Between January and August 2020, there has been approximately 48.2 thousand deaths in England and Wales with COVID-19 as an underlying cause. As illustrated in the table, the number of deaths as a result of COVID-19 are much higher than from either pneumonia or influenza. There has been over three times the number of deaths from COVID-19 than pneumonia and influenza so far in 2020. The overall number of confirmed COVID-19 cases in the UK can be found here. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

This statistic shows the deaths with influenza as an underlying cause in England and Wales in 2023, by age and gender. In this year, influenza was the underlying cause of *** deaths for women aged 90 years and over. Respiratory disease burden in the UK As of 2023, tuberculosis cases had also been on the rise, with ***** new cases and relapses reported in 2023. The ***** age group was most affected by this respiratory disease, accounting for approximately ***** cases. Pneumonia, another serious respiratory condition, caused over ***** deaths among women aged 90 and older in the same year, with a further ***** men in the same age group having pneumonia as their underlying cause of death. Vaccination prevalence and accessibility In the years 2014-2015, **** percent of individuals aged 65 and over in the North West of England were immunized against influenza. This was the region with the highest share of elderly vaccinated against influenza, while this figure was the lowest in London, around **** percent. Community pharmacies have played a crucial role in providing seasonal influenza vaccination services – as of 2023/24, ** percent of community pharmacies in the South of England offered influenza vaccination advanced service, while in London, the figure reached ** percent.

Forecast: Hospital Average Length of Stay for Acute Upper Respiratory Infections and Influenza Cases in the UK 2024 - 2028 Discover more data with ReportLinker!

Smoking is a leading preventable cause of chronic diseases like circulatory disease, cancer, and chronic lung conditions, worsening outcomes in acute illnesses. Despite reductions from public health campaigns, 13-16% of the UK population still smoke, with higher rates in hospital admissions. Smoking-related admissions cost over £870,000 annually, prompting a focus on smoking cessation, particularly in secondary care, where targeted interventions are effective. Influenza often leads to severe complications in hospitals, such as ICU admission and death, especially in older adults and those with chronic respiratory conditions. Smoking increases risks of mortality and ICU admission in influenza cases, but UK-specific data, especially on seasonal influenza, is limited. Updated data on high-risk groups, including smokers, is crucial to guide interventions. This dataset of 26,047 admissions between Jan 2018 and Jul 2024 with influenza, includes demography, serial physiology, assessments, diagnostic codes (ICD-10 & SNOMED-CT), initial presentation, ventilation, ICU transfers, prescriptions and outcomes. Geography: The West Midlands (WM) has a population of 6 million & includes a diverse ethnic & socio-economic mix. UHB is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & > 120 ITU bed capacity. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. Data set availability: Data access is available via the PIONEER Hub for projects which will benefit the public or patients. This can be by developing a new understanding of disease, by providing insights into how to improve care, or by developing new models, tools, treatments, or care processes. Data access can be provided to NHS, academic, commercial, policy and third sector organisations. Applications from SMEs are welcome. There is a single data access process, with public oversight provided by our public review committee, the Data Trust Committee. Contact pioneer@uhb.nhs.uk or visit www.pioneerdatahub.co.uk for more details. Available supplementary data: Matched controls; ambulance and community data. Unstructured data (images). We can provide the dataset in OMOP and other common data models and can build synthetic data to meet bespoke requirements. Available supplementary support: Analytics, model build, validation & refinement; A.I. support. Data partner support for ETL (extract, transform & load) processes. Bespoke and “off the shelf” Trusted Research Environment (TRE) build and run. Consultancy with clinical, patient & end-user and purchaser access/ support. Support for regulatory requirements. Cohort discovery. Data-driven trials and “fast screen” services to assess population size.

Forecast: Hospital Discharges for Acute Upper Respiratory Infections and Influenza Cases in the UK 2024 - 2028 Discover more data with ReportLinker!

