Seasonal influenza epidemics have a substantial public health and economic burden in the United States (US). On average, over 200,000 people are hospitalized and an estimated 23,000 people die from respiratory and circulatory complications associated with seasonal influenza virus infections each year. Annual direct medical costs and indirect productivity costs across the US have been found to average respectively at $10.4 billion and $16.3 billion. The objective of this study was to estimate the economic impact of severe influenza-induced illness on the US Veterans Affairs population. The five-year study period included 2010 through 2014. Influenza-attributed outcomes were estimated with a statistical regression model using observed emergency department (ED) visits, hospitalizations, and deaths from the Veterans Health Administration of the Department of Veterans Affairs (VA) electronic medical records and respiratory viral surveillance data from the Centers for Disease Control and Prevention (CDC). Data from VA’s Managerial Cost Accounting system were used to estimate the costs of the emergency department and hospital visits. Data from the Bureau of Labor Statistics were used to estimate the costs of lost productivity; data on age at death, life expectancy and economic valuations for a statistical life year were used to estimate the costs of a premature death. An estimated 10,674 (95% CI 8,661–12,687) VA ED visits, 2,538 (95% CI 2,112–2,964) VA hospitalizations, 5,522 (95% CI 4,834–6,210) all-cause deaths, and 3,793 (95% CI 3,375–4,211) underlying respiratory or circulatory deaths (inside and outside VA) among adult Veterans were attributable to influenza each year from 2010 through 2014. The annual value of lost productivity amounted to $27 (95% CI $24–31) million and the annual costs for ED visits were $6.2 (95% CI $5.1–7.4) million. Ninety-six percent of VA hospitalizations resulted in either death or a discharge to home, with annual costs totaling $36 (95% CI $30–43) million. The remaining 4% of hospitalizations were followed by extended care at rehabilitation and skilled nursing facilities with annual costs totaling $5.5 (95% CI $4.4–6.8) million. The annual monetary value of quality-adjusted life years (QALYs) lost amounted to $1.1 (95% CI $1.0–1.2) billion. In total, the estimated annual economic burden was $1.2 (95% CI $1.0–1.3) billion, indicating the substantial burden of seasonal influenza epidemics on the US Veterans Affairs population. Premature death was found to be the largest driver of these costs, followed by hospitalization.

This datasets displays the summary of the Geographic Spread of Influenza throughout the United States for the week ending on 5.17.2008. Each state is given a flu Status that is dependent on the spread of influenza throughout the state for the particular week. There are five levels of status that a state can obtain. They are: * No Activity: No laboratory-confirmed cases of influenza and no reported increase in the number of cases of ILI. * Sporadic: Small numbers of laboratory-confirmed influenza cases or a single laboratory-confirmed influenza outbreak has been reported, but there is no increase in cases of ILI. * Local: Outbreaks of influenza or increases in ILI cases and recent laboratory-confirmed influenza in a single region of the state. * Regional: Outbreaks of influenza or increases in ILI and recent laboratory confirmed influenza in at least 2 but less than half the regions of the state. * Widespread: Outbreaks of influenza or increases in ILI cases and recent laboratory-confirmed influenza in at least half the regions of the state. The information comes from the Centers for Disease Control and Prevention (CDC) To see more information about how this status is determined see http://www.cdc.gov/flu/weekly/fluactivity.htm for a full explanation of their system.

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.

