Excess mortality in Europe coincides with peaks of COVID-19, influenza and respiratory syncytial virus (RSV), November 2023 to February 2024.

Since the end of November 2023, the European Mortality Monitoring Network (EuroMOMO) has observed excess mortality in Europe. During weeks 48 2023-6 2024, preliminary results show a substantially increased rate of 95.3 (95% CI:  91.7-98.9) excess all-cause deaths per 100,000 person-years for all ages. This excess mortality is seen in adults aged 45 years and older, and coincides with widespread presence of COVID-19, influenza and respiratory syncytial virus (RSV) observed in many European countries during the 2023/24 winter season.

SARS-CoV-2 Omicron variants BA.1 and BA.2 both show similarly reduced disease severity of COVID-19 compared to Delta, Germany, 2021 to 2022.

German national surveillance data analysis shows that hospitalisation odds associated with Omicron lineage BA.1 or BA.2 infections are up to 80% lower than with Delta infection, primarily in ≥ 35-year-olds. Hospitalised vaccinated Omicron cases' proportions (2.3% for both lineages) seemed lower than those of the unvaccinated (4.4% for both lineages). Independent of vaccination status, the hospitalisation frequency among cases with Delta seemed nearly threefold higher (8.3%) than with Omicron (3.0% for both lineages), suggesting that Omicron inherently causes less severe disease.

[Healthcare-associated infections and antimicrobial use in long-term care facilities. German results of the third European point prevalence survey HALT-3]. / Nosokomiale Infektionen und Antibiotikaanwendung in Langzeitpflegeeinrichtungen. Deutsche Ergebnisse der dritten europäischen Punkt-Prävalenz-Erhebung HALT-3.

BACKGROUND AND OBJECTIVE: The essential role of infection prevention in long-term care facilities has become evident during the current SARS-CoV­2 pandemic. In order to obtain a reliable database on nosocomial infections and antibiotic use, the European Centre for Disease Prevention and Control (ECDC) initiated the third point prevalence survey in European long-term care facilities from 2016 to 2017 (HALT-3). MATERIAL AND METHODS: In Germany, 131 facilities with 10,565 residents participated voluntarily. On a single day in 2016, the number of nosocomial infections and/or uses of antibiotics as well as care characteristics and risk factors of the residents were recorded. Infections were documented based on symptoms using an algorithm in accordance with the McGeer surveillance criteria for long-term care facilities. RESULTS: A nosocomial infection was documented in 177 residents, which corresponds to a prevalence of 1.7% (95% CI: 1.3-2.1), still low in comparison with the European prevalence (mean value 3.9%). Urinary tract infections were the most common infections at almost 50%, followed by respiratory, skin, and soft-tissue infections. The type of infection was consistent with the most common indications for antibiotic use. Antibiotic use was documented in 143 residents (prevalence of 1.4%, 95% CI: 1.1-1.7). The frequent use of fluoroquinolones with over 20% of all prescriptions was noticeable. CONCLUSIONS: The establishment of facility-based surveillance of the most common infections and antibiotic consumption, together with the creation of guidelines specifically tailored to the geriatric population, could contribute to improving infection prevention and control as well as a more rational use of antibiotics, thus increasing the quality and safety of care.

[Recording of SARS-CoV-2 laboratory tests in Germany]. / Erfassung der Labortestungen auf SARS-CoV-2 in Deutschland.

The collection of data on SARS-CoV­2 tests is central to the assessment of the infection rate in the context of the COVID-19 pandemic. At the Robert Koch Institute (RKI), data collected from various laboratory data recording systems are consolidated. First, this article aims to exemplify significant aspects regarding test procedures. Subsequently the different systems for recording laboratory tests are described and test numbers from the RKI test laboratory query and the laboratory-based SARS-CoV­2 surveillance as well as accounting data from the Association of Statutory Health Insurance Physicians for SARS-CoV­2 laboratory tests are shown.Early in the pandemic, the RKI test laboratory query and the laboratory-based SARS-CoV­2 surveillance became available and able to evaluate data on performed tests and test capacities. By recording the positive and negative test results, statements about the total number of tests and the proportion of positive test rates can be made. While the aggregate test numbers are largely representative nationwide, they are not always representative at the state and district level. The billing data of the Association of Statutory Health Insurance Physicians can complement the laboratory data afterwards. In addition, it can provide a retrospective assessment of the total number of SARS-CoV­2 numbers in Germany, because the services provided by statutory health insurers (around 85% of the population in Germany) are included. The various laboratory data recording systems complement one another and the evaluations flow into the recommended measures for the pandemic response.

