A Pilot Study on Behavioural and Physiological Indicators of Emotions in Donkeys.

Recognizing animal emotions is critical to their welfare and can lead to a better relationship with humans and the environment, especially in a widespread species like the donkey, which is often prone to welfare issues. This study aims to assess the emotional response of donkeys through an operant conditioning task with two presumed different emotional contents. Specifically, a within-subject design including positive and negative conditions was conducted, collecting behavioural and physiological (heart rate variability and HRV) parameters. Facial expressions, postures, and movements were analysed by principal component analysis and behavioural diversity indexes (frequencies, activity budgets, richness, Shannon and Gini-Simpson). During the positive condition, both ears were held high and sideways (left: r = -0.793, p < 0.0001; right: r = -0.585, p = 0.011), while the ears were frontally erected (left: r = 0.924, p < 0.0001; right: r = 0.946, p < 0.0001) during the negative one. The latter was also associated with an increased tendency to walk (r = 0.709, p = 0.001), walk away (r = 0.578, p = 0.012), more frequent changes in the body position (VBody position = 0, p = 0.022), and greater behavioural complexity (VGini-Simpson Index = 4, p = 0.027). As for HRV analysis, the root mean square of successive beat-to-beat differences (rMSSD) was significantly lower after the negative condition. These non-invasive parameters could be considered as possible indicators of donkeys' emotional state.

Study of the Interface between Wild Bird Populations and Poultry and Their Potential Role in the Spread of Avian Influenza.

Water birds play a crucial role in disseminating and amplifying avian influenza viruses (AIVs) in the environment. However, they may have limited interactions with domestic facilities, raising the hypothesis that other wild birds may play the bridging role in introducing AIVs into poultry. An ornithocoenosis study, based on census-transect and camera-trapping methods, was conducted in 2019 in ten poultry premises in northeast Italy to characterize the bird communities and envisage the species that might act as bridge hosts for AIVs. The data collected were explored through a series of multivariate analyses (correspondence analysis and non-metric multidimensional scaling), and biodiversity indices (observed and estimated richness, Shannon entropy and Pielou's evenness). The analyses revealed a high level of complexity in the ornithic population, with 147 censused species, and significant qualitative and quantitative differences in wild bird species composition, both in space and in time. Among these, only a few were observed in close proximity to the farm premises (i.e., Magpies, Blackbirds, Cattle Egrets, Pheasants, Eurasian Collared Doves, and Wood Pigeons), thus suggesting their potential role in spilling over AIVs to poultry; contrarily, waterfowls appeared to be scarcely inclined to close visits, especially during autumn and winter seasons. These findings stress the importance of ongoing research on the wild-domestic bird interface, advocating for a wider range of species to be considered in AIVs surveillance and prevention programs.

Integration of Epidemiological and Genomic Data to Investigate H5N1 HPAI Outbreaks in Northern Italy in 2021-2022.

Between October 2021 and April 2022, 317 outbreaks caused by highly pathogenic avian influenza (HPAI) H5N1 viruses were notified in poultry farms in the northeastern Italian regions. The complete genomes of 214 strains were used to estimate the genetic network based on the similarity of the viruses. An exponential random graph model (ERGM) was used to assess the effect of 'at-risk contacts', 'same owners', 'in-bound/out-bound risk windows overlap', 'genetic differences', 'geographic distances', 'same species', and 'poultry company' on the probability of observing a link within the genetic network, which can be interpreted as the potential propagation of the epidemic via lateral spread or a common source of infection. The variables 'same poultry company' (Est. = 0.548, C.I. = [0.179; 0.918]) and 'risk windows overlap' (Est. = 0.339, C.I. = [0.309; 0.368]) were associated with a higher probability of link formation, while the 'genetic differences' (Est. = -0.563, C.I. = [-0.640; -0.486]) and 'geographic distances' (Est. = -0.058, C.I. = [-0.078; -0.038]) indicated a reduced probability. The integration of epidemiological data with genomic analyses allows us to monitor the epidemic evolution and helps to explain the dynamics of lateral spreads casting light on the potential diffusion routes. The 2021-2022 epidemic stresses the need to further strengthen the biosecurity measures, and to encourage the reorganization of the poultry production sector to minimize the impact of future epidemics.

An integrated system for the management of environmental data to support veterinary epidemiology.

