Note: This COVID-19 data set is no longer being updated as of December 1, 2023. Access current COVID-19 data on the CDPH respiratory virus dashboard (https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Respiratory-Viruses/RespiratoryDashboard.aspx) or in open data format (https://data.chhs.ca.gov/dataset/respiratory-virus-dashboard-metrics).

As of August 17, 2023, data is being updated each Friday.

For death data after December 31, 2022, California uses Provisional Deaths from the Center for Disease Control and Prevention’s National Center for Health Statistics (NCHS) National Vital Statistics System (NVSS). Prior to January 1, 2023, death data was sourced from the COVID-19 registry. The change in data source occurred in July 2023 and was applied retroactively to all 2023 data to provide a consistent source of death data for the year of 2023.

As of May 11, 2023, data on cases, deaths, and testing is being updated each Thursday. Metrics by report date have been removed, but previous versions of files with report date metrics are archived below.

All metrics include people in state and federal prisons, US Immigration and Customs Enforcement facilities, US Marshal detention facilities, and Department of State Hospitals facilities. Members of California's tribal communities are also included.

The "Total Tests" and "Positive Tests" columns show totals based on the collection date. There is a lag between when a specimen is collected and when it is reported in this dataset. As a result, the most recent dates on the table will temporarily show NONE in the "Total Tests" and "Positive Tests" columns. This should not be interpreted as no tests being conducted on these dates. Instead, these values will be updated with the number of tests conducted as data is received.

As of July 2nd, 2024 the COVID-19 Deaths by Population Characteristics Over Time dataset has been retired. This dataset is archived and will no longer update. We will be publishing a cumulative deaths by population characteristics dataset that will update moving forward.

A. SUMMARY This dataset shows San Francisco COVID-19 deaths by population characteristics and by date. This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. Because of this, death totals for previous days may increase or decrease. More recent data is less reliable.

Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how deaths have been distributed among different subgroups. This information can reveal trends and disparities among groups.

B. HOW THE DATASET IS CREATED As of January 1, 2023, COVID-19 deaths are defined as persons who had COVID-19 listed as a cause of death or a significant condition contributing to their death on their death certificate. This definition is in alignment with the California Department of Public Health and the national https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">Council of State and Territorial Epidemiologists. Death certificates are maintained by the California Department of Public Health.

Data on the population characteristics of COVID-19 deaths are from: *Case reports *Medical records *Electronic lab reports *Death certificates

Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths.

To protect resident privacy, we summarize COVID-19 data by only one characteristic at a time. Data are not shown until cumulative citywide deaths reach five or more.

Data notes on each population characteristic type is listed below.

Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases.

Gender * The City collects information on gender identity using these guidelines.

C. UPDATE PROCESS Updates automatically at 06:30 and 07:30 AM Pacific Time on Wednesday each week.

Dataset will not update on the business day following any federal holiday.

D. HOW TO USE THIS DATASET Population estimates are only available for age groups and race/ethnicity categories. San Francisco population estimates for race/ethnicity and age groups can be found in a view based on the San Francisco Population and Demographic Census dataset. These population estimates are from the 2016-2020 5-year American Community Survey (ACS).

This dataset includes many different types of characteristics. Filter the “Characteristic Type” column to explore a topic area. Then, the “Characteristic Group” column shows each group or category within that topic area and the number of deaths on each date.

New deaths are the count of deaths within that characteristic group on that specific date. Cumulative deaths are the running total of all San Francisco COVID-19 deaths in that characteristic group up to the date listed.

This data may not be immediately available for more recent deaths. Data updates as more information becomes available.

To explore data on the total number of deaths, use the COVID-19 Deaths Over Time dataset.

E. CHANGE LOG

• 9/11/2023 - on this date, we began using an updated definition of a COVID-19 death to align with the California Department o

*** The County of Santa Clara Public Health Department discontinued updates to the COVID-19 data tables effective June 30, 2025. The COVID-19 data tables will be removed from the Open Data Portal on December 30, 2025. For current information on COVID-19 in Santa Clara County, please visit the Respiratory Virus Dashboard [sccphd.org/respiratoryvirusdata]. For any questions, please contact phinternet@phd.sccgov.org ***

The dataset provides information about the demographics and characteristics of deaths with COVID-19 by racial/ethnic groups among Santa Clara County residents. Source: California Reportable Disease Information Exchange. Data notes: The Other category for the race/ethnicity graph includes American Indian/Alaska Native and people who identify as multi-racial.

