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.

Following the outbreak of the H1N1 influenza pandemic of 1918, which came to be known as the Spanish Flu, the number of deaths due to influenza and pneumonia soared. Pneumonia was caused either by the influenza or by a bacterial superinfection that took hold due to the patient's weakened state as a result of the influenza, for this reason, influenza deaths and pneumonia deaths were recorded together as one. Pennsylvania had the highest mortality rate due to the pandemic, where there were over 880 fatalities per 100,000 people; meaning that approximately 0.9 percent of the state's population died from the Spanish Flu pandemic in 1918.

When compared with the 1915 mortality rates, many states, such as California and Pennsylvania, saw their mortality rate due to influenza and pneumonia increase five-fold by 1818, which was the worst year of the pandemic. While the mortality rate decreased significantly in the year 1919, there was no US state where it fell to it's pre-pandemic level, and the 1919 mortality rate was still double the pre-pandemic rate in some states such as California, South Carolina and Washington.

The burden of influenza in the United States can vary from year to year depending on which viruses are circulating, how many people receive an influenza vaccination, and how effective the vaccination is in that particular year. During the 2023-2024 flu season, around 28,000 people lost their lives to the disease. Although most people recover from influenza without needing medical care, the disease can be deadly among young children, the elderly, and those with weakened immune systems or chronic illnesses. Deaths due to influenza Even though most people recover from influenza without medical care, influenza and pneumonia can be deadly, especially for older people and those with certain preexisting conditions. Influenza is a common cause of pneumonia and although most cases of influenza do not develop into pneumonia, those that do are often more severe and more deadly. Deaths due to influenza are most common among the elderly, with a mortality rate of around 32 per 100,000 population during the 2023-2024 flu season. In comparison, the mortality rate for those aged 50 to 64 years was 9.1 per 100,000 population. Flu vaccinations The most effective way to prevent influenza is to receive an annual influenza vaccination. These vaccines have proven to be safe and are usually cheap and easily accessible. Nevertheless, every year a large share of the population in the United States still fails to get vaccinated against influenza. For example, in the 2022-2023 flu season, only 35 percent of those aged 18 to 49 years received a flu vaccination. Unsurprisingly, children and the elderly are the most likely to get vaccinated. It is estimated that during the 2022-2023 flu season, vaccinations prevented over 929 thousand influenza cases among children aged 6 months to 4 years.

The graph illustrates the number of flu-related deaths in the United States for each flu season from 2010-2011 to 2023-2024*. The x-axis represents the flu seasons, labeled from '10-11 to '23*-24*, while the y-axis shows the annual number of flu deaths. Throughout this period, flu deaths vary significantly, ranging from a low of 4,900 in the 2021-2022* season to a high of 51,000 in both the 2014-2015 and 2017-2018 seasons. Other notable figures include 36,000 deaths in 2010-2011, 42,000 in 2012-2013, and a recent increase to 28,000 in the 2023*-2024* season. The data exhibits considerable fluctuations with no consistent upward or downward trend, highlighting the variability in flu mortality rates over the years. This information is presented in a line graph format, effectively showcasing the yearly changes and peaks in flu-related deaths across the United States.

*Data for the 2021-2022 and 2022-2023 seasons are estimated.

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

In 2021, there were four death cases caused by the influenza virus in China. The death rate of the virus amounted to approximately 0.0003 out of ten million people. Influenza, commonly known as "flu", is a highly contagious respiratory disease caused by influenza A or B viruses and can be prevented by vaccines. It should be noted that the Chinese health authorities calculate death cases for infectious diseases differently, counting only patients who died directly from the infectious disease.

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".

Following variables were used for confounding adjustment. All variables are measured at the time of hospital admission.

