Covid-19 Testing by Geography and Date
Covid-19 Testing by Geography and Date
<i><b>Note: As of April 16, 2021, this dataset will update daily with a five-day data lag.</i></b>
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 in 2020
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).
<strong>The total number of positive test results is not equal to the total number of COVID-19 cases in San Francisco. </strong>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
<strong>B. HOW THE DATASET IS CREATED</strong>
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 <a href="https://data.sfgov.org/Geographic-Locations-and-Boundaries/Analysis-Neighborhoods/p5b7-5n3h
">analysis neighborhood</a> and specimen collection date.
Data are prepared by close of business Monday through Saturday for public display.
<strong>C. UPDATE PROCESS</strong>
Updates automatically at 05:00 Pacific Time each day. Redundant runs are scheduled at 07:00 and 09:00 in case of pipeline failure.
<strong>D. HOW TO USE THIS DATASET</strong>
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 widesprea
|Name||Socrata field name||Column name in ||Data type||Description|
|Cumulative Indeterminate Tests||cumulative_indeterminate_tests||cumulative_indeterminate_tests||Number||Cumulative indeterminate tests collected as of the specified date for residents living in the area|
|Cumulative Negative Tests||cumulative_negative_tests||cumulative_negative_tests||Number||Cumulative negative tests collected as of the specified date for residents living in the area|
|New Negative Tests||new_negative_tests||new_negative_tests||Number||Negative tests collected on the specified date for residents living in the area|
|Cumulative Positive Tests||cumulative_positive_tests||cumulative_positive_tests||Number||Cumulative positive tests collected as of the specified date for residents living in the area|
|id||id||id||Text||The identifier for the area type|
|area_type||area_type||area_type||Text||Type of geographic area|
|Specimen Collection Date||specimen_collection_date||specimen_collection_date||Calendar date||Date tests were collected|
|Cumulative Tests||cumulative_tests||cumulative_tests||Number||Cumulative tests collected as of the specified date for residents living in the area|
|acs_population||acs_population||acs_population||Number||The population from the latest 5-year estimates from the American Community Survey (2015-2019)|
|New Tests||new_tests||new_tests||Number||Total tests collected on the specified date for residents living in the area|
|Cumulative Testing Rate||cumulative_testing_rate||cumulative_testing_rate||Number||The cumulate testing in the area, calculated as (cumulative tests /acs_population) * 10000 which is a rate per 10,000 residents|
|New Positive Tests||new_positive_tests||new_positive_tests||Number||Positive tests collected on the specified date for residents living in the area|
|New Indeterminate Tests||new_indeterminate_tests||new_indeterminate_tests||Number||Indeterminate tests collected on the specified date for residents living in the area|