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Harvard Researchers Create First County-Level Nationwide COVID-19 Policy Dataset

Harvard Medical School's Gordon Hall sits across the HMS quadrangle.
Harvard Medical School's Gordon Hall sits across the HMS quadrangle. By Justin C. Wong
By Ethan Lee, Crimson Staff Writer

Harvard researchers have released the first county-level map showing nationwide data on policies established to combat the spread of COVID-19.

The dataset illustrates the presence of seven different types of COVID-19 policies across more than 1,200 U.S. counties and federally recognized Native American nations.

Roughly 80 volunteers from Harvard and other institutions crowdsourced the dataset, organized at healthcare nonprofit Hikma Health. Cray V. Noah, a Harvard Medical School student and project organizer, said the complex nature of the data collection made the large number of volunteers crucial to the project’s success.

“You can't automate it – you can't have a bot go through and get this kind of data for you, just because there's so much variation from county to county,” Noah said. “So it actually takes a human to go look through, decipher, discern, and figure out what policies a given county actually has in place.”

Noah said his team has already made new discoveries through mathematical models based on the dataset, and project organizers expect it will prove useful for many COVID-19 researchers.

“The preliminary results have shown a couple things,” Noah said. “There's actually just as much intrastate variation in a lot of these COVID policies as interstate. And so that kind of highlights the fact that this more granular data is really important because the demographics and the culture and everything from county to county is so different.”

Noah said the interactive and accessible nature of the map will also make it an asset for users without medical or statistical backgrounds

“Someone maybe without an epidemiology or scientific background can go in and click around on these counties and see the raw data themselves,” Noah said. “A lot of times people are just seeing someone’s spin on data, but this, they can actually go in and see the raw data, the policies, the timestamps on the policies, and the way that the COVID infection rate was affected.”

Next steps the team plans to undertake include releasing its dataset crowdsourcing protocol so others can take similar approaches to gather information on COVID-19, Noah said.

“I think we definitely are at the point now where we will be doing our own mathematical analyses and modeling,” Noah said. “We'll also be publishing this protocol, this crowdsourcing protocol we used, so everyone can see how it was done. At the very least, those are two tangible things that will come out of this for us personally. And then the big hope is that this dataset finds its way into the hands of influential modelers and researchers.”

—Staff writer Ethan Lee can be reached at

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