Background:Tick-borne encephalitis (TBE), caused by tick-borne encephalitis virus (TBEV), is a zoonotic disease that can lead to severe neurological symptoms. Given the increasing number of reported human TBE cases in Europe, we developed a spatio-temporal predictive model to infer the year-to-year probability of human TBE occurrence across Europe at the regional and municipal administrative levels. Methods:We derived the distribution of human TBE cases at the regional level during 2017-2022 by using data provided by the European Centre for Disease Prevention and Control (ECDC), and at the municipal level by using data provided by Austria, Finland, Italy, Lithuania, and Slovakia. We modeled the probability of presence of human TBE cases at the regional and municipal levels for the period 2017-2025 with a boosted regression trees model, including covariates that affect both the natural hazard of virus circulation and human exposure to tick bites. Findings:Areas with the highest probability of human TBE infections are located in central-eastern Europe, the Baltic states, and along the coastline of Nordic countries. Our results highlight a statistically significant rising trend in human TBE risk not only in north-western, but also in south-western European countries. Such areas are characterised by the presence of key tick host species, forested areas, intense human activity in forests, steep drops in late summer temperatures and high precipitation amounts during the driest months. The model showed good predictive performance, with a mean AUC of 0.84 (SD = 0.03), sensitivity of 0.83 (SD = 0.01), and specificity of 0.80 (SD = 0.01) at the regional level, and a mean AUC of 0.82 (SD = 0.03), sensitivity of 0.83 (SD = 0.01), and specificity of 0.69 (SD = 0.01) at the municipal level. Interpretation:With ongoing climate and land use changes, the number of human TBE cases is likely to increase and spread into new areas. This highlights the importance of predictive models that can identify potential risk areas to support disease prevention and control efforts by public health authorities. The approach adopted, by fitting a One Health framework and leveraging lagged covaries, enables timely one-year-ahead predictions and enhances our current understanding of TBE risk under a global change scenario.
Important questions remain regarding differences in geographical and age-specific mortality patterns as the COVID-19 pandemic evolved in consecutive waves, and how COVID-19 mortality compares to seasonal influenza. In a pandemic situation, excess all-cause mortality provides a more complete and robust measure than cause-specific mortality. Data submitted by 26 countries participating in the European Mortality Monitoring (EuroMOMO) network between 2020 and 2023 was analysed to quantify excess all-cause mortality during the COVID-19 pandemic. Excess mortality from this period was compared to previous influenza seasons from 2014 to 2019. Pooled estimates of excess mortality showed four main waves during the COVID-19 pandemic period, most markedly in people aged 65 years and above, with timing and magnitude that varied between countries. Here we show that prior to implementation of control measures and COVID-19 vaccination, excess mortality greatly exceeded typical seasonal influenza mortality, but later during the pandemic was at levels comparable to influenza.
The sugar beet weevil is considered one of the most economically important insect pests in sugar beet cultivation. A promising biological control strategy involves the natural interaction between entomopathogenic fungi and arthropods. The successful application of M. brunneum as part of integrated biological control strategies against the sugar beet weevil has already been demonstrated resulting in lethal mycosis. However, the efficacy of this strain is affected by multiple factors. The intestinal microbiome of insects harbours beneficial microbes that possess various functions, such as defence mechanisms against insect-pathogens. Thus, investigating intestinal microbial interactions in combination with Metarhizium-application could reveal microbes that modulate susceptibility to pathogens. This study investigated whether intestinal microbial interactions influence mycosis caused by M. brunneum and M. robertsii. We analysed the intestinal microbiome of both treated and untreated sugar beet weevils, distinguishing between mycotic and non-mycotic individuals at the time of death. Notably, Pantoea and Enterobacter were significantly associated with mycotic individuals and may act as a potential antagonist to Metarhizium. In contrast, healthy individuals harboured diverse microbial communities that may provide a protective barrier against entomopathogens. However, the intestinal microbiome of non-mycotic specimens also comprised genera with presumed insecticidal properties, including Serratia, Penicillium and Cladosporium. The last two were also observed in the intestines of male individuals, which were generally at a higher risk of mortality. Further investigation is needed to confirm their insecticidal potential in the sugar beet weevil. A combined application could improve the efficacy of Metarhizium-based biocontrol, contributing to more sustainable pest management strategies.