Over 12 million people in the United States died from all causes between the beginning of January 2020 and August 21, 2023. Over 1.1 million of those deaths were with confirmed or presumed COVID-19.

Vaccine rollout in the United States Finding a safe and effective COVID-19 vaccine was an urgent health priority since the very start of the pandemic. In the United States, the first two vaccines were authorized and recommended for use in December 2020. One has been developed by Massachusetts-based biotech company Moderna, and the number of Moderna COVID-19 vaccines administered in the U.S. was over 250 million. Moderna has also said that its vaccine is effective against the coronavirus variants first identified in the UK and South Africa.

These datasets comprise the main analyses for the paper “Household Transmission of Seasonal Coronavirus Infections: Results from the Flu Watch cohort study”, published in Wellcome Open Research. Details of the statistical methods are reported in the article. Datasets are given in CSV format and, where relevant, in .dta format. Descriptions for each dataset are as follows:

Household_CoV_acquired.csv/dta – data required to compute the proportion of cases presumably acquired outside of the household versus and the proportion acquired from household transmission. Each row represents an anonymised PCR-confirmed seasonal coronavirus case.

Household_CoV_TransmissionRisk.csv/dta – data required to compute the risk of symptomatic onward household transmission following a seasonal coronavirus index case, and perform stratified descriptive analyses.

Household_CoV_SAR.csv/.dta – data required to compute the seasonal coronavirus secondary attack risk overall and by strain. Each row represents an anonymised exposed-index pair from a given outbreak.

HH Transmission Serial Interval.csv – presents available, anonymised data required to compute the median clinical-onset serial interval overall and by strain for each household outbreak

Seasonal influenza surveillance is usually carried out by sentinel general practitioners (GPs) who compile weekly reports based on the number of influenza-like illness (ILI) clinical cases observed among visited patients. This traditional practice for surveillance generally presents several issues, such as a delay of one week or more in releasing reports, population biases in the health-seeking behaviour, and the lack of a common definition of ILI case. On the other hand, the availability of novel data streams has recently led to the emergence of non-traditional approaches for disease surveillance that can alleviate these issues. In Europe, a participatory web-based surveillance system called Influenzanet represents a powerful tool for monitoring seasonal influenza epidemics thanks to aid of self-selected volunteers from the general population who monitor and report their health status through Internet-based surveys, thus allowing a real-time estimate of the level of influenza circulating in the population. In this work, we propose an unsupervised probabilistic framework that combines time series analysis of self-reported symptoms collected by the Influenzanet platforms and performs an algorithmic detection of groups of symptoms, called syndromes. The aim of this study is to show that participatory web-based surveillance systems are capable of detecting the temporal trends of influenza-like illness even without relying on a specific case definition. The methodology was applied to data collected by Influenzanet platforms over the course of six influenza seasons, from 2011-2012 to 2016-2017, with an average of 34,000 participants per season. Results show that our framework is capable of selecting temporal trends of syndromes that closely follow the ILI incidence rates reported by the traditional surveillance systems in the various countries (Pearson correlations ranging from 0.69 for Italy to 0.88 for the Netherlands, with the sole exception of Ireland with a correlation of 0.38). The proposed framework was able to forecast quite accurately the ILI trend of the forthcoming influenza season (2016-2017) based only on the available information of the previous years (2011-2016). Furthermore, to broaden the scope of our approach, we applied it both in a forecasting fashion to predict the ILI trend of the 2016-2017 influenza season (Pearson correlations ranging from 0.60 for Ireland and UK, and 0.85 for the Netherlands) and also to detect gastrointestinal syndrome in France (Pearson correlation of 0.66). The final result is a near-real-time flexible surveillance framework not constrained by any specific case definition and capable of capturing the heterogeneity in symptoms circulation during influenza epidemics in the various European countries.

