32 datasets found
  1. Mortality rate for influenza in the U.S. in 2023-2024, by age group

    • statista.com
    Updated Apr 14, 2025
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    Statista (2025). Mortality rate for influenza in the U.S. in 2023-2024, by age group [Dataset]. https://www.statista.com/statistics/1127799/influenza-us-mortality-rate-by-age-group/
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    Dataset updated
    Apr 14, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023 - 2024
    Area covered
    United States
    Description

    The mortality rate from influenza in the United States is by far highest among those aged 65 years and older. During the 2023-2024 flu season, the mortality rate from influenza for this age group was around 32.1 per 100,000 population. The burden of influenza The impact of influenza in the U.S. varies from season to season, but in the 2023-2024 flu season, there were an estimated 40 million cases. These cases resulted in around 470,000 hospitalizations. Although most people recover from influenza without requiring medical treatment, the disease can be deadly for young children, the elderly, and those with weakened immune systems or chronic illnesses. During the 2023-2024 flu season, around 28,000 people in the U.S. lost their lives due to influenza. Impact of vaccinations The most effective way to prevent influenza is to receive an annual vaccination at the beginning of flu season. Flu vaccines are safe and can greatly reduce the burden of the disease. During the 2022-2023 flu season, vaccinations prevented around 2,479 deaths among those aged 65 years and older. Although flu vaccines are usually cheap and easily accessible, every year a large share of the population in the U.S. still does not get vaccinated. For example, during the 2022-2023 flu season, only about 35 percent of those aged 18 to 49 years received a flu vaccination.

  2. Rate of influenza-related hospitalizations in the U.S. in 2023-2024, by age...

    • statista.com
    Updated Apr 14, 2025
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    Statista (2025). Rate of influenza-related hospitalizations in the U.S. in 2023-2024, by age group [Dataset]. https://www.statista.com/statistics/1127795/influenza-us-hospitalization-rate-by-age-group/
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    Dataset updated
    Apr 14, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023 - 2024
    Area covered
    United States
    Description

    In the United States, the highest rate of hospitalizations due to influenza are among those aged 65 years and older. During the 2023-2024 flu season, the rate of hospitalizations due to influenza among this age group was about 401 per 100,000 population, compared to a rate of around 47 per 100,000 for those aged 5 to 17 years. Influenza is a common viral infection that usually does not require medical treatment. However, for the very young, the old, and those with certain pre-existing conditions, influenza can be serious and even deadly. The burden of influenza in the United States The impact of influenza in the United States varies from year to year depending on the strain that is most prevalent during that season and the immunity in the population. Preliminary estimates show that around 28,000 people died from influenza during the 2023-2024 flu season. However, during the 2017-2018 flu season, an estimated 52,000 people lost their lives to influenza. The importance of flu vaccines The best way to avoid catching the flu and to reduce the virus’s overall burden on society is by receiving an annual flu vaccination. The CDC currently recommends that everyone over 6 months of age should get a flu vaccination every year, preferably by the end of October. The flu vaccine is safe, efficient, and reduces the number of illnesses, hospitalizations, and deaths caused by the virus. For example, during the 2022-2023 flu season, it was estimated that vaccinations averted almost 65 thousand influenza-related hospitalizations. However, despite the proven benefits and wide availability of flu vaccinations, a large percentage of people in the United States fail to receive a vaccination every year. During the 2022-2023 flu season, only about 35 percent of those aged 18 to 49 years were vaccinated against influenza, compared to 70 percent of those aged 65 years and older.

  3. f

    Probabilities of H1N1 influenza illnesses, hospitalizations, and deaths by...

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Lisa A. Prosser; Tara A. Lavelle; Anthony E. Fiore; Carolyn B. Bridges; Carrie Reed; Seema Jain; Kelly M. Dunham; Martin I. Meltzer (2023). Probabilities of H1N1 influenza illnesses, hospitalizations, and deaths by age and risk status. [Dataset]. http://doi.org/10.1371/journal.pone.0022308.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Lisa A. Prosser; Tara A. Lavelle; Anthony E. Fiore; Carolyn B. Bridges; Carrie Reed; Seema Jain; Kelly M. Dunham; Martin I. Meltzer
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    LR  =  lower-risk; HR  =  higher-risk.1Data from seasonal influenza illness was used to estimate the ratio of high risk to low risk based on expert opinion that although the incidence for pH1N1 and seasonal influenza varied substantially by age, the conditional probability of influenza-related complications for high risk and low risk patients would likely be similar for pH1N1 and seasonal (i.e., within an age group, high risk patients would be more likely to experience influenza-related complications than low-risk patients for both pH1N1 and seasonal influenza).

  4. Leading causes of death, total population, by age group

    • www150.statcan.gc.ca
    • ouvert.canada.ca
    • +1more
    Updated Feb 19, 2025
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    Government of Canada, Statistics Canada (2025). Leading causes of death, total population, by age group [Dataset]. http://doi.org/10.25318/1310039401-eng
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    Dataset updated
    Feb 19, 2025
    Dataset provided by
    Statistics Canadahttps://statcan.gc.ca/en
    Area covered
    Canada
    Description

    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.

  5. f

    Annual estimates of influenza-attributed all-cause mortality and...

