NOTE: This dataset has been retired and marked as historical-only. Weekly rates of COVID-19 cases, hospitalizations, and deaths among people living in Chicago by vaccination status and age. Rates for fully vaccinated and unvaccinated begin the week ending April 3, 2021 when COVID-19 vaccines became widely available in Chicago. Rates for boosted begin the week ending October 23, 2021 after booster shots were recommended by the Centers for Disease Control and Prevention (CDC) for adults 65+ years old and adults in certain populations and high risk occupational and institutional settings who received Pfizer or Moderna for their primary series or anyone who received the Johnson & Johnson vaccine. Chicago residency is based on home address, as reported in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE) and Illinois National Electronic Disease Surveillance System (I-NEDSS). Outcomes: • Cases: People with a positive molecular (PCR) or antigen COVID-19 test result from an FDA-authorized COVID-19 test that was reported into I-NEDSS. A person can become re-infected with SARS-CoV-2 over time and so may be counted more than once in this dataset. Cases are counted by week the test specimen was collected. • Hospitalizations: COVID-19 cases who are hospitalized due to a documented COVID-19 related illness or who are admitted for any reason within 14 days of a positive SARS-CoV-2 test. Hospitalizations are counted by week of hospital admission. • Deaths: COVID-19 cases who died from COVID-19-related health complications as determined by vital records or a public health investigation. Deaths are counted by week of death. Vaccination status: • Fully vaccinated: Completion of primary series of a U.S. Food and Drug Administration (FDA)-authorized or approved COVID-19 vaccine at least 14 days prior to a positive test (with no other positive tests in the previous 45 days). • Boosted: Fully vaccinated with an additional or booster dose of any FDA-authorized or approved COVID-19 vaccine received at least 14 days prior to a positive test (with no other positive tests in the previous 45 days). • Unvaccinated: No evidence of having received a dose of an FDA-authorized or approved vaccine prior to a positive test. CLARIFYING NOTE: Those who started but did not complete all recommended doses of an FDA-authorized or approved vaccine prior to a positive test (i.e., partially vaccinated) are excluded from this dataset. Incidence rates for fully vaccinated but not boosted people (Vaccinated columns) are calculated as total fully vaccinated but not boosted with outcome divided by cumulative fully vaccinated but not boosted at the end of each week. Incidence rates for boosted (Boosted columns) are calculated as total boosted with outcome divided by cumulative boosted at the end of each week. Incidence rates for unvaccinated (Unvaccinated columns) are calculated as total unvaccinated with outcome divided by total population minus cumulative boosted, fully, and partially vaccinated at the end of each week. All rates are multiplied by 100,000. Incidence rate ratios (IRRs) are calculated by dividing the weekly incidence rates among unvaccinated people by those among fully vaccinated but not boosted and boosted people. Overall age-adjusted incidence rates and IRRs are standardized using the 2000 U.S. Census standard population. Population totals are from U.S. Census Bureau American Community Survey 1-year estimates for 2019. All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. This dataset reflects data known to CDPH at the time when the dataset is updated each week. Numbers in this dataset may differ from other public sources due to when data are reported and how City of Chicago boundaries are defined. For all datasets related to COVID-19, see https://data.cityofchic

After October 13, 2022, this dataset will no longer be updated as the related CDC COVID Data Tracker site was retired on October 13, 2022.

This dataset contains historical trends in vaccinations and cases by age group, at the US national level. Data is stratified by at least one dose and fully vaccinated. Data also represents all vaccine partners including jurisdictional partner clinics, retail pharmacies, long-term care facilities, dialysis centers, Federal Emergency Management Agency and Health Resources and Services Administration partner sites, and federal entity facilities.

