A. SUMMARY
Medical provider confirmed COVID-19 cases and confirmed COVID-19 related deaths in San Francisco, CA aggregated by Census ZIP Code Tabulation Areas and normalized by 2018 American Community Survey (ACS) 5-year estimates for population data to calculate rate per 10,000 residents.

Cases and deaths are both mapped to the residence of the individual, not to where they were infected or died. For example, if one was infected in San Francisco at work but lives in the East Bay, those are not counted as SF Cases or if one dies in Zuckerberg San Francisco General but is from another county, that is also not counted in this dataset.

Dataset is cumulative and covers cases going back to March 2nd, 2020 when testing began. It is updated daily.

B. HOW THE DATASET IS CREATED
Addresses from medical data are geocoded by the San Francisco Department of Public Health (SFDPH). Those addresses are spatially joined to the geographic areas. Counts are generated based on the number of address points that match each geographic area. The 2018 ACS estimates for population provided by the Census are used to create a rate which is equal to ([count] / [acs_population]) * 10000) representing the number of cases per 10,000 residents.

C. UPDATE PROCESS
Geographic analysis is scripted by SFDPH staff and synced to this dataset each day.

D. HOW TO USE THIS DATASET
Privacy rules in effect
To protect privacy, certain rules are in effect:
1. Case counts greater than 0 and less than 10 are dropped - these will be null (blank) values
2. Cases dropped altogether for areas where acs_population < 1000

Rate suppression in effect where counts lower than 20
Rates are not calculated unless the case count is greater than or equal to 20. Rates are generally unstable at small numbers, so we avoid calculating them directly. We advise you to apply the same approach as this is best practice in epidemiology.

A note on Census ZIP Code Tabulation Areas (ZCTAs)
ZIP Code Tabulation Areas are special boundaries created by the U.S. Census based on ZIP Codes developed by the USPS. They are not, however, the same thing. ZCTAs are areal representations of routes. Read how the Census develops ZCTAs on their website.

This dataset is a filtered view of another dataset
You can find a full dataset of cases and deaths summarized by this and other geographic areas.

A. SUMMARY
This dataset represents the COVID-19 positive confirmed cases by gender. Demographic and transmission data are based on information reported from case interviews, laboratories, and providers. This data may not be immediately available for recently reported cases and data will change to reflect as information becomes available. Cumulative counts of 5 or fewer are excluded from the dataset.

B. HOW THE DATASET IS CREATED
Information on cases and deaths including case demographic and transmission details is reported from a combination of data sources including electronic and faxed laboratory reports, case interviews, medical providers, and electronic medical record systems. These multiple streams of data are merged, deduplicated, undergo quality assurance and other data verification processes, and are continually updated to maximize completeness of information and reporting on San Francisco residents with COVID-19.

C. UPDATE PROCESS
Updates automatically at 05:00 Pacific Time each day. Redundant runs are scheduled at 07:00 and 09:00 in case of pipeline failure.

D. HOW TO USE THIS DATASET
Unknowns may become known over time as more information is gathered.

Gender groups resulting in 5 or fewer cumulative cases are dropped for privacy reasons.

There are five other datasets related to cases:
1. COVID-19 Cases Summarized by Date, Transmission and Case Disposition
2. COVID-19 Cases Summarized by Age Group
3. COVID-19 Cases Summarized by Race and Ethnicity
4. COVID-19 Cases Summarized by Sexual Orientation
5. COVID-19 Cases Summarized by Homelessness Status

A. SUMMARY
This dataset is meant to serve as an official record of the Healthy Streets Operations Center's (HSOC) daily tent counts within the Tenderloin neighborhood. These counts track the City's progress towards fulfilling its commitment to reduce tents in the Tenderloin by 70% of the number observed during a tent count conducted on June 5th. HSOC began operations to move unsheltered individuals into Shelter-in-Place (SIP) hotel rooms on June 10th.

B. HOW THE DATASET IS CREATED
Urban Alchemy, a community organization under contract with the Department of Public Works, takes a daily census of tents within the Tenderloin neighborhood. This data is then validated and processed by City staff and presented here.