Flu vaccine uptake (%) in school aged children from Reception to Year 6 (age 4 to 11 year olds) between 1st September to the end of January.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 70% vaccine uptake in school aged children in Reception to Year 6 (age 4 to 11 years old).Definition of numeratorThe total number of children in the respective eligible age cohort that have received at least one dose of influenza vaccine from 1 September in school, pharmacy, and general practice.Definition of denominatorThe total number of children eligible for influenza vaccination in the LA geography and children educated out of school in the LA geography, defined by child age on 31 AugustCaveatsData for ICBs are estimated from local authority data. In most cases, ICBs are coterminous with local authorities, so the ICB figures are precise. In cases where local authorities cross ICB boundaries, the local authority data are proportionally split between ICBs, based on the population located in each ICB.The affected ICBs are:Bath and North East Somerset, Swindon and WiltshireBedfordshire, Luton and Milton KeynesBuckinghamshire, Oxfordshire and Berkshire WestCambridgeshire and PeterboroughFrimleyHampshire and Isle of WightHertfordshire and West EssexHumber and North YorkshireLancashire and South CumbriaNorfolk and WaveneyNorth East and North CumbriaSuffolk and North East EssexSurrey HeartlandsSussexWest YorkshireRead 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 may fall outside the listed read codes. Therefore, it is important to note that for the reasons mentioned, this data should not be used for GP payment purposes.This collection is regularly submitted for approval from the Data Coordination Board (DCB).

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Influenza Vaccine Market Size 2024-2028

The influenza vaccine market size is forecast to increase by USD 3.76 billion at a CAGR of 8.09% between 2023 and 2028. The market is experiencing significant growth due to the increasing prevalence and incidence of severe influenza cases, particularly among children. The Global Influenza Program's emphasis on vaccination as a preventative measure is driving market expansion. Combination vaccines, which offer protection against multiple strains of the virus, are gaining popularity due to their convenience and effectiveness. Furthermore, the development of mRNA vaccines, which utilize advanced technology to produce a more potent immune response, is a promising trend in the market. The market for Influenza vaccines encompasses various types, including inactivated vaccines, live attenuated vaccines, quadrivalent vaccines, mono vaccine, trivalent vaccines, pnemucoccol vaccine, pediatric vaccines, and adult vaccines. Despite these advancements, challenges persist, including the difficulty in diagnosing influenza due to its non-specific symptoms and the need for annual revaccination to maintain immunity. Overall, the market is poised for continued growth as the demand for effective vaccines to prevent the spread of influenza remains high.

Market Analysis

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The market is a significant sector within the global healthcare industry, with a continuous demand due to the seasonal nature of the influenza virus and the ongoing threat of potential pandemics. This market caters to various demographics, including children and adults, through various vaccine types and administration methods. Seasonal influenza vaccines are the primary focus of the market, with two main types: inactivated vaccines and live attenuated vaccines. Inactivated vaccines, also known as flu shots, use killed viruses to stimulate an immune response, while live attenuated vaccines, or nasal sprays, use weakened live viruses.

Furthermore, both types offer protection against the three or four strains of the virus predicted to cause the most significant impact during a season. Quadrivalent vaccines, a more recent addition to the market, protect against an additional B strain, broadening the scope of coverage and potentially reducing the risk of infection. Trivalent vaccines, which protect against three strains, continue to be available and are often used in mass vaccination programs. The pediatric segment of the market is of significant importance due to the vulnerability of children to severe influenza cases. The global influenza program, a collaborative effort between the World Health Organization (WHO) and various national health organizations, plays a crucial role in ensuring the availability of vaccines for children and other at-risk populations.

In addition, combination vaccines, which offer protection against influenza and other diseases, are gaining popularity in the market due to their convenience and potential for reducing the number of vaccinations required. MRNA vaccines, a newer technology, have shown promising results in clinical trials and may become a significant player in the market in the coming years. The market is influenced by several factors, including the severity of seasonal epidemics, the availability and affordability of vaccines, and the public's perception of vaccine efficacy and safety. Hospital and retail pharmacies serve as essential distribution channels for these vaccines, ensuring they reach the end consumer in a timely and convenient manner.