BackgroundInfluenza and respiratory syncytial virus (RSV) associated mortality has not been well-established in tropical Africa.MethodsWe used the negative binomial regression method and the rate-difference method (i.e. deaths during low and high influenza/RSV activity months), to estimate excess mortality attributable to influenza and RSV using verbal autopsy data collected through a health and demographic surveillance system in Western Kenya, 2007–2013. Excess mortality rates were calculated for a) all-cause mortality, b) respiratory deaths (including pneumonia), c) HIV-related deaths, and d) pulmonary tuberculosis (TB) related deaths.ResultsUsing the negative binomial regression method, the mean annual all-cause excess mortality rate associated with influenza and RSV was 14.1 (95% confidence interval [CI] 0.0–93.3) and 17.1 (95% CI 0.0–111.5) per 100,000 person-years (PY) respectively; and 10.5 (95% CI 0.0–28.5) and 7.3 (95% CI 0.0–27.3) per 100,000 PY for respiratory deaths, respectively. Highest mortality rates associated with influenza were among ≥50 years, particularly among persons with TB (41.6[95% CI 0.0–122.7]); and with RSV were among <5 years. Using the rate-difference method, the excess mortality rate for influenza and RSV was 44.8 (95% CI 36.8–54.4) and 19.7 (95% CI 14.7–26.5) per 100,000 PY, respectively, for all-cause deaths; and 9.6 (95% CI 6.3–14.7) and 6.6 (95% CI 3.9–11.0) per 100,000 PY, respectively, for respiratory deaths.ConclusionsOur study shows a substantial excess mortality associated with influenza and RSV in Western Kenya, especially among children <5 years and older persons with TB, supporting recommendations for influenza vaccination and efforts to develop RSV vaccines.

NNDSS - Table I. infrequently reported notifiable diseases - 2018. In this Table, provisional cases of selected infrequently reported notifiable diseases (<1,000 cases reported during the preceding year) are displayed. This tables excludes U.S. territories. Notice: The case counts for Haemophilus influenzae, invasive disease Nontypeable" and "Non-b serotype" were switched for 2018 weeks 1-52. Note: These are provisional cases of selected national notifiable diseases from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data from the 50 states, New York City, the District of Columbia are collated and published weekly on the NNDSS Data and Statistic web page (https://wwwn.cdc.gov/nndss/data-and-statistics.html). Cases reported by state health departments to CDC for weekly publication are provisional because of the time needed to complete case follow-up. Therefore, numbers presented in later weeks may reflect changes made to these counts as additional information becomes available. The national surveillance case definitions used to define a case are available on the NNDSS web site at https://wwwn.cdc.gov/nndss/. Information about the weekly provisional data and guides to interpreting data are available at: https://wwwn.cdc.gov/nndss/infectious-tables.html. Footnote: —: No reported cases. N: Not reportable. NA: Not available. NN: Not Nationally Notifiable. NP: Nationally notifiable but not published. Cum: Cumulative year-to-date counts. Case counts for reporting years 2017 and 2018 are provisional and subject to change. Data for years 2013 through 2016 are finalized. For further information on interpretation of these data, see http://wwwn.cdc.gov/nndss/document/ProvisionalNationaNotifiableDiseasesSurveillanceData20100927.pdf. † This table does not include cases from the U.S. territories. § Calculated by summing the incidence counts for the current week, the 2 weeks preceding the current week, and the 2 weeks following the current week, for a total of 5 preceding years. Additional information is available at https://wwwn.cdc.gov/nndss/document/5yearweeklyaverage.pdf. ¶ Not reportable in all jurisdictions. Data from states where the condition is not reportable are excluded from this table, except for the arboviral diseases and influenza-associated pediatric mortality. Reporting exceptions are available at http://wwwn.cdc.gov/nndss/downloads.html. ** Please refer to the CDC WONDER for weekly updates to the footnote for this condition. †† Please refer to the CDC WONDER for weekly updates to the footnote for this condition. §§ Novel influenza A virus infections are human infections with influenza A viruses that are different from currently circulating human seasonal influenza viruses. With the exception of one avian lineage influenza A (H7N2) virus, all novel influenza A virus infections reported to CDC since 2013 have been variant influenza viruses. ¶¶ Prior to 2018, cases of paratyphoid fever were included with salmonellosis cases (see Table II). *** Prior to 2015, CDC's National Notifiable Diseases Surveillance System (NNDSS) did not receive electronic data about incident cases of specific viral hemorrhagic fevers; instead data were collected in aggregate as "viral hemorrhagic fevers'. NNDSS was updated beginning in 2015 to receive data for each of the viral hemorrhagic fevers listed.