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Yinong Young-Xu; Robertus van Aalst; Ellyn Russo; Jason K. H. Lee; Ayman Chit (2023). Annual estimates of influenza-attributed all-cause mortality and influenza-attributed mortality adjusted for respiratory or circulatory cause of death as the proportion of all deaths by risk and age group averaged over five respiratory seasons. [Dataset]. http://doi.org/10.1371/journal.pone.0169344.t005
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Yinong Young-Xu; Robertus van Aalst; Ellyn Russo; Jason K. H. Lee; Ayman Chit
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Annual estimates of influenza-attributed all-cause mortality and influenza-attributed mortality adjusted for respiratory or circulatory cause of death as the proportion of all deaths by risk and age group averaged over five respiratory seasons.

  6. f

    Table_1_Impact of influenza related hospitalization in Spain:...

    • figshare.com
    docx
    Updated Apr 2, 2024
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    José-Manuel Ramos-Rincón; Héctor Pinargote-Celorio; Pilar González-de-la-Aleja; José Sánchez-Payá; Sergio Reus; Juan-Carlos Rodríguez-Díaz; Esperanza Merino (2024). Table_1_Impact of influenza related hospitalization in Spain: characteristics and risk factor of mortality during five influenza seasons (2016 to 2021).DOCX [Dataset]. http://doi.org/10.3389/fpubh.2024.1360372.s001
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    docxAvailable download formats
    Dataset updated
    Apr 2, 2024
    Dataset provided by
    Frontiers
    Authors
    José-Manuel Ramos-Rincón; Héctor Pinargote-Celorio; Pilar González-de-la-Aleja; José Sánchez-Payá; Sergio Reus; Juan-Carlos Rodríguez-Díaz; Esperanza Merino
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundEstimating the global influenza burden in terms of hospitalization and death is important for optimizing prevention policies. Identifying risk factors for mortality allows for the design of strategies tailored to groups at the highest risk. This study aims to (a) describe the clinical characteristics of hospitalizations with a diagnosis of influenza over five flu seasons (2016–2017 to 2020–2021), (b) assess the associated morbidity (hospitalization rates and ICU admissions rate), mortality and cost of influenza hospitalizations in different age groups and (c) analyze the risk factors for mortality.MethodsThis retrospective study included all hospital admissions with a diagnosis of influenza in Spain for five influenza seasons. Data were extracted from the Spanish National Surveillance System for Hospital Data from 1 July 2016 to 30 June 2021. We identified cases coded as having influenza as a primary or secondary diagnosis (International Classification of Diseases, 10th revision, J09-J11). The hospitalization rate was calculated relative to the general population. Independent predictors of mortality were identified using multivariable logistic regression.ResultsOver the five seasons, there were 127,160 hospitalizations with a diagnosis of influenza. The mean influenza hospitalization rate varied from 5/100,000 in 2020–2021 (COVID-19 pandemic) to 92.9/100,000 in 2017–2018. The proportion of influenza hospitalizations with ICU admission was 7.4% and was highest in people aged 40–59 years (13.9%). The case fatality rate was 5.8% overall and 9.4% in those aged 80 years or older. Median length of stay was 5 days (and 6 days in the oldest age group). In the multivariable analysis, independent risk factors for mortality were male sex (odds ratio [OR] 1.14, 95% confidence interval [95% CI] 1.08–1.20), age (

  7. Number of influenza cases in the United States from 2011-2024

    • statista.com
    Updated Apr 14, 2025
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    Statista (2025). Number of influenza cases in the United States from 2011-2024 [Dataset]. https://www.statista.com/statistics/861113/estimated-number-of-flu-cases-us/
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    Dataset updated
    Apr 14, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    Influenza, also called the flu, is one of the most infectious diseases worldwide. Its symptoms range from mild to severe, and include sore throat, cough, runny nose, fever, headache, and muscle pain, but can also cause severe illness and death among high-risk populations such as the elderly and children. During the 2023-2024 flu season, there were 40 million cases of influenza in the United States. Influenza deaths Although influenza does not require medical attention for most people, it can be deadly, and causes thousands of deaths every year. The impact of influenza varies from year to year. The number of influenza deaths during the 2023-2024 flu season was 27,965. The vast majority of deaths attributed to influenza during the 2023-2024 flu season occurred among those aged 65 years and older. Vaccination An annual influenza vaccination remains the most effective way of preventing influenza. During the 2022-2023 flu season, influenza vaccinations prevented an estimated 2,479 deaths among U.S. adults aged 65 years and older. Although, flu vaccinations are accessible and cheap, a large share of the United States population still fails to get vaccinated every year. In 2022-2023, only 35 percent of those aged 18 to 49 years received a flu vaccination, much lower compared to children and the elderly.

  8. f

    Table_5_Impact of influenza related hospitalization in Spain:...