NOTE: This dataset has been retired and marked as historical-only. The recommended dataset to use in its place is https://data.cityofchicago.org/Health-Human-Services/COVID-19-Vaccination-Coverage-Citywide/6859-spec. COVID-19 vaccinations administered to Chicago residents based on the reported race-ethnicity and age group of the person vaccinated, as provided by the medical provider in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE). Vaccination Status Definitions: ·People with at least one vaccine dose: Number of people who have received at least one dose of any COVID-19 vaccine, including the single-dose Johnson & Johnson COVID-19 vaccine. ·People with a completed vaccine series: Number of people who have completed a primary COVID-19 vaccine series. Requirements vary depending on age and type of primary vaccine series received. ··People with an original booster dose: Number of people who have a completed vaccine series and have received at least one additional monovalent dose. This includes people who received a monovalent booster dose and immunocompromised people who received an additional primary dose of COVID-19 vaccine. Monovalent doses were created from the original strain of the virus that causes COVID-19. People with a bivalent dose: Number of people who received a bivalent (updated) dose of vaccine. Updated, bivalent doses became available in Fall 2022 and were created with the original strain of COVID-19 and newer Omicron variant strains. Weekly cumulative totals by vaccination status are shown for each combination of race-ethnicity and age group. Note that each age group has a row where race-ethnicity is "All" so care should be taken when summing rows. Vaccinations are counted based on the date on which they were administered. Weekly cumulative totals are reported from the week ending Saturday, December 19, 2020 onward (after December 15, when vaccines were first administered in Chicago) through the Saturday prior to the dataset being updated. Population counts are from the U.S. Census Bureau American Community Survey (ACS) 2019 1-year estimates. For some of the age groups by which COVID-19 vaccine has been authorized in the United States, race-ethnicity distributions were specifically reported in the ACS estimates. For others, race-ethnicity distributions were estimated by the Chicago Department of Public Health (CDPH) by weighting the available race-ethnicity distributions, using proportions of constituent age groups. Coverage percentages are calculated based on the cumulative number of people in each population subgroup (age group by race-ethnicity) who have each vaccination status as of the date, divided by the estimated number of Chicago residents in each subgroup. Actual counts may exceed population estimates and lead to >100% coverage, especially in small race-ethnicity subgroups of each age group. All coverage percentages are capped at 99%. All data are provisional and subject to change. Information is updated as additional details are received and it is, in fact, very common for recent dates to be incomplete and to be updated as time goes on. At any given time, this dataset reflects data currently known to CDPH. Numbers in this dataset may differ from other public sources due to when data are reported and how City of Chicago boundaries are defined. CDPH uses the most complete data available to estimate COVID-19 vaccination coverage among Chicagoans, but there are several limitations that impact our estimates. Data reported in I-CARE only include doses administered in Illinois and some doses administered outside of Illinois reported historically by Illinois providers. Doses administered by the federal Bureau of Prisons and Department of Defense are also not currently reported in I-CARE. The Veterans Health Administration began reporting doses in I-CARE beginning September 2022. Due to people receiving vaccinations that are not recorded in I-CARE that c

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.

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.

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 12+ and age 5+ denominators have been uploaded as archived tables.

Starting June 30, 2021, the dataset has been reconfigured so that all updates are appended to one dataset to make it easier for API and other interfaces. In addition, historical data has been extended back to January 5, 2021.

This dataset shows full, partial, and at least 1 dose coverage rates by zip code tabulation area (ZCTA) for the state of California. Data sources include the California Immunization Registry and the American Community Survey’s 2015-2019 5-Year data.

This is the data table for the LHJ Vaccine Equity Performance dashboard. However, this data table also includes ZTCAs that do not have a VEM score.

This dataset also includes Vaccine Equity Metric score quartiles (when applicable), which combine the Public Health Alliance of Southern California’s Healthy Places Index (HPI) measure with CDPH-derived scores to estimate factors that impact health, like income, education, and access to health care. ZTCAs range from less healthy community conditions in Quartile 1 to more healthy community conditions in Quartile 4.

The Vaccine Equity Metric is for weekly vaccination allocation and reporting purposes only. CDPH-derived quartiles should not be considered as indicative of the HPI score for these zip codes. CDPH-derived quartiles were assigned to zip codes excluded from the HPI score produced by the Public Health Alliance of Southern California due to concerns with statistical reliability and validity in populations smaller than 1,500 or where more than 50% of the population resides in a group setting.

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.

For some ZTCAs, vaccination coverage may exceed 100%. This may be a result of many people from outside the county coming to that ZTCA to get their vaccine and providers reporting the county of administration as the county of residence, and/or the DOF estimates of the population in that ZTCA are too low. Please note that population numbers provided by DOF are projections and so may not be accurate, especially given unprecedented shifts in population as a result of the pandemic.

