The actual contribution of migratory birds in spreading West Nile (WNV) and Usutu virus (USUV) across Europe and from Africa to old countries is still controversial. In this study, we reported the results of molecular and serological surveys on migrating birds sampled during peaks of spring and autumn migration at 11 Italian sites located along important flyways, from 2012 to 2014. A total of 1335 specimens made of individual or pooled sera, and organs from 275 dead birds were tested for WNV and USUV RNA by real time PCR (RT-PCR). Furthermore, sera were tested by serum neutralization assay for detecting WNV and USUV neutralizing antibodies. Molecular tests detected WNV lineage 2 RNA in a pool made of three Song Thrush (Turdus philomelos) sera sampled in autumn, and lineage 1 in kidneys of six trans-Saharan birds sampled in spring. Neutralizing antibodies against WNV and USUV were found in 5.80% (n = 72; 17 bird species) and 0.32% (n = 4; 4 bird species) of the tested sera, respectively. Our results do not exclude the role of migratory birds as potential spreaders of WNV and USUV from Africa and Central Europe to Mediterranean areas and highlight the importance of a more extensive active surveillance of zoonotic viruses.

In January 2022, West Nile virus (WNV) lineage 2 (L2) was detected in an adult female goshawk rescued near Perugia in the region of Umbria (Italy). The animal showed neurological symptoms and died 15 days after its recovery in a wildlife rescue center. This was the second case of WNV infection recorded in birds in the Umbria region during the cold season, when mosquitoes, the main WNV vectors, are usually not active. According to the National Surveillance Plan, the Umbria region is included amongst the WNV low-risk areas. The necropsy evidenced generalized pallor of the mucous membranes, mild splenomegaly, and cerebral edema. WNV L2 was detected in the brain, heart, kidney, and spleen homogenate using specific RT-PCR. Subsequently, the extracted viral RNA was sequenced. A Bayesian phylogenetic analysis performed through a maximum-likelihood tree showed that the genome sequence clustered with the Italian strains within the European WNV strains among the central-southern European WNV L2 clade. These results, on the one hand, confirmed that the WNV L2 strains circulating in Italy are genetically stable and, on the other hand, evidenced a continuous WNV circulation in Italy throughout the year. In this report case, a bird-to-bird WNV transmission was suggested to support the virus overwintering. The potential transmission through the oral route in a predatory bird may explain the relatively rapid spread of WNV, as well as other flaviviruses characterized by similar transmission patterns. However, rodent-to-bird transmission or mosquito-to-bird transmission cannot be excluded, and further research is needed to better understand WNV transmission routes during the winter season in Italy.

West Nile Disease (WND) is one of the most spread zoonosis in Italy and Europe caused by a vector-borne virus. Its transmission cycle is well understood, with birds acting as the primary hosts and mosquito vectors transmitting the virus to other birds, while humans and horses are occasional dead-end hosts. Identifying suitable environmental conditions across large areas containing multiple species of potential hosts and vectors can be difficult. The recent and massive availability of Earth Observation data and the continuous development of innovative Machine Learning methods can contribute to automatically identify patterns in big datasets and to make highly accurate identification of areas at risk. In this paper, we investigated the West Nile Virus (WNV) circulation in relation to Land Surface Temperature, Normalized Difference Vegetation Index and Surface Soil Moisture collected during the 160 days before the infection took place, with the aim of evaluating the predictive capacity of lagged remotely sensed variables in the identification of areas at risk for WNV circulation. WNV detection in mosquitoes, birds and horses in 2017, 2018 and 2019, has been collected from the National Information System for Animal Disease Notification. An Extreme Gradient Boosting model was trained with data from 2017 and 2018 and tested for the 2019 epidemic, predicting the spatio-temporal WNV circulation two weeks in advance with an overall accuracy of 0.84. This work lays the basis for a future early warning system that could alert public authorities when climatic and environmental conditions become favourable to the onset and spread of WNV.

In Italy, West Nile virus (WNV) appeared for the first time in the Tuscany region in 1998. After 10 years of absence, it re-appeared in the areas surrounding the Po River delta, affecting eight provinces in three regions. Thereafter, WNV epidemics caused by genetically divergent isolates have been documented every year in the country. Since 2018, only WNV Lineage 2 has been reported in the Italian territory. In October 2020, WNV Lineage 1 (WNV-L1) re-emerged in Italy, in the Campania region. This is the first occurrence of WNV-L1 detection in the Italian territory since 2017. WNV was detected in the internal organs of a goshawk (Accipiter gentilis) and a kestrel (Falco tinnunculus). The RNA extracted in the goshawk tissue samples was sequenced, and a Bayesian phylogenetic analysis was performed by a maximum-likelihood tree. Genome analysis, conducted on the goshawk WNV complete genome sequence, indicates that the strain belongs to the WNV-L1 Western-Mediterranean (WMed) cluster. Moreover, a close phylogenetic similarity is observed between the goshawk strain, the 2008–2011 group of Italian sequences, and European strains belonging to the Wmed cluster. Our results evidence the possibility of both a new re-introduction or unnoticed silent circulation in Italy, and the strong importance of keeping the WNV surveillance system in the Italian territory active.

The occurrence of West Nile Virus (WNV) represents one of the most common mosquito-borne zoonosis viral infections. Its circulation is usually associated with climatic and environmental conditions suitable for vector proliferation and virus replication. On top of that, several statistical models have been developed to shape and forecast WNV circulation: in particular, the recent massive availability of Earth Observation (EO) data, coupled with the continuous advances in the field of Artificial Intelligence, offer valuable opportunities. In this paper, we seek to predict WNV circulation by feeding Deep Neural Networks (DNNs) with satellite images, which have been extensively shown to hold environmental and climatic features. Notably, while previous approaches analyze each geographical site independently, we propose a spatial-aware approach that considers also the characteristics of close sites. Specifically, we build upon Graph Neural Networks (GNN) to aggregate features from neighbouring places, and further extend these modules to consider multiple relations, such as the difference in temperature and soil moisture between two sites, as well as the geographical distance. Moreover, we inject time-related information directly into the model to take into account the seasonality of virus spread. We design an experimental setting that combines satellite images – from Landsat and Sentinel missions – with ground truth observations of WNV circulation in Italy. We show that our proposed Multi-Adjacency Graph Attention Network (MAGAT) consistently leads to higher performance when paired with an appropriate pre-training stage. Finally, we assess the importance of each component of MAGAT in our ablation studies.

Four goats were inoculated with an inactivated peste des petits ruminants virus (PPRV) vaccine. Three unvaccinated goats were kept as controls. After 36 days, the four goats were revaccinated. The immune response was monitored by virus neutralization test showing that two doses of the vaccine were able to stimulate strong immune response in all the vaccinated animals. The vaccinated goat and the controls were challenged with virulent PPRV intranasally. After PPRV challenge, the three control goats showed fever, viremia and virus excretion through mucosal surfaces, whereas the vaccinated goats were fully protected against PPRV infection and replication.