Environmental factors associated with the prevalence of ESBL/AmpC-producing Escherichia coli in wild boar (Sus scrofa).

Antimicrobial resistances (AMR) in bacteria, such as ESBL/AmpC-producing E. coli, are a burden to human and animal health. This burden is mainly driven by the consumption and release of antimicrobial substances into the environment. The pollution and contamination of habitats by AMR in bacteria and antimicrobial substances can lead to the transmission of bacterial AMR to wildlife. Therefore, it is necessary to understand the transmission cycle of antibiotics and resistant bacteria between humans, and animals as well as their occurrences in the environment. Environmental factors associated with the occurrence of bacterial AMR in wildlife can lead to a better understanding of the distribution of bacterial AMR in humans and animals using One Health approaches. Here, we analyzed data gathered in the framework of the German zoonoses monitoring program in 2016 and 2020 using spatiotemporal statistics to identify relevant environmental factors (e.g., livestock density, climatic variables, and human density) in association with the spatial distribution of ESBL/AmpC-producing E. coli. For this purpose, we developed a generic data integration and analysis pipeline to link spatially explicit environmental factors to the monitoring data. Finally, we built a binomial generalized linear mixed model (GLMM) to determine the factors associated with the spatial distribution of ESBL/AmpC-producing E. coli. In 2016 and 2020, 807 fecal samples from hunted wild boar (Sus scrofa L.) were randomly taken in 13 federal states and selectively analyzed for ESBL/AmpC-producing E. coli. Forty-eight isolates were identified in 12 German federal states, with an overall prevalence of 6%. We observed an almost three times higher probability of ESBL/AmpC-producing E. coli isolates in wild boar in counties with high cattle densities (OR = 2.57, p ≤ 0.01). Furthermore, we identified a seasonal effect in areas with high precipitation during the off-hunting seasons (OR = 2.78, p = 0.025) and low precipitation throughout the years (OR = 0.42, p = 0.025). However, due to the low amount of identified isolates, confidence intervals were wide, indicating a high level of uncertainty. This suggests that further studies on smaller scales need to be conducted with multiannual data and improved metadata, e.g., on the location, the hunting procedure, and species characteristics to be collected during field sampling.

One Health Consensus Report Annotation Checklist (OH-CRAC): A cross-sector checklist to support harmonized annotation of surveillance data in reports.

To facilitate cross-sector integration of surveillance data it is necessary to improve and harmonize the meta-information provided in surveillance data reports. Cross-sector integration of surveillance results in sector-specific reports is frequently difficult as reports with a focus on a single sector often lack aspects of the relevant meta-information necessary to clarify the surveillance context. Such reporting deficiencies reduce the value of surveillance reports to the One Health community. The One Health Consensus Report Annotation Checklist (OH-CRAC), described in this paper along with potential application scenarios, was developed to improve the current practice of annotating data presented in surveillance data reports. It aims to provide guidance to researchers and reporting officers on what meta-information should be collected and provided to improve the completeness and transparency of surveillance data reports. The OH-CRAC can be adopted by all One Health-related sectors and due to its cross-sector design, it supports the mutual mapping of surveillance meta-information from sector-specific surveillance reports on federal, national and international levels. To facilitate the checklist completion, OH-CRAC is also available as an online resource that allows the collection of surveillance meta-information in an easy and user-friendly manner. Completed OH-CRAC checklists can be attached as annexes to the corresponding surveillance data reports or even to individual data files regardless of the data source. In this way, reports and data become better interpretable, usable and comparable to information from other sectors, improving their value for all surveillance actors and providing a better foundation for advice to risk managers.

Stability of Hepatitis E Virus After Drying on Different Surfaces.

The hepatitis E virus (HEV) causes acute and chronic hepatitis in humans. The zoonotic HEV genotype 3 is mainly transmitted by consumption of contaminated food produced from infected animals. However, transmission via contaminated surfaces has also to be considered. Here, the genotype 3c strain 47832c was dried on steel, wood, plastics and ceramics, stored at 23 °C or 3 °C for up to 8 weeks and remaining infectivity was titrated on cell culture. During the drying process, only a mean 0.2 log10 decrease of HEV infectivity was observed. At 23 °C, remaining infectious virus was detected until week 4 on most surfaces, but HEV was completely inactivated (> 4 log10 decrease) after 8 weeks. At 3 °C, HEV was detectable up to 8 weeks on most surfaces, with an average 2.3 log10 decrease. HEV showed the highest stability on plastics, which was lower on ceramics and steel, and lowest on wood. The addition of bovine serum albumin mimicking high protein load had only a slight stabilizing effect. In conclusion, HEV shows a high stability against drying and subsequent storage on different surfaces. Strict application of hygienic measures during food production is therefore crucial in order to prevent HEV persistence on surfaces and subsequent cross-contamination.

A one health glossary to support communication and information exchange between the human health, animal health and food safety sectors.

