A summary of the process for school reopening and a dashboard to show the reopening status of schools that have submitted a letter of interest to open in-person instruction.

A. SUMMARY
Data on daily hospital bed use and available capacity at San Francisco acute care hospitals from April 2020 onward. Long Term Care facilities (like Laguna Honda and Kentfield) are not included in this data as acute care patients cannot be admitted to these facilities.
B. HOW THE DATASET IS CREATED
This hospital capacity information is based on data that all SF acute care hospitals report to the San Francisco Department of Public Health.
C. UPDATE PROCESS
Updated daily, dataset uploaded manually by staff. This data is on a 2-day lag to account for the time needed to get complete data from all SF acute care hospitals and validate this data.
D. HOW TO USE THIS DATASET
This data provides visibility into current occupancy levels and use of San Francisco acute care hospitals and potential ability to accommodate anticipated surges of COVID patients.
Data includes current census of COVID-19 patients (including both confirmed cases and suspected COVID patients) and other patients in acute care hospitals, shown in the “Status” column. The “Status” column also includes all available beds.
This daily census information is stratified by type of bed (acute care, intensive care, and surge) in the “Bed Type” column. Acute care beds treat patients with illnesses and injuries including recovery from surgeries. Intensive care (ICU) beds are for sicker patients in need of critical and life support services that can include the use of a ventilator. Surge beds are the additional beds that can be made available to handle an influx of COVID-19 patients; surge beds are differentiated between acute care surge beds and ICU surge beds.
Note: The current census of COVID patients shown here may not always match the hospitalizations data (https://data.sfgov.org/COVID-19/COVID-19-Hospitalizations/nxjg-bhem), as that data includes all hospitals and long term care facilities. As described above, those long term care facilities are not included here as they don’t have the capacity to take in additional acute care patients and therefore aren’t included in capacity measures.

A. SUMMARY
This dataset contains COVID-19 positive confirmed cases aggregated by several different geographic areas and by day. COVID-19 cases are mapped to the residence of the individual and shown on the date the positive test was collected. In addition, 2018 American Community Survey (ACS) 5-year population estimates are included to calculate the cumulative rate per 10,000 residents.

Dataset covers cases going back to March 2nd, 2020 when testing began. This data may not be immediately available for recently reported cases and data will change to reflect as information becomes available. Data updated daily.

Geographic areas summarized are:
1. Analysis Neighborhoods
2. Census Tracts
3. Census Zip Code Tabulation Areas

B. HOW THE DATASET IS CREATED
Addresses from the COVID-19 case 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 for a given date.

The 2018 ACS estimates for population provided by the Census are used to create a cumulative rate which is equal to ([cumulative count up to that date] / [acs_population]) * 10000) representing the number of total cases per 10,000 residents (as of the specified date).

COVID-19 case data undergo quality assurance and other data verification processes and are continually updated to maximize completeness and accuracy of information. This means data may change for previous days as information is updated.

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

D. HOW TO USE THIS DATASET
This dataset can be used to track the spread of COVID-19 throughout the city, in a variety of geographic areas. Note that the new cases column in the data represents the number of new cases confirmed in a certain area on the specified day, while the cumulative cases column is the cumulative total of cases in a certain area as of the specified date.

Privacy rules in effect
To protect privacy, certain rules are in effect:
1. Any area with a cumulative case count less than 10 are dropped for all days the cumulative count was less than 10. These will be null values.
2. Once an area has a cumulative case count of 10 or greater, that area will have a new row of case data every day following.
3. Cases are dropped altogether for areas where acs_population < 1000
4. Deaths data are not included in this dataset for privacy reasons. The low COVID-19 death rate in San Francisco, along with other publicly available information on deaths, means that deaths data by geography and day is too granular and potentially risky. Read more in our privacy guidelines

Rate suppression in effect where counts lower than 20
Rates are not calculated unless the cumulative 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.

Rows included for Citywide case counts
Rows are included for the Citywide case counts and incidence rate eve

A. SUMMARY
Geographic zones of the priority areas in the Tenderloin neighborhood used in the COVID-19 assessment and Tenderloin Neighborhood Plan. See more details on the plan here:
https://sf.gov/news/san-francisco-releases-tenderloin-neighborhood-safety-assessment-and-plan-covid-19

B. HOW THE DATASET IS CREATED
A team of representative City departments from the Healthy Streets Operation Center (Department of Emergency Management, Department of Public Health, Department of Homelessness and Supportive Housing, Human Rights Commission, San Francisco Police Department, San Francisco Fire Department, and Department of Public Works), SF Homeless Outreach Team, Felton Institute, and community groups and stakeholders was assembled to design and implement a robust Tenderloin Neighborhood Needs Assessment. This assessment was conducted on the morning of April 28, 2020 and consisted of multi-disciplinary teams walking each block of an area of the Tenderloin broken into six geographic zones. These zone locations are shown in the plan, and are mapped in this dataset.

C. UPDATE PROCESS
This is a reference map that will not be updated.

D. HOW TO USE THIS DATASET
These zones can be used with other datasets to track trends by zone. Note that these zones are the priority zones for the Tenderloin Plan and do not represent the entire Tenderloin Neighborhood boundary. For a boundary of the entire Tenderloin, use the analysis neighborhood boundary: https://data.sfgov.org/Geographic-Locations-and-Boundaries/Analysis-Neighborhoods/p5b7-5n3h

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. Data are prepared by close of business daily for public display.

C. UPDATE PROCESS
Updated daily, dataset uploaded manually by staff

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

A. SUMMARY
This dataset contains the locations of the temporary manifolds (water spigots) that the San Francisco Public Utilities Commission (SFPUC) has provided in response to the COVID-19 emergency.
All manifolds are open from 7:00am-5:00pm daily. On weekdays, the manifolds are staffed from 9:00-5:00pm with a staff member to monitor and sanitize the station, and provide cups to residents.

B. HOW THE DATASET IS CREATED
The SFPUC manages the manifolds and updates locations as needed.

C. UPDATE PROCESS
Updated automatically daily at 7am.

D. HOW TO USE THIS DATASET
This dataset can be used with other geospatial layers to look at the distribution of these COVID response manifolds in relation to other resources or points of interest. It's important to note that these manifolds are additional hand-washing stations that have been distributed during the COVID emergency - this dataset is not representative of all public-access water sources and should not be used to assess broader access to clean water.

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 daily for public display.

C. UPDATE PROCESS
Updated daily.

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-19 is in San Francisco and it helps public health officials determine if we are testing enough given the number of people who are testing positive. When there are fewer than 20 positives tests for a given neighborhood and time period,

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. Data are prepared by close of business daily for public display.

C. UPDATE PROCESS
Updated daily, dataset uploaded manually by staff

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. COVID-19 Tests by Neighborhood and Date

A. SUMMARY
This dataset represents the COVID-19 positive confirmed cases by comorbidities (underlying conditions). Comorbidities (underlying conditions) for COVID-19 cases are reported when a person has one or more underlying health conditions, such as chronic lung disease including asthma or emphysema, diabetes, cardiovascular disease or liver disease, present at the time of diagnosis.

Data on comorbidities 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 including details on any underlying conditions 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. Data are prepared by close of business daily for public display.

C. UPDATE PROCESS
Updated daily, dataset uploaded manually by staff

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

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.