BACKGROUNDWest Nile virus (WNV) and Usutu virus (USUV) outbreaks in Europe pose growing public health concerns. In Austria, human WNV and USUV infections occur nearly every year since 2009 with notable case number variations.AIMWe analysed annual incidences and spatiotemporal distributions of human WNV and USUV infections in Austria in 2009-2024.METHODSAnnual incidence rates of laboratory-confirmed WNV and USUV cases recorded through the national surveillance were calculated, stratified by age, sex, clinical presentation, exposure place and virus sequence.RESULTSDuring 2009-2024, recorded case numbers were highest in 2024, with 37 WNV (19 male/18 female; median age: 62 years, range: 18-88) and 27 USUV infections (18 male/9 female; median age: 59 years, range: 20-69). Nineteen WNV cases developed West Nile neuroinvasive disease, while no USUV cases had neurological disease. Thirty-four of the WNV cases and all USUV cases were locally acquired. In northern Burgenland, an eastern Austrian region with an avian hotspot and only sporadic cases previously reported, WNV and USUV incidences respectively rose from averages of 0.6 and 1.0 per 100,000 in previous years to 6.6 and 4.2 per 100,000 in 2024. All 25 sequences analysed in 2024 from locally acquired WNV cases were of lineage 2. Among 15 USUV sequences, 14 belonged to the Europe-2 and one to the Africa-3 clade.CONCLUSIONHuman WNV and USUV infection increases in a previously low-incidence region underscore their increasing public health impact in Austria. Strengthening surveillance and response measures is essential for early detection, guiding prevention efforts, and ensuring blood donor safety.
IntroductionStaphylococcus epidermidis is an opportunistic pathogen causing bloodstream and device-associated infections. Due to the use of linezolid (LZD) against infections caused by multidrug-resistant Gram-positive bacteria, the emergence of LZD-resistant S. epidermidis (LRSE) is an increasing concern. This study aimed to characterize genomic clusters, resistance mechanisms, and epidemiological links among LRSE isolates collected during a suspected outbreak in two Austrian hospitals.MethodsA confirmed case was defined as a patient with LRSE (MIC > 4 mg/L) isolated from clinical or screening samples in Hospital A or Hospital B between March 2023 and April 2025. All isolates underwent whole-genome sequencing (WGS) for typing and identification of resistance determinants. Epidemiological data, including the hospital and ward of detection as well as inter-hospital transfers, were analyzed to explore potential epidemiological links between cases.ResultsA total of 53 LRSE cases were identified, including 22 in Hospital A and 31 in Hospital B. The Linezolid isolate originated from a patient admitted to Hospital B after traveling abroad and no epidemiological link with the LRSE cases was identified. Epidemiological and genomic data identified five clusters belonging to three sequence types (ST2, ST5, ST22). Most Cluster 1 cases were detected in Hospital B, especially in the surgical ICU, while Clusters 2–4 were exclusively identified in Hospital A. However, the available epidemiological information was insufficient to determine transmission direction or identify the origin of the clusters. Forty-five of 53 LRSE isolates displayed high-level LZD resistance (MIC ≥48 mg/L). Distinct resistance-associated mutations were identified in each ST, including G2576U in ST2 isolates, C2534U and U2504A in ST22 isolates, and characteristic alterations in ribosomal proteins L3 and L4.ConclusionGenomic analysis identified five distinct LRSE clusters belonging to three STs and revealed ST-specific resistance mutations, suggesting multiple independent evolutionary pathways to LZD resistance. However, limited epidemiological information, including incomplete data on LZD administration and patient movements, prevented definitive assessment of transmission dynamics. Our findings demonstrate the utility of WGS for the detection and characterization of LRSE clusters and highlight the importance of comprehensive epidemiological data for interpreting genomic links.
