Deaths counts for influenza, pneumonia, and COVID-19 reported to NCHS by week ending date, by state and HHS region, and age group.

Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretabilty. We also formatted the data into a standard data format.

Each Project Tycho dataset contains case counts for a specific condition (e.g. measles) and for a specific country (e.g. The United States). Case counts are reported per time interval. In addition to case counts, datsets include information about these counts (attributes), such as the location, age group, subpopulation, diagnostic certainty, place of aquisition, and the source from which we extracted case counts. One dataset can include many series of case count time intervals, such as "US measles cases as reported by CDC", or "US measles cases reported by WHO", or "US measles cases that originated abroad", etc.

Depending on the intended use of a dataset, we recommend a few data processing steps before analysis:

• Analyze missing data: Project Tycho datasets do not inlcude time intervals for which no case count was reported (for many datasets, time series of case counts are incomplete, due to incompleteness of source documents) and users will need to add time intervals for which no count value is available. Project Tycho datasets do include time intervals for which a case count value of zero was reported.
• Separate cumulative from non-cumulative time interval series. Case count time series in Project Tycho datasets can be "cumulative" or "fixed-intervals". Cumulative case count time series consist of overlapping case count intervals starting on the same date, but ending on different dates. For example, each interval in a cumulative count time series can start on January 1st, but end on January 7th, 14th, 21st, etc. It is common practice among public health agencies to report cases for cumulative time intervals. Case count series with fixed time intervals consist of mutually exxclusive time intervals that all start and end on different dates and all have identical length (day, week, month, year). Given the different nature of these two types of case count data, we indicated this with an attribute for each count value, named "PartOfCumulativeCountSeries".

This file contains the complete set of data reported to 122 Cities Mortality Reposting System. The system was retired as of 10/6/2016. While the system was running each week, the vital statistics offices of 122 cities across the United States reported the total number of death certificates processed and the number of those for which pneumonia or influenza was listed as the underlying or contributing cause of death by age group (Under 28 days, 28 days - 1 year, 1-14 years, 15-24 years, 25-44 years, 45-64 years, 65-74 years, 75-84 years, and - 85 years). U:Unavailable. - : No reported cases.* Mortality data in this table were voluntarily reported from 122 cities in the United States, most of which have populations of >100,000. A death is reported by the place of its occurrence and by the week that the death certificate was filed. Fetal deaths are not included. Total includes unknown ages. More information on Flu Activity & Surveillance is available at http://www.cdc.gov/flu/weekly/fluactivitysurv.htm.

Provisional counts of the number of death occurrences in England and Wales due to coronavirus (COVID-19) and influenza and pneumonia, by age, sex and place of death.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

Note: On April 30, 2024, the Federal mandate for COVID-19 and influenza associated hospitalization data to be reported to CDC’s National Healthcare Safety Network (NHSN) expired. Hospitalization data beyond April 30, 2024, will not be updated on the Open Data Portal. Hospitalization and ICU admission data collected from summer 2020 to May 10, 2023, are sourced from the California Hospital Association (CHA) Survey. Data collected on or after May 11, 2023, are sourced from CDC's National Healthcare Safety Network (NHSN).

Data is from the California Department of Public Health (CDPH) Respiratory Virus State Dashboard at https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/Respiratory-Viruses/RespiratoryDashboard.aspx.

Data are updated each Friday around 2 pm.

For COVID-19 death data: As of January 1, 2023, data was sourced from the California Department of Public Health, California Comprehensive Death File (Dynamic), 2023–Present. Prior to January 1, 2023, death data was sourced from the COVID-19 case registry. The change in data source occurred in July 2023 and was applied retroactively to all 2023 data to provide a consistent source of death data for the year of 2023. Influenza death data was sourced from the California Department of Public Health, California Comprehensive Death File (Dynamic), 2020–Present.

COVID-19 testing data represent data received by CDPH through electronic laboratory reporting of test results for COVID-19 among residents of California. Testing date is the date the test was administered, and tests have a 1-day lag (except for the Los Angeles County, which has an additional 7-day lag). Influenza testing data represent data received by CDPH from clinical sentinel laboratories in California. These laboratories report the aggregate number of laboratory-confirmed influenza virus detections and total tests performed on a weekly basis. These data do not represent all influenza testing occurring in California and are available only at the state level.