Data from influenza A virus (IAV) infected ferrets (Mustela putorius furo) provides invaluable information towards the study of novel and emerging viruses that pose a threat to human health. This gold standard animal model can recapitulate many clinical signs of infection present in IAV-infected humans, support virus replication of human and zoonotic strains without prior adaptation, and permit evaluation of virus transmissibility by multiple modes. While ferrets have been employed in risk assessment settings for >20 years, results from this work are typically reported in discrete stand-alone publications, making aggregation of raw data from this work over time nearly impossible. Here, we describe a dataset of 728 ferrets inoculated with 126 unique IAV, conducted by a single research group (NCIRD/ID/IPB/Pathogenesis Laboratory Team) under a uniform experimental protocol. This collection of morbidity, mortality, and viral titer data represents the largest publicly available dataset to date of in vivo-generated IAV infection outcomes on a per-individual ferret level. Published Data Descriptor for more information: Kieran TJ, Sun X, Creager HM, Tumpey TM, Maine TR, Belser JA. 2024. An aggregated dataset of serial morbidity and titer measurements from influenza A virus-infected ferrets. Sci Data 11, 510. https://doi.org/10.1038/s41597-024-03256-6 Additional publications using and describing data: Kieran TJ, Sun X, Maines TR, Beauchemin CAA, Belser JA. 2024. Exploring associations between viral titer measurements and disease outcomes in ferrets inoculated with 125 contemporary influenza A viruses. J Virol98:e01661-23.https://doi.org/10.1128/jvi.01661-23 Belser JA, Kieran TJ, Mitchell ZA, Sun X, Mayfield K, Tumpey TM, Spengler JR, Maines TR. 2024. Key considerations to improve the normalization, interpretation and reproducibility of morbidity data in mammalian models of viral disease. Dis Model Mech; 17 (3): dmm050511. doi: https://doi.org/10.1242/dmm.050511 Kieran TJ, Sun X, Maines TR, Belser JA. 2024. Machine learning approaches for influenza A virus risk assessment identifies predictive correlates using ferret model in vivo data. Communications Biology 7, 927. https://doi.org/10.1038/s42003-024-06629-0

In 2023, the number of deaths from influenza in Japan decreased to 1383 cases, which marked an increase compared to just 24 cases in the previous year. The death rate from influenza amounted to 1.1 death cases per 100,000 inhabitants in 2023.

Eight geographical divisions showing population and influenza mortality information for their respective towns and cities.

Flu Vaccination Market Outlook

The global flu vaccination market size was valued at approximately USD 5.8 billion in 2023 and is projected to reach around USD 9.7 billion by 2032, growing at a CAGR of 5.8% during the forecast period. This growth is driven by increasing awareness about the importance of flu vaccination, advancements in vaccine technology, and supportive government policies. With the evolving healthcare landscape and the rising prevalence of influenza, the flu vaccination market is poised for significant expansion across various regions.

The primary growth factor for the flu vaccination market is the rising awareness regarding the critical role of flu vaccines in preventing seasonal influenza outbreaks. Governments and healthcare organizations worldwide have been actively advocating for increased vaccination coverage, emphasizing the vaccine's effectiveness in reducing flu-related morbidity and mortality. Public health campaigns, educational initiatives, and community outreach programs have collectively contributed to higher vaccination rates, thereby driving market growth.

Another significant factor propelling the market is the advancements in vaccine technology. The development of more effective and safer vaccines, including cell-based and recombinant technologies, has enhanced the efficacy and accessibility of flu vaccines. These innovations have addressed some of the limitations associated with traditional egg-based vaccines, such as longer production times and allergic reactions. As a result, the adoption of advanced flu vaccines is on the rise, further boosting market growth.

Additionally, the growing geriatric population is a crucial factor driving the demand for flu vaccinations. Older adults are more susceptible to severe flu-related complications, making vaccination essential for this age group. The increasing prevalence of chronic diseases among the elderly, which can exacerbate flu symptoms, has further underscored the importance of flu vaccination. As the global population ages, the demand for flu vaccines is expected to rise, thereby contributing to market expansion.

