Abstract
Avian migration plays a critical role in the transmission of vector-borne diseases, including West Nile Virus (WNV). WNV has become endemic in Northern Italy's Po Valley since 2008, affecting many resident bird species, and in Sardinia, where WNV circulation has been mainly reported in migratory birds. Sporadic cases have also been reported in southern Italy, and some northern regions along the Tyrrhenian coast. A comprehensive One Health approach, integrating human, terrestrial vertebrate, and entomological surveillance, is vital for the timely detection of the seasonal virus spread to applying preventive measures (Candeloro et al., 2020).
This study investigates avian migration's role in shaping the dynamics of WNV in Italy, enhancing understanding of transmission patterns. Ringing and recovery data of birds ringed in Italy (from 2008 to 2017) were retrieved from ISPRA's Italian Ringing Center.
Spatial clustering and network analysis were employed to generate and characterize the bird migration network (Lamb et al., 2019). The network included 31 spatial clusters and 71 links. Strong agreement between network metrics (In-degree, Out-degree, In-strength, Out-strength, and Betweenness) and WNV cases was observed. Clusters encompassing regions featured by the presence of endemic areas were found to be highly vulnerable or able to spread the infection. Tuscany and Lazio Regions emerged as network hubs, underlining their significant role in WNV circulation.
The Giant Strongly Connected Component (GSCC) linked the endemic area to other WNV-affected Regions. Community detection analysis highlighted connections during the spring season between northern Sardinia, Tuscany, and Abruzzi Regions, accordingly with GSCC. During summer, GSCC extended to southern Sardinia. Except for Campania, low northern-southern Italy connections correlated with fewer outbreaks observed in the latter. Dynamic measures, like Forward/Backward Reachable Set (FRS/BRS), accounted for time/direction and confirmed the previous results. BRS, during the epidemic season, showed a limited connection from the endemic area to central-southern Italy.
To explain the disease's spatial-temporal distribution, we developed a network-based stochastic SEI model, accounting for the suitability of WNV circulation, uncertainty in the timing of movements, and disease incubation period. Evaluated scenarios: 1) Disease spread within Italy from endemic areas, 2) Introduction from Africa.
Results confirmed and expanded on network analysis. In scenario 1, infection reached clusters including Sardinia, Campania, and Basilicata (30-35% simulations), despite unfavorable seasonal conditions for viral circulation at the time of exposure. Liguria showed infection during favorable conditions. In scenario 2, southern Italy (e.g., Puglia) had foreign-origin infections. Notably, northern Sardinia, in Scenario 1, showed autumn exposure pick in this scenario.
The study analysed selected bird species' migration in Italy using static, seasonal, and dynamic network analysis. Viral circulation was detected and supported by the SEI model. Concerns about data representativeness, particularly in Sicily and Sardinia, highlighting the need for broader migration data, including telemetry data.
References
Candeloro, L., Ippoliti, C., Iapaolo, F., Monaco, F., Morelli, D., Cuccu, R., Fronte, P., et al. (2020). Predicting WNV Circulation in Italy Using Earth Observation Data and Extreme Gradient Boosting Model. Remote Sensing, 12(18), 3064. MDPI AG. Retrieved from http://dx.doi.org/10.3390/rs12183064
Lamb, J. S., Paton, P. W. C., Osenkowski, J. E., Badzinski, S. S., Berlin, A. M., Bowman, T., Dwyer, C., Fara, L. J., Gilliland, S. G., Kenow, K., Lepage, C., Mallory, M. L., Olsen, G. H., Perry, M. C., Petrie, S. A., Savard, J. L., Savoy, L., Schummer, M., Spiegel, C. S., & McWilliams, S. R. (2019). Spatially explicit network analysis reveals multi-species annual cycle movement patterns of sea ducks. Ecological applications : a publication of the Ecological Society of America, 29(5), e01919. https://doi-org.bibliosan.idm.oclc.org/10.1002/eap.1919