This table is updated every Friday.

A. SUMMARY This dataset shows San Francisco COVID-19 deaths by population characteristics. This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. Because of this, death totals may increase or decrease. Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how deaths have been distributed among different subgroups. This information can reveal trends and disparities among groups. B. HOW THE DATASET IS CREATED As of January 1, 2023, COVID-19 deaths are defined as persons who had COVID-19 listed as a cause of death or a significant condition contributing to their death on their death certificate. This definition is in alignment with the California Department of Public Health and the national Council of State and Territorial Epidemiologists. Death certificates are maintained by the California Department of Public Health. Data on the population characteristics of COVID-19 deaths are from: Case reports Medical records Electronic lab reports Death certificates Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths. To protect resident privacy, we summarize COVID-19 data by only one population characteristic at a time. Data are not shown until cumulative citywide deaths reach five or more. Data notes on select population characteristic types are listed below. Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases. Gender * The City collects information on gender identity using these guidelines. C. UPDATE PROCESS Updates automatically at 06:30 and 07:30 AM Pacific Time on Wednesday each week. Dataset will not update on the business day following any federal holiday. D. HOW TO USE THIS DATASET Population estimates are only available for age groups and race/ethnicity categories. San Francisco population estimates for race/ethnicity and age groups can be found in a dataset based on the San Francisco Population and Demographic Census dataset.These population estimates are from the 2018-2022 5-year American Community Survey (ACS). This dataset includes several characteristic types. Filter the “Characteristic Type” column to explore a topic area. Then, the “Characteristic Group” column shows each group or category within that topic area and the number of cumulative deaths. Cumulative deaths are the running total of all San Francisco COVID-19 deaths in that characteristic group up to the date listed. To explore data on the total number of deaths, use the COVID-19 Deaths Over Time dataset. E. CHANGE LOG

A. SUMMARY This dataset represents San Francisco COVID-19 related deaths by day. This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. Because of this, death totals for previous days may increase or decrease. More recent data is less reliable. B. HOW THE DATASET IS CREATED As of January 1, 2023, COVID-19 deaths are defined as persons who had COVID-19 listed as a cause of death or a significant condition contributing to their death on their death certificate. This definition is in alignment with the California Department of Public Health and the national Council of State and Territorial Epidemiologists. Death data is provided by the California Department of Public Health. It takes time to process this data. Because of this, death totals may increase or decrease over time. Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths. C. UPDATE PROCESS Updates automatically at 06:30 and 07:30 AM Pacific Time on Wednesday each week. Dataset will not update on the business day following any federal holiday. D. HOW TO USE THIS DATASET This dataset shows new deaths and cumulative deaths by date of death. New deaths are the count of deaths on that specific date. Cumulative deaths are the running total of all San Francisco COVID-19 deaths up to the date listed. Use the Deaths by Population Characteristics Over Time dataset to see deaths by different subgroups including race/ethnicity, age, and gender. E. CHANGE LOG 9/11/2023 – on this date, we began using an updated definition of a COVID-19 death to align with the California Department of Public Health. This change was applied to COVID-19 deaths retrospectively beginning on 1/1/2023. More information about the recommendation by the Council of State and Territorial Epidemiologists that motivated this change can be found here. 4/6/2023 - the State implemented system updates to improve the integrity of historical data. 1/22/2022 - system updates to improve timeliness and accuracy of cases and deaths data were implemented.

Note: This dataset is on hiatus.

CDPH strives to respond equitably to the COVID-19 pandemic and is therefore interested in how different communities are impacted. Collecting and reporting health equity data helps to identify health disparities and improve the state’s response. To that end, CDPH tracks cases, deaths, and testing by race and ethnicity as well as other social determinants of health, such as income, crowded housing, and access to health insurance.

During the response, CDPH used a health equity metric, defined as the positivity rate in the most disproportionately-impacted communities according to the Healthy Places Index. The purpose of this metric was to ensure California reopened its economy safely by reducing disease transmission in all communities. This metric is tracked and reported in comparison to statewide positivity rate. More information is available at https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/COVID-19/CaliforniaHealthEquityMetric.aspx.

