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Purpose: Hypertoxigenic Streptococcus pyogenes emm1 lineage M1UK has recently been associated with upsurges of invasive infections and scarlet fever in several countries, but whole-genome sequencing surveillance data of lineages circulating in Germany is lacking. In this study, we investigated recent iGAS isolates from our laboratory at a German tertiary care center for the presence of the M1UK lineage. Methods: Whole-genome sequencing was employed to characterize a collection of 47 consecutive non-copy isolates recovered from blood cultures (21) and tissue samples (26) in our laboratory between October 2022 and April 2023. Results: M protein gene (emm) typing distinguished 14 different emm types, with emm1 (17) being the dominant type. Single-nucleotide polymorphism (SNP) analysis confirmed the presence of all 27 SNPs characteristic for the M1UK lineage in 14 of 17 emm1 isolates. Conclusion: This study has shown for the first time that M1UK is present in Germany and might constitute a driving force in the observed surge of GAS infections. This observation mirrors developments in the UK and other countries and underscores the importance of WGS surveillance to understand the epidemiology of GAS. [ABSTRACT FROM AUTHOR]

Purpose: In spine care, frailty is associated with poor outcomes. The aim of this study was to describe changes in frailty in spine care during the coronavirus disease 2019 (COVID-19) pandemic and their relation to surgical management and outcomes. Methods: Patients hospitalized for spine pathologies between January 1, 2019, and May 17, 2022, within a nationwide network of 76 hospitals in Germany were retrospectively included. Patient frailty, types of surgery, and in-hospital mortality rates were compared between pandemic and pre-pandemic periods. Results: Of the 223,418 included patients with spine pathologies, 151,766 were admitted during the pandemic and 71,652 during corresponding pre-pandemic periods in 2019. During the pandemic, the proportion of high-frailty patients increased from a range of 5.1–6.1% to 6.5–8.8% (p < 0.01), while the proportion of low frailty patients decreased from a range of 70.5–71.4% to 65.5–70.1% (p < 0.01). In most phases of the pandemic, the Elixhauser comorbidity index (ECI) showed larger increases among high compared to low frailty patients (by 0.2–1.8 vs. 0.2–0.8 [p < 0.01]). Changes in rates of spine surgery were associated with frailty, most clearly in rates of spine fusion, showing consistent increases among low frailty patients (by 2.2–2.5%) versus decreases (by 0.3–0.8%) among high-frailty patients (p < 0.02). Changes in rates of in-hospital mortality were not associated with frailty. Conclusions: During the COVID-19 pandemic, the proportion of high-frailty patients increased among those hospitalized for spine pathologies in Germany. Low frailty was associated with a rise in rates of spine surgery and high frailty with comparably larger increases in rates of comorbidities. [ABSTRACT FROM AUTHOR]

Background: Critical infrastructure (CRITIS) in hospitals has become the focus of resilience research due to the impact of the COVID-19 pandemic and also the events in Ukraine. This foundational research examines overall contexts, categorizing and quantifying them. Previous research examined limited scale damage situations with little CRITIS involvement: Worst case studies are missing. The vulnerabilities of the CRITIS of one or more countries will likewise be a prime target for attack in current and future conflicts or criminal extortion, this is especially true in the healthcare sector. Therefore, detailed research with a black swan scenario is necessary in this field. Objective: The aim of the study was to create and validate a categorized and weighted model for the self-assessment of the resilience of critical infrastructure in German hospitals at different levels of care before the exemplary scenario of a prolonged supraregional power blackout. Material and methods: Using an explorative design, experts from 8 hospitals of different care levels performed an expert-based qualitative system analysis to develop, weight and test the model. The resilience index was then calculated using adapted interdependence analyses in a Vester influence matrix. Results: A total of 7 categories and 24 subcategories of hospital CRITIS were identified. There are several key elements: rank 1 of active elements is the emergency power system (E1), and for passive elements, it is the nursing staff (P2). This means that the emergency power system has the greatest impact on all other areas and the nursing staff are most dependent on all others for their work. The most critical elements, because they are most intertwined in the overall system, are the situation center/command staff (Z1) and technical staff (P3), on which the entire system depends. From the weighted individual elements of CRITIS, an overall resilience for a hospital can be calculated (resilience index). The developed model can be used by hospital crisis experts as part of a self-assessment to provide a basis for risk management, financial planning, technical planning, personnel planning or crisis and disaster management. Conclusion: The categorization and quantification of critical infrastructure (CRITIS) in hospitals with the aim of resilience documentation and optimization is possible. The model that has been developed allows rapid adaptation to changing initial situations and increases in resilience that can be realized in the short and medium term. Emergency and crisis preparedness is a dynamic process, which has been combined here with the further development of critical infrastructure. Consequently, there can be no final state to be achieved but only a certain best possible framework within which the hospital as a business enterprise can operate. The classification of the categories in the model must also be constantly further developed and adapted to the current status. Once the explorative and qualitative basic research has been completed, it is necessary in a further step to subject the model, which has been validated by experts, to a broader review. Ideally, this will be done using quantitative methods and a significantly larger sample. [ABSTRACT FROM AUTHOR]

