Global Seasonal Influenza Mortality Estimates: A Comparison of 3 Different Approaches.
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SUBMITTER: Cozza V
PROVIDER: S-EPMC8218989 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundEstimates of influenza-associated mortality are important for national and international decision making on public health priorities. Previous estimates of 250 000-500 000 annual influenza deaths are outdated. We updated the estimated number of global annual influenza-associated respiratory deaths using country-specific influenza-associated excess respiratory mortality estimates from 1999-2015.MethodsWe estimated country-specific influenza-associated respiratory excess mortality rates (EMR) for 33 countries using time series log-linear regression models with vital death records and influenza surveillance data. To extrapolate estimates to countries without data, we divided countries into three analytic divisions for three age groups (<65 years, 65-74 years, and ≥75 years) using WHO Global Health Estimate (GHE) respiratory infection mortality rates. We calculated mortality rate ratios (MRR) to account for differences in risk of influenza death across countries by comparing GHE respiratory infection mortality rates from countries without EMR estimates with those with estimates. To calculate death estimates for individual countries within each age-specific analytic division, we multiplied randomly selected mean annual EMRs by the country's MRR and population. Global 95% credible interval (CrI) estimates were obtained from the posterior distribution of the sum of country-specific estimates to represent the range of possible influenza-associated deaths in a season or year. We calculated influenza-associated deaths for children younger than 5 years for 92 countries with high rates of mortality due to respiratory infection using the same methods.FindingsEMR-contributing countries represented 57% of the global population. The estimated mean annual influenza-associated respiratory EMR ranged from 0·1 to 6·4 per 100 000 individuals for people younger than 65 years, 2·9 to 44·0 per 100 000 individuals for people aged between 65 and 74 years, and 17·9 to 223·5 per 100 000 for people older than 75 years. We estimated that 291 243-645 832 seasonal influenza-associated respiratory deaths (4·0-8·8 per 100 000 individuals) occur annually. The highest mortality rates were estimated in sub-Saharan Africa (2·8-16·5 per 100 000 individuals), southeast Asia (3·5-9·2 per 100 000 individuals), and among people aged 75 years or older (51·3-99·4 per 100 000 individuals). For 92 countries, we estimated that among children younger than 5 years, 9243-105 690 influenza-associated respiratory deaths occur annually.InterpretationThese global influenza-associated respiratory mortality estimates are higher than previously reported, suggesting that previous estimates might have underestimated disease burden. The contribution of non-respiratory causes of death to global influenza-associated mortality should be investigated.FundingNone.
| S-EPMC5935243 | biostudies-literature
Project description:BackgroundUntil recently, the World Health Organization (WHO) estimated the annual mortality burden of influenza to be 250 000 to 500 000 all-cause deaths globally; however, a 2017 study indicated a substantially higher mortality burden, at 290 000-650 000 influenza-associated deaths from respiratory causes alone, and a 2019 study estimated 99 000-200 000 deaths from lower respiratory tract infections directly caused by influenza. Here we revisit global and regional estimates of influenza mortality burden and explore mortality trends over time and geography.MethodsWe compiled influenza-associated excess respiratory mortality estimates for 31 countries representing 5 WHO regions during 2002-2011. From these we extrapolated the influenza burden for all 193 countries of the world using a multiple imputation approach. We then used mixed linear regression models to identify factors associated with high seasonal influenza mortality burden, including influenza types and subtypes, health care and socio-demographic development indicators, and baseline mortality levels.ResultsWe estimated an average of 389 000 (uncertainty range 294 000-518 000) respiratory deaths were associated with influenza globally each year during the study period, corresponding to ~ 2% of all annual respiratory deaths. Of these, 67% were among people 65 years and older. Global burden estimates were robust to the choice of countries included in the extrapolation model. For people <65 years, higher baseline respiratory mortality, lower level of access to health care and seasons dominated by the A(H1N1)pdm09 subtype were associated with higher influenza-associated mortality, while lower level of socio-demographic development and A(H3N2) dominance was associated with higher influenza mortality in adults ≥65 years.ConclusionsOur global estimate of influenza-associated excess respiratory mortality is consistent with the 2017 estimate, despite a different modelling strategy, and the lower 2019 estimate which only captured deaths directly caused by influenza. Our finding that baseline respiratory mortality and access to health care are associated with influenza-related mortality in persons <65 years suggests that health care improvements in low and middle-income countries might substantially reduce seasonal influenza mortality. Our estimates add to the body of evidence on the variation in influenza burden over time and geography, and begin to address the relationship between influenza-associated mortality, health and development.
