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.

BackgroundThe timing of the biannual WHO influenza vaccine composition selection and production cycle has been historically directed to the influenza seasonality patterns in the temperate regions of the northern and southern hemispheres. Influenza activity, however, is poorly understood in the tropics with multiple peaks and identifiable year-round activity. The evidence-base needed to take informed decisions on vaccination timing and vaccine formulation is often lacking for the tropics and subtropics. This paper aims to assess influenza seasonality in the tropics and subtropics. It explores geographical grouping of countries into vaccination zones based on optimal timing of influenza vaccination.MethodsInfluenza seasonality was assessed by different analytic approaches (weekly proportion of positive cases, time series analysis, etc.) using FluNet and national surveillance data. In case of discordance in the seasonality assessment, consensus was built through discussions with in-country experts. Countries with similar onset periods of their primary influenza season were grouped into geographical zones.ResultsThe number and period of peak activity was ascertained for 70 of the 138 countries in the tropics and subtropics. Thirty-seven countries had one and seventeen countries had two distinct peaks. Countries near the equator had secondary peaks or even identifiable year-round activity. The main influenza season in most of South America and Asia started between April and June. The start of the main season varied widely in Africa (October and December in northern Africa, April and June in Southern Africa and a mixed pattern in tropical Africa). Eight “influenza vaccination zones” (two each in America and Asia, and four in Africa and Middle East) were defined with recommendations for vaccination timing and vaccine formulation. The main limitation of our study is that FluNet and national surveillance data may lack the granularity to detect sub-national variability in seasonality patterns.ConclusionDistinct influenza seasonality patterns, though complex, could be ascertained for most countries in the tropics and subtropics using national surveillance data. It may be possible to group countries into zones based on similar recommendations for vaccine timing and formulation.

Mortality estimates of the 1918 influenza pandemic vary considerably, and recent estimates have suggested that there were 50 million to 100 million deaths worldwide. We investigated the global mortality burden using an indirect estimation approach and 2 publicly available data sets: the Human Mortality Database (13 countries) and data extracted from the records of the Statistical Abstract for British India. The all-cause Human Mortality Database was used to estimate mortality annually for 1916-1921 for detailed age groups. Three different calculation methods were applied to the data (low, medium, and high scenarios), and we used a multilevel regression model to control for distorting factors (e.g., war and the underlying time trend in mortality). Total pandemic mortality was an estimated 15 million deaths worldwide in 1918 (n = 2.5 million in 1919) after including the rates for British India and controlling for wars and the underlying mortality trend. According to our validity analysis, simulations of total number of deaths being greater than 25 million are not realistic based on the underlying mortality rates included in Human Mortality Database and in British India. Our results suggest the global death impact of the 1918 pandemic was important (n = 17.4 million) but not as severe as most frequently cited estimates.

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Background Knowledge on age-specific hospitalizations associated with RSV infection is limited due to limited testing, especially in older children and adults in whom RSV infections are not expected to be severe. Burden estimates based on RSV coding of hospital admissions are known to underestimate the burden of RSV. We aimed to provide robust and reliable age-specific burden estimates of RSV-associated hospital admissions based on data on respiratory infections from national health registers and laboratory-confirmed cases of RSV. Methods We conducted multiseason regression analysis of weekly hospitalizations with respiratory infection and weekly laboratory-confirmed cases of RSV and influenza as covariates, based on national health registers and laboratory databases across 6 European countries. The burden of RSV-associated hospitalizations was estimated by age group, clinical diagnosis, and presence of underlying medical conditions. Results Across the 6 European countries, hospitalizations of children with respiratory infections were clearly associated with RSV, with associated proportions ranging from 28% to 60% in children younger than 3 months and we found substantial proportions of admissions to hospital with respiratory infections associated with RSV in children younger than 3 years. Associated proportions were highest among hospitalizations with ICD-10 codes of “bronchitis and bronchiolitis.” In all 6 countries, annual incidence of RSV-associated hospitalizations was &gt;40 per 1000 persons in the age group 0–2 months. In age group 1–2 years the incidence rate ranged from 1.3 to 10.5 hospitalizations per 1000. Adults older than 85 years had hospitalizations with respiratory infection associated to RSV in all 6 countries although incidence rates were low. Conclusions Our findings highlight the substantial proportion of RSV infections among hospital admissions across different ages and may help public health professionals and policy makers when planning prevention and control strategies. In addition, our findings provide valuable insights for health care professionals attending to both children and adults presenting with symptoms of viral respiratory infections.

Relative humidity, minimum temperature, and cloud cover are important predictors of RSV activity in the Netherlands, with the effect of relative humidity being most consistent.

We reviewed the diagnostic accuracy of SARS-CoV-2 serological tests. Random-effects models yielded a summary sensitivity of 82% for IgM, and 85% for IgG and total antibodies. For specificity, the pooled estimate were 98% for IgM and 99% for IgG and total antibodies. In populations with ≤ 5% of seroconverted individuals, unless the assays have perfect (i.e. 100%) specificity, the positive predictive value would be ≤ 88%. Serological tests should be used for prevalence surveys only in hard-hit areas.

Background Respiratory syncytial virus (RSV) infections are one of the leading causes of lower respiratory tract infections and have a major burden on society. For prevention and control to be deployed effectively, an improved understanding of the seasonality of RSV is necessary. Objectives The main objective of this study was to contribute to a better understanding of RSV seasonality by examining the GERi multi‐country surveillance dataset. Methods RSV seasons were included in the analysis if they contained ≥100 cases. Seasonality was determined using the “average annual percentage” method. Analyses were performed at a subnational level for the United States and Brazil. Results We included 601 425 RSV cases from 12 countries. Most temperate countries experienced RSV epidemics in the winter, with a median duration of 10–21 weeks. Not all epidemics fit this pattern in a consistent manner, with some occurring later or in an irregular manner. More variation in timing was observed in (sub)tropical countries, and we found substantial differences in seasonality at a subnational level. No association was found between the timing of the epidemic and the dominant RSV subtype. Conclusions Our findings suggest that geographical location or climatic characteristics cannot be used as a definitive predictor for the timing of RSV epidemics and highlight the need for (sub)national data collection and analysis.