Application of a new methodology and R package reveals a high burden of healthcare-associated infections (HAI) in Germany compared to the average in the European Union/European Economic Area, 2011 to 2012.

BackgroundHealthcare-associated infections (HAIs) pose a major challenge to health systems. Burden of disease estimations in disability-adjusted life years (DALYs) are useful for comparing and ranking HAIs.AimTo estimate the number of five common HAIs, their attributable number of deaths and burden for Germany.MethodsWe developed a new method and R package that builds on the approach used by the Burden of Communicable Diseases in Europe (BCoDE) project to estimate the burden of HAIs for individual countries. We used data on healthcare-associated Clostridioides difficile infection, healthcare-associated pneumonia, healthcare-associated primary bloodstream infection, healthcare-associated urinary tract infection and surgical-site infection, which were collected during the point prevalence survey of HAIs in European acute-care hospitals between 2011 and 2012.ResultsWe estimated 478,222 (95% uncertainty interval (UI): 421,350-537,787) cases for Germany, resulting in 16,245 (95% UI: 10,863-22,756) attributable deaths and 248,920 (95% UI: 178,693-336,239) DALYs. Despite the fact that Germany has a relatively low hospital prevalence of HAIs compared with the European Union/European Economic Area (EU/EEA) average, the burden of HAIs in Germany (308.2 DALYs/100,000 population; 95% UI: 221.2-416.3) was higher than the EU/EEA average (290.0 DALYs/100,000 population; 95% UI: 214.9-376.9). Our methodology is applicable to other countries in or outside of the EU/EEA. An R package is available from https://CRAN.R-project.org/package=BHAI.ConclusionThis is the first study to estimate the burden of HAIs in DALYs for Germany. The large number of hospital beds may be a contributing factor for a relatively high burden of HAIs in Germany. Further focus on infection prevention control, paired with reduction of avoidable hospital stays, is needed to reduce the burden of HAIs in Germany.

TT-seq captures enhancer landscapes immediately after T-cell stimulation.

To monitor transcriptional regulation in human cells, rapid changes in enhancer and promoter activity must be captured with high sensitivity and temporal resolution. Here, we show that the recently established protocol TT-seq ("transient transcriptome sequencing") can monitor rapid changes in transcription from enhancers and promoters during the immediate response of T cells to ionomycin and phorbol 12-myristate 13-acetate (PMA). TT-seq maps eRNAs and mRNAs every 5 min after T-cell stimulation with high sensitivity and identifies many new primary response genes. TT-seq reveals that the synthesis of 1,601 eRNAs and 650 mRNAs changes significantly within only 15 min after stimulation, when standard RNA-seq does not detect differentially expressed genes. Transcription of enhancers that are primed for activation by nucleosome depletion can occur immediately and simultaneously with transcription of target gene promoters. Our results indicate that enhancer transcription is a good proxy for enhancer regulatory activity in target gene activation, and establish TT-seq as a tool for monitoring the dynamics of enhancer landscapes and transcription programs during cellular responses and differentiation.

Simultaneous characterization of sense and antisense genomic processes by the double-stranded hidden Markov model.

Hidden Markov models (HMMs) have been extensively used to dissect the genome into functionally distinct regions using data such as RNA expression or DNA binding measurements. It is a challenge to disentangle processes occurring on complementary strands of the same genomic region. We present the double-stranded HMM (dsHMM), a model for the strand-specific analysis of genomic processes. We applied dsHMM to yeast using strand specific transcription data, nucleosome data, and protein binding data for a set of 11 factors associated with the regulation of transcription.The resulting annotation recovers the mRNA transcription cycle (initiation, elongation, termination) while correctly predicting strand-specificity and directionality of the transcription process. We find that pre-initiation complex formation is an essentially undirected process, giving rise to a large number of bidirectional promoters and to pervasive antisense transcription. Notably, 12% of all transcriptionally active positions showed simultaneous activity on both strands. Furthermore, dsHMM reveals that antisense transcription is specifically suppressed by Nrd1, a yeast termination factor.