| S-EPMC6815659 | biostudies-literature
Project description:BackgroundAssessing the mortality impact of the 2009 influenza A H1N1 virus (H1N1pdm09) is essential for optimizing public health responses to future pandemics. The World Health Organization reported 18,631 laboratory-confirmed pandemic deaths, but the total pandemic mortality burden was substantially higher. We estimated the 2009 pandemic mortality burden through statistical modeling of mortality data from multiple countries.Methods and findingsWe obtained weekly virology and underlying cause-of-death mortality time series for 2005-2009 for 20 countries covering ?35% of the world population. We applied a multivariate linear regression model to estimate pandemic respiratory mortality in each collaborating country. We then used these results plus ten country indicators in a multiple imputation model to project the mortality burden in all world countries. Between 123,000 and 203,000 pandemic respiratory deaths were estimated globally for the last 9 mo of 2009. The majority (62%-85%) were attributed to persons under 65 y of age. We observed a striking regional heterogeneity, with almost 20-fold higher mortality in some countries in the Americas than in Europe. The model attributed 148,000-249,000 respiratory deaths to influenza in an average pre-pandemic season, with only 19% in persons <65 y. Limitations include lack of representation of low-income countries among single-country estimates and an inability to study subsequent pandemic waves (2010-2012).ConclusionsWe estimate that 2009 global pandemic respiratory mortality was ?10-fold higher than the World Health Organization's laboratory-confirmed mortality count. Although the pandemic mortality estimate was similar in magnitude to that of seasonal influenza, a marked shift toward mortality among persons <65 y of age occurred, so that many more life-years were lost. The burden varied greatly among countries, corroborating early reports of far greater pandemic severity in the Americas than in Australia, New Zealand, and Europe. A collaborative network to collect and analyze mortality and hospitalization surveillance data is needed to rapidly establish the severity of future pandemics. Please see later in the article for the Editors' Summary.
| S-EPMC3841239 | biostudies-literature
Project description:Seasonal influenza poses serious problems for global public health, being a significant contributor to morbidity and mortality. In England, there has been a long-standing national vaccination programme, with vaccination of at-risk groups and children offering partial protection against infection. Transmission models have been a fundamental component of analysis, informing the efficient use of limited resources. However, these models generally treat each season and each strain circulating within that season in isolation. Here, we amalgamate multiple data sources to calibrate a susceptible-latent-infected-recovered type transmission model for seasonal influenza, incorporating the four main strains and mechanisms linking prior season epidemiological outcomes to immunity at the beginning of the following season. Data pertaining to nine influenza seasons, starting with the 2009/10 season, informed our estimates for epidemiological processes, virological sample positivity, vaccine uptake and efficacy attributes, and general practitioner influenza-like-illness consultations as reported by the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC). We performed parameter inference via approximate Bayesian computation to assess strain transmissibility, dependence of present season influenza immunity on prior protection, and variability in the influenza case ascertainment across seasons. This produced reasonable agreement between model and data on the annual strain composition. Parameter fits indicated that the propagation of immunity from one season to the next is weaker if vaccine derived, compared to natural immunity from infection. Projecting the dynamics forward in time suggests that while historic immunity plays an important role in determining annual strain composition, the variability in vaccine efficacy hampers our ability to make long-term predictions.
| S-EPMC6837557 | biostudies-literature
Project description:ImportanceCardiovascular deaths and influenza epidemics peak during winter in temperate regions.ObjectivesTo quantify the temporal association between population increases in seasonal influenza infections and mortality due to cardiovascular causes and to test if influenza incidence indicators are predictive of cardiovascular mortality during the influenza season.Design, setting, and participantsTime-series analysis of vital statistics records and emergency department visits in New York City, among cardiovascular deaths that occurred during influenza seasons between January 1, 2006, and December 31, 2012. The 2009 novel influenza A(H1N1) pandemic period was excluded from temporal analyses.ExposuresEmergency department visits for influenza-like illness, grouped by age (?0 years and ?65 years) and scaled by laboratory surveillance data for viral types and subtypes, in the previous 28 days.Main outcomes and measuresMortality due to cardiovascular disease, ischemic heart disease, and myocardial infarction.ResultsAmong adults 65 years and older, who accounted for 83.0% (73?363 deaths) of nonpandemic cardiovascular mortality during influenza seasons, seasonal average influenza incidence was correlated year to year with excess cardiovascular mortality (Pearson correlation coefficients ?0.75, P???.05 for 4 different influenza indicators). In daily time-series analyses using 4 different influenza metrics, interquartile range increases in influenza incidence during the previous 21 days were associated with an increase between 2.3% (95% CI, 0.7%-3.9%) and 6.3% (95% CI, 3.7%-8.9%) for cardiovascular disease mortality and between 2.4% (95% CI, 1.1%-3.6%) and 6.9% (95% CI, 4.0%-9.9%) for ischemic heart disease mortality among adults 65 years and older. The associations were most acute and strongest for myocardial infarction mortality, with each interquartile range increase in influenza incidence during the previous 14 days associated with mortality increases between 5.8% (95% CI, 2.5%-9.1%) and 13.1% (95% CI, 5.3%-20.9%). Out-of-sample prediction of cardiovascular mortality among adults 65 years and older during the 2009-2010 influenza season yielded average estimates with 94.0% accuracy using 4 different influenza metrics.Conclusions and relevanceEmergency department visits for influenza-like illness were associated with and predictive of cardiovascular disease mortality. Retrospective estimation of influenza-attributable cardiovascular mortality burden combined with accurate and reliable influenza forecasts could predict the timing and burden of seasonal increases in cardiovascular mortality.