Furthermore, swine flu vaccines, while not a regular component of the seasonal the market, are produced and distributed in response to outbreaks or pandemics. The production and distribution of these vaccines require a rapid response and significant resources, highlighting the importance of a strong global influenza program and the flexibility of vaccine manufacturers. In conclusion, the market is a dynamic and evolving sector within the healthcare industry. With ongoing research and development, the market continues to offer new solutions to protect against the influenza virus, ensuring public health and safety.

Market Segmentation

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Distribution Channel

  Hospitals and pharmacies
  Government and institutional
  Others


Type

  Live attenuated influenza vaccines
  Recombinant influenza vaccines


Geography

  North America

    Canada
    US


  Europe

    UK


  Asia

    China
    India


  Rest of World (ROW)

By Distribution Channel Insights

The hospitals and pharmacies segment is estimated to witness significant growth during the forecast period.The market in the US is categorized by distributio

Seasonal influenza is a contagious respiratory viral illness. There are four types of seasonal influenza viruses (A, B, C, and D); however, only types A and B cause human disease of public health concern (WHO, 2014). Influenza transmission occurs when people with flu cough, sneeze, or talk and disseminate droplets. These droplets can land in the mouths or noses of people who then inhale them into the lungs (CDC, 2018).
GlobalData epidemiologists used age- and sex-specific diagnosed prevalence rates to forecast the diagnosed prevalent cases. GlobalData epidemiologists applied country-specific prevalence rates of HS, wherever available, to each country’s population to obtain the number of estimated diagnosed incident cases. Read More

Timing (calendar week in 2009) of key events related to the A/H1N1 pandemic (between April 2009 to March 2010), in the Czech Republic, Denmark, Germany, Spain and the UK (England); pertaining to the epidemiology (cases and deaths), media attention, vaccination and risk perception.

The influenza pandemic of 1918, known as the Spanish Flu, was one of the deadliest and widespread pandemics in human history. The scale of the outbreak, as well as limitations in technology, medicine and communication, create difficulties when trying to uncover accurate figures relating to the pandemic. Estimates suggest that the virus, known as the H1N1 influenza virus, infected more than one quarter of the global population, which equated to approximately 500 million people in 1920. It was responsible for roughly 25 million fatalities, although some projections suggest that it could have caused double this number of deaths. The exact origins of this strain of influenza remain unclear to this day, however it was first noticed in Western Europe in the latter stages of the First World War. Wartime censorship in Europe meant that the severity of the pandemic was under-reported, while news outlets in neutral Spain were free to report openly about the impact of the virus; this gave the illusion that the virus was particularly strong in Spain, giving way to the term "Spanish Flu".

Effects of the virus

By late summer 1918, the pandemic had spread across the entire continent, and the H1N1 virus had mutated into a deadlier strain that weakened the infected's immune system more than traditional influenzas. Some studies suggest that, in contrast to these traditional influenza viruses, having a stronger immune system was actually a liability in the case of the H1N1 virus as it triggered what is known as a "cytokine storm". This is where white blood cells release proteins called cytokines, which signal the body to attack the virus, in turn releasing more white blood cells which release more cytokines. This cycle over-works and greatly weakens the immune system, often giving way to other infections; most commonly pneumonia in the case of the Spanish Flu. For this reason, the Spanish Flu had an uncommonly high fatality rate among young adults, who are traditionally the healthiest group in society. Some theories for the disproportionate death-rate among young adults suggest that the elderly's immune systems benefitted from exposure to earlier influenza pandemics, such as the "Asiatic/Russian Flu" pandemic of 1889.