Healthcare-associated pneumonia in acute care hospitals in European Union/European Economic Area countries: an analysis of data from a point prevalence survey, 2011 to 2012.

An aim of the ECDC point prevalence survey (PPS) in European Union/European Economic Area acute care hospitals was to acquire standardised healthcare-associated infections (HAI) data. We analysed one of the most common HAIs in the ECDC PPS, healthcare-associated pneumonia (HAP). Standardised HAI case definitions were provided and countries were advised to recruit nationally representative subsets of hospitals. We calculated 95% confidence intervals (CIs) around prevalence estimates and adjusted for clustering at hospital level. Of 231,459 patients in the survey, 2,902 (1.3%; 95% CI: 1.2-1.3) fulfilled the case definition for a HAP. HAPs were most frequent in intensive care units (8.1%; 95% CI: 7.4-8.9) and among patients intubated on the day of the survey (15%; 95% CI: 14-17; n = 737 with HAP). The most frequently reported microorganism was Pseudomonas aeruginosa (17% of 1,403 isolates), followed by Staphylococcus aureus (12%) and Klebsiella spp. (12%). Antimicrobial resistance was common among isolated microorganisms. The most frequently prescribed antimicrobial group was penicillins, including combinations with beta-lactamase inhibitors. HAPs occur regularly among intubated and non-intubated patients, with marked differences between medical specialities. HAPs remain a priority for preventive interventions, including surveillance. Our data provide a reference for future prevalence of HAPs at various settings.

Annotation of genomics data using bidirectional hidden Markov models unveils variations in Pol II transcription cycle.

DNA replication, transcription and repair involve the recruitment of protein complexes that change their composition as they progress along the genome in a directed or strand-specific manner. Chromatin immunoprecipitation in conjunction with hidden Markov models (HMMs) has been instrumental in understanding these processes, as they segment the genome into discrete states that can be related to DNA-associated protein complexes. However, current HMM-based approaches are not able to assign forward or reverse direction to states or properly integrate strand-specific (e.g., RNA expression) with non-strand-specific (e.g., ChIP) data, which is indispensable to accurately characterize directed processes. To overcome these limitations, we introduce bidirectional HMMs which infer directed genomic states from occupancy profiles de novo. Application to RNA polymerase II-associated factors in yeast and chromatin modifications in human T cells recovers the majority of transcribed loci, reveals gene-specific variations in the yeast transcription cycle and indicates the existence of directed chromatin state patterns at transcribed, but not at repressed, regions in the human genome. In yeast, we identify 32 new transcribed loci, a regulated initiation-elongation transition, the absence of elongation factors Ctk1 and Paf1 from a class of genes, a distinct transcription mechanism for highly expressed genes and novel DNA sequence motifs associated with transcription termination. We anticipate bidirectional HMMs to significantly improve the analyses of genome-associated directed processes.

Modelling and simulating generic RNA-Seq experiments with the flux simulator.

High-throughput sequencing of cDNA libraries constructed from cellular RNA complements (RNA-Seq) naturally provides a digital quantitative measurement for every expressed RNA molecule. Nature, impact and mutual interference of biases in different experimental setups are, however, still poorly understood-mostly due to the lack of data from intermediate protocol steps. We analysed multiple RNA-Seq experiments, involving different sample preparation protocols and sequencing platforms: we broke them down into their common--and currently indispensable--technical components (reverse transcription, fragmentation, adapter ligation, PCR amplification, gel segregation and sequencing), investigating how such different steps influence abundance and distribution of the sequenced reads. For each of those steps, we developed universally applicable models, which can be parameterised by empirical attributes of any experimental protocol. Our models are implemented in a computer simulation pipeline called the Flux Simulator, and we show that read distributions generated by different combinations of these models reproduce well corresponding evidence obtained from the corresponding experimental setups. We further demonstrate that our in silico RNA-Seq provides insights about hidden precursors that determine the final configuration of reads along gene bodies; enhancing or compensatory effects that explain apparently controversial observations can be observed. Moreover, our simulations identify hitherto unreported sources of systematic bias from RNA hydrolysis, a fragmentation technique currently employed by most RNA-Seq protocols.

