Note: In these datasets, a person is defined as up to date if they have received at least one dose of an updated COVID-19 vaccine. The Centers for Disease Control and Prevention (CDC) recommends that certain groups, including adults ages 65 years and older, receive additional doses.

On 6/16/2023 CDPH replaced the booster measures with a new “Up to Date” measure based on CDC’s new recommendations, replacing the primary series, boosted, and bivalent booster metrics The definition of “primary series complete” has not changed and is based on previous recommendations that CDC has since simplified. A person cannot complete their primary series with a single dose of an updated vaccine. Whereas the booster measures were calculated using the eligible population as the denominator, the new up to date measure uses the total estimated population. Please note that the rates for some groups may change since the up to date measure is calculated differently than the previous booster and bivalent measures.

This data is from the same source as the Vaccine Progress Dashboard at https://covid19.ca.gov/vaccination-progress-data/ which summarizes vaccination data at the county level by county of residence. Where county of residence was not reported in a vaccination record, the county of provider that vaccinated the resident is included. This applies to less than 1% of vaccination records. The sum of county-level vaccinations does not equal statewide total vaccinations due to out-of-state residents vaccinated in California.

These data do not include doses administered by the following federal agencies who received vaccine allocated directly from CDC: Indian Health Service, Veterans Health Administration, Department of Defense, and the Federal Bureau of Prisons.

Totals for the Vaccine Progress Dashboard and this dataset may not match, as the Dashboard totals doses by Report Date and this dataset totals doses by Administration Date. Dose numbers may also change for a particular Administration Date as data is updated.

Previous updates:

• On March 3, 2023, with the release of HPI 3.0 in 2022, the previous equity scores have been updated to reflect more recent community survey information. This change represents an improvement to the way CDPH monitors health equity by using the latest and most accurate community data available. The HPI uses a collection of data sources and indicators to calculate a measure of community conditions ranging from the most to the least healthy based on economic, housing, and environmental measures.

• Starting on July 13, 2022, the denominator for calculating vaccine coverage has been changed from age 5+ to all ages to reflect new vaccine eligibility criteria. Previously the denominator was changed from age 16+ to age 12+ on May 18, 2021, then changed from age 12+ to age 5+ on November 10, 2021, to reflect previous changes in vaccine eligibility criteria. The previous datasets based on age 16+ and age 5+ denominators have been uploaded as archived tables.

• Starting on May 29, 2021 the methodology for calculating on-hand inventory in the shipped/delivered/on-hand dataset has changed. Please see the accompanying data dictionary for details. In addition, this dataset is now down to the ZIP code level.

**Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool ** As of January 26, 2023, the population counts are based on Statistics Canada’s 2021 estimates. The coverage methodology has been revised to calculate age based on the current date and deceased individuals are no longer included. The method used to count daily dose administrations has changed is now based on the date delivered versus the day entered into the data system. Historical data has been updated. Please note that Cases by Vaccination Status data will no longer be published as of June 30, 2022. Please note that case rates by vaccination status and age group data will no longer be published as of July 13, 2022. Please note that Hospitalization by Vaccination Status data will no longer be published as of June 30, 2022. Learn more about COVID-19 vaccines. ##Data includes: * daily and total doses administered * individuals with at least one dose * individuals fully vaccinated * total doses given to fully vaccinated individuals * vaccinations by age * percentage of age group * individuals with at least one dose, by PHU, by age group * individuals fully vaccinated, by PHU, by age group * COVID-19 cases by status: not fully vaccinated, fully vaccinated, vaccinated with booster * individuals in hospital due to COVID-19 (excluding ICU) by status: unvaccinated, partially vaccinated, fully vaccinated * individuals in ICU due to COVID-19 by status: unvaccinated, partially vaccinated, fully vaccinated, unknown * rate of COVID-19 cases per 100,000 by status and age group * rate per 100,000 (7-day average) by status and age group All data reflects totals from 8 p.m. the previous day. This dataset is subject to change. Additional notes * Data entry of vaccination records is still in progress, therefore the dosage data may not be a full representation of all vaccination doses administered in Ontario. * The data does not include dosage data where consent was not provided for vaccination records to be entered into the provincial CoVax system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information into CoVax. ##Hospitalizations and cases by vaccination status Hospitalizations * This is a new data collection and the data quality will continue to improve as hospitals continue to submit data. * In order to understand the vaccination status of patients currently hospitalized, a new data collection process was developed and this may cause discrepancies between other hospitalization numbers being collected using a different data collection process. * Data on patients in ICU are being collected from two different data sources with different extraction times and public reporting cycles. The existing data source (Critical Care Information System, CCIS) does not have vaccination status. * Historical data for hospitalizations by region may change over time as hospitals update previously entered data. * Due to incomplete weekend and holiday reporting, vaccination status data for hospital and ICU admissions is not updated on Sundays, Mondays and the day after holidays * Unvaccinated is defined as not having any dose, or between 0-13 days after administration of the first dose of a COVID-19 vaccine. * Partially vaccinated is defined as 14 days or more after the first dose of a 2-dose series COVID-19 vaccine, or between 0-13 days after administration of the second dose * Fully vaccinated is defined as 14 days or more after receipt of the second dose of a 2-dose series COVID-19 vaccine Cases * The cases by vaccination status may not match the daily COVID-19 case count because records with a missing or invalid health card number cannot be linked.

This dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool Data includes: * Date on which the death occurred * Age group * 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster ##Additional notes As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm. As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category. 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. 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. The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON. “Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results. Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts. Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different. Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported. Rates for the most recent days are subject to reporting lags All data reflects totals from 8 p.m. the previous day. This dataset is subject to change.

On 6/28/2023, data on cases by vaccination status will be archived and will no longer update.

A. SUMMARY This dataset represents San Francisco COVID-19 positive confirmed cases by vaccination status over time, starting January 1, 2021. Cases are included on the date the positive test was collected (the specimen collection date). Cases are counted in three categories: (1) all cases; (2) unvaccinated cases; and (3) completed primary series cases.

1. All cases: Includes cases among all San Francisco residents regardless of vaccination status.

2. Unvaccinated cases: Cases are considered unvaccinated if their positive COVID-19 test was before receiving any vaccine. Cases that are not matched to a COVID-19 vaccination record are considered unvaccinated.

3. Completed primary series cases: Cases are considered completed primary series if their positive COVID-19 test was 14 days or more after they received their 2nd dose in a 2-dose COVID-19 series or the single dose of a 1-dose vaccine. These are also called “breakthrough cases.”

On September 12, 2021, a new case definition of COVID-19 was introduced that includes criteria for enumerating new infections after previous probable or confirmed infections (also known as reinfections). A reinfection is defined as a confirmed positive PCR lab test more than 90 days after a positive PCR or antigen test. The first reinfection case was identified on December 7, 2021.

Data is lagged by eight days, meaning the most recent specimen collection date included is eight days prior to today. All data updates daily as more information becomes available.

B. HOW THE DATASET IS CREATED Case information is based on confirmed positive laboratory tests reported to the City. The City then completes quality assurance and other data verification processes. Vaccination data comes from the California Immunization Registry (CAIR2). The California Department of Public Health runs CAIR2. Individual-level case and vaccination data are matched to identify cases by vaccination status in this dataset. Case records are matched to vaccine records using first name, last name, date of birth, phone number, and email address.

We include vaccination records from all nine Bay Area counties in order to improve matching rates. This allows us to identify breakthrough cases among people who moved to the City from other Bay Area counties after completing their vaccine series. Only cases among San Francisco residents are included.

C. UPDATE PROCESS Updates automatically at 08:00 AM Pacific Time each day.

D. HOW TO USE THIS DATASET Total San Francisco population estimates 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). To identify total San Francisco population estimates, filter the view on “demographic_category_label” = “all ages”.

Population estimates by vaccination status are derived from our publicly reported vaccination counts, which can be found at COVID-19 Vaccinations Given to SF Residents Over Time.

The dataset includes new cases, 7-day average new cases, new case rates, 7-day average new case rates, percent of total cases, and 7-day average percent of total cases for each vaccination category.

New cases are the count of cases where the positive tests were collected on that specific specimen collection date. The 7-day rolling average shows the trend in new cases. The rolling average is calculated by averaging the new cases for a particular day with the prior 6 days.

New case rates are the count of new cases per 100,000 residents in each vaccination status group. The 7-day rolling average shows the trend in case rates. The rolling average is calculated by averaging the case rate for a particular day with the prior six days. Percent of total new cases shows the percent of all cases on each day that were among a particular vaccination status.

Here is more information on how each case rate is calculated:

1. The case rate for all cases is equal to the number of new cases among all residents divided by the estimated total resident population.

2. Unvaccinated case rates are equal to the number of new cases among unvaccinated residents divided by the estimated number of unvaccinated residents. The estimated number of unvaccinated residents is calculated by subtracting the number of residents that have received at least one dose of a vaccine from the total estimated resident population.

3. Completed primary series case rates are equal to the number of new cases among completed primary series residents divided by the estimated number of completed primary series residents. The estimated number of completed primary series residents is calculated by taking the number of residents who have completed their primary series over time and adding a 14-day delay to the “date_administered” column, to align with the definition of “Completed primary series cases” above.

E. CHANGE LOG

• 6/28/2023 - data on cases by vaccination status are no longer being updated. This data is currently through 6/20/2023 (as of 6/28/2023) and will not include any new data after this date.
  
• 4/6/2023 - the State implemented system updates to improve the integrity of historical data.
• 2/21/2023 - system updates to improve reliability and accuracy of cases data were implemented.
• 1/31/2023 - updated “sf_population” column to reflect the 2020 Census Bureau American Community Survey (ACS) San Francisco Population estimates.
• 1/31/2023 - renamed column “last_updated_at” to “data_as_of”.
• 1/22/2022 - system updates to improve timeliness and accuracy of cases and deaths data were implemented.
• 7/15/2022 - reinfections added to cases dataset. See section SUMMARY for more information on how reinfections are identified.
• 7/15/2022 - references to “fully vaccinated” replaced with “completed primary series” in column “vaccination_status".
• 7/15/2022 - rows with “partially vaccinated” in column “vaccination_status” removed from dataset.