TABLE III. Deaths in 122 U.S. cities – 2016. 122 Cities Mortality Reporting System — Each week, the vital statistics offices of 122 cities across the United States report the total number of death certificates processed and the number of those for which pneumonia or influenza was listed as the underlying or contributing cause of death by age group (Under 28 days, 28 days –1 year, 1-14 years, 15-24 years, 25-44 years, 45-64 years, 65-74 years, 75-84 years, and ≥ 85 years). FOOTNOTE: U: Unavailable. —: No reported cases. * Mortality data in this table are voluntarily reported from 122 cities in the United States, most of which have populations of 100,000 or more. A death is reported by the place of its occurrence and by the week that the death certificate was filed. Fetal deaths are not included. † Pneumonia and influenza. § Total includes unknown ages.

Effective September 27, 2023, this dataset will no longer be updated. Similar data are accessible from wonder.cdc.gov. Deaths involving COVID-19, pneumonia, and influenza reported to NCHS by sex, age group, and jurisdiction of occurrence.

Analysis of ‘Deaths in 122 U.S. cities’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/deaths-in-122-u-s-citiese on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

TABLE III. Deaths in 122 U.S. cities – 2016. 122 Cities Mortality Reporting System — Each week, the vital statistics offices of 122 cities across the United States report the total number of death certificates processed and the number of those for which pneumonia or influenza was listed as the underlying or contributing cause of death by age group (Under 28 days, 28 days –1 year, 1-14 years, 15-24 years, 25-44 years, 45-64 years, 65-74 years, 75-84 years, and ≥ 85 years).

FOOTNOTE: U: Unavailable. —: No reported cases. * Mortality data in this table are voluntarily reported from 122 cities in the United States, most of which have populations of 100,000 or more. A death is reported by the place of its occurrence and by the week that the death certificate was filed. Fetal deaths are not included.

†Pneumonia and influenza.

§ Total includes unknown ages.

Source: https://catalog.data.gov/dataset/table-iii-deaths-in-122-u-s-cities

This dataset was created by Health and contains around 5000 samples along with Reporting Area, All Causes, By Age (years), All Ages**, technical information and other features such as: - All Causes, By Age (years), All Ages**, Flag - All Causes, By Age (years), Lt 1, Flag - and more.

How to use this dataset

• Analyze All Causes, By Age (years), ≥65, Flag in relation to All Causes, By Age (years), ≥65
• Study the influence of P&i† Total on All Causes, By Age (years), 25–44, Flag
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Health

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

Monthly Cumulative Number and Percent of Persons Who Received ≥1 Influenza Vaccination Doses, by Flu Season, Age Group, and Jurisdiction

• Influenza vaccination coverage for children and adults is assessed through U.S. jurisdictions’ Immunization Information Systems (IIS) data, submitted from jurisdictions to CDC monthly in aggregate by age group. More information about the IIS can be found at https://www.cdc.gov/vaccines/programs/iis/about.html.

• Influenza vaccination coverage estimate numerators include the number of people receiving at least one dose of influenza vaccine in a given flu season, based on information that state, territorial, and local public health agencies report to CDC. Some jurisdictions’ data may include data submitted by tribes. Estimates include persons who are deceased but received a vaccination during the current season. People receiving doses are attributed to the jurisdiction in which the person resides unless noted otherwise. Quality and completeness of data may vary across jurisdictions. Influenza vaccination coverage denominators are obtained from 2020 U.S. Census Bureau population estimates.

• Monthly estimates shown are cumulative, reflecting all persons vaccinated from July through a given month of that flu season. Cumulative estimates include any historical data reported since the previous submission. National estimates are not presented since not all U.S. jurisdictions are currently reporting their IIS data to CDC. Jurisdictions reporting data to CDC include U.S. states, some localities, and territories.

