Integrated genomic surveillance (IGS), i.e. the integrated analysis of pathogen whole genome sequencing and classical epidemiological data, can contribute substantially to the disease surveillance and infection prevention activities of local public health authorities (LPHAs).

Our aim was to characterise how LPHAs use IGS, and factors required or important for their implementation, in the context of the German public health system.

We employed a mixed-methods design combining a quantitative survey of 60 LPHAs in three German states with five qualitative case studies based on LPHAs in four German localities and one state-level public health authority.

Approximately half of LPHAs reported adoption of IGS; applications included outbreak analysis (n = 25), targeting and evaluation of infection control measures (n = 25 and n = 18, respectively) and characterisation of pathogen transmission chains (n = 25). Factors identified as required or important for the implementation of IGS in LPHAs included fast sample-to-result turnaround times, organisational data interpretation capabilities and clearly defined surveillance sampling strategies. Based on the case studies in which the adoption of IGS was successful, we formulate recommendations for implementing IGS at the level of LPHAs, including establishment of dedicated IGS analysis teams within LPHAs, use of user-friendly digital solutions (e.g. browser-based dashboards) for data exchange and analysis, and implementation of IGS in collaboration with local academic institutions.

Our analysis paves the way for increasing the implementation of IGS by LPHAs in Germany and other countries with similarly structured public health systems.

Escherichia coli, a pathogen commonly infecting humans and bovines, is a prime sentinel indicator and predictor for antimicrobial resistance (AMR). Tracking epidemiological trends of AMR is essential to address this global One Health threat.

To perform a comprehensive retrospective epidemiological analysis of AMR trends in E. coli isolated from human urine and blood and bovine specimens, and compare with antimicrobial consumption or sales data for humans.

All E. coli isolates with susceptibility results from human urine (n = 122,419), blood (n = 2,373) and bovine specimens (n = 585) from 2012–23 in the Mid-West of Ireland were analysed. The resistance trends of nine commonly used antimicrobials were compared with their consumption by humans or sales in community and hospital settings.

Over the 12-year period, resistance against common antimicrobials was lowest among the bovine isolates (range: 2–44%). Human urine isolates showed lower resistance (5–59%) than bloodstream isolates (12–69%). There was a downward trend in resistance to all antimicrobials between 2012 and 2023 in the human isolates (p < 0.001), except for piperacillin/tazobactam where resistance increased, in each case correlating with antimicrobial usage. Bovine isolates demonstrated reduced resistance to co-amoxiclav (p = 0.001), with no trend observed for other antimicrobials.

Our data showed reduced resistance to many antimicrobials for E. coli from human and bovine populations in our region. Increased use of ‘preferred’ antimicrobials in humans and reduced use of those ‘to be avoided’ was observed. The findings indicate the emerging effectiveness of AMR strategies and highlight the value of One Health AMR.

Tick-borne encephalitis virus (TBEV) is expanding its range in Europe, with increasing human cases reported. Since the first detection of TBEV in ticks in the United Kingdom in 2019, one possible, two probable and two confirmed autochthonous cases in humans have been reported.

We aimed to understand the environmental and ecological factors limiting TBEV foci at their range edge and predict suitable areas for TBEV establishment across Great Britain (GB) by modelling patterns of exposure to TBEV in deer.

We developed spatial risk models for TBEV by integrating data between 2018 and 2021 on antibodies against tick-borne flavivirus in fallow, muntjac, red and roe deer with data on potential risk factors, including climate, land use, forest connectivity and distributions of bank voles and yellow-necked mice. We overlayed modelled suitability for TBEV exposure across GB with estimations on number of visitors to predict areas of high human exposure risk.

Models for fallow, muntjac and roe deer performed well in independent validation (Boyce index > 0.92). Probable exposure to TBEV was more likely to occur in sites with a greater percentage cover of coniferous woodland, with multiple deer species, higher winter temperatures and rates of spring warming.

The resulting TBEV suitability maps can be used by public health bodies in GB to tailor surveillance and identify probable high-risk areas for human exposure to guide awareness raising and vaccination policy. Combining animal surveillance and iterative spatial risk modelling can enhance preparedness in areas of tick-borne disease emergence.