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.

Bat-borne virus surveillance is necessary for determining inter-species transmission risks and is important due to the wide-range of bat species which may harbour potential pathogens. This study aimed to monitor coronaviruses (CoVs) and paramyxoviruses (PMVs) in bats roosting in northwest Italian regions. Our investigation was focused on CoVs and PMVs due to their proven ability to switch host and their zoonotic potential. Here we provide the phylogenetic characterization of the highly conserved polymerase gene fragments. Family-wide PCR screenings were used to test 302 bats belonging to 19 different bat species. Thirty-eight animals from 12 locations were confirmed as PCR positive, with an overall detection rate of 12.6% [95% CI: 9.3–16.8]. CoV RNA was found in 36 bats belonging to eight species, while PMV RNA in three Pipistrellus spp. Phylogenetic characterization have been obtained for 15 alpha- CoVs, 5 beta-CoVs and three PMVs; moreover one P. pipistrellus resulted co-infected with both CoV and PMV. A divergent alpha-CoV clade from Myotis nattereri SpA is also described. The compact cluster of beta-CoVs from R. ferrumequinum roosts expands the current viral sequence database, specifically for this species in Europe. To our knowledge this is the first report of CoVs in Plecotus auritus and M. oxygnathus, and of PMVs in P. kuhlii. This study identified alpha and beta-CoVs in new bat species and in previously unsurveyed Italian regions. To our knowledge this represents the first and unique report of PMVs in Italy. The 23 new bat genetic sequences presented will expand the current molecular bat-borne virus databases. Considering the amount of novel bat-borne PMVs associated with the emergence of zoonotic infections in animals and humans in the last years, the definition of viral diversity within European bat species is needed. Performing surveillance studies within a specific geographic area can provide awareness of viral burden where bats roost in close proximity to spillover hosts, and form the basis for the appropriate control measures against potential threats for public health and optimal management of bats and their habitats.

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.

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.

Peletto S, et al. J Vet Sci. 2009 Jun;10(2):115-120. http://dx.doi.org/10.4142/jvs.2009.10.2.115