Percentage distribution of respondents by source of information about COVID-19 vaccines and race/ethnicity, as well as percentage of those fully vaccinated in each sub-group, 2023.

The COVID-19 pandemic highlighted the crucial role of vaccines in controlling the virus. Despite their effectiveness, however, vaccine hesitancy remained a challenge, particularly within certain population groups. This multi-disciplinary study investigates the diverse socio-demographic factors influencing COVID-19 vaccination decisions in the United States. Through a nationally representative survey of 5,240 people, the research explores the interplay of information sources, religious beliefs, political party, and demographic characteristics of the respondents. Our findings reveal associations of main sources of information with vaccination likelihood, with the Centers for Disease Control and Prevention demonstrating the highest association with full vaccination. Religious beliefs are significant determinants, with Evangelical Protestants exhibiting the lowest vaccination rates. We also highlight the intricate relationship between political leanings and vaccination behavior, emphasizing higher levels of vaccination among Democrats. Demographic variables, including age, education, gender, and race/ethnicity, also play pivotal roles, exposing disparities in vaccination access and decisions. In particular, older individuals and those with higher levels of education show a greater inclination to achieve full vaccination, while women and African Americans are less likely to attain complete vaccination. Lastly, while major ethnoracial groups seem to respond to different sources of information similarly, there are also nuanced differences, such as Asians being especially likely to be fully vaccinated if they depend on the CDC or other health sources while more disadvantaged groups seem less responsive to these sources. Overall, this research provides a comprehensive analysis of the nuanced factors shaping vaccination behavior. It contributes valuable knowledge to public health strategies, emphasizing the need for targeted communication campaigns tailored to diverse communities.

The dataset provides valuable insights into COVID-19 vaccine hesitancy at the county level in Oklahoma. It includes key variables such as the FIPS code and county name for identification purposes, along with estimates of hesitancy levels and social vulnerability index (SVI) categories. These indicators enable users to assess the prevalence of vaccine hesitancy and identify areas that may require targeted intervention and educational campaigns. Additionally, the CVAC level of concern for vaccination rollout offers insights into community readiness and helps tailor vaccination strategies accordingly. Furthermore, demographic variables such as ethnicity breakdowns allow for a nuanced understanding of vaccine uptake among different population groups, facilitating targeted outreach efforts to address disparities and improve overall vaccination coverage.Note: Due to constraints in ArcGIS Pro, the data variables are truncated in the provided dataset. For a clear understanding of the variables, please refer to the table provided below.Variable (CSV)Variable (Shapefile)DescriptionFIPS CodeFIPS CodeFederal Information Processing Standards (FIPS) code for identifying counties.County NameCounty NameName of the county.StateStateName of the state.Estimated hesitantEstimatedEstimated percentage of population hesitant or unsure about COVID-19 vaccination.Estimated hesitant or unsureEstimate_1Estimated percentage of population hesitant or unsure about COVID-19 vaccination.Estimated strongly hesitantEstimate_2Estimated percentage of population strongly hesitant about COVID-19 vaccination.Social Vulnerability Index (SVI)Social VulA measure of the resilience of communities when confronted by external stresses on human health.SVI categorySVI categoCategorization of Social Vulnerability Index (SVI) based on specific thresholds.CVAC level of concern for vaccination rolloutCVAC levelLevel of concern for COVID-19 vaccination rollout, as determined by the Community Vaccine Advisory Committee (CVAC).Percent adults fully vaccinated against COVID-19Percent adPercentage of adults fully vaccinated against COVID-19 as of a specific date.Percent HispanicPercent HiPercentage of Hispanic population in the county.Percent non-Hispanic American Indian/Alaska NativeNon-HispanPercentage of non-Hispanic American Indian/Alaska Native population in the county.Percent non-Hispanic AsianNon-Hisp_1Percentage of non-Hispanic Asian population in the county.Percent non-Hispanic BlackNon-Hisp_2Percentage of non-Hispanic Black population in the county.Percent non-Hispanic Native Hawaiian/Pacific IslanderNon-Hisp_3Percentage of non-Hispanic Native Hawaiian/Pacific Islander population in the county.Percent non-Hispanic WhiteNon-HispaPercentage of non-Hispanic White population in the county.

