ABSTRACT
Wildlife can represent a reservoir of zoonotic pathogens and a public health problem. In the present study, we investigated the spread of zoonotic pathogens (Salmonella spp., Yersinia enterocolitica, Listeria monocytogenes, Shiga-toxin-producing Escherichia coli (STEC), and hepatitis E virus (HEV)) considering the presence of virulence and antibiotic resistance genes in game meat from animals hunted in northwest Italy. During two hunting seasons (2020 to 2022), samples of liver and/or muscle tissue were collected from chamois (n = 48), roe deer (n = 26), deer (n = 39), and wild boar (n = 35). Conventional microbiology and biomolecular methods were used for the detection, isolation, and characterization of the investigated pathogens. Two L. monocytogenes serotype IIa strains were isolated from wild boar liver; both presented fosfomycin resistance gene and a total of 22 virulence genes were detected and specified in the text. Eight Y. enterocolitica biotype 1A strains were isolated from chamois (2), wild boar (5), and deer (1) liver samples; all showed streptogramin and beta-lactam resistance genes; the virulence genes found were myfA (8/8 strains), ymoA (8/8), invA (8/8), ystB (8/8), and ail (4/8). Our data underscore the potential role of wildlife as a carrier of zoonotic and antibiotic-resistant pathogens in northwest Italy and a food safety risk for game meat consumers.
ABSTRACT
The widespread diffusion of the wild boar on the Italian territory and its consistent use for hunting have created the possibility to conduct multiple studies on the pathologies afflicting this ungulate. Nevertheless, in the last two decades, only some pathologies such as classical and African Swine Fever, Tuberculosis, Brucellosis from Brucella suis have benefited from substantial public funding and the consequent great interest from the scientific world, while less attention was addressed to parasitic diseases including sarcoptic mange. Therefore, to fill this gap, the purpose of this study was to contribute to the knowledge of sarcoptic mange in the wild boar population in Aosta Valley in the Northwest of Italy, including sympatric species as foxes. Due to past field surveys, it has been possible to find a possible role of snow metrics in the spread of this pathogen. Even if there are only empirical evidence and the mechanism remain unknown remote sensing analysis considering snow metrics were performed to provide to veterinarians, foresters, biologists, and ecologists new tools to better understand wield board dynamics and join to ordinary tool an instrument to enhance management and planning strategies. The snow metrics (SM) were derived from USGS NASA Landsat 8 L2A retrieved from Theia CNES platform and processed in Orfeo Toolbox LIS extension package. The relationship between SM and the disease spread was tested per each Aosta Valley municipality obtaining LISA maps for each hunting season. The results have showed that this parasite is present in an endemic form even if with rather low prevalence values, equal to 1.2% in the season hunting season 2013/2014, and equal to 7.5% in the hunting season 2014/2015. Moreover, within simultaneous given values of SM, sarcoptic mange seem to find good conditions for spreading.
ABSTRACT
Changes in land use and land cover as well as feedback on the climate deeply affect the landscape worldwide. This phenomenon has also enlarged the human-wildlife interface and amplified the risk of potential new zoonoses. The expansion of the human settlement is supposed to affect the spread and distribution of wildlife diseases such as canine distemper virus (CDV), by shaping the distribution, density, and movements of wildlife. Nevertheless, there is very little evidence in the scientific literature on how remote sensing and GIS tools may help the veterinary sector to better monitor the spread of CDV in wildlife and to enforce ecological studies and new management policies in the near future. Thus, we perform a study in Northwestern Italy (Aosta Valley Autonomous Region), focusing on the relative epidemic waves of CDV that cause a virulent disease infecting different animal species with high host mortality. CDV has been detected in several mammalian from Canidae, Mustelidae, Procyonidae, Ursidae, and Viverridae families. In this study, the prevalence is determined at 60% in red fox (Vulpes vulpes, n = 296), 14% in wolf (Canis lupus, n = 157), 47% in badger (Meles meles, n = 103), and 51% in beech marten (Martes foina, n = 51). The detection of CDV is performed by means of real-time PCR. All the analyses are done using the TaqMan approach, targeting the chromosomal gene for phosphoprotein, gene P, that is involved in the transcription and replication of the virus. By adopting Earth Observation Data, we notice that CDV trends are strongly related to an altitude gradient and NDVI entropy changes through the years. A tentative model is developed concerning the ground data collected in the Aosta Valley region. According to our preliminary study, entropy computed from remote-sensing data can represent a valuable tool to monitor CDV spread as a proxy data predictor of the intensity of fragmentation of a given landscape and therefore also to monitor CDV. In conclusion, the evaluation from space of the landscape variations regarding the wildlife ecological corridors due to anthropic or natural disturbances may assist veterinarians and wildlife ecologists to enforce management health policies in a One Health perspective by pointing out the time and spatial conditions of interaction between wildlife. Surveillance and disease control actions are supposed to be carried out to strengthen the usage of geospatial analysis tools and techniques. These tools and techniques can deeply assist in better understanding and monitoring diseases affecting wildlife thanks to an integrated management approach.