    • figshare.com
    docx
    Updated Apr 2, 2024
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    José-Manuel Ramos-Rincón; Héctor Pinargote-Celorio; Pilar González-de-la-Aleja; José Sánchez-Payá; Sergio Reus; Juan-Carlos Rodríguez-Díaz; Esperanza Merino (2024). Table_5_Impact of influenza related hospitalization in Spain: characteristics and risk factor of mortality during five influenza seasons (2016 to 2021).DOCX [Dataset]. http://doi.org/10.3389/fpubh.2024.1360372.s005
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    docxAvailable download formats
    Dataset updated
    Apr 2, 2024
    Dataset provided by
    Frontiers
    Authors
    José-Manuel Ramos-Rincón; Héctor Pinargote-Celorio; Pilar González-de-la-Aleja; José Sánchez-Payá; Sergio Reus; Juan-Carlos Rodríguez-Díaz; Esperanza Merino
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundEstimating the global influenza burden in terms of hospitalization and death is important for optimizing prevention policies. Identifying risk factors for mortality allows for the design of strategies tailored to groups at the highest risk. This study aims to (a) describe the clinical characteristics of hospitalizations with a diagnosis of influenza over five flu seasons (2016–2017 to 2020–2021), (b) assess the associated morbidity (hospitalization rates and ICU admissions rate), mortality and cost of influenza hospitalizations in different age groups and (c) analyze the risk factors for mortality.MethodsThis retrospective study included all hospital admissions with a diagnosis of influenza in Spain for five influenza seasons. Data were extracted from the Spanish National Surveillance System for Hospital Data from 1 July 2016 to 30 June 2021. We identified cases coded as having influenza as a primary or secondary diagnosis (International Classification of Diseases, 10th revision, J09-J11). The hospitalization rate was calculated relative to the general population. Independent predictors of mortality were identified using multivariable logistic regression.ResultsOver the five seasons, there were 127,160 hospitalizations with a diagnosis of influenza. The mean influenza hospitalization rate varied from 5/100,000 in 2020–2021 (COVID-19 pandemic) to 92.9/100,000 in 2017–2018. The proportion of influenza hospitalizations with ICU admission was 7.4% and was highest in people aged 40–59 years (13.9%). The case fatality rate was 5.8% overall and 9.4% in those aged 80 years or older. Median length of stay was 5 days (and 6 days in the oldest age group). In the multivariable analysis, independent risk factors for mortality were male sex (odds ratio [OR] 1.14, 95% confidence interval [95% CI] 1.08–1.20), age (

  9. E

    Global burden of respiratory infections associated with seasonal influenza...

    • find.data.gov.scot
    • dtechtive.com
    csv, txt
    Updated Mar 10, 2020
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    University of Edinburgh. Usher Institute, Centre for Global Health (2020). Global burden of respiratory infections associated with seasonal influenza in young children in 2018: a systematic review and modelling study [Dataset]. http://doi.org/10.7488/ds/2778
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    csv(0.0459 MB), csv(0.0849 MB), txt(0.0166 MB), csv(0.0579 MB), csv(0.0605 MB), csv(0.3107 MB), csv(0.2451 MB), csv(0.1298 MB), csv(0.4116 MB)Available download formats
    Dataset updated
    Mar 10, 2020
    Dataset provided by
    University of Edinburgh. Usher Institute, Centre for Global Health
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Background # Seasonal influenza virus is a common cause of acute lower respiratory infection (ALRI) in young children. In 2008, we estimated that 20 million influenza-virus-associated ALRI and 1 million influenza-virus-associated severe ALRI occurred in children under 5 years globally. Despite this substantial burden, only a few low-income and middle-income countries have adopted routine influenza vaccination policies for children and, where present, these have achieved only low or unknown levels of vaccine uptake. Moreover, the influenza burden might have changed due to the emergence and circulation of influenza A/H1N1pdm09. We aimed to incorporate new data to update estimates of the global number of cases, hospital admissions, and mortality from influenza-virus-associated respiratory infections in children under 5 years in 2018. # Methods # We estimated the regional and global burden of influenza-associated respiratory infections in children under 5 years from a systematic review of 100 studies published between Jan 1, 1995, and Dec 31, 2018, and a further 57 high-quality unpublished studies. We adapted the Newcastle-Ottawa Scale to assess the risk of bias. We estimated incidence and hospitalisation rates of influenza-virus-associated respiratory infections by severity, case ascertainment, region, and age. We estimated in-hospital deaths from influenza virus ALRI by combining hospital admissions and in-hospital case-fatality ratios of influenza virus ALRI. We estimated the upper bound of influenza virus-associated ALRI deaths based on the number of in-hospital deaths, US paediatric influenza-associated death data, and population-based childhood all-cause pneumonia mortality data in six sites in low-income and lower-middle-income countries. # Findings # In 2018, among children under 5 years globally, there were an estimated 109*5 million influenza virus episodes (uncertainty range [UR] 63*1-190*6), 10*1 million influenza-virus-associated ALRI cases (6*8-15*1); 870 000 influenza-virus-associated ALRI hospital admissions (543 000-1 415 000), 15 300 in-hospital deaths (5800-43 800), and up to 34 800 (13 200-97 200) overall influenza-virus-associated ALRI deaths. Influenza virus accounted for 7% of ALRI cases, 5% of ALRI hospital admissions, and 4% of ALRI deaths in children under 5 years. About 23% of the hospital admissions and 36% of the in-hospital deaths were in infants under 6 months. About 82% of the in-hospital deaths occurred in low-income and lower-middle-income countries. # Interpretation # A large proportion of the influenza-associated burden occurs among young infants and in low-income and lower middle-income countries. Our findings provide new and important evidence for maternal and paediatric influenza immunisation, and should inform future immunisation policy particularly in low-income and middle-income countries.

  10. z

    Data from: Disparities in influenza mortality and transmission related to...