| S-EPMC5158013 | biostudies-literature
Project description:BackgroundTimely monitoring of COVID-19 impact on mortality is critical for rapid risk assessment and public health action.AimBuilding upon well-established models to estimate influenza-related mortality, we propose a new statistical Attributable Mortality Model (AttMOMO), which estimates mortality attributable to one or more pathogens simultaneously (e.g. SARS-CoV-2 and seasonal influenza viruses), while adjusting for seasonality and excess temperatures.MethodsData from Nationwide Danish registers from 2014-week(W)W27 to 2020-W22 were used to exemplify utilities of the model, and to estimate COVID-19 and influenza attributable mortality from 2019-W40 to 2020-W20.ResultsSARS-CoV-2 was registered in Denmark from 2020-W09. Mortality attributable to COVID-19 in Denmark increased steeply, and peaked in 2020-W14. As preventive measures and national lockdown were implemented from 2020-W12, the attributable mortality started declining within a few weeks. Mortality attributable to COVID-19 from 2020-W09 to 2020-W20 was estimated to 16.2 (95% confidence interval (CI): 12.0 to 20.4) per 100,000 person-years. The 2019/20 influenza season was mild with few deaths attributable to influenza, 3.2 (95% CI: 1.1 to 5.4) per 100,000 person-years.ConclusionAttMOMO estimates mortality attributable to several pathogens simultaneously, providing a fuller picture of mortality by COVID-19 during the pandemic in the context of other seasonal diseases and mortality patterns. Using Danish data, we show that the model accurately estimates mortality attributable to COVID-19 and influenza, respectively. We propose using standardised indicators for pathogen circulation in the population, to make estimates comparable between countries and applicable for timely monitoring.
| S-EPMC7908066 | biostudies-literature
Project description:BACKGROUND:Understanding the global spatiotemporal pattern of seasonal influenza is essential for influenza control and prevention. Available data on the updated global spatiotemporal pattern of seasonal influenza are scarce. This study aimed to assess the spatiotemporal pattern of seasonal influenza after the 2009 influenza pandemic. METHODS:Weekly influenza surveillance data in 86 countries from 2010 to 2017 were obtained from FluNet. First, the proportion of influenza A in total influenza viruses (PA) was calculated. Second, weekly numbers of influenza positive virus (A and B) were divided by the total number of samples processed to get weekly positive rates of influenza A (RWA) and influenza B (RWB). Third, the average positive rates of influenza A (RA) and influenza B (RB) for each country were calculated by averaging RWA, and RWB of 52?weeks. A Kruskal-Wallis test was conducted to examine if the year-to-year change in PA in all countries were significant, and a universal kriging method with linear semivariogram model was used to extrapolate RA and RB in all countries. RESULTS:PA ranged from 0.43 in Zambia to 0.98 in Belarus, and PA in countries with higher income was greater than those countries with lower income. The spatial patterns of high RB were the highest in sub-Saharan Africa, Asia-Pacific region and South America. RWA peaked in early weeks in temperate countries, and the peak of RWB occurred a bit later. There were some temperate countries with non-distinct influenza seasonality (e.g., Mauritius and Maldives) and some tropical/subtropical countries with distinct influenza seasonality (e.g., Chile and South Africa). CONCLUSIONS:Influenza seasonality is not predictable in some temperate countries, and it is distinct in Chile, Argentina and South Africa, implying that the optimal timing for influenza vaccination needs to be chosen with caution in these unpredictable countries.
