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

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

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.

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.

A. SUMMARY This dataset represents the COVID-19 vaccinations given to residents of San Francisco. All vaccines given to SF residents are included, no matter where the vaccination took place (the vaccine may have been administered in San Francisco or outside of San Francisco). The data are broken down by multiple demographic stratifications. This dataset also includes COVID-19 vaccinations given to SF residents by the San Francisco Department of Public Health (SFDPH).

Data provides counts for residents who have received at least one dose, residents who have completed a primary vaccine series, residents who have received one or two monovalent (not bivalent) booster doses, and residents who have received a bivalent booster dose. A primary vaccine series is complete after an individual has received all intended doses of the initial series. There are one, two, and three dose primary vaccine series.

B. HOW THE DATASET IS CREATED Information on doses administered to those who live in San Francisco is from the California Immunization Registry (CAIR2), run by the California Department of Public Health (CDPH). The information on individuals’ city of residence, age, race, and ethnicity are also recorded in CAIR and are self-reported at the time of vaccine administration.

In order to estimate the percent of San Franciscans vaccinated, we provide the 2016-2020 American Community Survey (ACS) population estimates for each demographic group.

C. UPDATE PROCESS Updated daily via automated process

D. HOW TO USE THIS DATASET 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).

Before analysis, you must filter the dataset to the desired stratification of data using the "overall_segment" column.

For example, filtering "overall_segment" to "All SF Residents by Age Bracket, Administered by All Providers" will filter the data to residents whose vaccinations were administered by any provider. You can then further segment the data and calculate percentages by Age Brackets.

If you filter "overall_segment" to "All SF Residents by Race/Ethnicity, Administered by DPH Only", you will see the race/ethnicity breakdown for residents who received vaccinations from the San Francisco Department of Public Health (SFDPH).

If you filter "overall_segment" to "All SF Residents by Age Group, Administered by All Providers" you will see vaccination counts of various age eligibility groups that were administered by any provider.

To count the number of individuals vaccinated (with any primary series dose), use the "total_recipients" column. To count the number of individuals who have completed their primary vaccine series, use the "total_series_completed" column. To count the number of primary series doses administered (1st, 2nd, 3rd, or single doses), use the "total_primary_series_doses" column.

To count the number of individuals who received one or two monovalent (not bivalent) booster doses, use the "total_booster_recipients" and "total_2nd_booster_recipients" columns. To count the number of individuals who received their first bivalent booster dose, use the "total_bivalent_booster_recipients" column. To count the number of monovalent (not including bivalent) or bivalent booster doses administered, use the "total_booster_doses" or "total_bivalent_booster_doses" columns.

E. ARCHIVED DATA A previous version of this dataset was archived on 10/27/2022. For historical purposes, you can access the archived dataset at the following link:

ARCHIVED: COVID-19 Vaccine Doses Given to San Franciscans by Demographics

F. CHA

This dataset provides values for CORONAVIRUS VACCINATION RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

A. SUMMARY This dataset represents all San Francisco (SF) residents who have received a vaccine for certain respiratory viruses that circulate more heavily in the fall and winter months. All vaccines given to SF residents are included, even if they received their vaccination elsewhere in California. The data are broken down by demographic and geographical stratifications. COVID-19: This dataset represents all SF residents who are considered up to date on their COVID-19 vaccine. A person is up to date if they have received at least one dose of the 2024–2025 COVID-19 vaccine. The specific up-to-date criteria can be found on the California Department of Public Health (CDPH) website. (Note: As of November 2024, this dataset only contains data regarding COVID-19 vaccinations. This documentation will be updated as other seasonal vaccination data is added). B. HOW THE DATASET IS CREATED Information on doses administered to those who live in SF is from the California Immunization Registry (CAIR2), run by CDPH. The information on individuals’ city of residence, age, race, and ethnicity are also recorded in CAIR and are self-reported at the time of vaccine administration. In order to estimate the percent of San Franciscans vaccinated, we provide the 2018-2022 American Community Survey (ACS) population estimates for each demographic group and analysis neighborhood. C. UPDATE PROCESS Updated daily via automated process. D. HOW TO USE THIS DATASET SF population estimates for race/ethnicity and age groups can be found in a view based on the San Francisco Population and Demographic Census dataset. SF population estimates for analysis neighborhoods can be found in a view based on the San Francisco Population and Geography Census dataset. Both of these views use population estimates from the 2018-2022 5-year ACS. Before analysis, you must filter the dataset to the desired stratification of data using the “vaccine_type” and "demographic_group" columns. For example, filtering “vaccine_type” to “COVID-19” will allow you to only look at rows corresponding to COVID-19 vaccinations. Filtering “demographic_subgroup” to “Analysis Neighborhood” will allow you to only look at rows corresponding to SF neighborhoods. You can then calculate the percentages of those up to date with their COVID-19 vaccinations by neighborhood. The “vaccine_subtype” field provides information about the current vaccine product being tracked in this dataset. E. CHANGE LOG 11/5/2024 - Dataset updated to reflect up to date status for the 2024-2025 monovalent formulation of the COVID-19 vaccine. 7/2/2024 - Population estimates were updated to reflect the most recent ACS data.