    • zenodo.org
    • explore.openaire.eu
    • +1more
    csv, zip
    Updated May 28, 2022
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    Kyra H. Grantz; Madhura S. Rane; Henrik Salje; Gregory E. Glass; Stephen E. Schachterle; Derek A. T. Cummings; Kyra H. Grantz; Madhura S. Rane; Henrik Salje; Gregory E. Glass; Stephen E. Schachterle; Derek A. T. Cummings (2022). Data from: Disparities in influenza mortality and transmission related to sociodemographic factors within Chicago in the pandemic of 1918 [Dataset]. http://doi.org/10.5061/dryad.48nv3
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    csv, zipAvailable download formats
    Dataset updated
    May 28, 2022
    Dataset provided by
    Zenodo
    Authors
    Kyra H. Grantz; Madhura S. Rane; Henrik Salje; Gregory E. Glass; Stephen E. Schachterle; Derek A. T. Cummings; Kyra H. Grantz; Madhura S. Rane; Henrik Salje; Gregory E. Glass; Stephen E. Schachterle; Derek A. T. Cummings
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Chicago
    Description

    Social factors have been shown to create differential burden of influenza across different geographic areas. We explored the relationship between potential aggregate-level social determinants and mortality during the 1918 influenza pandemic in Chicago using a historical dataset of 7,971 influenza and pneumonia deaths. Census tract-level social factors, including rates of illiteracy, homeownership, population, and unemployment, were assessed as predictors of pandemic mortality in Chicago. Poisson models fit with generalized estimating equations (GEEs) were used to estimate the association between social factors and the risk of influenza and pneumonia mortality. The Poisson model showed that influenza and pneumonia mortality increased, on average, by 32.2% for every 10% increase in illiteracy rate adjusted for population density, homeownership, unemployment, and age. We also found a significant association between transmissibility and population density, illiteracy, and unemployment but not homeownership. Lastly, analysis of the point locations of reported influenza and pneumonia deaths revealed fine-scale spatiotemporal clustering. This study shows that living in census tracts with higher illiteracy rates increased the risk of influenza and pneumonia mortality during the 1918 influenza pandemic in Chicago. Our observation that disparities in structural determinants of neighborhood-level health lead to disparities in influenza incidence in this pandemic suggests that disparities and their determinants should remain targets of research and control in future pandemics.

  11. f

    Risk factors associated with severe outcomes in adult hospitalized patients...

    • plos.figshare.com
    doc
    Updated May 31, 2023
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    Ana Martínez; Núria Soldevila; Arantxa Romero-Tamarit; Núria Torner; Pere Godoy; Cristina Rius; Mireia Jané; Àngela Domínguez (2023). Risk factors associated with severe outcomes in adult hospitalized patients according to influenza type and subtype [Dataset]. http://doi.org/10.1371/journal.pone.0210353
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    docAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Ana Martínez; Núria Soldevila; Arantxa Romero-Tamarit; Núria Torner; Pere Godoy; Cristina Rius; Mireia Jané; Àngela Domínguez
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Seasonal influenza is a cause of hospitalization, especially in people with underlying disease or extreme age, and its severity may differ depending on the types and subtypes of circulating viruses. We investigated the factors associated with ICU admission or death in hospitalized patients with severe laboratory-confirmed influenza according to the viral type and subtype. An observational epidemiological study was carried out in patients aged ≥18 years from 12 Catalan hospitals between 2010 and 2016. For each reported case we collected demographic, virological and clinical characteristics. A mixed-effects logistic regression model was used to estimate crude and adjusted ORs. 1726 hospitalized patients were included: 595 (34.5%) were admitted to the ICU and 224 (13.0%) died. Lower ICU admission was associated with age ≥75 years in all influenza types and subtypes and with age 65–74 years for type A. In contrast, the 65–74 and ≥75 years age groups were associated with an increased risk of death in all types and subtypes, especially for type B (aOR 27.42, 95% CI: 4.95–151.93 and 15.96; 95% CI: 3.01–84.68). The comorbidity most closely associated with severe outcomes was immune deficiency, which was associated with death for type B (aOR 9.02, 95% CI: 3.05–26.69) and subtype A(H1N1)pdm09 (aOR 3.16, 95% CI: 1.77–5.66). Older age was a differential factor for ICU admission and death: it was associated with lower ICU admission but a risk factor for death. The comorbidity with the closest association with death was immune deficiency, mainly in influenza type B patients.

  12. f

    Influenza vaccination in the elderly: 25 years follow-up of a randomized...

    • plos.figshare.com
    docx
    Updated Jun 1, 2023
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    Ruud Andreas Fritz Verhees; Carel Thijs; Ton Ambergen; Geert Jan Dinant; Johannes Andreas Knottnerus (2023). Influenza vaccination in the elderly: 25 years follow-up of a randomized controlled trial. No impact on long-term mortality [Dataset]. http://doi.org/10.1371/journal.pone.0216983
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    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Ruud Andreas Fritz Verhees; Carel Thijs; Ton Ambergen; Geert Jan Dinant; Johannes Andreas Knottnerus
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Influenza vaccination is proven effective in preventing influenza. However, long-term effects on mortality have never been supported by direct evidence. In this study we assessed the long-term outcome of influenza vaccination on mortality in the elderly by conducting a 25-year follow-up study of a RCT on the efficacy of influenza vaccination as baseline. The RCT had been conducted in the Netherlands 5 years before vaccination was recommended for those aged >65 and 17 years before recommending it for those aged >60. The RCT included 1838 community-dwelling elderly aged ≥ 60 that had received an intramuscular injection with the inactivated quadrivalent influenza vaccine (n = 927) or placebo (n = 911) during the 1991/1992 winter. In our follow-up study, outcomes included all-cause mortality, influenza-related mortality and seasonal mortality. Unadjusted and adjusted hazard ratios (HRs) were estimated by Cox regression and sub-hazard ratios (SHRs) by competing risk models. Secondary analyses included subgroup analyses by age and disease status. The vital status up to January 1, 2017 was provided in 1800/1838 (98%) of the cases. Single influenza vaccination did not reduce all-cause mortality when compared to placebo (adjusted HR 0.95, 95% CI 0.85−1.05). Also, no differences between vaccination and placebo group were shown for underlying causes of death or seasonal mortality. In those aged 60–64, median survival increased with 20.1 months (95% CI 2.4–37.9), although no effects on all-cause mortality (adjusted HR 0.86, 95% CI 0.72−1.03) could be demonstrated in survival analysis. In conclusion, this study did not demonstrate a statistically significant effect following single influenza vaccination on long-term mortality in community-dwelling elderly in general. We propose researchers designing future studies on influenza vaccination in the elderly to fit these studies for longer-term follow-up, and suggest age-group comparisons in observational research.Clinical trial registry number:NTR6179.

