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The COVID-19 pandemic and related preventive measures reduced influenza virus circulation, notably causing the disappearance of the B/Yamagata lineage of influenza viruses. In this Perspective, we discuss the implications that this development may have for global influenza epidemiology, and the adjustments that may need to be implemented concerning surveillance strategies and practices, laboratory safety protocols, and influenza vaccine formulations. The disappearance of the B/Yamagata lineage might indeed alter the dynamics of the influenza disease burden (although in a way that is difficult to predict at the moment), and associated diagnostic practices, and may also necessitate updated biosafety levels and revised influenza surveillance strategies. Furthermore, the World Health Organization (WHO) recommended in September 2023 the exclusion of B/Yamagata antigens from future vaccines, with a shift towards trivalent vaccines or modified quadrivalent vaccines; this new scenario underscores the importance of robust global respiratory virus surveillance, effective communication with healthcare professionals and the population to maintain trust in vaccines, and a collaborative approach among health policymakers and vaccine manufacturers to navigate this epidemiological change.

BackgroundThere is currently no standardised approach to estimate respiratory syncytial virus (RSV) epidemics' timing (or seasonality), a critical information for their effective prevention and control.AimWe aimed to provide an overview of methods to define RSV seasonality and identify factors supporting method choice or interpretation/comparison of seasonal estimates.MethodsWe systematically searched PubMed and Embase (2016-2021) for studies using quantitative approaches to determine the start and end of RSV epidemics. Studies' features (data-collection purpose, location, regional/(sub)national scope), methods, and assessment characteristics (case definitions, sampled population's age, in/outpatient status, setting, diagnostics) were extracted. Methods were categorised by their need of a denominator (i.e. numbers of specimens tested) and their retrospective vs real-time application. Factors worth considering when choosing methods and assessing seasonal estimates were sought by analysing studies.ResultsWe included 32 articles presenting 49 seasonality estimates (18 thereof through the 10% positivity threshold method). Methods were classified into eight categories, two requiring a denominator (1 retrospective; 1 real-time) and six not (3 retrospective; 3 real-time). A wide range of assessment characteristics was observed. Several studies showed that seasonality estimates varied when methods differed, or data with dissimilar assessment characteristics were employed. Five factors (comprising study purpose, application time, assessment characteristics, healthcare system and policies, and context) were identified that could support method choice and result interpretation.ConclusionMethods and assessment characteristics used to define RSV seasonality are heterogeneous. Our categorisation of methods and proposed framework of factors may assist in choosing RSV seasonality methods and interpretating results.

While two influenza B virus lineages have co-circulated, B/Yamagata-lineage circulation has not been confirmed since March 2020. The WHO FluNet database indicates that B/Yamagata-lineage detections were reported in 2021 and 2022. However, detections can result from use of quadrivalent live-attenuated vaccines. Of the type B viruses detected post-March 2020, all ascribed to a lineage have been B/Victoria-lineage. There is need for a global effort to detect and lineage-ascribe type B influenza viruses, to assess if B/Yamagata-lineage viruses have become extinct.

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.

IntroductionThe global epidemiology of many infectious diseases is changing, but little attention has been paid to whether the timing of seasonal influenza epidemics changed in recent years. This study investigated whether the timing of the peak of influenza epidemics has changed in countries of the World Health Organization (WHO) European Region between 1996 and 2016. 
 Methods: Surveillance data were obtained from the WHO FluNet database. For each country and season (July to June of the next year), the peak was defined as the week with the highest 3-week moving average for reported cases. Linear regression models were used to test for temporal trends in the timing of the epidemic peak in each country and to determine whether this differed geographically. 
 Results: More than 600,000 influenza cases were included from 38 countries of the WHO European Region. The timing of the epidemic peak changed according to a longitudinal gradient, occurring progressively later in Western Europe (e.g. by 2.8 days/season in Spain) and progressively earlier in Eastern Europe (e.g. by 3.5 days/season in the Russian Federation). 
 Discussion: These results were confirmed in several sensitivity analyses. Our findings have implications for influenza control and prevention measures in the WHO European Region, for instance for the implementation of influenza vaccination campaigns.

We aimed to assess the epidemiology and spatiotemporal patterns of influenza in the World Health Organization (WHO) European Region and evaluate the validity of partitioning the Region into five influenza transmission zones (ITZs) as proposed by the WHO. We used the FluNet database and included over 650,000 influenza cases from 2000 to 2015. We analysed the data by country and season (from July to the following June). We calculated the median proportion of cases caused by each virus type in a season, compared the timing of the primary peak between countries and used a range of cluster analysis methods to assess the degree of overlap between the WHO-defined and data-driven ITZs. Influenza A and B caused, respectively, a median of 83% and 17% cases in a season. There was a significant west-to-east and non-significant (p = 0.10) south-to-north gradient in the timing of influenza activity. Typically, influenza peaked in February and March; influenza A earlier than influenza B. Most countries in the WHO European Region would fit into two ITZs: 'Western Europe' and 'Eastern Europe'; countries bordering Asia may be better placed into extra-European ITZs. Our findings have implications for the presentation of surveillance data and prevention and control measures in this large WHO Region., (This article is copyright of The Authors, 2017.)

Healthcare-associated infections caused by multidrug-resistant organisms are associated with prolonged medical care, worse outcome and costly therapies. In Hungary, hospital-acquired infections (HAIs) due to epidemiologically important multidrug-resistant organisms are notifiable by law since 2004. Overall, 6,845 case-patients (59.8% men; median age: 65 years) were notified in Hungary from 2005 to 2010. One third of case-patients died in hospital. The overall incidence of infections increased from 5.4 in 2005 to 14.7 per 100,000 patient-days in 2010. Meticillin-resistant Staphylococcus aureus (MRSA) was the most frequently reported pathogen (52.2%), but while its incidence seemed to stabilise after 2007, notifications of multidrug-resistant Gram-negative organisms have significantly increased from 2005 to 2010. Surgical wound and bloodstream were the most frequently reported sites of infection. Although MRSA incidence has seemingly reached a plateau in recent years, actions aiming at reducing the burden of HAIs with special focus on Gram-negative multidrug-resistant organisms are needed in Hungary. Continuing promotion of antimicrobial stewardship, infection control methodologies, reinforced HAI surveillance among healthcare and infection control practitioners, and engagement of stakeholders, hospital managers and public health authorities to facilitate the implementation of existing guidelines and protocols are essential.

In October 2011, a cluster of four tick-borne encephalitis (TBE) cases was identified in Hungary. Initial investigations revealed a possible link with consumption of unpasteurised cow milk sold by a farmer without authorisation. We performed a cohort study including all regular customers of the farmer. Overall, eleven cases (seven confirmed and four suspected) were identified. Customers who had consumed the farmer’s unpasteurised cow milk had more than a two-fold increased risk for being a TBE case, although not at statistically significant level.