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-ZIP-Code/2ani-ic5x.

NOTE, 3/30/2023: We have added columns for bivalent (updated) doses to this dataset. We have also added age group columns for 0-17 and 18-64 and stopped updating the 5+ and 12+ columns, although previously published values remain for those columns.

COVID-19 vaccinations administered to Chicago residents based on the home ZIP Code of the person vaccinated, as provided by the medical provider in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE). The ZIP Code where a person lives is not necessarily the same ZIP Code where the vaccine was administered.

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 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.

·Total doses administered: Number of all COVID-19 vaccine doses administered.

Data Notes: Daily counts are shown for the total number of doses administered, number of people with at least one vaccine dose, number of people who have a completed vaccine series, and number of people who have received a bivalent dose. Cumulative totals for each measure as of that date are also provided. Vaccinations are counted based on the day the vaccine was administered.

Coverage percentages are calculated based on cumulative number of people who have received at least one vaccine dose, cumulative number of people who have a completed vaccine series, and cumulative number of people who have received a bivalent dose in each ZIP Code.

Population counts are from the U.S. Census Bureau American Community Survey 2015-2019 5-year estimates and can be seen in the ZIP Code, 2019 rows of the Chicago Population Counts dataset (https://data.cityofchicago.org/d/85cm-7uqa).

Actual counts may exceed population estimates and lead to >100% coverage, especially in areas with small population sizes. Additionally, the medical provider may report a work address or incorrect home address for the person receiving the vaccination which may lead to over or under estimates of vaccination coverage by geography. 

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.

For all datasets related to COVID-19, see https://data.cityofchicago.org/browse?limitTo=datasets&sortBy=alpha&tags=covid-19.

Data Source: Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE), U.S. Census Bureau American Community Survey

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 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.

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 over time. All vaccines given to people who live in San Francisco are included, no matter where the vaccination took place (the vaccine may have been administered in San Francisco or outside of San Francisco).

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, would only require a single dose for a resident to complete their primary vaccine series (as of December 21, 2021). The Pfizer vaccine for children under 5 requires three separate doses. Single dose vaccines counts are recorded in a separate column.

Summing the NEW_1ST_DOSES, NEW_2ND_DOSES, NEW_SINGLE_DOSES columns would give you the total count of primary vaccine series doses administered on a given day. To count the number of individuals who 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.

Regression analysis for composite unhappiness score and time by gender, census household pulse surveys, April 2020—April 2022.

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.

Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

This archived public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties.

The COVID-19 community levels were developed using a 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. The COVID-19 community level was 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 was classified as low, medium, or high.

COVID-19 Community Levels were used to 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.

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.

Archived Data Notes:

This dataset was renamed from "United States COVID-19 Community Levels by County as Originally Posted" to "United States COVID-19 Community Levels by County" on March 31, 2022.

March 31, 2022: Column name for county population was changed to “county_population”. No change was made to the data points previous released.

March 31, 2022: New column, “health_service_area_population”, was added to the dataset to denote the total population in the designated Health Service Area based on 2019 Census estimate.