The COVID-19 pandemic highlighted the crucial role of vaccines in controlling the virus. Despite their effectiveness, however, vaccine hesitancy remained a challenge, particularly within certain population groups. This multi-disciplinary study investigates the diverse socio-demographic factors influencing COVID-19 vaccination decisions in the United States. Through a nationally representative survey of 5,240 people, the research explores the interplay of information sources, religious beliefs, political party, and demographic characteristics of the respondents. Our findings reveal associations of main sources of information with vaccination likelihood, with the Centers for Disease Control and Prevention demonstrating the highest association with full vaccination. Religious beliefs are significant determinants, with Evangelical Protestants exhibiting the lowest vaccination rates. We also highlight the intricate relationship between political leanings and vaccination behavior, emphasizing higher levels of vaccination among Democrats. Demographic variables, including age, education, gender, and race/ethnicity, also play pivotal roles, exposing disparities in vaccination access and decisions. In particular, older individuals and those with higher levels of education show a greater inclination to achieve full vaccination, while women and African Americans are less likely to attain complete vaccination. Lastly, while major ethnoracial groups seem to respond to different sources of information similarly, there are also nuanced differences, such as Asians being especially likely to be fully vaccinated if they depend on the CDC or other health sources while more disadvantaged groups seem less responsive to these sources. Overall, this research provides a comprehensive analysis of the nuanced factors shaping vaccination behavior. It contributes valuable knowledge to public health strategies, emphasizing the need for targeted communication campaigns tailored to diverse communities.

Odds ratios and exponentials of standard errors from a multivariate logistic regression model predicting whether individuals are fully vaccinated for COVID-19, 2023.

Odds ratios and exponentials of standard errors from a multivariate logistic regression model for each race/ethnicity category predicting whether individuals are fully vaccinated for COVID-19, 2023.

As of 10/27/2022, this dataset will no longer update. To continue to access updated vaccination metrics given to SF residents, including newly added bivalent boosters, please navigate to the following page: COVID-19 Vaccinations Given to SF Residents Over Time.

A. SUMMARY This dataset represents the COVID-19 vaccinations given to San Franciscans by the San Francisco Department of Public Health (SF DPH) over time.

B. HOW THE DATASET IS CREATED Information on doses administered to those who live in San Francisco is from the California Immunization Registry (CAIR), run by the California Department of Public Health (CDPH).

C. UPDATE PROCESS Updated daily via automated process

D. HOW TO USE THIS DATASET Different vaccines have different dosage requirements. For example, the Moderna and the Pfizer vaccines require two doses in order for a resident to complete their primary vaccine series (as of December 21, 2021). Each dose is recorded separately in its respective dataset column. Other vaccines, such as Johnson & Johnson, only require a single dose for a resident to complete their primary vaccine series (as of December 21, 2021). Single dose vaccines counts are recorded in a separate dataset column.

Summing the NEW_1ST_DOSES, NEW_2ND_DOSES, NEW_SINGLE_DOSES columns gives you the total count of primary vaccine series doses administered on a given day. To count the number of individuals that have completed their primary vaccine series on a given day, use the NEW_SERIES_COMPLETED column. To count the number of individuals vaccinated (with any primary series dose) for the first time on a given day, use the NEW_RECIPIENTS column.

To count the number of individuals who got a vaccine booster on a given day, use the NEW_BOOSTER_RECIPIENTS column. To count the number of booster doses administered on a given day, use the NEW_BOOSTER_DOSES column. To count the total number of individuals who have received a booster over time, use the CUMULATIVE_BOOSTER_RECIPIENTS column. To count the total number of booster doses that have been administered over time, use the CUMULATIVE_BOOSTER_DOSES column.

In our public dashboards we combine this dataset with the US Census's 2019 five-year American Community Survey population estimates to estimate the percent of San Franciscans vaccinated.

Vaccinated vs. Unvaccinated.

Distribution of study population characteristics by vaccination status in each study period.