A remarkable excess mortality has coincided with the COVID-19 pandemic in Europe. We present preliminary pooled estimates of all-cause mortality for 24 European countries/federal states participating in the European monitoring of excess mortality for public health action (EuroMOMO) network, for the period March–April 2020. Excess mortality particularly affected ≥ 65 year olds (91% of all excess deaths), but also 45–64 (8%) and 15–44 year olds (1%). No excess mortality was observed in 0–14 year olds.
Objectives: Weekly monitoring of European all-cause excess mortality, the EuroMOMO network, observed high excess mortality during the influenza B/Yamagata dominated 2017/18 winter season, especially among elderly. We describe all-cause excess and influenza-attributable mortality during the season 2017/18 in Europe. Methods: Based on weekly reporting of mortality from 24 European countries or sub-national regions, representing 60% of the European population excluding the Russian and Turkish parts of Europe, we estimated age stratified all-cause excess morality using the EuroMOMO model. In addition, age stratified all-cause influenza-attributable mortality was estimated using the FluMOMO algorithm, incorporating influenza activity based on clinical and virological surveillance data, and adjusting for extreme temperatures. Results: Excess mortality was mainly attributable to influenza activity from December 2017 to April 2018, but also due to exceptionally low temperatures in February-March 2018. The pattern and extent of mortality excess was similar to the previous A(H3N2) dominated seasons, 2014/15 and 2016/17. The 2017/18 overall all-cause influenza-attributable mortality was estimated to be 25.4 (95%CI 25.0-25.8) per 100,000 population; 118.2 (116.4-119.9) for persons aged 65. Extending to the European population this translates into over-all 152,000 deaths. Conclusions: The high mortality among elderly was unexpected in an influenza B dominated season, which commonly are considered to cause mild illness, mainly among children. Even though A(H3N2) also circulated in the 2017/18 season and may have contributed to the excess mortality among the elderly, the common perception of influenza B only having a modest impact on excess mortality in the older population may need to be reconsidered.
We reviewed the case definitions used by 21 influenza sentinel-based surveillance networks in Western Europe. Two clinical syndromes were used with a wide range of case definitions that nevertheless shared common criteria. Although there is currently no international consensus, efforts are being undertaken to standardise influenza case definitions in Europe.
BackgroundInfluenza vaccines contain Influenza A and B antigens and are adjusted annually to match the characteristics of circulating viruses. In Germany, Influenza B viruses belonged to the B/Yamagata lineage, but since 2001, the antigenically distinct B/Victoria lineage has been co-circulating. Trivalent influenza vaccines (TIV) contain antigens of the two A subtypes A(H3N2) and A(H1N1), yet of only one B lineage, resulting in frequent vaccine mismatches. Since 2012, the WHO has been recommending vaccine strains from both B lineages, paving the way for quadrivalent influenza vaccines (QIV).MethodsUsing an individual-based simulation tool, we simulate the concomitant transmission of four influenza strains, and compare the effects of TIV and QIV on the infection incidence. Individuals are connected in a dynamically evolving age-dependent contact network based on the POLYMOD matrix; their age-distribution reproduces German demographic data and predictions. The model considers maternal protection, boosting of existing immunity, loss of immunity, and cross-immunizing events between the B lineages. Calibration to the observed annual infection incidence of 10.6% among young adults yielded a basic reproduction number of 1.575. Vaccinations are performed annually in October and November, whereby coverage depends on the vaccinees’ age, their risk status and previous vaccination status. New drift variants are introduced at random time points, leading to a sudden loss of protective immunity for part of the population and occasionally to reduced vaccine efficacy. Simulations run for 50 years, the first 30 of which are used for initialization. During the final 20 years, individuals receive TIV or QIV, using a mirrored simulation approach.ResultsUsing QIV, the mean annual infection incidence can be reduced from 8,943,000 to 8,548,000, i.e. by 395,000 infections, preventing 11.2% of all Influenza B infections which still occur with TIV (95% CI: 10.7-11.8%). Using a lower B lineage cross protection than the baseline 60%, the number of Influenza B infections increases and the number additionally prevented by QIV can be 5.5 times as high.ConclusionsVaccination with TIV substantially reduces the Influenza incidence compared to no vaccination. Depending on the assumed degree of B lineage cross protection, QIV further reduces Influenza B incidence by 11-33%.
Rapid identification of agronomically important genes is of pivotal interest for crop breeding. One source of such genes are crop wild relative (CWR) populations. Here we used a CWR population of <200 wild beets (B. vulgaris ssp. maritima), sampled in their natural habitat, to identify the sugar beet (Beta vulgaris ssp. vulgaris) resistance gene Rz2 with a modified version of mapping-by-sequencing (MBS). For that, we generated a draft genome sequence of the wild beet. Our results show the importance of preserving CWR in situ and demonstrate the great potential of CWR for rapid discovery of causal genes relevant for crop improvement. The candidate gene for Rz2 was identified by MBS and subsequently corroborated via RNA interference (RNAi). Rz2 encodes a CC-NB-LRR protein. Access to the DNA sequence of Rz2 opens the path to improvement of resistance towards rhizomania not only by marker-assisted breeding but also by genome editing.
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