BackgroundTick-borne encephalitis (TBE) is a vaccine-preventable disease involving the central nervous system. TBE became a notifiable disease on the EU/EEA level in 2012.AimWe aimed to provide an updated epidemiological assessment of TBE in the EU/EEA, focusing on spatiotemporal changes.MethodsWe performed a descriptive analysis of case characteristics, time and location using data of human TBE cases reported by EU/EEA countries to the European Centre for Disease Prevention and Control with disease onset in 2012-2020. We analysed data at EU/EEA, national, and subnational levels and calculated notification rates using Eurostat population data. Regression models were used for temporal analysis.ResultsFrom 2012 to 2020, 19 countries reported 29,974 TBE cases, of which 24,629 (98.6%) were autochthonous. Czechia, Germany and Lithuania reported 52.9% of all cases. The highest notification rates were recorded in Lithuania, Latvia, and Estonia (16.2, 9.5 and 7.5 cases/100,000 population, respectively). Fifty regions from 10 countries, had a notification rate ≥ 5/100,000. There was an increasing trend in number of cases during the study period with an estimated 0.053 additional TBE cases every week. In 2020, 11.5% more TBE cases were reported than predicted based on data from 2016 to 2019. A geographical spread of cases was observed, particularly in regions situated north-west of known endemic regions.ConclusionA close monitoring of ongoing changes to the TBE epidemiological situation in Europe can support the timely adaption of vaccination recommendations. Further analyses to identify populations and geographical areas where vaccination programmes can be of benefit are needed.

• MeSH
• klíšťová encefalitida * epidemiologie   prevence a kontrola   MeSH
• lidé MeSH
• vakcinace MeSH
• virové vakcíny * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• Geografické názvy
• Evropa MeSH
• Německo MeSH

BackgroundTimely treatment with neuraminidase inhibitors (NAI) can reduce severe outcomes in influenza patients.AimWe assessed the impact of antiviral treatment on in-hospital deaths of laboratory-confirmed influenza patients in 11 European Union countries from 2010/11 to 2019/20.MethodsCase-based surveillance data from hospitalised patients with known age, sex, outcome, ward, vaccination status, timing of antiviral treatment, and hospitalisation were obtained. A mixed effect logistic regression model using country as random intercept was applied to estimate the adjusted odds ratio (aOR) for in-hospital death in patients treated with NAIs vs not treated.ResultsOf 19,937 patients, 31% received NAIs within 48 hours of hospital admission. Older age (60-79 years aOR 3.0, 95% CI: 2.4-3.8; 80 years 8.3 (6.6-10.5)) and intensive care unit admission (3.8, 95% CI: 3.4-4.2) increased risk of dying, while early hospital admission after symptom onset decreased risk (aOR 0.91, 95% CI: 0.90-0.93). NAI treatment initiation within 48 hours and up to 7 days reduced risk of dying (0-48 hours aOR 0.51, 95% CI: 0.45-0.59; 3-4 days 0.59 (0.51-0.67); 5-7 days 0.64 (0.56-0.74)), in particular in patients 40 years and older (e.g. treatment within 48 hours: 40-59 years aOR 0.43, 95% CI: 0.28-0.66; 60-79 years 0.50 (0.39-0.63); ≥80 years 0.51 (0.42-0.63)).ConclusionNAI treatment given within 48 hours and possibly up to 7 days after symptom onset reduced risk of in-hospital death. NAI treatment should be considered in older patients to prevent severe outcomes.

• MeSH
• antivirové látky terapeutické užití   MeSH
• chřipka lidská * farmakoterapie   epidemiologie   MeSH
• guanidiny terapeutické užití   MeSH
• inhibitory enzymů terapeutické užití   MeSH
• lidé MeSH
• mortalita v nemocnicích MeSH
• neuraminidasa MeSH
• oseltamivir * terapeutické užití   MeSH
• senioři MeSH
• výsledek terapie MeSH
• zanamivir terapeutické užití   MeSH
• Check Tag
• lidé MeSH
• senioři MeSH
• Publikační typ
• časopisecké články MeSH

BackgroundUnderlying conditions are risk factors for severe COVID-19 outcomes but evidence is limited about how risks differ with age.AimWe sought to estimate age-specific associations between underlying conditions and hospitalisation, death and in-hospital death among COVID-19 cases.MethodsWe analysed case-based COVID-19 data submitted to The European Surveillance System between 2 June and 13 December 2020 by nine European countries. Eleven underlying conditions among cases with only one condition and the number of underlying conditions among multimorbid cases were used as exposures. Adjusted odds ratios (aOR) were estimated using 39 different age-adjusted and age-interaction multivariable logistic regression models, with marginal means from the latter used to estimate probabilities of severe outcome for each condition-age group combination.ResultsCancer, cardiac disorder, diabetes, immunodeficiency, kidney, liver and lung disease, neurological disorders and obesity were associated with elevated risk (aOR: 1.5-5.6) of hospitalisation and death, after controlling for age, sex, reporting period and country. As age increased, age-specific aOR were lower and predicted probabilities higher. However, for some conditions, predicted probabilities were at least as high in younger individuals with the condition as in older cases without it. In multimorbid patients, the aOR for severe disease increased with number of conditions for all outcomes and in all age groups.ConclusionWhile supporting age-based vaccine roll-out, our findings could inform a more nuanced, age- and condition-specific approach to vaccine prioritisation. This is relevant as countries consider vaccination of younger people, boosters and dosing intervals in response to vaccine escape variants.

• MeSH
• COVID-19 * MeSH
• hospitalizace MeSH
• lidé MeSH
• mortalita v nemocnicích MeSH
• SARS-CoV-2 MeSH
• senioři MeSH
• věkové faktory MeSH
• Check Tag
• lidé MeSH
• senioři MeSH
• Publikační typ
• časopisecké články MeSH

Background: Morbidity, severity, and mortality associated with annual influenza epidemics are of public health concern. We analyzed surveillance data on hospitalized laboratory-confirmed influenza cases admitted to intensive care units to identify common determinants for fatal outcome and inform and target public health prevention strategies, including risk communication. Methods: We performed a descriptive analysis and used Poisson regression models with robust variance to estimate the association of age, sex, virus (sub)type, and underlying medical condition with fatal outcome using European Union data from 2009 to 2017. Results: Of 13 368 cases included in the basic dataset, 2806 (21%) were fatal. Age ≥40 years and infection with influenza A virus were associated with fatal outcome. Of 5886 cases with known underlying medical conditions and virus A subtype included in a more detailed analysis, 1349 (23%) were fatal. Influenza virus A(H1N1)pdm09 or A(H3N2) infection, age ≥60 years, cancer, human immunodeficiency virus infection and/or other immune deficiency, and heart, kidney, and liver disease were associated with fatal outcome; the risk of death was lower for patients with chronic lung disease and for pregnant women. Conclusions: This study re-emphasises the importance of preventing influenza in the elderly and tailoring strategies to risk groups with underlying medical conditions.

• Publikační typ
• časopisecké články MeSH