• Because IIS data contain all vaccinations administered within a jurisdiction rather than a sample, standard errors were not calculated and statistical testing for differences in estimates across years were not performed.

• Laws and policies regarding the submission of vaccination data to an IIS vary by state, which may impact the completeness of vaccination coverage reflected for a jurisdiction. More information on laws and policies are found at https://www.cdc.gov/vaccines/programs/iis/policy-legislation.html.

• Coverage estimates based on IIS data are expected to differ from National Immunization Survey (NIS) estimates for children (https://www.cdc.gov/flu/fluvaxview/dashboard/vaccination-coverage-race.html) and adults (https://www.cdc.gov/flu/fluvaxview/dashboard/vaccination-adult-coverage.html) because NIS estimates are based on a sample that may not be representative after survey weighting and vaccination status is determined by survey respondent rather than vaccine records or administrations, and quality and completeness of IIS data may vary across jurisdictions. In general, NIS estimates tend to overestimate coverage due to overreporting and IIS estimates may underestimate coverage due to incompleteness of data in certain jurisdictions.

Age-standardised mortality rates for deaths involving coronavirus (COVID-19), non-COVID-19 deaths and all deaths by vaccination status, broken down by age group.

The Chicago Department of Public Health (CDPH) receives weekly deidentified provisional death certificate data for all deaths that occur in Chicago, which can include both Chicago and non-Chicago residents from the Illinois Department of Public Health (IDPH) Illinois Vital Records System (IVRS). CDPH scans for keywords to identify deaths with COVID-19, influenza, or respiratory syncytial virus (RSV) listed as an immediate cause of death, contributing factor, or other significant condition. The percentage of all reported deaths that are attributed to COVID-19, influenza, or RSV is calculated as the number of deaths for each respective disease divided by the number of deaths from all causes, multiplied by 100. This dataset reflects death certificates that have been submitted to IVRS at the time of transmission to CDPH each week – data from previous weeks are not updated with any new submissions to IVRS. As such, estimates in this dataset may differ from those reported through other sources. This dataset can be used to understand trends in COVID-19, influenza, and RSV mortality in Chicago but does not reflect official death statistics. Source: Provisional deaths from the Illinois Department of Public Health Illinois Vital Records System.

Analysis of ‘COVID-19 State Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/nightranger77/covid19-state-data on 28 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset is a per-state amalgamation of demographic, public health and other relevant predictors for COVID-19.

Deaths, Infections and Tests by State

The COVID Tracking Project: https://covidtracking.com/data/api

Used positive, death and totalTestResults from the API for, respectively, Infected, Deaths and Tested in this dataset. Please read the documentation of the API for more context on those columns

Predictor Data and Sources

Population (2020)

Density is people per meter squared https://worldpopulationreview.com/states/

ICU Beds and Age 60+

https://khn.org/news/as-coronavirus-spreads-widely-millions-of-older-americans-live-in-counties-with-no-icu-beds/

GDP

https://worldpopulationreview.com/states/gdp-by-state/

Income per capita (2018)

https://worldpopulationreview.com/states/per-capita-income-by-state/

Gini

https://en.wikipedia.org/wiki/List_of_U.S._states_by_Gini_coefficient

Unemployment (2020)

Rates from Feb 2020 and are percentage of labor force
https://www.bls.gov/web/laus/laumstrk.htm

Sex (2017)

Ratio is Male / Female
https://www.kff.org/other/state-indicator/distribution-by-gender/

Smoking Percentage (2020)

https://worldpopulationreview.com/states/smoking-rates-by-state/

Influenza and Pneumonia Death Rate (2018)

Death rate per 100,000 people
https://www.cdc.gov/nchs/pressroom/sosmap/flu_pneumonia_mortality/flu_pneumonia.htm

Chronic Lower Respiratory Disease Death Rate (2018)

Death rate per 100,000 people
https://www.cdc.gov/nchs/pressroom/sosmap/lung_disease_mortality/lung_disease.htm

