The Health and Economic Impacts of COVID-19 Interventions

State Policy Evaluation Tool

As of October 1, 2020, this tool is no longer being updated with new data. If you have queries about the tool, please contact

Facing the rapid spread of the coronavirus disease 2019 (COVID-19) pandemic, state and local leaders have taken unprecedented measures to protect their communities, such as closing schools and businesses, banning large gatherings, and placing residents under shelter-at-home orders.

These interventions are having wide-ranging effects on the health, economy, and social well-being of populations. As communities move toward recovery, policymakers face difficult questions about how and when to relax interventions and how to weigh the economic cost of prolonged mitigation measures against the risk of a second wave of the virus.

This tool supports decisionmakers in planning a recovery roadmap by estimating the effects of nonpharmaceutical interventions on health and economic outcomes. The tool also provides qualitative guidance on the efficacy, costs, and potential unintended consequences of a range of interventions.

The tool draws on an epidemiological model and an economic model to estimate effects, based on evidence from past epidemics, peer-reviewed literature, and data from the current pandemic. Data on current impacts are updated daily where available.

Key Findings

States that relax intervention measures in early May can expect to see

  • higher projected cases and deaths by September 1
  • rebounds in patient numbers for hospitals and intensive care units
  • rebounds that come sooner and can be more severe the further restrictions are relaxed
  • greater improvements in the economy the more restrictions are relaxed.

States that relax restrictions from June 1 can expect to see

  • smaller increases in cases and deaths by September 1, compared with opening sooner
  • patient numbers for hospitals and intensive care units rebound later and at lower numbers
  • smaller improvements in economic indicators.

Some states, such as New York, may have passed their highest peaks in active cases and hospitalizations, but for most, the worst is yet to come. Strict social distancing measures can delay this peak but cannot eliminate it without better treatments or a vaccine.

In states with high case numbers, drastically reducing social distancing can increase cases to unmanageable levels. The lag between reopening and the hospitalization spike can make this difficult to observe until it is too late.


This tool combines information from an epidemiological model, an economic model, and a qualitative policy analysis to assess the effects of various nonpharmaceutical interventions (NPIs).

The epidemiological model is a population-based model that divides the population into different clinical stages: susceptible (pre-infection), exposed, infected, and recovered. Data from prior disease outbreaks is combined with emerging data on COVID-19 to generate parameters that capture the flow of disease transmission.

The economic model is a simplified model of each state’s economy that incorporates the relationships across industries, households, and government. The model restricts output in certain sectors to estimate how NPIs are likely to interact with the economy, based on industry estimates or previous literature.

The qualitative assessment of NPIs is based on a policy analysis approach that compares policy alternatives across a set of decision criteria. The assessments are based on a review of the scientific and popular literature from current and past pandemics.

More information about the epidemiological and economic models, and the selection and assessment of non-pharmaceutical interventions, is available in the tool documentation.

Data Sources

Case counts, hospitalization, and fatality counts are from The COVID Tracking Project API.

Data on state interventions are from the COVID-19 US state policy database and the Kaiser Family Foundation.

Unemployment data are from the United States Department of Labor.