With COVID-19 still increasing in many communities across the United States, government officials are looking for ways to get ahead of the virus—often inviting innovative approaches. The newly launched Regulation, Evaluation, and Governance Lab (RegLab) at Stanford recently answered a request by the Detroit Health Department to help improve tracking of COVID-19 during the health crisis. Detroit was deploying its investigative resources to high-risk locations, like licensed nursing and elderly care facilities, but knew that its list was incomplete. RegLab, directed by Daniel Ho, William Benjamin Scott and Luna M. Scott Professor of Law, helped to augment the city’s list of buildings with vulnerable populations to prioritize public health investigations.
Scanning available data sources that could be deployed quickly, the RegLab team settled on voter registration files as a less restrictive and more efficient alternative to others, such as census and CDC data. The list enabled the team to quickly generate a list of large buildings with high densities of seniors who are more vulnerable to the virus.
“By using administrative data, Detroit might improve the effectiveness of its approach more than fivefold, holding the investigative resources constant,” according to Ho and two JD/PhD students, Mark Krass and Peter Henderson, who jointly posted a piece about the project for the blog Health Affairs. “We deployed this approach because it is fast, at a time when speed is required to compete with the spread of COVID-19, and could generate significant improvements in allocating scarce public health resources.” Ho added, “This type of fast and effective work will have many applications as governments think hard about how to reopen our economies intelligently.”