Joint Bayesian inference of condition-specific miRNA and transcription factor activities from combined gene and microRNA expression data.

MOTIVATION: There have been many successful experimental and bioinformatics efforts to elucidate transcription factor (TF)-target networks in several organisms. For many organisms, these annotations are complemented by miRNA-target networks of good quality. Attempts that use these networks in combination with gene expression data to draw conclusions on TF or miRNA activity are, however, still relatively sparse. RESULTS: In this study, we propose Bayesian inference of regulation of transcriptional activity (BIRTA) as a novel approach to infer both, TF and miRNA activities, from combined miRNA and mRNA expression data in a condition specific way. That means our model explains mRNA and miRNA expression for a specific experimental condition by the activities of certain miRNAs and TFs, hence allowing for differentiating between switches from active to inactive (negative switch) and inactive to active (positive switch) forms. Extensive simulations of our model reveal its good prediction performance in comparison to other approaches. Furthermore, the utility of BIRTA is demonstrated at the example of Escherichia coli data comparing aerobic and anaerobic growth conditions, and by human expression data from pancreas and ovarian cancer. AVAILABILITY AND IMPLEMENTATION: The method is implemented in the R package birta, which is freely available for Bio-conductor (>=2.10) on http://www.bioconductor.org/packages/release/bioc/html/birta.html.

Measurement of genome-wide RNA synthesis and decay rates with Dynamic Transcriptome Analysis (DTA).

Standard transcriptomics measures total cellular RNA levels. Our understanding of gene regulation would be greatly improved if we could measure RNA synthesis and decay rates on a genome-wide level. To that end, the Dynamic Transcriptome Analysis (DTA) method has been developed. DTA combines metabolic RNA labeling with standard transcriptomics to measure RNA synthesis and decay rates in a precise and non-perturbing manner. Here, we present the open source R/Bioconductor software package DTA. It implements all required bioinformatics steps that allow the accurate absolute quantification and comparison of RNA turnover.

Dynamic transcriptome analysis measures rates of mRNA synthesis and decay in yeast.

To obtain rates of mRNA synthesis and decay in yeast, we established dynamic transcriptome analysis (DTA). DTA combines non-perturbing metabolic RNA labeling with dynamic kinetic modeling. DTA reveals that most mRNA synthesis rates are around several transcripts per cell and cell cycle, and most mRNA half-lives range around a median of 11 min. DTA can monitor the cellular response to osmotic stress with higher sensitivity and temporal resolution than standard transcriptomics. In contrast to monotonically increasing total mRNA levels, DTA reveals three phases of the stress response. During the initial shock phase, mRNA synthesis and decay rates decrease globally, resulting in mRNA storage. During the subsequent induction phase, both rates increase for a subset of genes, resulting in production and rapid removal of stress-responsive mRNAs. During the recovery phase, decay rates are largely restored, whereas synthesis rates remain altered, apparently enabling growth at high salt concentration. Stress-induced changes in mRNA synthesis rates are predicted from gene occupancy with RNA polymerase II. DTA-derived mRNA synthesis rates identified 16 stress-specific pairs/triples of cooperative transcription factors, of which seven were known. Thus, DTA realistically monitors the dynamics in mRNA metabolism that underlie gene regulatory systems.

Supervised learning using routine surveillance data improves outbreak detection of Salmonella and Campylobacter infections in Germany.

The early detection of infectious disease outbreaks is a crucial task to protect population health. To this end, public health surveillance systems have been established to systematically collect and analyse infectious disease data. A variety of statistical tools are available, which detect potential outbreaks as abberations from an expected endemic level using these data. Here, we present supervised hidden Markov models for disease outbreak detection, which use reported outbreaks that are routinely collected in the German infectious disease surveillance system and have not been leveraged so far. This allows to directly integrate labeled outbreak data in a statistical time series model for outbreak detection. We evaluate our model using real Salmonella and Campylobacter data, as well as simulations. The proposed supervised learning approach performs substantially better than unsupervised learning and on par with or better than a state-of-the-art approach, which is applied in multiple European countries including Germany.