Active Physicians (2019)

https://www.kff.org/other/state-indicator/total-active-physicians/

Hospitals (2018)

https://www.kff.org/other/state-indicator/total-hospitals

Health spending per capita

Includes spending for all health care services and products by state of residence. Hospital spending is included and reflects the total net revenue. Costs such as insurance, administration, research, and construction expenses are not included.
https://www.kff.org/other/state-indicator/avg-annual-growth-per-capita/

Pollution (2019)

Pollution: Average exposure of the general public to particulate matter of 2.5 microns or less (PM2.5) measured in micrograms per cubic meter (3-year estimate)
https://www.americashealthrankings.org/explore/annual/measure/air/state/ALL

Medium and Large Airports

For each state, number of medium and large airports https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_the_United_States

Temperature (2019)

Note that FL was incorrect in the table, but is corrected in the Hottest States paragraph
https://worldpopulationreview.com/states/average-temperatures-by-state/
District of Columbia temperature computed as the average of Maryland and Virginia

Urbanization (2010)

Urbanization as a percentage of the population https://www.icip.iastate.edu/tables/population/urban-pct-states

Age Groups (2018)

https://www.kff.org/other/state-indicator/distribution-by-age/

School Closure Dates

Schools that haven't closed are marked NaN https://www.edweek.org/ew/section/multimedia/map-coronavirus-and-school-closures.html

Note that some datasets above did not contain data for District of Columbia, this missing data was found via Google searches manually entered.

--- Original source retains full ownership of the source dataset ---

Analysis of ‘Deaths in 122 U.S. cities - 1962-2016. 122 Cities Mortality Reporting System’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/259d9312-191c-4914-8c84-865676d22824 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

This file contains the complete set of data reported to 122 Cities Mortality Reposting System. The system was retired as of 10/6/2016. While the system was running each week, the vital statistics offices of 122 cities across the United States reported the total number of death certificates processed and the number of those for which pneumonia or influenza was listed as the underlying or contributing cause of death by age group (Under 28 days, 28 days - 1 year, 1-14 years, 15-24 years, 25-44 years, 45-64 years, 65-74 years, 75-84 years, and - 85 years). U:Unavailable. - : No reported cases.* Mortality data in this table were voluntarily reported from 122 cities in the United States, most of which have populations of >100,000. A death is reported by the place of its occurrence and by the week that the death certificate was filed. Fetal deaths are not included. Total includes unknown ages. More information on Flu Activity & Surveillance is available at http://www.cdc.gov/flu/weekly/fluactivitysurv.htm.

--- Original source retains full ownership of the source dataset ---

This dataset is a per-state amalgamation of demographic, public health and other relevant predictors for COVID-19.

Deaths, Infections and Tests by State

The COVID Tracking Project: https://covidtracking.com/data/api

Used positive, death and totalTestResults from the API for, respectively, Infected, Deaths and Tested in this dataset. Please read the documentation of the API for more context on those columns

Predictor Data and Sources

Population (2020)

Density is people per meter squared https://worldpopulationreview.com/states/

ICU Beds and Age 60+

https://khn.org/news/as-coronavirus-spreads-widely-millions-of-older-americans-live-in-counties-with-no-icu-beds/

GDP

https://worldpopulationreview.com/states/gdp-by-state/

Income per capita (2018)

https://worldpopulationreview.com/states/per-capita-income-by-state/

Gini

https://en.wikipedia.org/wiki/List_of_U.S._states_by_Gini_coefficient

Unemployment (2020)

Rates from Feb 2020 and are percentage of labor force
https://www.bls.gov/web/laus/laumstrk.htm

Sex (2017)

Ratio is Male / Female
https://www.kff.org/other/state-indicator/distribution-by-gender/

Smoking Percentage (2020)

https://worldpopulationreview.com/states/smoking-rates-by-state/

Influenza and Pneumonia Death Rate (2018)

Death rate per 100,000 people
https://www.cdc.gov/nchs/pressroom/sosmap/flu_pneumonia_mortality/flu_pneumonia.htm

Chronic Lower Respiratory Disease Death Rate (2018)

Death rate per 100,000 people
https://www.cdc.gov/nchs/pressroom/sosmap/lung_disease_mortality/lung_disease.htm