Decrease in life expectancy As the war in Europe came to an end, soldiers returning home brought the disease to all corners of the world, and the pandemic reached global proportions. Isolated and under-developed nations were especially vulnerable; particularly in Samoa, where almost one quarter of the population died within two months and life expectancy fell to just barely over one year for those born in 1918; this was due to the arrival of a passenger ship from New Zealand in November 1918, where the infected passengers were not quarantined on board, allowing the disease to spread rapidly. Other areas where life expectancy dropped below ten years for those born in 1918 were present-day Afghanistan, the Congo, Fiji, Guatemala, Kenya, Micronesia, Serbia, Tonga and Uganda. The British Raj, now Bangladesh, India and Pakistan, saw more fatalities than any other region, with as many as five percent of the entire population perishing as a result of the pandemic. The pandemic also had a high fatality rate among pregnant women and infants, and greatly impacted infant mortality rates across the world. There were several waves of the pandemic until late 1920, although they decreased in severity as time progressed, and none were as fatal as the outbreak in 1918. A new strain of the H1N1 influenza virus did re-emerge in 2009, and was colloquially known as "Swine Flu"; thankfully it had a much lower fatality rate due to medical advancements across the twentieth century.

BackgroundMeasures of the contribution of influenza to Streptococcus pneumoniae infections, both in the seasonal and pandemic setting, are needed to predict the burden of secondary bacterial infections in future pandemics to inform stockpiling. The magnitude of the interaction between these two pathogens has been difficult to quantify because both infections are mainly clinically diagnosed based on signs and symptoms; a combined viral–bacterial testing is rarely performed in routine clinical practice; and surveillance data suffer from confounding problems common to all ecological studies. We proposed a novel multivariate model for age-stratified disease incidence, incorporating contact patterns and estimating disease transmission within and across groups.Methods and findingsWe used surveillance data from England over the years 2009 to 2017. Influenza infections were identified through the virological testing of samples taken from patients diagnosed with influenza-like illness (ILI) within the sentinel scheme run by the Royal College of General Practitioners (RCGP). Invasive pneumococcal disease (IPD) cases were routinely reported to Public Health England (PHE) by all the microbiology laboratories included in the national surveillance system. IPD counts at week t, conditional on the previous time point t−1, were assumed to be negative binomially distributed. Influenza counts were linearly included in the model for the mean IPD counts along with an endemic component describing some seasonal background and an autoregressive component mimicking pneumococcal transmission. Using age-specific counts, Akaike information criterion (AIC)-based model selection suggested that the best fit was obtained when the endemic component was expressed as a function of observed temperature and rainfall. Pneumococcal transmission within the same age group was estimated to explain 33.0% (confidence interval [CI] 24.9%–39.9%) of new cases in the elderly, whereas 50.7% (CI 38.8%–63.2%) of incidence in adults aged 15–44 years was attributed to transmission from another age group. The contribution of influenza on IPD during the 2009 pandemic also appeared to vary greatly across subgroups, being highest in school-age children and adults (18.3%, CI 9.4%–28.2%, and 6.07%, CI 2.83%–9.76%, respectively). Other viral infections, such as respiratory syncytial virus (RSV) and rhinovirus, also seemed to have an impact on IPD: RSV contributed 1.87% (CI 0.89%–3.08%) to pneumococcal infections in the 65+ group, whereas 2.14% (CI 0.87%–3.57%) of cases in the group of 45- to 64-year-olds were attributed to rhinovirus. The validity of this modelling strategy relies on the assumption that viral surveillance adequately represents the true incidence of influenza in the population, whereas the small numbers of IPD cases observed in the younger age groups led to significant uncertainty around some parameter estimates.ConclusionsOur estimates suggested that a pandemic wave of influenza A/H1N1 with comparable severity to the 2009 pandemic could have a modest impact on school-age children and adults in terms of IPD and a small to negligible impact on infants and the elderly. The seasonal impact of other viruses such as RSV and rhinovirus was instead more important in the older population groups.