Geographical differences of carbapenem non-susceptible Enterobacterales and Acinetobacter spp. in Germany from 2017 to 2019.

BACKGROUND: Since May 2016, infection and colonisation with carbapenem non-susceptible Acinetobacter spp. (CRA) and Enterobacterales (CRE) have to be notified to health authorities in Germany. The aim of our study was to assess the epidemiology of CRA and CRE from 2017 to 2019 in Germany, to identify risk groups and to determine geographical differences of CRA and CRE notifications. METHODS: Cases were notified from laboratories to local public health authorities and forwarded to state and national level. Non-susceptibility was defined as intermediate or resistant to ertapenem, imipenem, or meropenem excluding intrinsic bacterial resistance or the detection of a carbapenemase gene. We analysed CRA and CRE notifications from 2017, 2018 and 2019 per 100,000 inhabitants (notification incidence), regarding their demographic, clinical and laboratory information. The effect of regional hospital-density on CRA and CRE notification incidence was estimated using negative binomial regression. RESULTS: From 2017 to 2019, 2278 CRA and 12,282 CRE cases were notified in Germany. CRA and CRE cases did not differ regarding demographic and clinical information, e.g. proportion infected. The notification incidence of CRA declined slightly from 0.95 in 2017 to 0.86 in 2019, whereas CRE increased from 4.23 in 2017 to 5.72 in 2019. The highest CRA and CRE notification incidences were found in the age groups above 70 years. Infants below 1 year showed a high CRE notification incidence, too. Notification incidences varied between 0.10 and 2.86 for CRA and between 1.49 and 9.99 for CRE by federal state. The notification incidence of CRA and CRE cases increased with each additional hospital per district. CONCLUSION: The notification incidence of CRA and CRE varied geographically and was correlated with the number of hospitals.The results support the assumption that hospitals are the main driver for higher CRE and CRA incidence. Preventive strategies and early control measures should target older age groups and newborns and areas with a high incidence.

Germany's Burden of Disease of Bloodstream Infections Due to Vancomycin-Resistant Enterococcus faecium between 2015-2020.

In Germany, there is an increasing amount of vancomycin-resistant Enterococcus faecium (VREfm) isolates in bloodstream infections (BSIs); however, estimates on recent incidences and disease burden are missing. We aim to estimate the incidence and calculate the annual disease burden in disease-adjusted life years (DALYs) for BSIs due to VREfm in Germany between 2015 and 2020 to support informed decision-making in the field of antimicrobial resistance (AMR). We used the Antibiotic Resistance Surveillance (ARS) system data to obtain incidence estimates. The estimated incidences were used in the Burden of Communicable Disease in Europe (BCoDE) toolkit to calculate the attributable DALYs. A total of 3417 VREfm blood culture-positive isolates were observed within ARS. The estimated incidence of VREfm-BSIs per 100,000 inhabitants increased from 1.4 (95% Uncertainty Interval [UI]: 0.8−1.9) in 2015 to 2.9 (95% UI: 2.4−3.3) in 2020. The estimated burden, expressed in DALYs per 100,000 inhabitants, increased from 8.5 (95% UI: 7.3−9.7; YLD = 0.9, YLL = 7.6) in 2015 to 15.6 (95% UI: 14.6−16.6; YLD = 1.6, YLL = 14) in 2020. The most affected groups within the observed period are the 65−69-year-old males with 262.9 DALYs per 100,000 inhabitants, and in the younger age groups (<30 years), the under-one-year-old with 43.1 DALYs per 100,000 inhabitants and 34.5 DALYs for male and female, respectively. The increasing DALYs of BSIs due to VREfm require targeted prevention and control measures to address their unequal distribution across gender and age, especially for older hospitalized patients, neonates, and infants in Germany.

Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017.