C. UPDATE PROCESS
Updated daily.

D. HOW TO USE THIS DATASET
This dataset can be used to monitor the number of tents in the Tenderloin and track progress of efforts to ensure that all residents have a safer place to sleep (like safe sleeping villages, hotels, and other shelters).

See more data on the Tenderloin COVID Response Plan here: https://data.sfgov.org/stories/s/Tenderloin-Plan-Data-and-Reporting/sc96-u6ry/

A. SUMMARY
This dataset represents the COVID-19 positive confirmed cases by homelessness. Demographic and transmission data are based on information reported from case interviews, laboratories, and providers. This data may not be immediately available for recently reported cases and data will change to reflect as information becomes available. Cumulative counts of 5 or fewer are excluded from the dataset.

B. HOW THE DATASET IS CREATED
Information on cases and deaths including case demographic and transmission details is reported from a combination of data sources including electronic and faxed laboratory reports, case interviews, medical providers, and electronic medical record systems. These multiple streams of data are merged, deduplicated, undergo quality assurance and other data verification processes, and are continually updated to maximize completeness of information and reporting on San Francisco residents with COVID-19.

C. UPDATE PROCESS
Updates automatically at 05:00 Pacific Time each day. Redundant runs are scheduled at 07:00 and 09:00 in case of pipeline failure.

D. HOW TO USE THIS DATASET
Unknowns may become known over time as more information is gathered.

Categories resulting in 5 or fewer cumulative cases are dropped for privacy reasons.

There are six other datasets related to cases:
1. COVID-19 Cases Summarized by Date, Transmission and Case Disposition
2. COVID-19 Cases Summarized by Age Group
3. COVID-19 Cases Summarized by Race and Ethnicity
4. COVID-19 Cases Summarized by Gender
5. COVID-19 Cases Summarized by Sexual Orientation
6. COVID-19 Cases Summarized by Comorbidities

A. SUMMARY
List of public works construction projects that the City Administrator has designated as serving an Essential Government Function. This designation allows a public works project to continue, provided that it has a Site-Specific Health and Safety Plan, Code of Safe Practices and posts a Social Distancing Protocol onsite.

B. HOW THE DATASET IS CREATED
City departments and other government agencies submit projects to the City Administrator. In consultation with the Health Officer, the City Administrator determines whether it meets an Essential Government Function. Only the projects that meet that test are listed here.

C. UPDATE PROCESS
Updated as required, dataset uploaded manually by staff.

D. HOW TO USE THIS DATASET
Data will be updated as available and may change as more information becomes available.

A. SUMMARY
This dataset includes COVID-19 tests by resident neighborhood and specimen collection date (the day the test was collected). Specifically, this dataset includes tests of San Francisco residents who listed a San Francisco home address at the time of testing. These resident addresses were then geo-located and mapped to neighborhoods. The resident address associated with each test is hand-entered and susceptible to errors, therefore neighborhood data should be interpreted as an approximation, not a precise nor comprehensive total.

In recent months, about 5% of tests are missing addresses and therefore cannot be included in any neighborhood totals. In earlier months, more tests were missing address data. Because of this high percentage of tests missing resident address data, this neighborhood testing data for March, April, and May should be interpreted with caution (see below)

Percentage of tests missing address information, by month
Mar - 33.6%
Apr - 25.9%
May - 11.1%
Jun - 7.2%
Jul - 5.8%
Aug - 5.4%
Sep - 5.1%
Oct (Oct 1-12) - 5.1%

To protect the privacy of residents, the City does not disclose the number of tests in neighborhoods with resident populations of fewer than 1,000 people. These neighborhoods are omitted from the data (they include Golden Gate Park, John McLaren Park, and Lands End).

Tests for residents that listed a Skilled Nursing Facility as their home address are not included in this neighborhood-level testing data. Skilled Nursing Facilities have required and repeated testing of residents, which would change neighborhood trends and not reflect the broader neighborhood's testing data.

This data was de-duplicated by individual and date, so if a person gets tested multiple times on different dates, all tests will be included in this dataset (on the day each test was collected).