ObjectivesThe aim of this study is to describe, visualize, and compare the trends and epidemiological features of the mortality rates of 10 notifiable respiratory infectious diseases in China from 2004 to 2020.SettingData were obtained from the database of the National Infectious Disease Surveillance System (NIDSS) and reports released by the National and local Health Commissions from 2004 to 2020. Spearman correlations and Joinpoint regression models were used to quantify the temporal trends of RIDs by calculating annual percentage changes (APCs) in the rates of mortality.ResultsThe overall mortality rate of RIDs was stable across China from 2004 to 2020 (R = −0.38, P = 0.13), with an APC per year of −2.2% (95% CI: −4.6 to 0.3; P = 0.1000). However, the overall mortality rate of 10 RIDs in 2020 decreased by 31.80% (P = 0.006) compared to the previous 5 years before the COVID-19 pandemic. The highest mortality occurred in northwestern, western, and northern China. Tuberculosis was the leading cause of RID mortality, and mortality from tuberculosis was relatively stable throughout the 17 years (R = −0.36, P = 0.16), with an APC of −1.9% (95% CI −4.1 to 0.4, P = 0.1000). Seasonal influenza was the only disease for which mortality significantly increased (R = 0.73, P = 0.00089), with an APC of 29.70% (95% CI 16.60–44.40%; P = 0.0000). The highest yearly case fatality ratios (CFR) belong to avian influenza A H5N1 [687.5 per 1,000 (33/48)] and epidemic cerebrospinal meningitis [90.5748 per 1,000 (1,010/11,151)]. The age-specific CFR of 10 RIDs was highest among people over 85 years old [13.6551 per 1,000 (2,353/172,316)] and was lowest among children younger than 10 years, particularly in 5-year-old children [0.0552 per 1,000 (58/1,051,178)].ConclusionsThe mortality rates of 10 RIDs were relatively stable from 2004 to 2020 with significant differences among Chinese provinces and age groups. There was an increased mortality trend for seasonal influenza and concerted efforts are needed to reduce the mortality rate of seasonal influenza in the future.

IntroductionWe compared hospitalization outcomes of young children hospitalized with COVID-19 to those hospitalized with influenza in the United States.MethodsPatients aged 0-<5 years hospitalized with an admission diagnosis of acute COVID-19 (April 2021-March 2022) or influenza (April 2019-March 2020) were selected from the PINC AI Healthcare Database Special Release. Hospitalization outcomes included length of stay (LOS), intensive care unit (ICU) admission, oxygen supplementation, and mechanical ventilation (MV). Inverse probability of treatment weighting was used to adjust for confounders in logistic regression analyses.ResultsAmong children hospitalized with COVID-19 (n = 4,839; median age: 0 years), 21.3% had an ICU admission, 19.6% received oxygen supplementation, 7.9% received MV support, and 0.5% died. Among children hospitalized with influenza (n = 4,349; median age: 1 year), 17.4% were admitted to the ICU, 26.7% received oxygen supplementation, 7.6% received MV support, and 0.3% died. Compared to children hospitalized with influenza, those with COVID-19 were more likely to have an ICU admission (adjusted odds ratio [aOR]: 1.34; 95% confidence interval [CI]: 1.21–1.48). However, children with COVID-19 were less likely to receive oxygen supplementation (aOR: 0.71; 95% CI: 0.64–0.78), have a prolonged LOS (aOR: 0.81; 95% CI: 0.75–0.88), or a prolonged ICU stay (aOR: 0.56; 95% CI: 0.46–0.68). The likelihood of receiving MV was similar (aOR: 0.94; 95% CI: 0.81, 1.1).ConclusionsHospitalized children with either SARS-CoV-2 or influenza had severe complications including ICU admission and oxygen supplementation. Nearly 10% received MV support. Both SARS-CoV-2 and influenza have the potential to cause severe illness in young children.

