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Coronavirus Risk Assessment Toolkit

View and download complete Coronavirus/COVID-19 Data

BestPlaces has released several data sets to help health professionals and policy makers gain insights into how severely COVID-19 might impact counties, metro areas and states.  BestPlaces has amassed an unparalleled collection of data on every city, town, state, metro area, county and zip code in the U.S. and is sharing their work to fight the Coronavirus.


In creating the Coronavirus Risk Assessment Toolkit (CRAT), the data team at BestPlaces assembled statistics for a variety of health resources and risk factors which can be used in forecasting models, geographic information systems (GIS) or spreadsheets.  The CRAT seamlessly covers the entire United States, with comparable data on all 51 states, 383 metropolitan areas, 3143 counties, and a special table focused on rural counties.

Anyone can view the data set online and copy the data for their own analysis.

Here are the metrics of the Toolkit, which have been identified by the health community as key resources or risk factors affecting the impact of the Coronavirus:

  • Population
  • Hospitals
  • Hospital beds
  • ICU beds
  • Percent of population over 65 years
  • Percent of population over 80 years
  • Percent of population with poor or fair health
  • Percent of population with diabetes
  • Percent of population over with obesity
  • Population density

One important feature of the CRAT is the inclusion of metropolitan area data.  Other data sets have been at the state or county level but this also aggregates data at the metro area.  This is significant because even if there are no hospitals or ICU beds in some of the smaller counties of a metro area, its health resources are commonly available to all residents of the metro.

Each of the geographies is coded with standard Census FIPS codes so the data can easily be combined with other datasets or visualized with any GIS application.  Counties which are part of the 383 U.S. metropolitan areas are tagged with the name and code of its metro area, relating it to the Metro Area table.


This is a valuable resource for a variety of groups:

  • National health officials can use it to identify potential hot spots before they flare up.
  • State and local health officials can compare their locale against areas of known infection, to assess the possible future impact on their region.
  • Policy makers and politicians can gain insights from the statistics which can help them gain better insights into the magnitude of the impact.
  • The media can use the data for stories about the resources available in their area, how local risk factors compare with the rest of the state and nation, and helping to power data-driven journalism.
  • The public is able to do their own assessment, perhaps finding some of their own answers to questions that have been raised by recent waves of Coronavirus news.


Sample data from the Risk Assessment Toolkit


No Risk Index?

One thing that the BestPlaces team is not doing is taking the final step of creating a Coronavirus Risk Index.  To do that, they would assign a level of weighting to each of the risk factors, and this is best done by health experts and scientists.  Assigning a Risk Index for a particular place may have serious repercussions.  A high Risk Index for a county or city could lead to increased fear and anxiety, and a low Risk Index may give a false sense of security.  Accordingly, BestPlaces will leave this calculation of a Risk Index in the hands of the scientific community and policy makers.

However, BestPlaces has used their expertise in ranking and comparing places to create an additional risk assessment scoring model.  In the BestPlaces scoring model, the Coronavirus data has been normalized across the categories to create a set of indexes, and each metric can be assigned a level of importance (weighting).  BestPlaces is making this model available to any group to aid in their work to combat the Coronavirus. Requests for the scoring model may be sent to �crat@bestplaces.net� with �Scoring model� in the subject, and include the name of the organization in the message.


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