The emergence of H7N9 Vaccines marks a significant advancement in the fight against avian influenza. These vaccines are specifically designed to combat the H7N9 strain, which has been a concern due to its potential to cause severe respiratory illness in humans. The development of H7N9 vaccines has been accelerated by global health organizations and pharmaceutical companies, aiming to provide effective protection against this particular strain. The introduction of these vaccines is expected to enhance the overall influenza vaccination strategy, offering an additional layer of defense against potential pandemics. As research continues, the integration of H7N9 vaccines into existing flu vaccination programs could further bolster public health efforts, ensuring comprehensive coverage against diverse influenza strains.

On a regional level, North America currently holds a significant share in the flu vaccination market, primarily due to the robust healthcare infrastructure, high awareness levels, and supportive government policies. The region's focus on preventive healthcare measures and the presence of key market players have also played a vital role. However, the Asia Pacific region is anticipated to witness the highest growth rate during the forecast period. Factors such as increasing healthcare expenditure, growing awareness, and government initiatives to improve vaccination coverage are driving the market in this region.

Vaccine Type Analysis

The flu vaccination market can be segmented by vaccine type into trivalent and quadrivalent vaccines. Trivalent vaccines, which protect against three strains of the influenza virus, have been the traditional choice for flu prevention. These vaccines have been extensively used and have a well-established track record of efficacy and safety. However, their coverage is limited to two influenza A strains and one influenza B strain, which may not provide comprehensive protection against all circulating strains.

In contrast, quadrivalent vaccines offer broader protection by including an additional influenza B strain. This added coverage is particularly beneficial during seasons when multiple B strains are in circulation. The increased efficacy of quadrivalent vaccines has led to their growing adoption in recent years. Healthcare providers and public health organizations are incre

Context

New York has presented the most cases compared to all states across the U.S..There have also been critiques regarding how much more unnoticed impact the flu has caused. My dataset allows us to compare whether or not this is true according to the most recent data.

Content

This COVID-19 data is from Kaggle whereas the New York influenza data comes from the U.S. government health data website. I merged the two datasets by county and FIPS code and listed the most recent reports of 2020 COVID-19 cases and deaths alongside the 2019 known influenza cases for comparison.

Acknowledgements

I am thankful to Kaggle and the U.S. government for making the data that made this possible openly available.

Inspiration

This data can be extended to answer the common misconceptions of the scale of the COVID-19 and common flu. My inspiration stems from supporting conclusions with data rather than simply intuition.

I would like my data to help answer how we can make U.S. citizens realize what diseases are most impactful.

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.

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.

In 2022, the highest death rate from influenza and pneumonia in Canada per 100,000 population was reported among those aged 90 years and older, with around 588 deaths. Individuals between 85 and 89 years followed, with a mortality rate from influenza and pneumonia of almost 210 deaths per 100,000 people. This statistic displays the death rate from influenza and pneumonia per 100,000 population in Canada during 2022, by age.

For current version see: https://data.sandiegocounty.gov/Health/2021-Communicable-Diseases/2fvf-e98n

Basic Metadata *Rates per 100,000 population. Age-adjusted rates per 100,000 2000 US standard population.

**Blank Cells: Rates not calculated for fewer than 5 events. Rates not calculated in cases where zip code is unknown.

***API: Asian/Pacific Islander. ***AIAN: American Indian/Alaska Native.

Prepared by: County of San Diego, Health & Human Services Agency, Public Health Services, Community Health Statistics Unit, 2019.

Code Source: ICD-9CM - AHRQ HCUP CCS v2015. ICD-10CM - AHRQ HCUP CCS v2018. ICD-10 Mortality - California Department of Public Health, Group Cause of Death Codes 2013; NHCS ICD-10 2e-v1 2017.

Data Guide, Dictionary, and Codebook: https://www.sandiegocounty.gov/content/dam/sdc/hhsa/programs/phs/CHS/Community%20Profiles/Public%20Health%20Services%20Codebook_Data%20Guide_Metadata_10.2.19.xlsx