| S-EPMC6942408 | biostudies-literature
Project description:BACKGROUND:The mortality burden of the 2009 A/H1N1 pandemic remains unclear in many countries due to delays in reporting of death statistics. We estimate the age- and cause-specific excess mortality impact of the pandemic in France, relative to that of other countries and past epidemic and pandemic seasons. METHODS:We applied Serfling and Poisson excess mortality approaches to model weekly age- and cause-specific mortality rates from June 1969 through May 2010 in France. Indicators of influenza activity, time trends, and seasonal terms were included in the models. We also reviewed the literature for country-specific estimates of 2009 pandemic excess mortality rates to characterize geographical differences in the burden of this pandemic. RESULTS:The 2009 A/H1N1 pandemic was associated with 1.0 (95% Confidence Intervals (CI) 0.2-1.9) excess respiratory deaths per 100,000 population in France, compared to rates per 100,000 of 44 (95% CI 43-45) for the A/H3N2 pandemic and 2.9 (95% CI 2.3-3.7) for average inter-pandemic seasons. The 2009 A/H1N1 pandemic had a 10.6-fold higher impact than inter-pandemic seasons in people aged 5-24 years and 3.8-fold lower impact among people over 65 years. CONCLUSIONS:The 2009 pandemic in France had low mortality impact in most age groups, relative to past influenza seasons, except in school-age children and young adults. The historical A/H3N2 pandemic was associated with much larger mortality impact than the 2009 pandemic, across all age groups and outcomes. Our 2009 pandemic excess mortality estimates for France fall within the range of previous estimates for high-income regions. Based on the analysis of several mortality outcomes and comparison with laboratory-confirmed 2009/H1N1 deaths, we conclude that cardio-respiratory and all-cause mortality lack precision to accurately measure the impact of this pandemic in high-income settings and that use of more specific mortality outcomes is important to obtain reliable age-specific estimates.
| S-EPMC3447811 | biostudies-literature
Project description:A global shortage and inequitable access to influenza vaccines has been cause for concern for developing countries who face dire consequences in the event of a pandemic. The Global Action Plan for Influenza Vaccines (GAP) was launched in 2006 to increase global capacity for influenza vaccine production to address these concerns. It is widely recognized that well-developed infrastructure to produce seasonal influenza vaccines leads to increased capacity to produce pandemic influenza vaccines. This article summarizes the results of a survey administered to 44 manufacturers to assess their production capacity for seasonal influenza and pandemic influenza vaccine production. When the GAP was launched in 2006, global production capacity for seasonal and pandemic vaccines was estimated to be 500million and 1.5billion doses respectively. Since 2006 there has been a significant increase in capacity, with the 2013 survey estimating global capacity at 1.5billion seasonal and 6.2billion pandemic doses. Results of the current survey showed that global seasonal influenza vaccine production capacity has decreased since 2013 from 1.504billion doses to 1.467billion doses. However, notwithstanding the overall global decrease in seasonal vaccine capacity there were notable positive changes in the distribution of production capacity with increases noted in South East Asia (SEAR) and the Western Pacific (WPR) regions, albeit on a small scale. Despite a decrease in seasonal capacity, there has been a global increase of pandemic influenza vaccine production capacity from 6.2 billion doses in 2013 to 6.4 billion doses in 2015. This growth can be attributed to a shift towards more quadrivalent vaccine production and also to increased use of adjuvants. Pandemic influenza vaccine production capacity is at its highest recorded levels however challenges remain in maintaining this capacity and in ensuring access in the event of a pandemic to underserved regions.
| S-EPMC5357707 | biostudies-other
Project description:Dengue presents a formidable and growing global economic and disease burden, with around half the world's population estimated to be at risk of infection. There is wide variation and substantial uncertainty in current estimates of dengue disease burden and, consequently, on economic burden estimates. Dengue disease varies across time, geography and persons affected. Variations in the transmission of four different viruses and interactions among vector density and host's immune status, age, pre-existing medical conditions, all contribute to the disease's complexity. This systematic review aims to identify and examine estimates of dengue disease burden and costs, discuss major sources of uncertainty, and suggest next steps to improve estimates. Economic analysis of dengue is mainly concerned with costs of illness, particularly in estimating total episodes of symptomatic dengue. However, national dengue disease reporting systems show a great diversity in design and implementation, hindering accurate global estimates of dengue episodes and country comparisons. A combination of immediate, short-, and long-term strategies could substantially improve estimates of disease and, consequently, of economic burden of dengue. Suggestions for immediate implementation include refining analysis of currently available data to adjust reported episodes and expanding data collection in empirical studies, such as documenting the number of ambulatory visits before and after hospitalization and including breakdowns by age. Short-term recommendations include merging multiple data sources, such as cohort and surveillance data to evaluate the accuracy of reporting rates (by health sector, treatment, severity, etc.), and using covariates to extrapolate dengue incidence to locations with no or limited reporting. Long-term efforts aim at strengthening capacity to document dengue transmission using serological methods to systematically analyze and relate to epidemiologic data. As promising tools for diagnosis, vaccination, vector control, and treatment are being developed, these recommended steps should improve objective, systematic measures of dengue burden to strengthen health policy decisions.
| S-EPMC4238988 | biostudies-literature