COVID-19 population characteristics

San Francisco COVID-19 death data by demographics.

Race or ethnicity

COVID-19 has harmed communities of color more than other groups. This is a result of institutionalized racism and structural inequities. There is no biological or genetic difference in COVID-19 risk by race. In general, people of different races engage in the same prevention measures.

This dashboard shows a comparison of COVID-19 deaths by race or ethnicity to the San Francisco population. If all race or ethnicity groups were impacted at the same rate, the percent of deaths would equal the population percentage. When a race or ethnicity group represents a higher percent of deaths than the population then they are more affected.

Data notes and sources

Data notes and sources

Deaths data source

San Francisco population estimates are from the 2020 5-year American Community Survey.

COVID-19 deaths among individuals who identified as "Other" or “Multi-racial” are not shown on this dashboard. These categories do not align with the American Community Survey definitions. This means we cannot compare deaths to the population. They are included in the public dataset. 

COVID-19 deaths missing race or ethnicity data are not shown in the dashboard. They are included in the public dataset.

City Response  

Advancing racial equity is one of the City's core values. Read more on the San Francisco Office of Racial Equity’s webpage.  

There has been an enormous effort to bring resources to the communities most harmed. Many of these efforts have been community-led. The City is proud to work alongside community partners in this work. For example, we: 

  • Collaborated with the Latino Task Force 

  • Partnered with community on the City’s testing strategy 

  • Supported Black-owned businesses with access to financial capital and zero-interest loans 

  • Partnered with community organizations on vaccine access programs 

  • Funded equity and neighborhood initiatives through our COVID Command Center  


This dashboard shows the number of COVID-19 deaths by gender.

Data notes and sources

Data notes and sources

Deaths data source

We collect information on gender identity using these guidelines

Learn about California's mandate that all counties report this data. 

Certain social factors that correlate with gender identity may contribute to COVID-19 risk. Learn more about this at the GenderSci Lab COVID Project.  

Tracking COVID-19 among transgender and gender nonconforming residents is a top priority. These residents may be particularly vulnerable because of structural inequities and other factors. We continue to work to ensure that these residents have access to the testing, resources, and support they may need. Learn more about transgender community services. 


COVID-19 deaths have been concentrated among older San Francisco residents.

Data notes and sources

Data notes and sources

Deaths data source

San Francisco population estimates are from the 2020 5-year American Community Survey.

Data limitations

Data on the population characteristics of COVID-19 deaths are from: 

  • Case reports

  • Medical records

  • Electronic lab reports

  • Death certificates

This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. 

Cumulative totals on this page include all deaths confirmed in San Francisco since testing began in late February 2020. 

To protect resident privacy, we summarize COVID-19 data by only one characteristic at a time. Data are not shown until cumulative citywide deaths reach five or more.

This data may undercount certain minorities. Residents who face stigma or discrimination in medical settings may not want to share some information. For example, stigma could result in a patient not sharing their gender identity. There are health inequities and barriers to healthcare for non-cisgender and non-heterosexual people.

The spread and severity of COVID-19 is complex. It has affected residents based on overlapping layers of structural inequities. This means that there may be intersections of populations who are particularly affected. For example, essential workers in a specific age group of a specific ethnicity. For this reason, you should interpret this data in context. Individual conclusions should be treated with caution.