March 31, 2022: FIPS codes for territories American Samoa, Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands were re-formatted to 5-digit numeric for records released on 3/3/2022 to be consistent with other records in the dataset.

March 31, 2022: Changes were made to the text fields in variables “county”, “state”, and “health_service_area” so the formats are consistent across releases.

March 31, 2022: The “%” sign was removed from the text field in column “covid_inpatient_bed_utilization”. No change was made to the data. As indicated in the column description, values in this column represent the percentage of staffed inpatient beds occupied by COVID-19 patients (7-day average).

March 31, 2022: Data values for columns, “county_population”, “health_service_area_number”, and “health_service_area” were backfilled for records released on 2/24/2022. These columns were added since the week of 3/3/2022, thus the values were previously missing for records released the week prior.

April 7, 2022: Updates made to data released on 3/24/2022 for Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands to correct a data mapping error.

April 21, 2022: COVID-19 Community Level (CCL) data released for counties in Nebraska for the week of April 21, 2022 have 3 counties identified in the high category and 37 in the medium category. CDC has been working with state officials to verify the data submitted, as other data systems are not providing alerts for substantial increases in disease transmission or severity in the state.

May 26, 2022: COVID-19 Community Level (CCL) data released for McCracken County, KY for the week of May 5, 2022 have been updated to correct a data processing error. McCracken County, KY should have appeared in the low community level category during the week of May 5, 2022. This correction is reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for several Florida counties for the week of May 19th, 2022, have been corrected for a data processing error. Of note, Broward, Miami-Dade, Palm Beach Counties should have appeared in the high CCL category, and Osceola County should have appeared in the medium CCL category. These corrections are reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for Orange County, New York for the week of May 26, 2022 displayed an erroneous case rate of zero and a CCL category of low due to a data source error. This county should have appeared in the medium CCL category.

June 2, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a data processing error. Tolland County, CT should have appeared in the medium community level category during the week of May 26, 2022. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a misspelling. The medium community level category for Tolland County, CT on the week of May 26, 2022 was misspelled as “meduim” in the data set. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Mississippi counties for the week of June 9, 2022 should be interpreted with caution due to a reporting cadence change over the Memorial Day holiday that resulted in artificially inflated case rates in the state.

July 7, 2022: COVID-19 Community Level (CCL) data released for Rock County, Minnesota for the week of July 7, 2022 displayed an artificially low case rate and CCL category due to a data source error. This county should have appeared in the high CCL category.

July 14, 2022: COVID-19 Community Level (CCL) data released for Massachusetts counties for the week of July 14, 2022 should be interpreted with caution due to a reporting cadence change that resulted in lower than expected case rates and CCL categories in the state.

July 28, 2022: COVID-19 Community Level (CCL) data released for all Montana counties for the week of July 21, 2022 had case rates of 0 due to a reporting issue. The case rates have been corrected in this update.

July 28, 2022: COVID-19 Community Level (CCL) data released for Alaska for all weeks prior to July 21, 2022 included non-resident cases. The case rates for the time series have been corrected in this update.

July 28, 2022: A laboratory in Nevada reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate will be inflated in Clark County, NV for the week of July 28, 2022.

August 4, 2022: COVID-19 Community Level (CCL) data was updated on August 2, 2022 in error during performance testing. Data for the week of July 28, 2022 was changed during this update due to additional case and hospital data as a result of late reporting between July 28, 2022 and August 2, 2022. Since the purpose of this data set is to provide point-in-time views of COVID-19 Community Levels on Thursdays, any changes made to the data set during the August 2, 2022 update have been reverted in this update.

August 4, 2022: COVID-19 Community Level (CCL) data for the week of July 28, 2022 for 8 counties in Utah (Beaver County, Daggett County, Duchesne County, Garfield County, Iron County, Kane County, Uintah County, and Washington County) case data was missing due to data collection issues. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 4, 2022: Due to a reporting cadence change, case rates for all Alabama counties will be lower than expected. As a result, the CCL levels published on August 4, 2022 should be interpreted with caution.