Data completeness is also critical to addressing inequities. CDPH reports data completeness by race and ethnicity, sexual orientation, and gender identity to better understand missingness in the data.

Health equity data is updated weekly. Data may be suppressed based on county population or total counts.

For more information on California’s commitment to health equity, please see https://covid19.ca.gov/equity/

This file contains COVID-19 death counts and rates by month and year of death, jurisdiction of residence (U.S., HHS Region) and demographic characteristics (sex, age, race and Hispanic origin, and age/race and Hispanic origin). United States death counts and rates include the 50 states, plus the District of Columbia.

Deaths with confirmed or presumed COVID-19, coded to ICD–10 code U07.1. Number of deaths reported in this file are the total number of COVID-19 deaths received and coded as of the date of analysis and may not represent all deaths that occurred in that period. Counts of deaths occurring before or after the reporting period are not included in the file.

Data during recent periods are incomplete because of the lag in time between when the death occurred and when the death certificate is completed, submitted to NCHS and processed for reporting purposes. This delay can range from 1 week to 8 weeks or more, depending on the jurisdiction and cause of death.

Death counts should not be compared across jurisdictions. Data timeliness varies by state. Some states report deaths on a daily basis, while other states report deaths weekly or monthly.

The ten (10) United States Department of Health and Human Services (HHS) regions include the following jurisdictions. Region 1: Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont; Region 2: New Jersey, New York; Region 3: Delaware, District of Columbia, Maryland, Pennsylvania, Virginia, West Virginia; Region 4: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee; Region 5: Illinois, Indiana, Michigan, Minnesota, Ohio, Wisconsin; Region 6: Arkansas, Louisiana, New Mexico, Oklahoma, Texas; Region 7: Iowa, Kansas, Missouri, Nebraska; Region 8: Colorado, Montana, North Dakota, South Dakota, Utah, Wyoming; Region 9: Arizona, California, Hawaii, Nevada; Region 10: Alaska, Idaho, Oregon, Washington.

Rates were calculated using the population estimates for 2021, which are estimated as of July 1, 2021 based on the Blended Base produced by the US Census Bureau in lieu of the April 1, 2020 decennial population count. The Blended Base consists of the blend of Vintage 2020 postcensal population estimates, 2020 Demographic Analysis Estimates, and 2020 Census PL 94-171 Redistricting File (see https://www2.census.gov/programs-surveys/popest/technical-documentation/methodology/2020-2021/methods-statement-v2021.pdf).

Rate are based on deaths occurring in the specified week and are age-adjusted to the 2000 standard population using the direct method (see https://www.cdc.gov/nchs/data/nvsr/nvsr70/nvsr70-08-508.pdf). These rates differ from annual age-adjusted rates, typically presented in NCHS publications based on a full year of data and annualized weekly age-adjusted rates which have been adjusted to allow comparison with annual rates. Annualization rates presents deaths per year per 100,000 population that would be expected in a year if the observed period specific (weekly) rate prevailed for a full year.

Sub-national death counts between 1-9 are suppressed in accordance with NCHS data confidentiality standards. Rates based on death counts less than 20 are suppressed in accordance with NCHS standards of reliability as specified in NCHS Data Presentation Standards for Proportions (available from: https://www.cdc.gov/nchs/data/series/sr_02/sr02_175.pdf.).

This dataset has been retired as of February 17, 2023. This dataset will be kept for historical purposes, but will no longer be updated. Similar data are available on the state’s open data portal: https://data.chhs.ca.gov/dataset/covid-19-time-series-metrics-by-county-and-state.

Provides the proportion of COVID-19 Cases, Hospitalizations, and Deaths by Age, Gender, and Race/Ethnicity categories.

Note: Between 1/1/2022 and 3/4/2022 hospitalization counts did not include in-patient hospitalizations with a COVID-19 positive test when the patient was in the hospital for a reason other than COVID-19. This included in-patient stays due to labor/delivery, trauma, or emergency surgery. Hospitalization reporting was modified to represent the disease severity of the Omicron variant accurately. As of 3/5/2022, we have resumed publishing the CDPH daily hospitalized patient census, which includes all in-patient hospitalizations with a COVID-19 positive test.