The total number of positive test results is not equal to the total number of COVID-19 cases in San Francisco. During this investigation, some test results are found to be for persons living outside of San Francisco and some people in San Francisco may be tested multiple times (which is common). To see the number of new confirmed cases by neighborhood, reference this map: https://data.sfgov.org/stories/s/Map-of-Cumulative-Cases/adm5-wq8i#new-cases-map

B. HOW THE DATASET IS CREATED
COVID-19 laboratory test data is based on electronic laboratory test reports. Deduplication, quality assurance measures and other data verification processes maximize accuracy of laboratory test information. All testing data is then geo-coded by resident address. Then data is aggregated by analysis neighborhood and specimen collection date.

Data are prepared by close of business Monday through Saturday for public display.

C. UPDATE PROCESS
Updates automatically at 05:00 Pacific Time each day. Redundant runs are scheduled at 07:00 and 09:00 in case of pipeline failure.

D. HOW TO USE THIS DATASET
Due to the high degree of variation in the time needed to complete tests by different labs there is a delay in this reporting. On March 24 the Health Officer ordered all labs in the City to report complete COVID-19 testing information to the local and state health departments.

In order to track trends over time, a data user can analyze this data by "specimen_collection_date".

Calculating Percent Positivity: The positivity rate is the percentage of tests that return a positive result for COVID-19 (positive tests divided by the sum of positive and negative tests). Indeterminate results, which could not conclusively determine whether COVID-19 virus was present, are not included in the calculation of percent positive. Percent positivity indicates how widespread COVID-

A. SUMMARY
It is the policy of the San Francisco Department of Public Health to comply with patient/client/resident rights regarding Protected Health Information (PHI) as set forth in the Health Insurance Portability and Accountability Act of 1996 (HIPAA). These guidelines exists to provide guidance only as it relates to the public release of COVID-19 data through the tracker webpages, so that public reporting of de-identified information of residents’ health status, demographic and other characteristics, and geographical information reflect consistent reporting practices and meaningful differences in health outcomes, conditions that impact health, and delivery of services while safeguarding patient/client/resident rights regarding PHI.

COVID-19 related data will be released routinely in a variety of data products related to the tracker, including datasets through SF OpenData. Some data products may include data by county or smaller analysis unit such as ZIP code, neighborhood, or census tract.

Download the attached PDF for the policy.

A. SUMMARY
This dataset includes San Francisco COVID-19 tests by race/ ethnicity and date. For each day, this dataset represents the daily count of tests collected by race/ethnicity, and how many of those were positive, negative, and indeterminate. Tests in this dataset include all tests collected from San Francisco residents who listed a San Francisco home address at the time of testing, and tests that were collected in San Francisco but had a missing home address. Data are based on information collected at the time of testing.

For recent data, about 25-30% of tests are missing race/ ethnicity information. Tests where the race/ ethnicity of the patient is unknown are included in the dataset under the "Unknown" category.

This data was de-duplicated by individual and date, so if a person gets tested multiple times on different dates, all tests will be included in this dataset (on the day each test was collected).

The total number of positive test results is not equal to the total number of COVID-19 cases in San Francisco. Each positive test result is investigated. During this investigation, some test results are found to be for persons living outside of San Francisco and some people in San Francisco may be tested multiple times. In both cases, these results are not included in San Francisco’s total COVID-19 case count. To track the number of cases by race/ ethnicity, see this dashboard: https://data.sfgov.org/stories/s/w6za-6st8

B. HOW THE DATASET IS CREATED
COVID-19 laboratory test data is based on electronic laboratory test reports. Deduplication, quality assurance measures and other data verification processes maximize accuracy of laboratory test information.

C. UPDATE PROCESS
Updates automatically at 05:00 Pacific Time each day. Redundant runs are scheduled at 07:00 and 09:00 in case of pipeline failure.

D. HOW TO USE THIS DATASET
Due to the high degree of variation in the time needed to complete tests by different labs there is a delay in this reporting. On March 24 the Health Officer ordered all labs in the City to report complete COVID-19 testing information to the local and state health departments.

In order to track trends over time, a data user can analyze this data by "specimen_collection_date".