IntroductionCOVID-19 vaccine inequities have been widespread across California, the United States, and globally. As COVID-19 vaccine inequities have not been fully understood in the youth population, it is vital to determine possible factors that drive inequities to enable actionable change that promotes vaccine equity among vulnerable minor populations.MethodsThe present study used the social vulnerability index (SVI) and daily vaccination numbers within the age groups of 12–17, 5–11, and under 5 years old across all 58 California counties to model the growth velocity and the anticipated maximum proportion of population vaccinated.ResultsOverall, highly vulnerable counties, when compared to low and moderately vulnerable counties, experienced a lower vaccination rate in the 12–17 and 5–11 year-old age groups. For age groups 5–11 and under 5 years old, highly vulnerable counties are expected to achieve a lower overall total proportion of residents vaccinated. In highly vulnerable counties in terms of socioeconomic status and household composition and disability, the 12–17 and 5–11 year-old age groups experienced lower vaccination rates. Additionally, in the 12–17 age group, high vulnerability counties are expected to achieve a higher proportion of residents vaccinated compared to less vulnerable counterparts.DiscussionThese findings elucidate shortcomings in vaccine uptake in certain pediatric populations across California and may help guide health policies and future allocation of vaccines, with special emphasis placed on vulnerable populations, especially with respect to socioeconomic status and household composition and disability.

Context

Vaccinations provide people the ability to develop immunity to particular diseases. When the majority of a population is vaccinated, “herd immunity” protects those who have not been vaccinated by blocking the spread of these diseases. A medical research paper published by The Lancet in 1998 suggested an association between the Measles/Mumps/Rubella (MMR) vaccine and Autism spectrum disorders. The paper was later fully-retracted due controversy surrounding the lead author, who had financial conflicts of interest and allegedly manipulated the study data. However, it generated worldwide concern over the safety of MMR and other types of vaccines, including Diphtheria/Tetanus/Pertussis (DTP).

In California by 2010, the growing trend for parents to opt out of having their children receive vaccines over the following decade coincided with the largest Pertussis outbreak in more than 60 years. Reduced vaccination frequency was also linked to a high-profile measles outbreak in 2014 that began at Disneyland. The resulting California state legislation (Senate Bill 277), signed June 2015, made it much more difficult for parents to opt out of vaccinations for their children. The data set will allow you to explore individual public and private school vaccination rates of incoming Kindergarten students for the 2000 to 2014 school years.

Content

The data are records for every school with ten or more students reporting the number of incoming Kindergarteners who provided either proof of immunization, personal beliefs exemption (PBE), or permanent medical exemption (PME). Annual records for the 2000-2001 through 2014-2015 school years have been formatted and combined. Common variables in these annual data sets included in the merged file are the number of students, school name, school county, the number of PBEs, PMEs, and number of students vaccinated for:

• Diphtheria/Tetanus/Pertussis (DTP)
• Polio
• Measles/Mumps/Rubella (MMR)

One additional file contains 5 years of county-level Pertussis case numbers and rates. Another additional data file contains the number of infant Pertussis cases for infants under three months old for each county in California between 2014-2015.

Geographic data are available in a file based on scripted geocode calls using the ggmap R package to find latitude and longitude data using the school names and county names. Not all calls returned a valid coordinate, so additional indicator variables in this file indicate the quality of the match. The isSchool indicator variable is 1 if the geocode search meta data included "school" and the countyMatch indicator is 1 if the latitude and longitude coordinates are contained within the appropriate county in CA.

References:

1. Retracted Lancet Research Article
2. Report on 2010 Pertussis Outbreak

Acknowledgements

Individual data files and detailed annual reports for every school year in this data set are provided by the California Department of Public Health (CDPH). Individual schools and licensed child care facilities are required to report immunization information to CDPH every year to maintain compliance with the California Health and Safety Code. Additional details as well as child care and 7th grade data files can be found on the CDPH website: https://www.cdph.ca.gov/programs/immunize/Pages/ImmunizationLevels.aspx

County level case data were pulled from the following report: https://archive.cdph.ca.gov/programs/immunize/Documents/Pertussis_Report_1-7-2015.pdf

Infant Pertussis data were reported to CDPH as of 2/10/2016. Additional Pertussis reports can be found here: https://www.cdph.ca.gov/programs/immunize/Pages/PertussisSummaryReports.aspx

Inspiration

While the Disneyland measles outbreak received much media attention, Pertussis outbreaks in California present great health risks to infants and the elderly. Can you predict which counties and schools are at greatest risk for outbreaks and/or quantify the association between vaccination rates and the number infant Pertussis cases?