Active Physicians (2019)

https://www.kff.org/other/state-indicator/total-active-physicians/

Hospitals (2018)

https://www.kff.org/other/state-indicator/total-hospitals

Health spending per capita

Includes spending for all health care services and products by state of residence. Hospital spending is included and reflects the total net revenue. Costs such as insurance, administration, research, and construction expenses are not included.
https://www.kff.org/other/state-indicator/avg-annual-growth-per-capita/

Pollution (2019)

Pollution: Average exposure of the general public to particulate matter of 2.5 microns or less (PM2.5) measured in micrograms per cubic meter (3-year estimate)
https://www.americashealthrankings.org/explore/annual/measure/air/state/ALL

Medium and Large Airports

For each state, number of medium and large airports https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_the_United_States

Temperature (2019)

Note that FL was incorrect in the table, but is corrected in the Hottest States paragraph
https://worldpopulationreview.com/states/average-temperatures-by-state/
District of Columbia temperature computed as the average of Maryland and Virginia

Urbanization (2010)

Urbanization as a percentage of the population https://www.icip.iastate.edu/tables/population/urban-pct-states

Age Groups (2018)

https://www.kff.org/other/state-indicator/distribution-by-age/

School Closure Dates

Schools that haven't closed are marked NaN https://www.edweek.org/ew/section/multimedia/map-coronavirus-and-school-closures.html

Note that some datasets above did not contain data for District of Columbia, this missing data was found via Google searches manually entered.

Analysis of ‘TABLE III. Deaths in 122 U.S. cities’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/ba37e142-60b9-4eff-ad8f-69029ea5b77e on 27 January 2022.

--- Dataset description provided by original source is as follows ---

TABLE III. Deaths in 122 U.S. cities – 2016. 122 Cities Mortality Reporting System — Each week, the vital statistics offices of 122 cities across the United States report the total number of death certificates processed and the number of those for which pneumonia or influenza was listed as the underlying or contributing cause of death by age group (Under 28 days, 28 days –1 year, 1-14 years, 15-24 years, 25-44 years, 45-64 years, 65-74 years, 75-84 years, and ≥ 85 years).

FOOTNOTE: U: Unavailable. —: No reported cases. * Mortality data in this table are voluntarily reported from 122 cities in the United States, most of which have populations of 100,000 or more. A death is reported by the place of its occurrence and by the week that the death certificate was filed. Fetal deaths are not included.

† Pneumonia and influenza.

§ Total includes unknown ages.

--- Original source retains full ownership of the source dataset ---

This is historical data. The update frequency has been set to "Static Data" and is here for historic value. Updated on 8/14/2024

Annual Season Influenza Vaccinations - This indicator shows the percentage of adults who are vaccinated annually against seasonal influenza. For many people, the seasonal flu is a mild illness, but for some it can lead to pneumonia, hospitalization, or death. Vaccination of persons in high-risk populations is especially important to reduce their risk of severe illness or death. Link to Data Details

Analysis of ‘SHIP Annual Season Influenza Vaccinations 2011-2017’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/c6c068e8-7e9a-4e48-85cf-c6a53678a6b3 on 26 January 2022.

--- Dataset description provided by original source is as follows ---

Annual Season Influenza Vaccinations - This indicator shows the percentage of adults who are vaccinated annually against seasonal influenza. For many people, the seasonal flu is a mild illness, but for some it can lead to pneumonia, hospitalization, or death. Vaccination of persons in high-risk populations is especially important to reduce their risk of severe illness or death.