Scholars have called to study how social cohesion is discursively negotiated and produced in communication behavior. However, empirical evidence remains scarce. In this study, we investigate to what extent and how civil society organizations (CSOs), part of the backbone of social integration in modern democracies, make references to social cohesion in their public self-portrayals. We develop a standardized measure for content analyzing the manifestation of social cohesion along three theoretical dimensions: social relations, connectedness, and orientation towards the common good. We apply our innovative content measure to the external communication of an original sample of nearly 800 CSOs in Germany, using their websites. Subsequently, we use data from an accompanying organizational survey of these institutions to investigate whether and how certain organizational features help explain variance in social cohesion rhetoric. Findings suggest that CSOs' external communications employ themes from all key dimensions of social cohesion, revealing a fair amount of variation on all three subdimensions and a summary index of the overall strength social cohesion rhetoric. These different emphases are contingent upon various organizational characteristics, namely the spheres in which CSOs are primarily active, their locations, and their target groups. Whereas culturally and media-oriented organizations as well as sports clubs are largely reluctant to make references to social cohesion, politically active CSOs and those addressing socially disadvantaged communities tend to push more in this direction. The latter tend to operate in more professionalized structures, indicating that referencing social cohesion legitimizes these groups' political and social purposes in the public sphere. [ABSTRACT FROM AUTHOR]

The sampling adjustment factor (SAF) can correct the underestimation of fixed time interval maxima (F-Maxima) relative to maxima of moving time windows (M-Maxima) as a direct consequence of temporal discretization of time series. Radar data can help to understand the significance of using moving window aggregation rather than fixed window. Here, we investigate SAFs for two gridded radar quantitative precipitation estimates from the German Meteorological Service (RADKLIM-RW and RADKLIM-YW, DWD 2018) with different temporal resolutions (5 min and hourly) and a spatial resolution of 1 km × 1 km from 2001 to 2016. For each grid cell's time series within Germany, the overall maximum intensities per chosen duration were derived with (1) moving and (2) fixed window aggregation. Correction factors (SAF) from fixed to moving window were retrieved. The findings of this study partly match previous findings, more for the 5-min product than for the hourly product. No clear dependency on topography or season could be derived from the analysis. It showed that high SAF are usually related to high(er) actual rainfall values. The study emphasises the probabilistic nature of the rainfall maxima correction and shows that it is important to not only consider average SAFs, but also take an in-depth look at the distribution when correcting maxima. As a consequence, design precipitation as used, e.g., in context of flash or urban floods could profit from spatially adjusted or uniform scaling, depending on the characteristics found in the spatial distribution of the SAFs. [ABSTRACT FROM AUTHOR]

