Maps of COVID-19 Cases
Tracking where COVID-19 cases and deaths are occurring within San Francisco is incredibly important to understand the impact of the pandemic, identify areas disproportionately affected, and to inform the City's response efforts. City public health officials can use this information, along with other relevant data on vulnerable populations, to direct resources to those most affected.
The two interactive maps below show the distribution of confirmed COVID-19 cases across San Francisco, for different time periods:
- New Cases Map: the distribution of new cases confirmed in the last 30 days
- Cumulative Cases Map: the distribution of all confirmed cases since COVID-19 testing began on March 2nd.
The purpose of these maps is to show how the rate of cases differs across the city; they do not show how case rates are changing over time. For more information about how the virus is spreading in San Francisco, see the average number of new cases confirmed each day, the key public health indicators, and this data set with geographic data of COVID-19 cases over time.
Understanding risk factors and disparities
- Risk Factors: Some risk factors contributing to COVID-19 transmission and severity include living in crowded conditions, being unable to limit outings, being over the age of 60, and having certain preexisting health conditions. Differences in the neighborhood case rates are caused by many factors and do not mean that any area of the city is inherently more or less safe.
- Structural Inequity: Current data show COVID-19 has disproportionately impacted communities of color in San Francisco, California, and across the United States. Structural racism is closely tied to many of the risk factors listed above as structural barriers to homeownership, education, jobs, and health care impact current housing conditions, job opportunities, and many of the social determinants of health.
- Institutional Racism: Another major factor contributing to the disproportionate geographic and racial impact on communities of color is historic discriminatory local, state and federal housing policies, such as redlining and urban renewal.
- Other Factors: Neighborhood trends may also be influenced by other factors like testing availability and the density of congregate housing.
San Francisco offering testing and help
Options for getting tested for COVID-19 are available to everyone in San Francisco, including people with and without health insurance. Learn more about how you can access testing.
San Francisco is offering a variety of resources to support residents, such as childcare for essential workers, help for residents needing access to food, and financial assistance for small businesses. For information about all the resources available, visit sf.gov/coronavirus or call 311.
Continue taking precautions
In order to protect yourself and others around you, continue to follow all health orders and recommendations. These include staying home as much as possible, wearing a face covering whenever you leave your home, and staying at least six feet away from others when going out for essential activities.
New Cases Map
This map shows the rate of new cases that have been confirmed in the past 30 days. Rates are calculated as the number of new cases per 10,000 residents. We calculate rates to be able to compare neighborhoods that have different populations.
This map may not reflect the current prevalence of COVID-19 in San Francisco because some of those diagnosed with COVID-19 in the past 30 days may have already recovered, and others who were diagnosed more than 30 days ago may still be ill.
Data updated daily; read all data notes.
Cumulative Cases Map
This map shows the sum of all cases that have been confirmed in San Francisco since testing began on March 2nd. This does not represent the current prevalence of COVID-19, as many people who were diagnosed with the disease have recovered and are no longer infected.
Data updated daily; read all data notes.
Additional information regarding risk factors and disparities
The spread of COVID-19 is dependent on many factors. This map alone cannot be used to determine why there have been more cases in some areas than others nor predict where additional cases are more likely to be in the future. Differences in the rate of cases do not mean that some areas of the city are more or less safe than others.
Some risk factors contributing to COVID-19 transmission, acquisition, or severity include:
- Living in crowded conditions
- Leaving the house for essential work, or being unable to limit outings
- Being over the age of 60
- Having certain preexisting health conditions
More information on COVID-19 risk factors are available at the Department of Public Health’s Disease Prevention and Control website.
Structural racism is closely tied to many of these risk factors and emerging data indicates communities of color bear a disproportionate burden of COVID-19 disease and death. Learn more about prioritizing vulnerable populations in this recent SF Health Advisory on Prioritizing Populations with Structural Barriers to Health.
Learn more about health disparities in our community in the 2019 San Francisco Community Health Needs Assessment.
In addition, testing plays a crucial role in understanding who has been exposed to the virus and in preventing further spread. Citywide testing capacity and access have been expanding over time. It is important to note that the number of cases in an area is related to the number of residents there who were tested. Likewise, the more we test, the more we expect to see the number of COVID-19 cases increase in San Francisco.
Data updated daily; some cases may not be mapped because of missing addresses
The figures are updated daily, and the rates will change as more individuals are tested; focused testing in any specific area will also greatly influence neighborhood case counts and rates. The number of cases displayed on the map will not add up to the total number of cases in the city because we do not have addresses for all confirmed cases.
Map shading and color categories adjust to group similar neighborhood case rates
Both maps are shaded by case rate and aim to highlight differences in case rates across the City. In order to appropriately shade case rates, we use an algorithmic method called ck-means to divide the distribution of case rates into distinct groups in which the within-group values are the most similar to one another. This means the color groups on the map for both neighborhood and census tracts adjust as the distribution changes over time.
Please refer to the legend as you use the map to see the current ranges and groups of rates.
Certain data suppressed to minimize re-identification of San Francisco residents
For privacy, all neighborhoods or census tracts with resident populations of fewer than 1,000 are excluded from the map. There must be 10 or more cases or deaths in a neighborhood or census tract to report the actual number.
Rates not calculated in areas with fewer than twenty cases
In addition, because of variability in the data, the rate of confirmed cases is not calculated for areas with fewer than twenty cases to avoid inaccurate conclusions about the prevalence of the virus in San Francisco. This is a standard practice to account for something called the Relative Standard Error.
Confirmed COVID-19 deaths compiled from multiple sources
The number of deaths is based on reports to SFDPH from healthcare providers, the Office of the Medical Examiner (OCME), and the California Department of Public Health Vital Records. People who have died with COVID-19 in a non-hospital setting or who were not examined by the OCME also may not have been tested, and they may not be included in the overall number of deaths from COVID-19. For individuals examined by OCME, it may take up to several months to determine the cause and manner of death.
Death counts too low for calculating and mapping rates
Because the number of deaths is low in San Francisco, death rates cannot be accurately calculated or mapped. Death rates will not be mapped unless the number of deaths increases and is large enough to be stable and statistically meaningful.