UC Berkeley’s Othering & Belonging Institute launched an interactive map of California on March 28 displaying consolidated information on coronavirus cases and other community factors.
Created by Othering & Belonging Institute researcher Arthur Gailes, the map compiles individual pieces of preexisting information from sources including the census and the New York Times. Othering & Belonging Institute researcher Samir Gambhir has also contributed to the map through data collection.
“We wanted to combine direct COVID-19 information with overlaid data that concern communities that were likely to be disproportionately harmed,” Gailes said. “Not just by the virus, but also by the downstream economic health.”
These data include each county’s number of hospital beds per 1,000 people, percentage of at-risk communities and percentage of overcrowded households. The map also displays the Centers for Disease Control and Prevention’s social vulnerability percentage, which is calculated based on indicators of socioeconomic status, household composition and disability status, among others.
According to Gailes, the map was created to compensate for the lack of focus on concerns surrounding marginalized communities. With the map, Gailes hopes to promote principles such as equitable distribution of resources that align with the Othering and Belonging Institute’s mission.
Gailes added that the map has also become important for governmental groups and charitable organizations that have contacted them for particular information. This information may assist the groups in allocating resources to those in need, according to Gailes.
Another important aspect of the map is that it works to identify communities that are underserved and address these inequities, according to Gailes. Such data include the percentage of seniors living in certain counties as well as students using the free and reduced-price meals program.
“We focus on helping people and drawing more attention to communities who may be disadvantaged,” Gailes said.
The map also provides data on the air pollution of each county. According to Gailes, air pollution has been shown to substantially increase the fatality rate from COVID-19 in China. While researchers are cautious when claiming correlations, the compiled data can potentially aid researchers in the future.
The research team is looking to add more indicators to the map in the future while also seeking to add a way to combine the indicators to understand intersections between different indicators and populations. Gailes noted that this could include a deeper look into certain communities that have limited access to information to try to understand where people may be lacking critical information.
“We’re working on the correlations between different indicators,” Gailes said. “We’re looking to add value into drawing off research that’s been done into areas that have been found separately to correlate with either the virus or communities affected by it and then display it in our map.”