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

Note: This dataset is on hiatus. CDPH strives to respond equitably to the COVID-19 pandemic and is therefore interested in how different communities are impacted. Collecting and reporting health equity data helps to identify health disparities and improve the state’s response. To that end, CDPH tracks cases, deaths, and testing by race and ethnicity as well as other social determinants of health, such as income, crowded housing, and access to health insurance. During the response, CDPH used a health equity metric, defined as the positivity rate in the most disproportionately-impacted communities according to the Healthy Places Index. The purpose of this metric was to ensure California reopened its economy safely by reducing disease transmission in all communities. This metric is tracked and reported in comparison to statewide positivity rate. More information is available at https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/COVID-19/CaliforniaHealthEquityMetric.aspx. Data completeness is also critical to addressing inequities. CDPH reports data completeness by race and ethnicity, sexual orientation, and gender identity to better understand missingness in the data. Health equity data is updated weekly. Data may be suppressed based on county population or total counts. For more information on California’s commitment to health equity, please see https://covid19.ca.gov/equity/

Per-capita excess mortality among California residents 18–65 years of age, by occupational sector and race/ethnicity, March through November 2020.

Data by medical encounter for the following conditions by age, race/ethnicity, and gender:

Influenza (Flu) Flu/Pneumonia Pneumonia Urinary Tract Infections

Rates per 100,000 population. Age-adjusted rates per 100,000 2000 US standard population.
Blank Cells: Rates not calculated for fewer than 11 events. Rates not calculated in cases where zip code is unknown. Geography not reported where there are no cases reported in a given year. SES: Is the median household income by SRA community. Data for SRAs only.
*The COVID-19 pandemic was associated with increases in all-cause mortality. COVID-19 deaths have affected the patterns of mortality including those of Communicable conditions.

Data sources: California Department of Public Health, Center for Health Statistics, Office of Health Information and Research, Vital Records Business Intelligence System (VRBIS). California Department of Health Care Access and Information (HCAI), Emergency Department Database and Patient Discharge Database, 2020. SANDAG Population Estimates, 2020 (vintage: 09/2022). Population estimates were derived using the 2010 Census and data should be considered preliminary. Prepared by: County of San Diego, Health and Human Services Agency, Public Health Services, Community Health Statistics Unit, February 2023.

2020 Community Profile Data Guide and Data Dictionary Dashboard: https://public.tableau.com/app/profile/chsu/viz/2020CommunityProfilesDataGuideandDataDictionaryDashboard_16763944288860/HomePage

Background: Long-term care facilities had the highest rate of COVID-19 deaths in Canada; thus, it was essential to understand the effectiveness of vaccines and the risk factors for outbreaks in the elderly residents of long-term care and retirement homes. Aims of the CITF-funded study: This study aimed to 1) understand the association between outbreaks and features of long-term care and retirement homes; 2) determine the recurrence rate of outbreaks in homes that have been previously exposed; 3) describe residents’ immune response to infection and vaccination; and 4) estimate vaccine effectiveness in residents. Methods: This cohort study recruited residents from participating long-term care and retirement home across Ontario through invitations from research coordinators. Study visits occurred at participants’ first dose and second dose of the COVID-19 vaccine, and then 3 weeks, 3 months, 6 months, 9, and 12 months post- second dose. For those who got a third dose, follow up was done 3 weeks, 3 months, and 6 months after their third dose. Staff, essential visitors, and resident participants were followed up every week or per visit for saliva surveillance active COVID infection . A DBS whole blood sample was given at enrolment and at each follow up for serology testing. Contributed dataset contents: The datasets include 1261 participants who completed baseline surveys between January 2021 and July 2023. 90% of participants gave one or more blood samples between April 2021 and April 2023 for analysis. A total of 6078 samples were collected. Variables include data in the following areas of information: demographics (date of birth, sex, race-ethnicity, indigeneity), general health (weight and height, smoking, flu vaccination, chronic conditions), SARS-CoV-2 outcomes (positive test results, hospitalizations), SARS-CoV-2 vaccination, and serology (IgA, IgG, and IgM against SARS-CoV-2 receptor-binding domain (RBD) and spike (S) protein).