  13. Data from: Association between the severity of influenza A(H7N9) virus...

    • data.niaid.nih.gov
    • zenodo.org
    • +1more
    zip
    Updated May 16, 2017
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    Victor Virlogeux; Juan Yang; Vicky Jing Fang; Luzhao Feng; Tim K. Tsang; Hui Jiang; Peng Wu; Jiandong Zheng; Eric H. Y. Lau; Ying Qin; Zhibin Peng; Joseph Sriyal Malik Peiris; Hongjie Yu; Benjamin J. Cowling (2017). Association between the severity of influenza A(H7N9) virus infections and length of the incubation period [Dataset]. http://doi.org/10.5061/dryad.g2j62
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    zipAvailable download formats
    Dataset updated
    May 16, 2017
    Dataset provided by
    Chinese Center for Disease Control and Prevention
    University of Hong Kong
    Authors
    Victor Virlogeux; Juan Yang; Vicky Jing Fang; Luzhao Feng; Tim K. Tsang; Hui Jiang; Peng Wu; Jiandong Zheng; Eric H. Y. Lau; Ying Qin; Zhibin Peng; Joseph Sriyal Malik Peiris; Hongjie Yu; Benjamin J. Cowling
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    China
    Description

    Background: In early 2013, a novel avian-origin influenza A(H7N9) virus emerged in China, and has caused sporadic human infections. The incubation period is the delay from infection until onset of symptoms, and varies from person to person. Few previous studies have examined whether the duration of the incubation period correlates with subsequent disease severity. Methods and Findings: We analyzed data of period of exposure on 395 human cases of laboratory-confirmed influenza A(H7N9) virus infection in China in a Bayesian framework using a Weibull distribution. We found a longer incubation period for the 173 fatal cases with a mean of 3.7 days (95% credibility interval, CrI: 3.4–4.1), compared to a mean of 3.3 days (95% CrI: 2.9–3.6) for the 222 non-fatal cases, and the difference in means was marginally significant at 0.47 days (95% CrI: -0.04, 0.99). There was a statistically significant correlation between a longer incubation period and an increased risk of death after adjustment for age, sex, geographical location and underlying medical conditions (adjusted odds ratio 1.70 per day increase in incubation period; 95% credibility interval 1.47–1.97). Conclusions: We found a significant association between a longer incubation period and a greater risk of death among human H7N9 cases. The underlying biological mechanisms leading to this association deserve further exploration.

  14. f

    Table_4_Impact of influenza related hospitalization in Spain:...

    • frontiersin.figshare.com
    docx
    Updated Apr 2, 2024
    + more versions
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    José-Manuel Ramos-Rincón; Héctor Pinargote-Celorio; Pilar González-de-la-Aleja; José Sánchez-Payá; Sergio Reus; Juan-Carlos Rodríguez-Díaz; Esperanza Merino (2024). Table_4_Impact of influenza related hospitalization in Spain: characteristics and risk factor of mortality during five influenza seasons (2016 to 2021).DOCX [Dataset]. http://doi.org/10.3389/fpubh.2024.1360372.s004
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    docxAvailable download formats
    Dataset updated
    Apr 2, 2024
    Dataset provided by
    Frontiers
    Authors
    José-Manuel Ramos-Rincón; Héctor Pinargote-Celorio; Pilar González-de-la-Aleja; José Sánchez-Payá; Sergio Reus; Juan-Carlos Rodríguez-Díaz; Esperanza Merino
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundEstimating the global influenza burden in terms of hospitalization and death is important for optimizing prevention policies. Identifying risk factors for mortality allows for the design of strategies tailored to groups at the highest risk. This study aims to (a) describe the clinical characteristics of hospitalizations with a diagnosis of influenza over five flu seasons (2016–2017 to 2020–2021), (b) assess the associated morbidity (hospitalization rates and ICU admissions rate), mortality and cost of influenza hospitalizations in different age groups and (c) analyze the risk factors for mortality.MethodsThis retrospective study included all hospital admissions with a diagnosis of influenza in Spain for five influenza seasons. Data were extracted from the Spanish National Surveillance System for Hospital Data from 1 July 2016 to 30 June 2021. We identified cases coded as having influenza as a primary or secondary diagnosis (International Classification of Diseases, 10th revision, J09-J11). The hospitalization rate was calculated relative to the general population. Independent predictors of mortality were identified using multivariable logistic regression.ResultsOver the five seasons, there were 127,160 hospitalizations with a diagnosis of influenza. The mean influenza hospitalization rate varied from 5/100,000 in 2020–2021 (COVID-19 pandemic) to 92.9/100,000 in 2017–2018. The proportion of influenza hospitalizations with ICU admission was 7.4% and was highest in people aged 40–59 years (13.9%). The case fatality rate was 5.8% overall and 9.4% in those aged 80 years or older. Median length of stay was 5 days (and 6 days in the oldest age group). In the multivariable analysis, independent risk factors for mortality were male sex (odds ratio [OR] 1.14, 95% confidence interval [95% CI] 1.08–1.20), age (

  15. h

    Supporting data for "Excess mortality during the COVID-19 pandemic in Hong...

