A questionnaire survey was promoted under the COST Actions “Network for Evaluation of One Health-NEOH” and “European Network for Neglected Vectors and Vector-Borne Infections-EURNEGVEC”, from June 2016 to April 2017, to collect information on the existence of One Health (OH) collaboration and implementation of OH initiatives in 37 EU COST Countries. The questionnaire was to be answered by key respondents representing the three major OH components: (i). Animal Health; (ii). Human Health/Public Health; (iii). Environmental Health. A target respondent rate of nine respondents/country was aimed for, representing the following categories: (i). ministries; (ii). academia-research; (iii). private sector and NGOs, associations and scientific societies. The questionnaire, composed of 27 questions organized in six sections, was circulated to target respondents by Committee Members of the two COST actions. A total of 171 respondents from 34 countries completed the questionnaire, mainly belonging to academic and research institutions (55.5%), and to Animal Health/Animal Science fields (53.8%). Although the majority (57.9%) declared they had heard about OH, few respondents (10.7%) provided a complete definition. The “human” and “animal” elements prevailed over other key elements of OH definition (ecosystem, intersectoral, transdisciplinary, holistic, collaboration). Overall, 62.6% respondents declared to take part in OH initiatives. Antimicrobial resistance, avian influenza and environmental pollution were cited as the top three OH issues over the past 5 years. Limitations and gaps in intersectoral collaboration included communication and organizational problems resulting in poor networking, differing priorities and a lack of understanding between sectors. Regarding control and monitoring of zoonotic diseases, respondents from different sectors preferentially selected their own directorates/ministries while actually in most countries both Ministry of Health and Ministry of Agriculture are engaged. According to respondents, the level of awareness of OH amongst the general public is limited. Similarly, a dearth of opportunities of collaborations at different institutional and/or professional levels was described. Our survey provided an overview of how respondents in COST countries perceived and experienced OH and current limits to OH implementation. Identifying how initiatives are currently working and knowing the promoting and hindering factors allowed suggesting strategies to promote efficiency and effectiveness of OH implementation in the future.

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A study in an intensive Italian rabbit farm was carried out to assess the effect of age category and anatomical site on detection of S. aureus and to describe the diversity of spa-types within farm, including workers. On 400 rabbits of different age, 2066 samples from the ear, nose, axilla, groin, perineum and lesions were analyzed and 595 S. aureus were isolated. In total, 284 (71.0%) were colonized by S. aureus in at least one anatomical site and 35 animals (8.8%) had lesions. S. aureus prevalence was higher in adults than other age categories. Ear (29.4%) and nose (27.2%) were the most frequently colonized sites. The presence of lesions due to S. aureus was strongly associated with the colonization of at least one body site and the risk of lesions was proportionate to the number of sites colonized by S. aureus. In addition, a genotypic characterization was performed for 96 S. aureus strains randomly selected. All isolates resulted as low-virulence methicillin-sensitive-Staphylococcus aureus (LV-MSSA). Five different clonal lineages were found: spa-t2802, the most frequently detected (53.1%), also in human samples; spa-t491 (38.5%); spa-t094; t605; and spa-t2036. Strains t094, t491 and t2036 have not been isolated in Italy before.

The breeding of meat rabbits is an important sector in the livestock industry in Italy. The focus of this study was to describe the antibiotic resistance profile distribution among the Methicillin-sensitive Staphylococcus aureus isolated in a rabbit farm. From 400 animals of different ages and three farm workers, 96 randomly selected strains isolated from various anatomical sites and lesions were analysed. According to spa typing and the resistance profiles towards veterinary and human antibiotics, 26 pathotypes were identified. The highest resistance was observed against Tetracyclines (92.3%) and Macrolides (80.8%), while almost all were susceptible to Penicillins, according to the limited use of β-lactams on the farm. In total, 92.3% of pathotypes were multidrug resistant (MDRs). Two MDR pathotypes belonging to the t2802 spa type were isolated from both farmers and rabbits. Age categories harboured significantly different pathotypes (p = 0.019), while no association was found between pathotypes and lesions (p = 0.128) or sampling sites (p = 0.491). The antibiotic resistance was observed to increase with the time spent in the farm environment (age category). The selective pressure exerted by antibiotic use acted by giving advantage to more resistant strains rather than by lowering susceptibility to various drug categories within strains.

