Maps of testing data help us to track neighborhood trends and disparities. We use this information to inform our testing strategy and outreach efforts.
To create testing maps, we first map every test to the home address of the person tested. This page includes all tests where a patient listed a San Francisco home address.
These maps include tests collected by all medical providers. This includes tests provided by the City and private medical providers (like Kaiser, One Medical, or Sutter).
Testing rate by neighborhood
Testing rates help us compare which neighborhoods have had the most residents tested. Rates take into account how many residents live in the neighborhood.
The neighborhood rate is the number of tests collected from that neighborhood’s residents divided by the total number of residents.
Darker blue neighborhoods have more tests per person. This means people who live in the darker blue neighborhoods were more likely to get tested. In light yellow neighborhoods, fewer residents have gotten tested.
Data notes and sources
Data notes and sources
Tests shown on this dashboard include tests collected in the last 2 months. Patient home addresses are geo-located and then mapped to analysis neighborhoods. The home address associated with each test is hand-entered and susceptible to errors. This means neighborhood data is an approximation, not a precise nor comprehensive total.
About 5% of tests are missing addresses. These tests are not included on the maps nor the dataset.
Testing rate = (all tests / residents) * 1,000
The testing rate is the total count of tests collected per 1,000 residents. The total count of tests includes positive, negative, and indeterminate test results.
We do not calculate the testing rate for areas with fewer than 20 total tests. Rates of small test counts are less reliable. These areas are shown in light grey.
San Francisco population estimates are from the 2020 5-year American Community Survey.
Tests for skilled nursing facility residents are not included in this data. Skilled nursing facilities administered a large number of tests because of they were required to repeatedly test their residents. This would change neighborhood trends and not reflect the broader neighborhood's testing data.
Tests are de-duplicated by individual and date. If a person gets tested several times on different dates, all tests will be in this data as individual tests.
Privacy protections
We do not share testing data for neighborhoods with small populations (less than 1,000 people). These neighborhoods include Golden Gate Park, John McLaren Park, and Lands End. This is in alignment with the City's privacy policy.
Test positivity rate by neighborhood
The neighborhood test positivity is the percent of tests with a positive result. We first add up all the positive tests for residents in a specific neighborhood. We then divide that by total tests of residents in that neighborhood.
Darker orange neighborhoods have had higher test positivity. This means residents were more likely to get a positive result. In lighter yellow neighborhoods, fewer residents got a positive result.
Neighborhoods not shown on the map did not have 20 positive tests in the past 2 months. We only calculate test positivity rates when there have been 20 positive tests in the last 2 months.
Data notes and sources
Data notes and sources
Tests shown on this dashboard include tests collected in the last 2 months. Patient addresses are mapped to analysis neighborhoods. The resident address associated with each test is hand-entered and susceptible to errors. This means neighborhood data is an approximation, not a precise nor comprehensive total.
Tests that are missing addresses are not included on the maps nor the dataset.
Test positivity rate = (positive tests) / (positive + negative tests)
The test positivity rate is the percentage of tests that have a positive result for COVID-19. Test positivity does not include indeterminate tests. The positivity rate is not calculated for areas with fewer than 20 positive tests. Rates of small test counts are less reliable.
Tests for skilled nursing facility residents are not included in this data. Skilled nursing facilities have required and repeated testing of residents. This would change neighborhood trends and not reflect the broader neighborhood's testing data.
Tests are de-duplicated by individual and date. If a person gets tested several times on different dates, all tests will be in this data as individual tests.
Privacy protections
We do not share testing data for neighborhoods with small populations (less than 1,000 people). These neighborhoods include Golden Gate Park, John McLaren Park, and Lands End. This is in alignment with the City's privacy policy.
Positive test ≠ new case
The total number of positive tests is not equal to the total number of new cases. The City verifies each positive test result. During this verification, some positive tests may not represent a new case. For example:
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If one person tested positive several times, that represents only one case
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During interviews, we could find that a test is for a person living outside of San Francisco
Testing data by neighborhood over time
These neighborhood trends change over time. We track testing data over time so that the City can adapt its testing strategy. These charts show how the test positivity and the testing rate change over time.
Choose a neighborhood from the list to see that neighborhood's trends.
Data notes and sources
Data notes and sources
Patient addresses are mapped to analysis neighborhoods. The resident address associated with each test is hand-entered and susceptible to errors. This means neighborhood data is an approximation, not a precise nor comprehensive total.
About 5% of tests are missing addresses. These tests are not included on the maps nor the dataset.
The test positivity rate is the percentage of tests that have a positive result for COVID-19. Test positivity does not include indeterminate tests. The test positivity rate is not calculated for areas with fewer than 20 positive tests. Rates of small test counts are less reliable. These areas are light grey.
The testing rate is the total count of tests collected per 1,000 residents. The total tests includes positive, negative, and indeterminate test results.
Tests for skilled nursing facility residents are not included in this data. Skilled nursing facilities have required and repeated testing of residents. This would change neighborhood trends and not reflect the broader neighborhood's testing data.
Tests are de-duplicated by individual and date. If a person gets tested several times on different dates, all tests will be in this data as individual tests.
Privacy protections
We do not share testing data for neighborhoods with small populations (less than 1,000 people). These neighborhoods include Golden Gate Park, John McLaren Park, and Lands End. This is in alignment with the City's privacy policy.
Positive test ≠ new case
The total number of positive tests is not equal to the total number of new cases. The City verifies each positive test result. During this verification, some positive tests may not represent a new case. For example:
-
If one person tested positive several times, that represents only one case
-
During interviews, we could find that a test is for a person living outside of San Francisco
Increasing testing in communities most harmed
COVID-19 has harmed communities of color more than other groups. Structural racism is closely tied to these inequities. Learn more about COVID-19 disparities and inequities.
Areas with high test positivity rates and low testing rates are our top priorities. We are working to increase testing rates in these communities.
City strategies
Testing data and maps enable San Francisco to address health and socioeconomic inequities. The City has deployed resources in areas with higher test positivity.
We partner with communities to create testing events, alternate test sites, and community "pop-up" sites.
We work with community partners to launch culturally responsive outreach and media. See testing resources in English, Spanish, Chinese and Filipino.
We also collaborate with private providers. Many tests are collected by private providers (like Kaiser, One Medical, or Sutter). We work with private providers to ensure everyone extends testing to priority communities.
We will continue to use data and feedback to adapt our strategies.