    • datahub.hku.hk
    xlsx
    Updated Apr 22, 2025
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    Shuqi Xu (2025). Supporting data for "Excess mortality during the COVID-19 pandemic in Hong Kong and South Korea" [Dataset]. http://doi.org/10.25442/hku.27273840.v1
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    xlsxAvailable download formats
    Dataset updated
    Apr 22, 2025
    Dataset provided by
    HKU Data Repository
    Authors
    Shuqi Xu
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Area covered
    Hong Kong
    Description

    Results data for the thesis on estimating the age-, sex-, cause-specific excess mortality during the COVID-19 pandemic in Hong Kong and South Korea.Thesis abstractBackgroundFew studies used a consistent methodology and adjusted for the risk of influenza-like illness (ILI) in historical mortality trends when estimating and comparing the cause-specific excess mortality (EM) during the COVID-19 pandemic. Previous studies demonstrated that excess mortality was widely reported from CVD and among the elderly. This study aims to estimate and compare the overall, age-, sex-, and cause-specific excess mortality during the COVID-19 pandemic in Hong Kong (HK) and South Korea (SK) with consideration of the impact of ILI.MethodsIn this population-based study, we first fitted a generalized additive model to the monthly mortality data from Jan 2010 to Dec 2019 in HK and SK before the COVID-19 pandemic. Then we applied the fitted model to estimate the EM from Jan 2020 to Dec 2022. The month index was modelled with a natural cubic spline. Akaike information criterion (AIC) was used to select the number of knots for the spline and inclusion of covariates such as monthly mean temperature, absolute humidity, ILI consultation rate, and the proxy for flu activity.FindingsFrom 2020 to 2022, the EM in HK was 239.8 (95% CrI: 184.6 to 293.9) per 100,000 population. Excess mortality from respiratory diseases (RD) (ICD-10 code: J00-J99), including COVID-19 deaths coded as J98.8, was 181.3 (95% CrI: 149.9 to 210.4) per 100,000. Except for RD, the majority of the EM in HK was estimated from cardiovascular diseases (CVD) (22.4% of the overall EM), influenza and pneumonia (16.2%), ischemic heart disease (8.9%), ill-defined causes (8.6%) and senility (6.7%). No statistically significant reduced deaths were estimated among other studied causes.From 2020 to 2022, the EM in SK was 204.7 (95% CrI: 161.6 to 247.2) per 100,000 population. Of note, COVID-19 deaths in SK were not included in deaths from RD but were recorded with the codes for emergency use as U07.1 or U07.2. The majority of the EM was estimated from ill-defined causes (32.0% of the overall EM), senility (16.6%), cerebrovascular disease (6.8%) and cardiovascular diseases (6.1%). Statistically significant reduction in mortality with 95 CrI lower than zero was estimated from vascular, other and unspecified dementia (-26.9% of expected deaths), influenza and pneumonia (-20.7%), mental and behavioural disorders (-18.8%) and respiratory diseases (-7.7%).InterpretationExcluding RD in HK which includes COVID-19 deaths, the majority of the EM in HK and SK was from CVD and senility. Mortality from influenza and pneumonia was estimated to have a statistically significant increase in HK but a decrease in SK probability due to different coding practices. HK had a heavier burden of excess mortality in the elderly age group 70-79 years and 80 years or above, while SK had a heavier burden in the age group of 60-69 years. Both HK and SK have a heavier burden of excess mortality from males than females. Better triage systems for identifying high-risk people of the direct or indirect impact of the epidemic are needed to minimize preventable mortality.

  16. f

    Data_Sheet_1_Influenza vs. COVID-19: Comparison of Clinical Characteristics...

    • frontiersin.figshare.com
    pdf
    Updated May 30, 2023
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    Almudena Laris-González; Martha Avilés-Robles; Clemen Domínguez-Barrera; Israel Parra-Ortega; José Luis Sánchez-Huerta; Karla Ojeda-Diezbarroso; Sergio Bonilla-Pellegrini; Víctor Olivar-López; Adrián Chávez-López; Rodolfo Jiménez-Juárez (2023). Data_Sheet_1_Influenza vs. COVID-19: Comparison of Clinical Characteristics and Outcomes in Pediatric Patients in Mexico City.PDF [Dataset]. http://doi.org/10.3389/fped.2021.676611.s001
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    pdfAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Frontiers
    Authors
    Almudena Laris-González; Martha Avilés-Robles; Clemen Domínguez-Barrera; Israel Parra-Ortega; José Luis Sánchez-Huerta; Karla Ojeda-Diezbarroso; Sergio Bonilla-Pellegrini; Víctor Olivar-López; Adrián Chávez-López; Rodolfo Jiménez-Juárez
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Mexico City
    Description

