Which Bay Area communities are hardest hit by the Covid-19 pandemic?

December 1, 2020

By Sarah Treuhaft, Eliza McCullough, and Alex Ramiller

In the Bay Area and across the United States, the pandemic has deepened preexisting racial inequities as people of color have been disproportionately exposed to the virus and harmed by its economic fallout. Because neighborhoods are highly segregated by race and income, communities of color often experience the highest rates of infection, becoming pandemic hotspots. While several Bay Area counties provide the ZIP code level data on Covid cases enabling the tracking of these spatial and racial inequities, this information has not yet been compiled into a single map, making it more difficult to identify regional pandemic hotspots and impacted communities.

Our real-time dashboard shows which communities in Alameda, San Francisco, Santa Clara, and Sonoma counties have had the highest rates of infection, revealing the outsized impact of the pandemic on Black and Latinx communities. 

To track the community-level impact of the pandemic, the Bay Area Equity Atlas is launching a new dashboard that provides ZIP code level data on Covid cases from the four Bay Area counties that publish such detailed geographic data: Alameda, San Francisco, Santa Clara, and Sonoma. The dashboard includes a map and scatterplots analyzing cumulative Covid cases in ZIP codes in relation to their share of Black and Latinx residents. The map and scatterplots are dynamically updated each day by pulling and scraping new data from the individual county websites.*

As the scatterplots show, there is a strong association between Covid-19 case rates and the share of Black and Latinx residents. Four ZIP codes have case rates above 4,000 per 100,000 people, with three located in East Oakland (94601, 94603, and 94621) and one in the Bayview/Hunters Point neighborhood in San Francisco (94124). All three of the East Oakland ZIP codes are majority-Latinx, while the Bayview/Hunters Point ZIP code has the largest black population in San Francisco. Other concentrations of COVID cases in these four counties are found in San Francisco’s Mission District, the city of Hayward, downtown and East San Jose, and southern Santa Clara County. 

Examining Covid case rates by the share of residents who are White and Asian or Pacific Islander (API), we found that case rates were strongly negatively associated with the proportion of the population that is White, and weakly associated with the size of the API population. It is important to note that within the large and diverse API community, some groups are experiencing high exposures and case rates. The region’s large Filipino population is highly concentrated in the health care workforce on the frontlines of the pandemic. In Alameda County, Pacific Islanders have the third highest rates after the Latinx and Black population, and statewide, Pacific Islanders have the second-highest case rates in California (after the Latinx population).

Years of discrimination and economic exclusion has made Bay Area communities of color more susceptible to Covid-19. As shown in our Profile of Frontline Workers, Latinx, Black, Filipinx, and immigrant workers are more likely to be in frontline occupations that have a higher risk of exposure. Community testing in the hard-hit Mission District, for example, found that 90 percent of those testing positive were unable to work from home. Workers of color are also overrepresented in low-wage positions that lack access to paid sick and family leave, Personal Protective Equipment, and other workplace safety precautions. Lack of access to health care and testing, and overcrowded housing conditions in the high-cost region also drive higher rates of transmission among people of color.  

While comprehensive ZIP code data is not available for Contra Costa, Marin, Napa, San Mateo, or Solano county, data on case rates in specific neighborhoods reveal hotspots in these counties as well: 

  • In Contra Contra Costa county, working-class San Pablo, where 90 percent of residents are people of color, is the hardest-hit city, followed by Bay Point, where 82 percent of residents are of color.

  • In Marin county, more than half of all cases are concentrated in the Canal neighborhood of San Rafael, home to many low-income Latinx immigrant service workers. The area has a 20 percent positivity rate, about three times the county average. 

  • In San Mateo county, East Palo Alto, where 78 percent of residents are Latinx or Black, currently has the highest case rate among the county’s cities and a positivity rate of 15 percent, far above the county average of 4 percent.

Targeted solutions are needed to address these inequities and protect the low-income communities of color that continue to face the greatest health and economic risks. Free, fast, community-based testing is crucial, yet a San Francisco Chronicle analysis from early summer found lower access to testing in low-income communities of color compared with wealthier, Whiter communities. Residents who test positive for the virus need to be able to quarantine alone; in overcrowded communities this can require providing access to hotel rooms. Essential workers need to be guaranteed safe working conditions, access to paid sick leave and affordable health care, and protections from losing their jobs if they become ill or if they speak out about health conditions. Los Angeles, for example, recently created worker-led public health councils to ensure that employers follow Covid-19 safety guidelines. Moreover, as unemployment benefits expire, federal CARE Act resources run out, and the end of eviction moratoria looms, local governments, philanthropy, and the business community must join forces with community-based organizations to provide rental assistance and other financial supports to prevent eviction and displacement.


* These figures underestimate the total spread of Covid-19; in San Francisco County, for example, reported case counts at the ZIP code level may omit as many as one-third of the reported cases because they cannot be associated with a specific location.