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Background: Despite the known relatively high disease burden of influenza, data are lacking regarding a critical epidemiological indicator, the case‐fatality ratio. Our objective was to infer age‐group and influenza (sub)type specific values by combining modelled estimates of symptomatic incidence and influenza‐attributable mortality. Methods: The setting was the Netherlands, 2011/2012 through 2019/2020 seasons. Sentinel surveillance data from general practitioners and laboratory testing were synthesised to supply age‐group specific estimates of incidence of symptomatic infection, and ecological additive modelling was used to estimate influenza‐attributable deaths. These were combined in an Bayesian inferential framework to estimate case‐fatality ratios for influenza A(H3N2), A(H1N1)pdm09 and influenza B, per 5‐year age‐group. Results: Case‐fatality estimates were highest for influenza A(H3N2) followed by influenza B and then A(H1N1)pdm09 and were highest for the 85+ years age‐group, at 4.76% (95% credible interval [CrI]: 4.52–5.01%) for A(H3N2), followed by influenza B at 4.08% (95% CrI: 3.77–4.39%) and A(H1N1)pdm09 at 2.51% (95% CrI: 2.09–2.94%). For 55–59 through 85+ years, the case‐fatality risk was estimated to double with every 3.7 years of age. Conclusions: These estimated case‐fatality ratios, per influenza sub(type) and per age‐group, constitute valuable information for public health decision‐making, for assessing the retrospective and prospective value of preventative interventions such as vaccination and for health economic evaluations. [ABSTRACT FROM AUTHOR]

Introduction: Since the first reports of COVID-19 cases, sex-discrepancies have been reported in COVID-19 mortality. We provide a detailed description of these sex differences in relation to age and comorbidities among notified cases as well as in relation to age and sex-specific mortality in the general Dutch population. Methods: Data on COVID-19 cases and mortality until May 31st 2020 was extracted from the national surveillance database with exclusion of healthcare workers. Association between sex and case fatality was analyzed with multivariable logistic regression. Subsequently, male–female ratio in standardized mortality ratios and population mortality rates relative to all-cause and infectious disease-specific mortality were computed stratified by age. Results: Male–female odds ratio for case fatality was 1.33 [95% CI 1.26–1.41] and among hospitalized cases 1.27 [95% CI 1.16–1.40]. This remained significant after adjustment for age and comorbidities. The male–female ratio of the standardized mortality ratio was 1.70 [95%CI 1.62–1.78]. The population mortality rate for COVID-19 was 35.1 per 100.000, with a male–female rate ratio of 1.25 (95% CI 1.18–1.31) which was higher than in all-cause population mortality and infectious disease mortality. Conclusion: Our study confirms male sex is a predisposing factor for severe outcomes of COVID-19, independent of age and comorbidities. In addition to general male–female-differences, COVID-19 specific mechanisms likely contribute to this mortality discrepancy. [ABSTRACT FROM AUTHOR]

Since the 2009 influenza pandemic, the Netherlands has used a weekly death monitoring system to estimate deaths in excess of expectations. We present estimates of excess deaths during the ongoing coronavirus disease (COVID-19) epidemic and 10 previous influenza epidemics. Excess deaths per influenza epidemic averaged 4,000. The estimated 9,554 excess deaths (41% in excess) during the COVID-19 epidemic weeks 12-19 of 2020 appeared comparable to the 9,373 excess deaths (18%) during the severe influenza epidemic of 2017-18. However, these deaths occurred in a shorter time, had a higher peak, and were mitigated by nonpharmaceutical control measures. Excess deaths were 1.8-fold higher than reported laboratory-confirmed COVID-19 deaths (5,449). Based on excess deaths and preliminary results from seroepidemiologic studies, we estimated the infection-fatality rate to be 1%. Monitoring of excess deaths is crucial for timely estimates of disease burden for influenza and COVID-19. Our data complement laboratory-confirmed COVID-19 death reports and enable comparisons between epidemics. [ABSTRACT FROM AUTHOR]

Background: Respiratory syncytial virus (RSV) is a leading cause of respiratory tract illness in young children and a major cause of hospital admissions globally.Methods: Here we fit age-structured transmission models with immunity propagation to data from the Netherlands (2012-2017). Data included nationwide hospitalizations with confirmed RSV, general practitioner (GP) data on attendance for care from acute respiratory infection, and virological testing of acute respiratory infections at the GP. The transmission models, equipped with key parameter estimates, were used to predict the impact of maternal and pediatric vaccination.Results: Estimates of the basic reproduction number were generally high (R0 > 10 in scenarios with high statistical support), while susceptibility was estimated to be low in nonelderly adults (<10% in persons 20-64 years) and was higher in older adults (≥65 years). Scenario analyses predicted that maternal vaccination reduces the incidence of infection in vulnerable infants (<1 year) and shifts the age of first infection from infants to young children.Conclusions: Pediatric vaccination is expected to reduce the incidence of infection in infants and young children (0-5 years), slightly increase incidence in 5 to 9-year-old children, and have minor indirect benefits. [ABSTRACT FROM AUTHOR]