Recent findings on Antibiotic Resistance (AR) have brought renewed attention to the comparison of data on AR from human and animal sectors. This is however a major challenge since the data is not harmonized. This study performs a comparative analysis of data on resistance combinations in Escherichia coli (E. coli) from different routine surveillance and monitoring systems for human and different animal populations in Germany. Data on E. coli isolates were collected between 2014 and 2017 from human clinical isolates, non-clinical animal isolates from food-producing animals and food, and clinical animal isolates from food-producing and companion animals from national routine surveillance and monitoring for AR in Germany. Sixteen possible resistance combinations to four antibiotics-ampicillin, cefotaxime, ciprofloxacin and gentamicin-for these populations were used for hierarchical clustering (Euclidian and average distance). All analyses were performed with the software R 3.5.1 (Rstudio 1.1.442). Data of 333,496 E. coli isolates and forty-one different human and animal populations were included in the cluster analysis. Three main clusters were detected. Within these three clusters, all human populations (intensive care unit (ICU), general ward and outpatient care) showed similar relative frequencies of the resistance combinations and clustered together. They demonstrated similarities with clinical isolates from different animal populations and most isolates from pigs from both non-clinical and clinical isolates. Isolates from healthy poultry demonstrated similarities in relative frequencies of resistance combinations and clustered together. However, they clustered separately from the human isolates. All isolates from different animal populations with low relative frequencies of resistance combinations clustered together. They also clustered separately from the human populations. Cluster analysis has been able to demonstrate the linkage among human isolates and isolates from various animal populations based on the resistance combinations. Further analyses based on these findings might support a better one-health approach for AR in Germany.

Starr: Simple Tiling ARRay analysis of Affymetrix ChIP-chip data.

BACKGROUND: Chromatin immunoprecipitation combined with DNA microarrays (ChIP-chip) is an assay used for investigating DNA-protein-binding or post-translational chromatin/histone modifications. As with all high-throughput technologies, it requires thorough bioinformatic processing of the data for which there is no standard yet. The primary goal is to reliably identify and localize genomic regions that bind a specific protein. Further investigation compares binding profiles of functionally related proteins, or binding profiles of the same proteins in different genetic backgrounds or experimental conditions. Ultimately, the goal is to gain a mechanistic understanding of the effects of DNA binding events on gene expression. RESULTS: We present a free, open-source R/Bioconductor package Starr that facilitates comparative analysis of ChIP-chip data across experiments and across different microarray platforms. The package provides functions for data import, quality assessment, data visualization and exploration. Starr includes high-level analysis tools such as the alignment of ChIP signals along annotated features, correlation analysis of ChIP signals with complementary genomic data, peak-finding and comparative display of multiple clusters of binding profiles. It uses standard Bioconductor classes for maximum compatibility with other software. Moreover, Starr automatically updates microarray probe annotation files by a highly efficient remapping of microarray probe sequences to an arbitrary genome. CONCLUSION: Starr is an R package that covers the complete ChIP-chip workflow from data processing to binding pattern detection. It focuses on the high-level data analysis, e.g., it provides methods for the integration and combined statistical analysis of binding profiles and complementary functional genomics data. Starr enables systematic assessment of binding behaviour for groups of genes that are alingned along arbitrary genomic features.

Accurate Promoter and Enhancer Identification in 127 ENCODE and Roadmap Epigenomics Cell Types and Tissues by GenoSTAN.

Accurate maps of promoters and enhancers are required for understanding transcriptional regulation. Promoters and enhancers are usually mapped by integration of chromatin assays charting histone modifications, DNA accessibility, and transcription factor binding. However, current algorithms are limited by unrealistic data distribution assumptions. Here we propose GenoSTAN (Genomic STate ANnotation), a hidden Markov model overcoming these limitations. We map promoters and enhancers for 127 cell types and tissues from the ENCODE and Roadmap Epigenomics projects, today's largest compendium of chromatin assays. Extensive benchmarks demonstrate that GenoSTAN generally identifies promoters and enhancers with significantly higher accuracy than previous methods. Moreover, GenoSTAN-derived promoters and enhancers showed significantly higher enrichment of complex trait-associated genetic variants than current annotations. Altogether, GenoSTAN provides an easy-to-use tool to define promoters and enhancers in any system, and our annotation of human transcriptional cis-regulatory elements constitutes a rich resource for future research in biology and medicine.