    Introduction: Respiratory viruses are among the leading causes of disease and death among children. Co-circulation of influenza and SARS-CoV2 can lead to diagnostic and management difficulties given the similarities in the clinical picture.Methods: This is a cohort of all children hospitalized with SARS-CoV2 infection from March to September 3rd 2020, and all children admitted with influenza throughout five flu-seasons (2013–2018) at a pediatric referral hospital. Patients with influenza were identified from the clinical laboratory database. All hospitalized patients with confirmed SARS-CoV2 infection were followed-up prospectively.Results: A total of 295 patients with influenza and 133 with SARS-CoV2 infection were included. The median age was 3.7 years for influenza and 5.3 years for SARS-CoV2. Comorbidities were frequent in both groups, but they were more common in patients with influenza (96.6 vs. 82.7%, p < 0.001). Fever and cough were the most common clinical manifestations in both groups. Rhinorrhea was present in more than half of children with influenza but was infrequent in those with COVID-19 (53.6 vs. 5.8%, p < 0.001). Overall, 6.4% percent of patients with influenza and 7.5% percent of patients with SARS-CoV2 infection died. In-hospital mortality and the need for mechanical ventilation among symptomatic patients were similar between groups in the multivariate analysis.Conclusions: Influenza and COVID-19 have a similar picture in pediatric patients, which makes diagnostic testing necessary for adequate diagnosis and management. Even though most cases of COVID-19 in children are asymptomatic or mild, the risk of death among hospitalized patients with comorbidities may be substantial, especially among infants.

  17. f

    Childhood immune imprinting to influenza A shapes birth year-specific risk...

    • figshare.com
    tiff
    Updated May 30, 2023
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    Katelyn M. Gostic; Rebecca Bridge; Shane Brady; Cécile Viboud; Michael Worobey; James O. Lloyd-Smith (2023). Childhood immune imprinting to influenza A shapes birth year-specific risk during seasonal H1N1 and H3N2 epidemics [Dataset]. http://doi.org/10.1371/journal.ppat.1008109
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    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOS Pathogens
    Authors
    Katelyn M. Gostic; Rebecca Bridge; Shane Brady; Cécile Viboud; Michael Worobey; James O. Lloyd-Smith
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Across decades of co-circulation in humans, influenza A subtypes H1N1 and H3N2 have caused seasonal epidemics characterized by different age distributions of cases and mortality. H3N2 causes the majority of severe, clinically attended cases in high-risk elderly cohorts, and the majority of overall deaths, whereas H1N1 causes fewer deaths overall, and cases shifted towards young and middle-aged adults. These contrasting age profiles may result from differences in childhood imprinting to H1N1 and H3N2 or from differences in evolutionary rate between subtypes. Here we analyze a large epidemiological surveillance dataset to test whether childhood immune imprinting shapes seasonal influenza epidemiology, and if so, whether it acts primarily via homosubtypic immune memory or via broader, heterosubtypic memory. We also test the impact of evolutionary differences between influenza subtypes on age distributions of cases. Likelihood-based model comparison shows that narrow, within-subtype imprinting shapes seasonal influenza risk alongside age-specific risk factors. The data do not support a strong effect of evolutionary rate, or of broadly protective imprinting that acts across subtypes. Our findings emphasize that childhood exposures can imprint a lifelong immunological bias toward particular influenza subtypes, and that these cohort-specific biases shape epidemic age distributions. As a consequence, newer and less “senior” antibody responses acquired later in life do not provide the same strength of protection as responses imprinted in childhood. Finally, we project that the relatively low mortality burden of H1N1 may increase in the coming decades, as cohorts that lack H1N1-specific imprinting eventually reach old age.

  18. f

    A Comparative Analysis of Influenza Vaccination Programs

    • plos.figshare.com
    pdf
    Updated Jun 1, 2023
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    Shweta Bansal; Babak Pourbohloul; Lauren Ancel Meyers (2023). A Comparative Analysis of Influenza Vaccination Programs [Dataset]. http://doi.org/10.1371/journal.pmed.0030387
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    pdfAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS Medicine
    Authors
    Shweta Bansal; Babak Pourbohloul; Lauren Ancel Meyers
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundThe threat of avian influenza and the 2004–2005 influenza vaccine supply shortage in the United States have sparked a debate about optimal vaccination strategies to reduce the burden of morbidity and mortality caused by the influenza virus. Methods and FindingsWe present a comparative analysis of two classes of suggested vaccination strategies: mortality-based strategies that target high-risk populations and morbidity-based strategies that target high-prevalence populations. Applying the methods of contact network epidemiology to a model of disease transmission in a large urban population, we assume that vaccine supplies are limited and then evaluate the efficacy of these strategies across a wide range of viral transmission rates and for two different age-specific mortality distributions. We find that the optimal strategy depends critically on the viral transmission level (reproductive rate) of the virus: morbidity-based strategies outperform mortality-based strategies for moderately transmissible strains, while the reverse is true for highly transmissible strains. These results hold for a range of mortality rates reported for prior influenza epidemics and pandemics. Furthermore, we show that vaccination delays and multiple introductions of disease into the community have a more detrimental impact on morbidity-based strategies than mortality-based strategies. ConclusionsIf public health officials have reasonable estimates of the viral transmission rate and the frequency of new introductions into the community prior to an outbreak, then these methods can guide the design of optimal vaccination priorities. When such information is unreliable or not available, as is often the case, this study recommends mortality-based vaccination priorities.