Environmental and climatic fluctuations can greatly influence the dynamics of infectious diseases of veterinary concern, or interfere with the implementation of relevant control measures. Including environmental and climatic aspects in epidemiological studies could provide policy makers with new insights to assign resources for measures to prevent or limit the spread of animal diseases, particularly those with zoonotic potential. The ever-increasing number of technologies and tools permits acquiring environmental data from various sources, including ground-based sensors and Satellite Earth Observation (SEO). However, the high heterogeneity of these datasets often requires at least some basic GIS (Geographic Information Systems) and/or coding skills to use them in further analysis. Therefore, the high availability of data does not always correspond to widespread use for research purposes. The development of an integrated data pre-processing system makes it possible to obtain information that could be easily and directly used in subsequent epidemiological analyses, supporting both research activities and the management of disease outbreaks. Indeed, such an approach allows for the reduction of the time spent on searching, downloading, processing and validating environmental data, thereby optimizing available resources and reducing any possible errors directly related to data collection. Although multitudes of free services that allow obtaining SEO data exist nowadays (either raw or pre-processed through a specific coding language), the availability and quality of information can be sub-optimal when dealing with very small scale and local data. In fact, some information sets (e.g., air temperature, rainfall), usually derived from ground-based sensors (e.g., agro-meteo station), are managed, processed and redistributed by agencies operating on a local scale which are often not directly accessible by the most common free SEO services (e.g., Google Earth Engine). The EVE (Environmental data for Veterinary Epidemiology) system has been developed to acquire, pre-process and archive a set of environmental information at various scales, in order to facilitate and speed up access by epidemiologists, researchers and decision-makers, also accounting for the integration of SEO information with locally sensed data.

Comparative efficacy of BG-Sentinel 2 and CDC-like mosquito traps for monitoring potential malaria vectors in Europe.

BACKGROUND: Different trapping devices and attractants are used in the mosquito surveillance programs currently running in Europe. Most of these devices target vector species belonging to the genera Culex or Aedes, and no studies have yet evaluated the effectiveness of different trapping devices for the specific targeting of Anopheles mosquito species, which are potential vectors of malaria in Europe. This study aims to fill this gap in knowledge by comparing the performance of trapping methods that are commonly used in European mosquito surveillance programs for Culex and Aedes for the specific collection of adults of species of the Anopheles maculipennis complex. METHODS: The following combinations of traps and attractants were used: (i) BG-Sentinel 2 (BG trap) baited with a BG-Lure cartridge (BG + lure), (ii) BG trap baited with a BG-Lure cartridge and CO2 (BG + lure + CO2), (iii) Centers for Disease Control and Prevention-like trap (CDC trap) baited with CO2 (CDC + CO2), (iv) CDC trap used with light and baited with BG-Lure and CO2 (CDC light + lure + CO2). These combinations were compared in the field using a 4 × 4 Latin square study design. The trial was conducted in two sites in northeastern Italy in 2019. Anopheles species were identified morphologically and a sub-sample of An. maculipennis complex specimens were identified to species level by molecular analysis. RESULTS: Forty-eight collections were performed on 12 different trapping days at each site, and a total of 1721 An. maculipennis complex specimens were captured. The molecular analysis of a sub-sample comprising 254 specimens identified both Anopheles messeae/Anopheles daciae (n = 103) and Anopheles maculipennis sensu stricto (n = 8) at site 1, while at site 2 only An. messeae/An. daciae (n = 143) was found. The four trapping devices differed with respect to the number of An. messeae/An. daciae captured. More mosquitoes were caught by the BG trap when it was used with additional lures (i.e. BG + lure + CO2) than without the attractant, CO2 [ratioBG+lure vs BG+lure+CO2 = 0.206, 95% confidence interval (CI) 0.101-0.420, P < 0.0001], while no significant differences were observed between CDC + CO2 and CDC light + lure + CO2 (P = 0.321). The addition of CO2 to BG + lure increased the ability of this combination to capture An. messeae/An. daciae by a factor of 4.85, and it also trapped more mosquitoes of other, non-target species (Culex pipiens, ratioBG+lure vs BG+lure+CO2 = 0.119, 95% CI 0.056-0.250, P < 0.0001; Ochlerotatus caspius, ratioBG+lure vs BG+lure+CO2 = 0.035, 95% CI 0.015-0.080, P < 0.0001). CONCLUSIONS: Our results show that both the BG-Sentinel and CDC trap can be used to effectively sample An. messeae/An. daciae, but that the combination of the BG-Sentinel trap with the BG-Lure and CO2 was the most effective means of achieving this. BG + lure + CO2 is considered the best combination for the routine monitoring of host-seeking An. maculipennis complex species such as An. messeae/An. daciae. The BG-Sentinel and CDC traps have value as alternative methods to human landing catches and manual aspiration for the standardized monitoring of Anopheles species in Europe.

Rapid spread of a new West Nile virus lineage 1 associated with increased risk of neuroinvasive disease during a large outbreak in northern Italy, 2022: One Health analysis.

