for the White House Coronavirus Task Force. To view a data visualization of our findings, click here, to learn how we validate this model to ensure accurate projections, click here, and to learn more about the methods of this model, see this abstract.

Next Steps

Using this real-time data, we are engaging with local, state, and federal policymakers who are managing the COVID-19 response to support their efforts. We aim to inform a safe approach to reopening society that also accounts for the economic and social impacts shelter-in-place strategies are having on low-income families and communities.

For more on PolicyLab's COVID-19 response, click here.

This project page was last updated in July 2020.

Suggested Citation

Children's Hospital of Philadelphia, PolicyLab. Forecasting the Impacts of Weather and Social Distancing on COVID-19 Transmission Across the U.S. [Online]. Available at: http://www.policylab.chop.edu. [Accessed: plug in date accessed here].