  19. Cost of influenza related health outcomes for different age and risk groups....

    • plos.figshare.com
    xls
    Updated May 31, 2023
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    Nargesalsadat Dorratoltaj; Achla Marathe; Bryan L. Lewis; Samarth Swarup; Stephen G. Eubank; Kaja M. Abbas (2023). Cost of influenza related health outcomes for different age and risk groups. [Dataset]. http://doi.org/10.1371/journal.pcbi.1005521.t005
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    xlsAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Nargesalsadat Dorratoltaj; Achla Marathe; Bryan L. Lewis; Samarth Swarup; Stephen G. Eubank; Kaja M. Abbas
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The costs of influenza related health outcomes of death, hospitalization, outpatient, and ill but not seeking medical care are based on the study by Carias et al [39], and are updated to 2015 US dollars.

  20. f

    Outcomes of Influenza A(H1N1)pdm09 Virus Infection: Results from Two...

    • plos.figshare.com
    doc
    Updated Jun 1, 2023
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    Ruth Lynfield; Richard Davey; Dominic E. Dwyer; Marcelo H. Losso; Deborah Wentworth; Alessandro Cozzi-Lepri; Kathy Herman-Lamin; Grazyna Cholewinska; Daniel David; Stefan Kuetter; Zelalem Ternesgen; Timothy M. Uyeki; H. Clifford Lane; Jens Lundgren; James D. Neaton (2023). Outcomes of Influenza A(H1N1)pdm09 Virus Infection: Results from Two International Cohort Studies [Dataset]. http://doi.org/10.1371/journal.pone.0101785
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    docAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Ruth Lynfield; Richard Davey; Dominic E. Dwyer; Marcelo H. Losso; Deborah Wentworth; Alessandro Cozzi-Lepri; Kathy Herman-Lamin; Grazyna Cholewinska; Daniel David; Stefan Kuetter; Zelalem Ternesgen; Timothy M. Uyeki; H. Clifford Lane; Jens Lundgren; James D. Neaton
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundData from prospectively planned cohort studies on risk of major clinical outcomes and prognostic factors for patients with influenza A(H1N1)pdm09 virus are limited. In 2009, in order to assess outcomes and evaluate risk factors for progression of illness, two cohort studies were initiated: FLU 002 in outpatients and FLU 003 in hospitalized patients.Methods and FindingsBetween October 2009 and December 2012, adults with influenza-like illness (ILI) were enrolled; outpatients were followed for 14 days and inpatients for 60 days. Disease progression was defined as hospitalization and/or death for outpatients, and hospitalization for >28 days, transfer to intensive care unit (ICU) if enrolled from general ward, and/or death for inpatients. Infection was confirmed by RT-PCR. 590 FLU 002 and 392 FLU 003 patients with influenza A (H1N1)pdm09 were enrolled from 81 sites in 17 countries at 2 days (IQR 1–3) and 6 days (IQR 4–10) following ILI onset, respectively. Disease progression was experienced by 29 (1 death) outpatients (5.1%; 95% CI: 3.4–7.2%) and 80 inpatients death (32), hospitalization >28 days (43) or ICU transfer (20). Disease progression (death) for hospitalized patients was 53.1% (26.6%) and 12.8% (3.8%), respectively, for those enrolled in the ICU and general ward. In pooled analyses for both studies, predictors of disease progression were age, longer duration of symptoms at enrollment and immunosuppression. Patients hospitalized during the pandemic period had a poorer prognosis than in subsequent seasons.ConclusionsPatients with influenza A(H1N1)pdm09, particularly when requiring hospital admission, are at high risk for disease progression, especially if they are older, immunodeficient, or admitted late in infection. These data reinforce the need for international trials of novel treatment strategies for influenza infection and serve as a reminder of the need to monitor the severity of seasonal and pandemic influenza epidemics globally.Trial RegistrationClinicalTrials.gov Identifiers: FLU 002- NCT01056354, FLU 003- NCT01056185.

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Statista (2025). Mortality rate for influenza in the U.S. in 2023-2024, by age group [Dataset]. https://www.statista.com/statistics/1127799/influenza-us-mortality-rate-by-age-group/
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Mortality rate for influenza in the U.S. in 2023-2024, by age group

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3 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Apr 14, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
2023 - 2024
Area covered
United States
Description

The mortality rate from influenza in the United States is by far highest among those aged 65 years and older. During the 2023-2024 flu season, the mortality rate from influenza for this age group was around 32.1 per 100,000 population. The burden of influenza The impact of influenza in the U.S. varies from season to season, but in the 2023-2024 flu season, there were an estimated 40 million cases. These cases resulted in around 470,000 hospitalizations. Although most people recover from influenza without requiring medical treatment, the disease can be deadly for young children, the elderly, and those with weakened immune systems or chronic illnesses. During the 2023-2024 flu season, around 28,000 people in the U.S. lost their lives due to influenza. Impact of vaccinations The most effective way to prevent influenza is to receive an annual vaccination at the beginning of flu season. Flu vaccines are safe and can greatly reduce the burden of the disease. During the 2022-2023 flu season, vaccinations prevented around 2,479 deaths among those aged 65 years and older. Although flu vaccines are usually cheap and easily accessible, every year a large share of the population in the U.S. still does not get vaccinated. For example, during the 2022-2023 flu season, only about 35 percent of those aged 18 to 49 years received a flu vaccination.

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