BACKGROUND: A new strain of WNV lineage 1 (WNV - 1) emerged in the Veneto Region, northern Italy, in 2021, eight years after the last outbreak of WNV - 1 in Italy. The virus, which co-circulates with WNV-2, has become endemic in the Region, where, in 2022, most human cases of neuroinvasive disease (WNND) reported in Europe have occurred. METHODS: Comparative analysis of the epidemiology and clinical presentation of WNV-1 and WNV-2 infection in humans, as well as the temporal and geographic distribution of WNV-1 and WNV-2 among wild birds and Culex pipiens mosquitoes in Veneto, from May 16th to August 21st, 2022, to determine if the high number of WNND cases was associated with WNV-1. RESULTS: As of August 21st, 2022, 222 human cases of WNV infection were confirmed by molecular testing, including 103 with fever (WNF) and 119 with WNND. WNV lineage was determined in 201 (90.5%) cases, comprising 138 WNV-1 and 63 WNV-2 infections. During the same period, 35 blood donors tested positive, including 30 in whom WNV lineage was determined (13 WNV-1 and 17 WNV-2). Comparative analysis of the distribution of WNV-1 and WNV-2 infections among WNND cases, WNF cases and WNV-positive blood donors showed that patients with WNND were more likely to have WNV-1 infection than blood donors (odds ratio 3.44; 95% CI 95% 1.54 to 8.24; p = 0.0043). As observed in humans, in wild birds WNV-1 had higher infectious rate (IR) and showed a more rapid expansion than WNV-2. At variance, the distribution of the two lineages was more even in mosquitoes, but with a trend of rapid increase of WNV-1 IR over WNV-2. CONCLUSIONS: Comparative analysis of WNV-1 vs WNV-2 infection in humans, wild birds, and mosquitos showed a rapid expansion of WNV-1 and suggested that WNV-1 infected patients might have an increased risk to develop severe disease.

Active Surveillance for Highly Pathogenic Avian Influenza Viruses in Wintering Waterbirds in Northeast Italy, 2020-2021.

The increasing involvement of wild waterfowl in H5 Highly Pathogenic Avian Influenza Virus (HPAIV) circulation continues to pose a threat to animal and public health worldwide. In winter 2020-2021, two field surveillance activities were carried out on a weekly basis, through virological and serological analyses, in 823 hunted and 521 trapped migratory aquatic birds in northeast Italy. Sixty Eurasian teals were recaptured several times, which allowed us to follow the progression of the HPAI H5 infection in naturally infected wild waterfowl. Oropharyngeal, cloacal, and feather swabs (OS, CS and FS) were collected from each duck and tested by real time rRT-PCR Type A influenza. The identified viruses were characterized and pathotyped by sequencing. Several viruses belonging to three different HPAI H5 subtypes were detected: H5N8, H5N5, and H5N1. High prevalence of infection with HPAI H5 clade 2.3.4.4b during November-December 2020 (up to 27.1%) was observed in captured Eurasian teals, while infection rates in hunted dabbling ducks, mainly Eurasian wigeons, showed the highest prevalence of infection in November 2020 (8.9%) and January 2021 (10.2%). All HPAI positive birds were also clinically healthy when recaptured weeks apart. The OS and FS showed the highest detection efficiency of HPAIV. Our results highlight that HPAI passive surveillance should be complemented by a targeted active surveillance to more efficiently detect novel HPAI viruses.

Inter-annual variability of the effects of intrinsic and extrinsic drivers affecting West Nile virus vector Culex pipiens population dynamics in northeastern Italy.

BACKGROUND: Vector-borne infectious diseases (VBDs) represent a major public health concern worldwide. Among VBDs, West Nile virus (WNV) showed an increasingly wider spread in temperate regions of Europe, including Italy. During the last decade, WNV outbreaks have been recurrently reported in mosquitoes, horses, wild birds, and humans, showing great variability in the temporal and spatial distribution pattern. Due to the complexity of the environment-host-vector-pathogen interaction and the incomplete understanding of the epidemiological pattern of the disease, WNV occurrences can be difficult to predict. The analyses of ecological drivers responsible for the earlier WNV reactivation and transmission are pivotal; in particular, variations in the vector population dynamics may represent a key point of the recent success of WNV and, more in general, of the VBDs. METHODS: We investigated the variations of Culex pipiens population abundance using environmental, climatic and trapping data obtained over nine years (2010 to 2018) through the WNV entomological surveillance programme implemented in northeastern Italy. An information theoretic approach (IT-AICc) and model-averaging algorithms were implemented to examine the relationship between the seasonal mosquito population growth rates and both intrinsic (e.g. intraspecific competition) and extrinsic (e.g. environmental and climatic variables) predictors, to identify the most significant combinations of variables outlining the Cx. pipiens population dynamics. RESULTS: Population abundance (proxy for intraspecific competition) and length of daylight were the predominant factors regulating the mosquito population dynamics; however, other drivers encompassing environmental and climatic variables also had a significant impact, although sometimes counterintuitive and not univocal. The analyses of the single-year datasets, and the comparison with the results obtained from the overall model (all data available from 2010 to 2018), highlighted remarkable differences in coefficients magnitude, sign and significance. These outcomes indicate that different combinations of factors might have distinctive, and sometimes divergent, effects on mosquito population dynamics. CONCLUSIONS: A more realistic acquaintance of the intrinsic and extrinsic mechanisms of mosquito population fluctuations in relation to continuous changes in environmental and climatic conditions is paramount to properly reinforce VBDs risk-based surveillance activities, to plan targeted density control measures and to implement effective early detection programmes.