The dataset provides a list of the wild birds identified and submitted under both passive and active (targeted) surveillance programmes in Great Britain for testing for Avian Influenza by the Animal and Plant Health Agency (APHA). The main emphasis in the surveillance programmes is on patrols of designated reserves by skilled wild bird ecologists and wardens to locate “found dead” wild birds, including “mass mortality incidents”. These Warden Patrols continue all-year-round, and are also seasonally targeted in the winter and spring periods (October to March) each year. Members of the public are also asked to remain vigilant for mass bird mortality incidents occurring in any location in GB and report these to the Defra Helpline. The criteria for a “mass mortality incident” are five or more wild birds of any species at any location in England, Scotland and Wales. The dataset contains information on the identity of the bird, the date, location and which samples were taken from those birds and their test results. Please Note: The location represents a 10km x 10km square in which the bird was found. Location data is provided by the submitter and is not verified and, if no location information is available, the location of the testing laboratory may be used. For further information and explanations of the data included in this dataset, please see the data dictionary available for download alongside this dataset. Attribution statement: ©Crown Copyright, APHA 2016

The dataset provides a list of the wild birds identified and submitted under both passive and active (targeted) surveillance programmes in Great Britain for testing for Avian Influenza by the Animal and Plant Health Agency (APHA). The main emphasis in the surveillance programmes is on patrols of designated reserves by skilled wild bird ecologists and wardens to locate “found dead” wild birds, including “mass mortality incidents”. These Warden Patrols continue all-year-round, and are also seasonally targeted in the winter and spring periods (October to March) each year. Members of the public are also asked to remain vigilant for mass bird mortality incidents occurring in any location in GB and report these to the Defra Helpline. The criteria for a “mass mortality incident” are five or more wild birds of any species at any location in England, Scotland and Wales. The dataset contains information on the identity of the bird, the date, location and which samples were taken from those birds and their test results. Please Note: The location represents a 10km x 10km square in which the bird was found. Location data is provided by the submitter and is not verified and, if no location information is available, the location of the testing laboratory may be used. For further information and explanations of the data included in this dataset, please see the data dictionary available for download alongside this dataset. Attribution statement: ©Crown Copyright, APHA 2016

BackgroundInfluenza A (H1N1)pdm09 (2009 H1N1) re-circulated as the predominant virus from January through February 2011 in China. National surveillance of 2009 H1N1 as a notifiable disease was maintained to monitor potential changes in disease severity from the previous season. Methodology/Principal FindingsTo describe the characteristics of hospitalized cases with 2009 H1N1 infection and analyze risk factors for severe illness during the 2010–2011winter season in China, we obtained surveillance data from hospitalized cases with 2009 H1N1 infection from November 2010 through May 2011, and reviewed medical records from 701 hospitalized cases. Age-standardized risk ratios were used to compare the age distribution of patients that were hospitalized and died due to 2009 H1N1 between the 2010–2011winter season to those during the 2009–2010 pandemic period. During the 2010–2011 winter season, children less than 5 years of age had the highest relative risk of hospitalization and death, followed by adults aged 65 years or older. Additionally, the relative risk of hospitalized cases aged 5–14 and 15–24 years was lower compared to children less than 5 years of age. During the winter season of 2010–2011, the proportions of adults aged 25 years or older for hospitalization and death were significantly higher than those during the 2009–2010 pandemic period. Being male, having a chronic medical condition, delayed hospital admission (≥3 days from onset) or delayed initiation of antiviral treatment (≥5 days from onset) were associated with severe illness among non-pregnant patients ≥2 years of age. Conclusions/SignificanceWe observed a change in high risk groups for hospitalization for 2009 H1N1 during the winter months immediately following the pandemic period compared to the high risk groups identified during the pandemic period. Our nationally notifiable disease surveillance system enabled us to understand the evolving epidemiology of 2009 H1N1 infection after the pandemic period.

