[Bacterial zoonoses of public health importance in Germany-incidence, distribution, and modes of transmission]. / Bakterielle Zoonosen mit Bedeutung für den öffentlichen Gesundheitsschutz in Deutschland ­ Vorkommen, Verbreitung und Übertragungswege.

Bacterial zoonotic pathogens are often the cause of diseases, sometimes with severe outcomes. They are mutually transferable between animals (both wild and domestic) and humans. The transmission paths are very variable and include oral intake via food, respiratory infection via droplets and aerosols, or infections via vectors such as tick bites or rodent contact. Furthermore, the emergence and spread of antibiotic-resistant bacterial pathogens is of paramount public health concern.The likelihood of further spread is influenced by various factors. These include the increase in international trade, the endangerment of animal habitats, and the increasingly closer contact between humans and wild animals. Additionally, changes in livestock and climate change may also contribute. Therefore, research into zoonoses serves to protect human and animal health and is of particular social, political, and economic importance.The aim of this review article is to present the range of infectious diseases caused by bacterial zoonotic pathogens in order to provide a better understanding of the important work in public health services, animal health services, and food safety control. The different transmission routes, epidemic potentials, and epidemiological measures of the exemplary selected diseases show the challenges for the public health system to monitor and control the spread of these bacterial pathogens in order to protect the population from disease.

A Joint Regional Analysis of Resistance Combinations in Escherichia coli in Humans and Different Food-Producing Animal Populations in Germany Between 2014 and 2017.

A joint comparative regional analysis of different resistance combinations across human and veterinary medicine has not been previously conducted in Germany. This study analyses 16 resistance combinations from four antibiotics in E. coli from different human and food-producing animal populations in three German regions: East, North West and South West. The E. coli data were collected from the three national surveillance and monitoring systems for antimicrobial resistance (AMR) bacteria in humans (ARS), food-safety (Zoonosis Monitoring) and animal pathogens (GERM-Vet) from January 2014 to December 2017. Analyses were performed using cluster analysis (hierarchical clustering, average linkage) in R. We included data from 537,215 E. coli isolates from human clinical isolates, from clinical as well as non-clinical isolates from food-producing animals and from food. The majority of the data originated from the North West region. There were two main clusters built on 54 different human and animal populations. We observed close similarities of resistance combinations in human isolates from the different regions within the same human populations from outpatient cares, general wards and ICUs. These resistance combinations clustered separately from non-clinical isolates from broilers, turkeys, cattle and pigs; except for some of clinical isolates from these populations which clustered closely to isolates from human populations. Frequently, the resistance combinations in E. coli isolates from farms clustered closely to the resistance combinations in isolates from slaughterhouses from broilers and turkeys over all regions. However, the resistance combinations in E. coli isolates from retail meat populations tended to cluster separately within their respective populations in between all regions.

SARS-CoV-2 outbreaks in hospitals and long-term care facilities in Germany: a national observational study.

BACKGROUND: Outbreaks of coronavirus disease (COVID-19) in hospitals and long-term care facilities (LTCFs) pose serious public health threats. We analysed how frequency and size of SARS-CoV-2 outbreaks in hospitals and LTCFs have altered since the beginning of the pandemic, in particular since the start of the vaccination campaign. METHODS: We used mandatory notification data on SARS-CoV-2 cases in Germany and stratified by outbreak cases in hospitals and LTCFs. German vaccination coverage data were analysed. We studied the association of the occurrence of SARS-CoV-2 outbreaks and outbreak cases with SARS-CoV-2 cases in Germany throughout the four pandemic waves. We built also counterfactual scenarios with the first pandemic wave as the baseline. FINDINGS: By 21 September 2021, there were 4,147,387 SARS-CoV-2 notified cases since March 2020. About 20% of these cases were reported as being related to an outbreak, with 1% of the cases in hospitals and 4% in LTCFs. The median number of outbreak cases in the different phases was smaller (≤5) in hospitals than in LTCFs (>10). In the first and second pandemic waves, we observed strong associations in both facility types between SARS-CoV-2 outbreak cases and total number of notified SARS-CoV-2 cases. However, during the third pandemic wave we observed a decline in outbreak cases in both facility types and only a weak association between outbreak cases and all cases. INTERPRETATION: The vaccination campaign and non-pharmaceutical interventions have been able to protect vulnerable risk groups in hospitals and LTCFs. FUNDING: No specific funding.

Comparison of MICs in Escherichia coli isolates from human health surveillance with MICs obtained for the same isolates by broth microdilution.

