Beginning March 1, 2022, the "COVID-19 Case Surveillance Public Use Data" will be updated on a monthly basis. This case surveillance public use dataset has 12 elements for all COVID-19 cases shared with CDC and includes demographics, any exposure history, disease severity indicators and outcomes, presence of any underlying medical conditions and risk behaviors, and no geographic data.,

This dataset compiles daily snapshots of publicly reported data on 2019 Novel Coronavirus (COVID-19) testing in Ontario. [Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak.](https://covid-19.ontario.ca/) Data includes: * approximation of onset date * age group * patient gender * case acquisition information * patient outcome * reporting Public Health Unit (PHU) * postal code, website, longitude, and latitude of PHU This dataset is subject to change. Please review the [daily epidemiologic summaries](https://covid-19.ontario.ca/covid-19-epidemiologic-summaries-public-health-ontario) for information on variables, methodology, and technical considerations. ##Additional information **This data is no longer available on this page. Information about COVID-19, and other respiratory viruses, is available through Public Health Ontario’s [“Ontario Respiratory Virus Tool"](https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool).** On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. This impacts data captured in the column ‘Outcome1’. Due to changes in data availability, the following variables will be removed from this file, effective Thursday April 13, 2023: ‘Case_AcquisitionInfo’, ‘Outbreak_Related’. Also due to changes in data availability, the variable ‘Outcome1’ will be equal to ‘Fatal’ (deaths due to COVID-19) or blank (all other cases) The methodology used to count COVID-19 deaths has changed to exclude deaths not caused by COVID. This impacts data captured in the column ‘‘Outcome1’ starting with data posted to the catalogue on March 11, 2022. CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags. ##Related dataset(s) * [Status of COVID-19 cases in Ontario](https://data.ontario.ca/dataset/status-of-covid-19-cases-in-ontario)

This public use dataset has 11 data elements reflecting COVID-19 community levels for all available counties. This dataset contains the same values used to display information available at https://www.cdc.gov/coronavirus/2019-ncov/science/community-levels-county-map.html. CDC looks at the combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days — to determine the COVID-19 community level. The COVID-19 community level is determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge. Using these data, the COVID-19 community level is classified as low, medium , or high. COVID-19 Community Levels can help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals. See https://www.cdc.gov/coronavirus/2019-ncov/science/community-levels.html for more information. Visit CDC’s COVID Data Tracker County View* to learn more about the individual metrics used for CDC’s COVID-19 community level in your county. Please note that county-level data are not available for territories. Go to https://covid.cdc.gov/covid-data-tracker/#county-view. For the most accurate and up-to-date data for any county or state, visit the relevant health department website. *COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.

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A. SUMMARY Case information on COVID-19 Laboratory testing. This data includes a daily count of test results reported, and how many of those were positive, negative, and indeterminate. Reported tests include tests with a positive, negative or indeterminate result. Indeterminate results, which could not conclusively determine whether COVID-19 virus was present, are not included in the calculation of percent positive. Testing for the novel coronavirus is available through commercial, clinical, and hospital laboratories, as well as the SFDPH Public Health Laboratory. Tests are de-duplicated by an individual and date. This means that if a person gets tested multiple times on different dates in the last 30 days, all of those individual tests will be included in this data as individual tests (on each specimen collection date). Total positive test results is not equal to the total number of COVID-19 cases in San Francisco. B. HOW THE DATASET IS CREATED Laboratory test volume and positivity for COVID-19 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. A redundant run is scheduled at 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 "result_date" and see how the count of reported results and positivity rate have changed over time. E. CHANGE LOG,

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