Collaboration across sectors, disciplines and countries is a key concept to achieve the overarching One Health (OH) objective for better human, animal and environmental health. Differences in terminology and interpretation of terms are still a significant hurdle for cross-sectoral information exchange and collaboration within the area of OH including One Health Surveillance (OHS). The development of the here described glossary is a collaborative effort of three projects funded within the One Health European Joint Programme (OHEJP). We describe the infrastructure of the OHEJP Glossary, as well as the methodology to create such a cross-sectoral web resource in a collaborative manner. The new OHEJP Glossary allows OH actors to identify terms with different or shared interpretation across sectors. Being aware of such differences in terminology will help overcome communication hurdles in the future and consequently support collaboration and a more inclusive development of OHS. The OHEJP Glossary was implemented as a web-based, user-friendly and searchable infrastructure that complies with the Findable, Accessible, Interoperable, Reusable (FAIR) data principles. Maintenance, enrichment and quality control of the OHEJP Glossary is supported through a flexible and updatable curation infrastructure. This increases the uptake potential and exploitation of the OHEJP Glossary by other OH initiatives or tools and services.

One Health Surveillance Codex: promoting the adoption of One Health solutions within and across European countries.

Cross-sector communication, collaboration and knowledge exchange are still significant challenges for practical adoption of the One Health paradigm. To address these needs the "One Health Surveillance Codex" (OHS Codex) was established to provide a framework for the One Health community to continuously share practical solutions (e.g. tools, technical resources, guidance documents and experiences) applicable for national and international stakeholders from different One Health Surveillance sectors. Currently, the OHS Codex provides a number of resources that support the adoption of the OH paradigm in areas linked to the harmonization and interpretation of surveillance data. The OHS Codex framework comprises four high-level "action" principles, which respectively support collaboration, knowledge exchange, data interoperability, and dissemination. These principles match well with priority areas identified in the "Tripartite Guide to Addressing Zoonotic Diseases in Countries" published by WHO, FAO and OIE. Within each of the four principles, the OHS Codex provides a collection of useful resources as well as pointers to success stories for the application of these resources. As the OHS Codex is designed as an open community framework, it will continuously evolve and adapt to the needs of the OH community in the future.

Effect of Sodium Chloride, Sodium Nitrite and Sodium Nitrate on the Infectivity of Hepatitis E Virus.

Hepatitis E virus (HEV) infection can cause acute and chronic hepatitis in humans. The zoonotic HEV genotype 3, which is highly prevalent in Europe, is mainly transmitted by consumption of raw meat and raw meat products produced from infected pigs or wild boars. High salt concentrations represent an important measure to preserve meat products and to inactivate foodborne pathogens. Here, an HEV preparation in phosphate-buffered saline (PBS) was subjected to different salt concentrations and the remaining infectivity was measured in a cell culture assay. Treatments with up to 20% sodium chloride for 24 h at 23 °C, with and without addition of 0.015% sodium nitrite or 0.03% sodium nitrate, did not lead to virus inactivation as compared to PBS only. Conditions usually applied for short-term and long-term fermented raw sausages were simulated by incubation at 22 °C for up to 6 days and at 16 °C for up to 8 weeks, respectively. Only 2% sodium chloride with 0.015% sodium nitrite showed a weak (< 1 log10), but significant, infectivity reduction after 2 and 4 days as compared to PBS only. Addition of 2% sodium chloride and 0.03% sodium nitrate showed a slight, but not significant, decrease in infectivity after 2 and 8 weeks as compared to PBS only. In conclusion, HEV is highly stable at high salt concentrations and at salt conditions usually applied to preserve raw meat products.

STEM: An Open Source Tool for Disease Modeling.

The Spatiotemporal Epidemiologic Modeler (STEM) is an open source software project supported by the Eclipse Foundation and used by a global community of researchers and public health officials working to track and, when possible, control outbreaks of infectious disease in human and animal populations. STEM is not a model or a tool designed for a specific disease; it is a flexible, modular framework supporting exchange and integration of community models, reusable plug-in components, and denominator data, available to researchers worldwide at www.eclipse.org/stem. A review of multiple projects illustrates its capabilities. STEM has been used to study variations in transmission of seasonal influenza in Israel by strains; evaluate social distancing measures taken to curb the H1N1 epidemic in Mexico City; study measles outbreaks in part of London and inform local policy on immunization; and gain insights into H7N9 avian influenza transmission in China. A multistrain dengue fever model explored the roles of the mosquito vector, cross-strain immunity, and antibody response in the frequency of dengue outbreaks. STEM has also been used to study the impact of variations in climate on malaria incidence. During the Ebola epidemic, a weekly conference call supported the global modeling community; subsequent work modeled the impact of behavioral change and tested disease reintroduction via animal reservoirs. Work in Germany tracked salmonella in pork from farm to fork; and a recent doctoral dissertation used the air travel feature to compare the potential threats posed by weaponizing infectious diseases. Current projects include work in Great Britain to evaluate control strategies for parasitic disease in sheep, and in Germany and Hungary, to validate the model and inform policy decisions for African swine fever. STEM Version 4.0.0, released in early 2019, includes tools used in these projects and updates technical aspects of the framework to ease its use and re-use.