Geomatics and satellite remote sensing offer useful analysis tools for several technical-scientific fields. This work, with reference to a regional case of study, investigates remote sensing potentialities for describing relationships between environment and diseases affecting wildlife at landscape level in the light of climate change effects onto vegetation. Specifically, the infectious keratoconjunctivitis (IKC) of chamois (Rupicapra rupicapra L.) in Aosta Valley (NW Italy) was investigated at the regional level. IKC (Mycoplasma conjunctivae) is a contagious disease for domestic and wild ruminants (Caprinae and Ovinae). Two types of analysis were performed: one aimed at exploring by remotely sensed data phenological metrics (PMs) and evapotranspiration (ET) trends of vegetation in the area; one investigating the correlation between PMs and ET, versus IKC prevalence. The analysis was based on TERRA MODIS image time series ranging from 2000 to 2019. Ground data about IKC were available for a shorter time range: 2009–2019. Consequently, PMs and ET trend investigations were focused on the whole times range (2000–2019); conversely, correlation analysis was achieved with reference to the reduced 2009–2019 period. The whole study was based on freely available data from public archives. MODIS products, namely MOD13Q1 v.6 and MOD16A2, were used to derive PM and ET trends, respectively. Shuttle Radar Topography Mission (SRTM) Digital Terrain Model (DTM) was used to describe local topography; CORINE Land Cover map was adopted to describe land use classes. PMs and ET (as derivable from EO data) proved to significantly changed their values in the last 20 years, with a continuous progressive trend. As far as correlation analysis was concerned, ET and some PMs (specifically, End of Season (EOS) and Length of Season (LOS) proved significantly condition IKC prevalence. According to results, the proposed methodology can be retained as an effective tool for supporting public health and eco-pathological sectors. Specifically, it can be intended for a continuous monitoring of effects that climatic dynamics determine onto wild animals in the Alpine area, included diseases and zoonosis, moving future environmental management and planning towards the One Health perspective.

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.

Introduction: Yersiniosis is a zoonosis causing gastroenteritis, diarrhoea, and occasionally reactive arthritis and septicaemia. Cases are often linked to meat consumption and the most common aetiological agent is the Gram-negative bacilliform Yersinia enterocolitica bacterium. The occurrence of Yersinia spp. among wild animals has mostly been studied in wild boar, but it has seldom been in other species. Material and Methods: A total of 1,868 faecal samples from animals found dead or hunted were collected between 2015 and 2018 in the Valle d’Aosta region of the northwestern Italian Alps. Alpine ibex faecal samples were collected during a health monitoring program in 2018. Bacteria were isolated via PCR and confirmed as Y. enterocolitica biochemically. Strain antimicrobial susceptibility was tested by Kirby–Bauer disc diffusion, and the presence of virulence factors and antimicrobial resistance genes was investigated using whole-genome sequencing. Results: Yersinia enterocolitica strains of biotype 1A were detected in six faecal samples from red deer (0.93%), roe deer (0.49%) and red foxes (0.7%). Strains found in beech martens (3.57%) and Alpine ibex (2.77%) belonged to biotypes 1B and 5, respectively and harboured the pYPTS01 plasmid that had only been detected in Y. pseudotuberculosis PB1/+. All the isolates were resistant to ampicillin and erythromycin. Conclusion: The biovar 1A strains exhibited different virulence factors and behaved like non-pathogenic commensals. The strain from an Alpine ibex also harboured the self-transmissible pYE854 plasmid that can mobilise itself and the pYPTS01 plasmid to other strains. The beech marten could be considered a sentinel animal for Y. enterocolitica. Phenotypic resistance may account for the ability of all the strains to resist β-lactams.