Staphylococcal infections represent a challenge in companion animals and hospitalized patients. This study aimed to assess the resistance of Staphylococcus pseudintermedius isolates, against a broad panel of antibacterials, including exclusive to human medicine. A total of 40 S. pseudintermedius were collected from clinical specimens of dogs (n = 31) and cats (n = 5). All strains were tested for 20 antibacterials, namely 14 Critical Important and eight Highly Important Antibacterials (CIA and HIA, respectively), indicative for 18 antimicrobial classes. All strains were susceptible to seven antibiotics (daptomycin, fosfomycin, fusidic acid, linezolid, quinupristin-dalfopristin, teicoplanin/vancomycin, tigecycline). The highest resistance was against penicillin (97.5% Confidence Interval [CI]: 83.8–100.0), whereas the lowest against telavancin (2.5%, CI: 0.0–16.2). Resistance versus Highest Priority CIA was observed, namely against macrolides (70.0, CI: 52.1–84.3), quinolones (62.5, CI: 44.5–78.3), 5th generation cephalosporins (7.5, CI: 1.3–21.6), and glycopeptides (2.5%, CI: 0.0–14.2). Among High Priority CIA, strains were resistant only to aminoglycosides (65.0, CI: 47.0–80.4) and ansamycins (12.5, CI: 3.8–28.1). We observed the highest resistance against veterinary medicine antibacterials, but there was also resistance against antibacterials exclusive to human medicine, namely ceftaroline (7.5, CI: 1.0–23.8) and telavancin. S. pseudintermedius zoonotic potential and its rate of acquisition of new resistance should encourage surveillance on a broad spectrum of antibacterials.

Wild and domestic animals can be usefully employed as sentinels for the surveillance of diseases with an impact on public health. In the case of tick-borne encephalitis virus (TBEV), the detection of antibodies in animals can be more effective than screening ticks for detecting TBEV foci, due to the patchy distribution of the virus. In the Piedmont region, northwestern Italy, TBEV is considered absent, but an increase in tick densities, of Ixodes ricinus in particular, has been observed, and TBEV is spreading in bordering countries, e.g., Switzerland. Therefore, we collected sera from wild ungulates during the hunting season (October–December) from 2017 to 2019 in the Susa Valley, Italian western Alps, and screened them for TBEV antibodies by a commercial competitive ELISA test. We collected 267 serum samples by endocranial venous sinuses puncture from red deer, roe deer and northern chamois carcasses. The animals were hunted in 13 different municipalities, at altitudes ranging between 750 and 2800 m a.s.l. The serological survey for TBEV yielded negative results. Borderline results for five serum samples were further confirmed as negative for TBEV by a plaque reduction neutralisation test. To date, our results indicate that TBEV is not circulating in western Piedmont. However, monitoring of TBEV should continue since TBEV and its vector are spreading in Europe. The wide-range distribution of wild ungulates and their role as feeding hosts, make them useful indicators of the health threats posed by Ixodid ticks.

A semi-quantitative risk assessment was developed to classify pig farms in terms of the probability of introduction of African swine fever virus (ASFV). Following on-farm data collection via a specific checklist, we applied a modified failure mode and effect analysis (FMEA) to calculate the risk priority codes (RPC's), indicating increasing risk levels ranging from 1 to 5. The importance of biosecurity measures was attributed by experts. To consider geographic risk factors, we classified pig farms based on local density of farmed pigs, and on the estimated wild boar population density. The combination of RPC's with geographical risk factors resulted into a final ranking of pig farms in terms of the risk of ASFV introduction. Furthermore, the estimation of frequency and levels of non-compliance with biosecurity measures was used to identify weak points in risk prevention at farm level. The outcome of the risk assessment was affected by choices in assigning non-compliance scores and importance to specific components of biosecurity. The method was applied in 60 commercial farms in major pig production areas in Italy. Furthermore, we applied a reduced version of our checklist in 12 non-commercial/small commercial (≤20 pigs) farms in the northern Apennines. In commercial farms, highest RPC's were obtained for biosecurity measures associated with personnel practices and farm buildings/planimetry. Intervention should be addressed to training of personnel on biosecurity and ASF, to avoid contacts with other pig herds, and to improve practices in the entrance into the farm. Sharing trucks with other farms, and loading/unloading of pigs were other weak points. Fencing was classified as insufficient in 70% of the commercial farms. Among these farms, breeding units were characterised by the lowest risk of ASFV introduction (although differences among median ranks were not statistically significant: P-value = 0.07; Kruskal–Wallis test), and increasing herd size was not significantly correlated with a higher risk (Kendall's τ = −0.13; P-value = 0.14). Density of farmed pig was greatest in the main pig production area in northern Italy. Conversely, exposure to wild boars was greatest for non-commercial/small commercial farms on the Apennines, which were also characterised by non-compliance with critical biosecurity measures.