Since the introduction of widely available e-scooter rentals in Hamburg, Germany in June of 2019, our emergency department has seen a sharp increase in the amount of e-scooter related injuries. Despite a rising number of studies certain aspects of e-scooter mobility remain unclear. This study examines the various aspects of e-scooter associated injuries with one of the largest cohorts to date. Electronic patient records of emergency department admissions were screened for e-scooter associated injuries between June 2019 and December 2021. Patient demographic data, mechanism of injury, alcohol consumption, helmet usage, sustained injuries and utilized medical resources were recorded. Overall, 268 patients (57% male) with a median age of 30.3 years (IQR 23.3; 40.0) were included. 252 (94%) were e-scooter riders themselves, while 16 (6%) were involved in crashes associated with an e-scooter. Patients in non-rider e-scooter crashes were either cyclists who collided with e-scooter riders or older pedestrians (median age 61.2 years) who tripped over parked e-scooters. While e-scooter riders involved in a crash sustained an impact to the head or face in 58% of cases, those under the influence of alcohol fell on their head or face in 84% of cases. This resulted in a large amount of maxillofacial soft tissue lacerations and fractures. Extremity fractures and dislocations were more often recorded for the upper extremities. This study comprises one of the largest cohorts of e-scooter associated injuries to date. Older pedestrians are at risk to stumble over parked e-scooters. E-scooter crashes with riders who consumed alcohol were associated with more severe injuries, especially to the head and face. Restricted e-scooter parking, enforcement of drunk driving laws for e-scooters, and helmet usage should be recommended. [ABSTRACT FROM AUTHOR]

Forests provide important ecosystem services such as carbon sequestration. Forest landscapes are intrinsically heterogeneous—a problem for biomass and productivity assessment using remote sensing. Forest structure constitutes valuable additional information for the improved estimation of these variables. However, survey of forest structure by remote sensing remains a challenge which results mainly from the differences in forest structure metrics derived by using remote sensing compared to classical structural metrics from field data. To understand these differences, remote sensing measurements were linked with an individual-based forest model. Forest structure was analyzed by lidar remote sensing using metrics for the horizontal and vertical structures. To investigate the role of forest structure for biomass and productivity estimations in temperate forests, 25 lidar metrics of 375,000 simulated forest stands were analyzed. For the lidar-based metrics, top-of-canopy height arose as the best predictor for describing horizontal forest structure. The standard deviation of the vertical foliage profile was the best predictor for the vertical heterogeneity of a forest. Forest structure was also an important factor for the determination of forest biomass and aboveground wood productivity. In particular, horizontal structure was essential for forest biomass estimation. Predicting aboveground wood productivity must take into account both horizontal and vertical structures. In a case study based on these findings, forest structure, biomass and aboveground wood productivity are mapped for whole of Germany. The dominant type of forest in Germany is dense but less vertically structured forest stands. The total biomass of all German forests is 2.3 Gt, and the total aboveground woody productivity is 43 Mt/year. Future remote sensing missions will have the capability to provide information on forest structure (e.g., from lidar or radar). This will lead to more accurate assessments of forest biomass and productivity. These estimations can be used to evaluate forest ecosystems related to climate regulation and biodiversity protection. [ABSTRACT FROM AUTHOR]

In fragmented landscapes, plant species persistence depends on functional connectivity in terms of pollen flow to maintain genetic diversity within populations, and seed dispersal to re-colonize habitat patches following local extinction. Connectivity in plants is commonly modeled as a function of the physical distance between patches, without testing alternative dispersal vectors. In addition, pre- and post-dispersal processes such as seed production and establishment are likely to affect patch colonization rates. Here, we test alternative models of potential functional connectivity with different assumptions on source patch effects (patch area and species occupancy) and dispersal (relating to distance among patches, matrix composition, and sheep grazing routes) against empirical patch colonization rates at the community level (actual functional connectivity), accounting for post-dispersal effects in terms of structural elements providing regeneration niches for establishment. Our analyses are based on two surveys in 1989 and in 2009 of 48 habitat specialist plants in 62 previously abandoned calcareous grassland patches in the Southern Franconian Alb in Bavaria, Germany. The best connectivity model S, as identified by multi-model inference, combined distance along sheep grazing routes including consistently and intermittently grazed patches with mean species occupancy in 1989 as a proxy for pre-dispersal effects. Community-level patch colonization rates depended to equal degrees on connectivity and post-dispersal process. Our study highlights that actual functional connectivity of calcareous grassland communities cannot be approximated by structural connectivity based on physical distance alone, and modeling of functional connectivity needs to consider pre- and post-dispersal processes. [ABSTRACT FROM AUTHOR]