Data by medical encounter for the following conditions by age, race/ethnicity, and gender:
Alzheimer's Disease
Alzheimer's Disease and Related Dementias (ADRD)
Dementia
Neurocognitive Disorders
Parkinson's Disease

Rates per 100,000 population. Age-adjusted rates per 100,000 2000 US standard population.
Blank Cells: Rates not calculated for fewer than 11 events. Rates not calculated in cases where zip code is unknown. Geography not reported where there are no cases reported in a given year. SES: Is the median household income by SRA community. Data for SRAs only.
*The COVID-19 pandemic was associated with increases in all-cause mortality. COVID-19 deaths have affected the patterns of mortality, including those of ADRD conditions.

Data sources: California Department of Public Health, Center for Health Statistics, Office of Health Information and Research, Vital Records Business Intelligence System (VRBIS). California Department of Health Care Access and Information (HCAI), Emergency Department Database and Patient Discharge Database, 2020. SANDAG Population Estimates, 2020 (vintage: 09/2022). Population estimates were derived using the 2010 Census and data should be considered preliminary. Prepared by: County of San Diego, Health and Human Services Agency, Public Health Services, Community Health Statistics Unit, February 2023.

2020 Community Profile Data Guide and Data Dictionary Dashboard: https://public.tableau.com/app/profile/chsu/viz/2020CommunityProfilesDataGuideandDataDictionaryDashboard_16763944288860/HomePage

Survey results from countries around the world show that significant shares of people living in the United States, Russia, and Australia believed the media had overblown the coronavirus pandemic. In India, almost three-quarters of respondents said the media had exaggerated the extent of the outbreak.

Cases surge in the United States At the time of the survey in mid-March 2020, the United States had confirmed around 1,700 COVID-19 cases, leading many respondents to agree that the media had exaggerated the extent of the virus. By the end of April, the U.S. was one of the most severely affected countries worldwide, with more than one million cases. The coronavirus has spread rapidly from coast to coast, and New York and California – two of the most populous states in the country – have recorded the highest number of cases.

India provides vaccine hope When the media survey was conducted, fewer than 100 coronavirus cases had been confirmed in India, but a sharp increase in numbers soon led to the country’s Prime Minister imposing a nationwide lockdown. As the global race to develop a safe treatment for COVID-19 intensifies, many experts are looking to India. The country has emerged as a major vaccine manufacturer in recent years, developing treatments that are used against leprosy and polio. Several Indian firms have started work on a potential vaccine, but there are many obstacles to overcome, and millions of doses will be needed worldwide.

Data by medical encounter for the following conditions by age, race/ethnicity, and gender: Congenital Anomalies Maternal Complications

Visit https://www.sandiegocounty.gov/content/sdc/hhsa/programs/phs/maternal_child_family_health_services/MCFHSstatistics.html to view MCFHS perinatal health indicators, including: Live Births Low Birth Weight Teen Births Fetal Mortality Early Prenatal Care Infant Mortality Preterm Birth Maternal Deaths

Rates per 100,000 population. Age-adjusted rates per 100,000 2000 US standard population. Blank Cells: Rates not calculated for fewer than 11 events. Rates not calculated in cases where zip code is unknown. Geography not reported where there are no cases reported in a given year. SES: Is the median household income by SRA community. Data for SRAs only. *The COVID-19 pandemic was associated with increases in all-cause mortality. COVID-19 deaths have affected the patterns of mortality including those of Maternal Child Health conditions.

Data sources: California Department of Public Health, Center for Health Statistics, Office of Health Information and Research, Vital Records Business Intelligence System (VRBIS). California Department of Health Care Access and Information (HCAI), Emergency Department Database and Patient Discharge Database, 2020. SANDAG Population Estimates, 2020 (vintage: 09/2022). Population estimates were derived using the 2010 Census and data should be considered preliminary. Prepared by: County of San Diego, Health and Human Services Agency, Public Health Services, Community Health Statistics Unit, February 2023.

2020 Community Profile Data Guide and Data Dictionary Dashboard: https://public.tableau.com/app/profile/chsu/viz/2020CommunityProfilesDataGuideandDataDictionaryDashboard_16763944288860/HomePage