--- Original source retains full ownership of the source dataset ---

Chicago residents who are up to date with influenza vaccines by ZIP Code, based on the reported home address and age group of the person vaccinated, as provided by the medical provider in the Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE). “Up to date” refers to individuals aged 6 months and older who have received 1+ doses of influenza vaccine during the current season, defined as the beginning of July (MMWR week 27) through the end of the following June (MMWR week 26). Data Notes: Weekly cumulative totals of people up to date are shown for each combination ZIP Code and age group. Note there are rows where age group is "All ages" so care should be taken when summing rows. Weeks begin on a Sunday and end on a Saturday. Coverage percentages are calculated based on the cumulative number of people in each ZIP Code and age group who are considered up to date as of the week ending date divided by the estimated number of people in that subgroup. Population counts are obtained from the 2020 U.S. Decennial Census. For ZIP Codes mostly outside Chicago, coverage percentages are not calculated because reliable Chicago-only population counts are not available. Actual counts may exceed population estimates and lead to coverage estimates that are greater than 100%, especially in smaller ZIP Codes with smaller populations. 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 underestimation of vaccination coverage by geography. All coverage percentages are capped at 99%. The Chicago Department of Public Health (CDPH) uses the most complete data available to estimate influenza vaccination coverage among Chicagoans, but there are several limitations that impact our estimates. Influenza vaccine administration is not required to be reported in Illinois, except for publicly funded vaccine (e.g., Vaccines for Children, Section 317). Individuals may receive vaccinations that are not recorded in I-CARE, such as those administered in another state, or those administered by a provider that does not submit data to I-CARE, causing underestimation of the number individuals who received an influenza vaccine for the current season. 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 influenza, see https://data.cityofchicago.org/browse?limitTo=datasets&sortBy=alpha&tags=flu . Data Source: Illinois Comprehensive Automated Immunization Registry Exchange (I-CARE), U.S. Census Bureau 2020 Decennial Census

Flu vaccine uptake (%) in adults aged 65 and over, who received the flu vaccination between 1st September to the end of February as recorded in the GP record. The February collection has been adopted for our end of season figures from 2017 to 2018. All previous data is the same definitions but until the end of January rather than February to consider data returning from outside the practice and later in practice vaccinations.RationaleInfluenza (also known as Flu) is a highly infectious viral illness spread by droplet infection. The flu vaccination is offered to people who are at greater risk of developing serious complications if they catch the flu. The seasonal influenza programme for England is set out in the Annual Flu Letter. Both the flu letter and the flu plan have the support of the Chief Medical Officer (CMO), Chief Pharmaceutical Officer (CPhO), and Director of Nursing.Vaccination coverage is the best indicator of the level of protection a population will have against vaccine-preventable communicable diseases. Immunisation is one of the most effective healthcare interventions available, and flu vaccines can prevent illness and hospital admissions among these groups of people. Increasing the uptake of the flu vaccine among these high-risk groups should also contribute to easing winter pressure on primary care services and hospital admissions. Coverage is closely related to levels of disease. Monitoring coverage identifies possible drops in immunity before levels of disease rise.The UK Health Security Agency (UKHSA) will continue to provide expert advice and monitoring of public health, including immunisation. NHS England now has responsibility for commissioning the flu programme, and GPs continue to play a key role. NHS England teams will ensure that robust plans are in place locally and that high vaccination uptake levels are reached in the clinical risk groups. For more information, see the Green Book chapter 19 on Influenza.The Annual Flu Letter sets out the national vaccine uptake ambitions each year. In 2021 to 2022, the national ambition was to achieve at least 85 percent vaccine uptake in those aged 65 and over. Prior to this, the national vaccine uptake ambition was 75 percent, in line with WHO targets.Definition of numeratorNumerator is the number of vaccinations administered during the influenza season between 1st September and the end of February.Definition of denominatorDenominator is the GP registered population on the date of extraction including patients who have been offered the vaccine but refused it, as the uptake rate is measured against the overall eligible population. For more detailed information please see the user guide, available to view and download from https://www.gov.uk/government/collections/vaccine-uptake#seasonal-flu-vaccine-uptakeCaveatsRead codes are primarily used for data collection purposes to extract vaccine uptake data for patients who fall into one or more of the designated clinical risk groups. The codes identify individuals at risk, and therefore eligible for flu vaccination. However, it is important to note that there may be some individuals with conditions not specified in the recommended risk groups for vaccination, who may be offered influenza vaccine by their GP based on clinical judgement and according to advice contained in the flu letter and Green Book, and thus are likely to fall outside the listed Read codes. Therefore, this data should not be used for GP payment purposes.