OBJECTIVES: Human health surveillance and food safety monitoring systems use different antimicrobial susceptibility testing (AST) methods. In this study, we compared the MICs of Escherichia coli isolates provided by these methods. METHODS: E. coli isolates (n = 120) from human urine samples and their MICs were collected from six medical laboratories that used automated AST methods based on bacterial growth kinetic analyses. These isolates were retested using broth microdilution, which is used by the food safety monitoring system. The essential and categorical agreements (EA and CA), very major errors (VME), major errors (ME) and minor errors (mE) for these two methods were calculated for 11 antibiotics using broth microdilution as a reference. For statistical analysis, clinical breakpoints provided by EUCAST were used. RESULTS: Five study laboratories used VITEK®2 and one MicroScan (Walkaway Combo Panel). Out of 120 isolates, 118 isolates (98.3%) were confirmed as E. coli. The 99 E. coli isolates from five study laboratories that used VITEK®2 showed high proportions of EA and CA with full agreements for gentamicin, meropenem, imipenem and ertapenem. Additionally, 100% CA was also observed in cefepime. Few VME (0.5%), ME (1.9%) and mE (1.5%) were observed across all antibiotics. One VME for ceftazidime (7.1%) and 12 MEs for ampicillin (29.4%), cefotaxime (2.4%), ciprofloxacin (3.2%), tigecycline (1.5%) and trimethoprim (22.2%) were detected. CONCLUSIONS: MICs from E. coli isolates produced by VITEK®2 were similar to those determined by broth microdilution. These results will be valuable for comparative analyses of resistance data from human health surveillance and food safety monitoring systems.

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.

The epidemiology of carbapenem-non-susceptible Acinetobacter species in Europe: analysis of EARS-Net data from 2013 to 2017.

BACKGROUND: Due to limited therapeutic options and their association with high mortality and morbidity, carbapenem-non-susceptible Acinetobacter spp. (CNA) are of significant public health importance. This study aimed to describe current epidemiological trends of CNA proportions in Europe and to identify factors that are associated with carbapenem non-susceptibility of isolates from patients with invasive Acinetobacter spp. infections. METHODS: Data from routine carbapenem susceptibility testing of 18,412 invasive clinical Acinetobacter spp. isolates from 30 European countries in 2013-2017 were analysed using descriptive statistical analyses and uni- and multivariable regression analyses. These data were obtained from the European Antimicrobial Resistance Surveillance Network (EARS-Net). RESULTS: The population-weighted mean proportion of carbapenem-non-susceptible Acinetobacter spp. in Europe is 35.6% (95% confidence interval [CI] 29.7-42.0%). With CNA proportions of 75.5% (95% CI 71.2-79.4%) and 71.5% (95% CI 66.7-75.9%) the burden of CNA is particularly high in Southern and Eastern European regions. In contrast, Northern and Western European regions recorded CNA proportions of 2.8% (95% CI 1.2-6.0%) and 6.3% (95% CI 4.5-8.9%), respectively. Population-weighted mean CNA proportions are especially high in Acinetobacter spp. isolates from intensive care units (54.0% [95% CI 47.6-60.3%]). Male gender, age above 20 years and ICU admission were identified as independent factors associated with an increased likelihood of CNA. CONCLUSION: The burden of carbapenem-non-susceptible Acinetobacter spp. is particularly high in Southern and Eastern Europe. There is a risk that resistance could spread to other parts of Europe. Therefore, increased efforts in infection control and antibiotic stewardship, particularly in Intensive Care Units, are necessary to combat the spread of CNA in Europe.

Recombinant production of A1S_0222 from Acinetobacter baumannii ATCC 17978 and confirmation of its DNA-(adenine N6)-methyltransferase activity.

Acinetobacter baumannii appears as an often multidrug-resistant nosocomial pathogen in hospitals worldwide. Its remarkable persistence in the hospital environment is probably due to intrinsic and acquired resistance to disinfectants and antibiotics, tolerance to desiccation stress, capability to form biofilms, and is possibly facilitated by surface-associated motility. Our attempts to elucidate surface-associated motility in A. baumannii revealed a mutant inactivated in a putative DNA-(adenine N6)-methyltransferase, designated A1S_0222 in strain ATCC 17978. We recombinantly produced A1S_0222 as a glutathione S-transferase (GST) fusion protein and purified it to near homogeneity through a combination of GST affinity chromatography, cation exchange chromatography and PD-10 desalting column. Furthermore we demonstrate A1S_0222-dependent adenine methylation at a GAATTC site. We propose the name AamA (Acinetobacteradenine methyltransferase A) in addition to the formal names M.AbaBGORF222P/M.Aba17978ORF8565P. Small angle X-ray scattering (SAXS) revealed that the protein is monomeric and has an extended and likely two-domain shape in solution.