BackgroundA novel avian influenza A (H7N9) virus has caused great morbidity as well as mortality since its emergence in Eastern China in February 2013. However, the possible risk factors for death are not yet fully known.Methods and FindingsPatients with H7N9 virus infection between March 1 and August 14, 2013 in Jiangsu province were enrolled. Data were collected with a standard form. Mean or percentage was used to describe the features, and Fisher's exact test or t-test test was used to compare the differences between fatal and nonfatal cases with H7N9 virus infection. A total of 28 patients with H7N9 virus infection were identified among whom, nine (32.1%) died. The median age of fatal cases was significant higher than nonfatal cases (P<0.05). Patients with older age were more strongly associated with increased odds of death (OR = 30.0; 95% CI, 2.85–315.62). Co-morbidity with chronic lung disease and hypertension were risk factors for mortality (OR = 14.40; 95% CI, 1.30–159.52, OR = 6.67; 95% CI, 1.09–40.43, respectively). Moreover, the presence of either bilateral lung inflammation or pulmonary consolidation on chest imaging on admission was related with fatal outcome (OR = 7.00; 95%CI, 1.10–44.61). Finally, dynamic monitoring showed that lymphopenia was more significant in fatal group than in nonfatal group from day 11 to week five (P<0.05). The decrease in oxygenation indexes were observed in most cases and more significantly in fatal cases after week three (P<0.05), and the value of nearly all fatal cases were below 200 mmHg during our evaluation period.ConclusionsAmong cases with H7N9 virus infection, increased age accompanied by co-morbidities was the risk of death. The severity of lung infection at admission, the persistence of lymphocytopenia, and the extended duration of lower oxygenation index all contributed to worsened outcomes of patients with H7N9 virus infection.

Between 2020 and 2023, high pathogenicity avian influenza virus (HPAIV) H5Nx clade 2.3.4.4b caused devastating outbreaks across Europe and the United Kingdom among domestic poultry and wild bird populations. During winter 2022, unexpected mortality was observed in four of fourteen outdoor captive Humboldt penguins in a British zoological collection, without prior clinical signs. Swabs, one whole carcass and two heads were submitted for notifiable avian disease laboratory investigation. Clinical material was inspected by veterinary pathologists using an established post mortem procedure and tissues were collected for official sampling according to a standard notifiable avian disease testing algorithm. A defined selection of tissues was tested using real-time reverse transcription PCR, whole-genome sequencing, histopathology and immunohistochemistry. Following molecular testing for H5N1 infection, positive results were detected in five of the 12 birds sampled. On gross examination of the carcass, generalized congestion was present. Histopathology revealed necrosis and acute inflammation, primarily in the spleen, liver and lungs. Immunohistochemistry demonstrated viral antigen in endothelial cells and lymphoid cells particularly in lung, spleen, liver, brain and heart muscle. This finding strongly suggests that endothelial cells and lymphoid cells are the primary targets for HPAIV infection in Humboldt penguins. Molecular characterization identified the causative agent as HPAIV H5N1 clade 2.3.4.4b, genotyped as AIV223 according to the UK scheme. This was the first time that this genotype had been recorded in the UK. These findings provide novel insights into the pathobiology of this virus in naturally infected captive Humboldt penguins. Natural HPAIV H5N1 infection causes mortality and pathology in Humboldt penguins.Molecular analysis identified the aetiology as a novel H5N1 clade 2.3.4.4b genotype.Immunohistochemical analysis demonstrated infection of endothelial cells, macrophages and reticular cells in lymphoid tissue. Natural HPAIV H5N1 infection causes mortality and pathology in Humboldt penguins. Molecular analysis identified the aetiology as a novel H5N1 clade 2.3.4.4b genotype. Immunohistochemical analysis demonstrated infection of endothelial cells, macrophages and reticular cells in lymphoid tissue.