Calculating Percent Positivity: The positivity rate is the percentage of tests that return a positive result for COVID-19 (positive tests divided by the sum of positive and negative tests). Indeterminate results, which could not conclusively determine whether COVID-19 virus was present, are not included in the calculation of percent positive. When there are fewer than 20 positives tests for a given race/ethnicity and time period, the positivity rate is not calculated for the public tracker because rates of small test counts are less reliable.

Calculating Testing Rates: To calculate the testing rate per 10,000 residents, divide the total number of tests collected (positive, negative, and indeterminate results) for the specified race/ ethnicity by the total number of residents who identify as that race/ ethnicity (according to the 2018 5-year estimates from the American Community Survey), then multiply by 10,000. When there are fewer than 20 total tests for a given race/ethnicity and time period, the testing rate is not calculated for the public tracker because rates of small test counts are less reliable.

Read more about how this data is updated and validated daily: https://data.sfgov.org/stories/s/nudz-9tg2

There are two other datasets related to tests:
1. COVID-19 Tests
2.

A. SUMMARY
This dataset contains the locations of all Pit Stops in San Francisco, including those added during the COVID emergency. The Pit Stop program is managed by San Francisco Public Works and aims to provide clean and safe public toilets, sinks, used needle receptacles and dog waste stations in San Francisco's most impacted neighborhoods. In response to the COVID emergency, additional Pit Stops have been added across the City in order to ensure everyone has access to clean and safe toilets and sinks.

Learn more about this Pit Stop Program: https://sfpublicworks.wixsite.com/pitstop

B. HOW THE DATASET IS CREATED
This dataset is linked to the Pit Stop Program's map of pit stops and updated daily to match that map.

C. UPDATE PROCESS
Automatically updated daily at 7am.

D. HOW TO USE THIS DATASET
This dataset can be used with other geospatial layers to look at the distribution of Pit Stops in relation to other resources or points of interest. It's important to note that Pit Stops are not the only public restrooms in the City (there are many managed by the Parks Department, for example), and there are additional hand-washing stations that have been distributed during the COVID emergency that are not shown here. This dataset only includes Pit Stops and should not be used to assess broader access to bathrooms, water, or syringe disposal.

A. SUMMARY
This dataset represents the COVID-19 positive confirmed cases by sexual orientation for adult cases (18 or older) where the lab result was reported after April 28th.

Information on sexual orientation is collected from individuals who are 18 years or older and who opt to provide it during case interviews. The Department of Public Health began asking for this information on April 28, 2020. To gather this information, SFDPH follows their Principles for Collecting, Coding, and Reporting Identity Data: Sexual Orientation Guidelines.

Read more about California's mandate that all counties report data on sexual orientation and gender identity.

Demographic data (including sexual orientation) are based on information reported from case interviews, laboratories, and providers. This data may not be immediately available for recently reported cases and data will change to reflect as information becomes available. Cumulative counts of 5 or fewer are excluded from the dataset.

B. HOW THE DATASET IS CREATED
Information on COVID-19 case demographic details (like sexual orientation) is reported from a combination of data sources including electronic and faxed laboratory reports, case interviews, medical providers, and electronic medical record systems. These multiple streams of data are merged, deduplicated, undergo quality assurance and other data verification processes, and are continually updated to maximize completeness of information and reporting on San Francisco residents with COVID-19.

C. UPDATE PROCESS
Updates automatically at 05:00 Pacific Time each day. Redundant runs are scheduled at 07:00 and 09:00 in case of pipeline failure.

D. HOW TO USE THIS DATASET
This data may undercount certain minorities who have faced stigma and discrimination, particularly in medical settings (and therefore may not disclose their gender identity or sexual orientation, for example).

Missing data (coded here as "missing") may become known over time as more information is gathered.

Sexual Orientation groups resulting in 5 or fewer cumulative cases are dropped for privacy reasons.

There are five other datasets related to cases:
1. COVID-19 Cases Summarized by Date, Transmission and Case Disposition
2. COVID-19 Cases Summarized by Age Group
3. COVID-19 Cases Summarized by Race and Ethnicity
4. COVID-19 Cases Summarized by Gender
5. COVID-19 Cases Summarized by Homelessness Status