August 11, 2022: COVID-19 Community Level (CCL) data for the week of August 4, 2022 for South Carolina have been updated to correct a data collection error that resulted in incorrect case data. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 18, 2022: COVID-19 Community Level (CCL) data for the week of August 11, 2022 for Connecticut have been updated to correct a data ingestion error that inflated the CT case rates. CDC, in collaboration with CT, has resolved the issue and the correction is reflected in this update.

August 25, 2022: A laboratory in Tennessee reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate may be inflated in many counties and the CCLs published on August 25, 2022 should be interpreted with caution.

August 25, 2022: Due to a data source error, the 7-day case rate for St. Louis County, Missouri, is reported as zero in the COVID-19 Community Level data released on August 25, 2022. Therefore, the COVID-19 Community Level for this county should be interpreted with caution.

September 1, 2022: Due to a reporting issue, case rates for all Nebraska counties will include 6 days of data instead of 7 days in the COVID-19 Community Level (CCL) data released on September 1, 2022. Therefore, the CCLs for all Nebraska counties should be interpreted with caution.

September 8, 2022: Due to a data processing error, the case rate for Philadelphia County, Pennsylvania,

Regression analysis for composite unhappiness scores by education levels, COVID-19 and vaccinations, 2021 & 2022.

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 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.

CDC is collaborating with Vitalant Research Institute, American Red Cross, and Westat Inc. to conduct a nationwide COVID-19 seroprevalence survey of blood donors. De-identified blood samples are tested for antibodies to SARS-CoV-2 to better understand the percentage of people in the United States who have antibodies against SARS-CoV-2 (the virus that causes COVID-19) and to track how this percentage changes over time. Both SARS-CoV-2 infection and COVID-19 vaccines currently used in the United States result in production of anti-spike (anti-S) antibodies but only infection results in production of anti-nucleocapsid (anti-N) antibodies. Infection-induced seroprevalence estimates the proportion of the population with antibody evidence of previous SARS-CoV-2 infection and refers to the percent of the population with anti-nucleocapsid antibodies. Combined infection-Induced and Vaccination-Induced seroprevalence estimates the proportion of the population with antibody evidence of previous SARS-CoV-2 infection, COVID-19 vaccination, or both, and refers to the percent of the population that has anti-spike antibodies, anti-nucleocapsid antibodies, or both.

This link connects to a webpage that displays the data from the Nationwide Blood Donor Seroprevalence Survey. It offers an interactive visualization available at https://covid.cdc.gov/covid-data-tracker/#nationwide-blood-donor-seroprevalence-2022

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

IntroductionVaccine-preventable diseases continue to cause morbidity and mortality despite the introduction of childhood immunizations. Recent media reports from Canada and the United States of America (USA) have highlighted a rise in childhood illnesses like measles, which could have been prevented with vaccines. Parents play a pivotal role in ensuring their children receive timely vaccinations. Immunization reminders can help parents who forget or miss vaccination appointments. In the USA, current literature indicates that Black children have lower vaccination rates than other racialized children and vaccine reminders may improve measles vaccine uptake among Black parents. However, there is limited data in Canada on vaccine uptake in children of Black parents, with evidence suggesting vaccine hesitancy among the Black population.ObjectiveThis scoping review aims to map out existing literature on immunization reminder strategies among parents to identify their impact in improving childhood vaccination rates and promoting child health.Inclusion criteriaThe review will include studies conducted in Canada and the United States of America that focus on immunization reminders for parents who have children under six years and published in English between 2015 and 2025.MethodsDatabase and hand-searching of journals and gray literature will be carried out to retrieve pertinent articles. Studies that meet the inclusion criteria will be eligible for selection. The process of selecting eligible studies will then be summarized on a PRISMA-ScR chart. Collated in data-extraction tables will be authorship information, publication date, methods and findings. The findings, key arguments and themes will be analyzed using a thematic analysis and summarized using a narrative summary.ConclusionThis review will contribute to the existing knowledge on parental preferences for vaccine reminder strategies and their usefulness in increasing childhood vaccination rates. The findings will inform and improve public health strategies aimed at boosting vaccine uptake among children.