BACKGROUND: Epidemiological data are crucial to monitoring progress towards the 2030 Hepatitis C Virus (HCV) elimination targets. Our aim was to estimate the prevalence of chronic HCV infection (cHCV) in the European Union (EU)/European Economic Area (EEA) countries in 2019. METHODS: Multi-parameter evidence synthesis (MPES) was used to produce national estimates of cHCV defined as: π = πrecρrec + πexρex + πnonρnon; πrec, πex, and πnon represent cHCV prevalence among recent people who inject drugs (PWID), ex-PWID, and non-PWID, respectively, while ρrec, ρex, and ρnon represent the proportions of these groups in the population. Information sources included the European Centre for Disease Prevention and Control (ECDC) national operational contact points (NCPs) and prevalence database, the European Monitoring Centre for Drugs and Drug Addiction databases, and the published literature. FINDINGS: The cHCV prevalence in 29 of 30 EU/EEA countries in 2019 was 0.50% [95% Credible Interval (CrI): 0.46%, 0.55%]. The highest cHCV prevalence was observed in the eastern EU/EEA (0.88%; 95% CrI: 0.81%, 0.94%). At least 35.76% (95% CrI: 33.07%, 38.60%) of the overall cHCV prevalence in EU/EEA countries was associated with injecting drugs. INTERPRETATION: Using MPES and collaborating with ECDC NCPs, we estimated the prevalence of cHCV in the EU/EEA to be low. Some areas experience higher cHCV prevalence while a third of prevalent cHCV infections was attributed to PWID. Further efforts are needed to scale up prevention measures and the diagnosis and treatment of infected individuals, especially in the east of the EU/EEA and among PWID. FUNDING: ECDC.
- Publikační typ
- časopisecké články 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
Since December 2019, over 1.5 million SARS-CoV-2-related fatalities have been recorded in the World Health Organization European Region - 90.2% in people ≥ 60 years. We calculated lives saved in this age group by COVID-19 vaccination in 33 countries from December 2020 to November 2021, using weekly reported deaths and vaccination coverage. We estimated that vaccination averted 469,186 deaths (51% of 911,302 expected deaths; sensitivity range: 129,851-733,744; 23-62%). Impact by country ranged 6-93%, largest when implementation was early.
- MeSH
- COVID-19 * MeSH
- lidé MeSH
- SARS-CoV-2 MeSH
- Světová zdravotnická organizace MeSH
- vakcinace MeSH
- vakcíny proti COVID-19 * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
Prioritisation of elderly people in COVID-19 vaccination campaigns aimed at reducing severe outcomes in this group. Using EU/EEA surveillance and vaccination uptake, we estimated the risk ratio of case, hospitalisation and death notifications in people 80 years and older compared with 25-59-year-olds. Highest impact was observed for full vaccination uptake 80% or higher with reductions in notification rates of cases up to 65% (IRR: 0.35; 95% CI: 0.13-0.99), hospitalisations up to 78% (IRR: 0.22; 95% CI: 0.13-0.37) and deaths up to 84% (IRR: 0.16; 95% CI: 0.13-0.20).
- MeSH
- COVID-19 * MeSH
- hospitalizace MeSH
- lidé MeSH
- SARS-CoV-2 MeSH
- senioři MeSH
- vakcinace MeSH
- vakcíny proti COVID-19 * 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
Background: Meningococcal disease continues to be a global public health concern due to its epidemic potential, severity, and sequelae. The global epidemiological data on circulating meningococcal serogroups have never been reviewed concurrently with the laboratory capacity for meningococcal surveillance at the national level. We, therefore, aimed to conduct a country-level review of meningococcal surveillance, serogroup distribution, and vaccine use. Methods: We conducted a systematic literature review across six databases to identify studies (published January 1, 2010 to October 16, 2017) and grey literature reporting meningococcal serogroup data for the years 2010-2016. We performed independent random effects meta-analyses for serogroups A, B, C, W, X, Y, and other. We developed and circulated a questionnaire-based survey to surveillance focal points in countries (N = 95) with known regional bacterial meningitis surveillance programs to assess their surveillance capacity and summarized using descriptive methods. Results: We included 173 studies from 59 countries in the final analysis. The distribution of meningococcal serogroups differed markedly between countries and regions. Meningococcal serogroups C and W accounted for substantial proportions of meningococcal disease in most of Africa and Latin America. Serogroup B was the predominant cause of meningococcal disease in many locations in Europe, the Americas, and the Western Pacific. Serogroup Y also caused many cases of meningococcal disease in these regions, particularly in Nordic countries. Survey responses were received from 51 countries. All countries reported the ability to confirm the pathogen in-country, while approximately 30% either relied on reference laboratories for serogrouping (N = 10) or did not serogroup specimens (N = 5). Approximately half of countries did not utilize active laboratory-based surveillance system (N = 22). Nationwide use of a meningococcal vaccine varied, but most countries (N = 36) utilized a meningococcal vaccine at least for certain high-risk population groups, in private care, or during outbreaks. Conclusions: Due to the large geographical variations in circulating meningococcal serogroups, each country should continue to be monitored for changes in major disease-causing serogroups in order to inform vaccine and control policies. Similarly, laboratory capacity should be appropriately scaled up to more accurately understand local epidemiology and disease burden, as well as the impact of vaccination programs.
- MeSH
- celosvětové zdraví statistika a číselné údaje MeSH
- lidé MeSH
- meningokokové infekce epidemiologie prevence a kontrola MeSH
- meningokokové vakcíny aplikace a dávkování MeSH
- Neisseria meningitidis genetika MeSH
- průzkumy a dotazníky MeSH
- séroskupina MeSH
- surveillance populace * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- systematický přehled MeSH
