BackgroundUnderstanding wildlife disease ecology is becoming an urgent need due to the continuous emergence and spread of several wildlife zoonotic diseases. West Nile Virus (WNV) is the most widespread arthropod-borne virus in the world, and in recent decades there has been an increase both in geographic range, and in the frequency of symptomatic infections in humans and wildlife. The principal vector for WNV in Europe is the common house Culex pipiens mosquito, which feeds on a wide variety of vertebrate host species. Variation in mosquito feeding preference has been described as one of the most influential parameters driving intensity and timing of WNV infection in the United States, but feeding preferences for this species have been little studied in Europe.MethodsHere, we estimated feeding preference for wild Cx. pipiens in northern Italy, using molecular analysis to identify the origin of blood meals, and avian census to control host abundance variations. Additionally, we used host bird odour extracts to test experimentally mosquito preferences in the absence of environmental variations.ResultsFor the first time, we demonstrate a clear feeding preference for the common blackbird (Turdus merula), both for wild collected specimens and in the lab, suggesting a potential important role for this species in the WNV epidemiology in Europe. A seasonal decrease in abundance of blackbirds is associated with increased feeding on Eurasian magpies (Pica pica), and this may be linked to seasonal emergence of WNV in humans. Feeding preferences on blackbirds are more marked in rural areas, while preference for magpies is higher in peridomestic areas. Other species, such as the house sparrow (Passer domesticus) appear to be selected by mosquitoes opportunistically in relation to its abundance.ConclusionsOur findings provide new insights into the ecology of Cx. pipiens in Europe and may give useful indications in terms of implementing targeted WNV surveillance plans. However, a clearer understanding of spatio-temporal variations of Cx. pipiens feeding preferences, and targeted studies on reservoir competence for WNV for these species are therefore now urgently needed as this is essential to describe disease dynamics and quantify virus transmission risk.

Metabarcoding provides a powerful tool for ecological studies of biodiversity and trophic interactions (Deiner et al., 2017;Taberlet et al., 2018). By combining high-throughput sequencing (HTS) with DNA barcoding, large volumes of high-resolution data can be generated from many samples simultaneously (Taberlet et al., 2018). As an accurate means of detecting and identifying not just common species, but also cryptic and rare species, metabarcoding has in many cases superseded traditional methods such as morphological analysis

West Nile Virus (WNV) is a globally important mosquito borne virus, with significant implications for human and animal health. The emergence and spread of new lineages, and increased pathogenicity, is the cause of escalating public health concern. Pinpointing the environmental conditions that favour WNV circulation and transmission to humans is challenging, due both to the complexity of its biological cycle, and the under-diagnosis and reporting of epidemiological data. Here, we used remote sensing and GIS to enable collation of multiple types of environmental data over a continental spatial scale, in order to model annual West Nile Fever (WNF) incidence across Europe and neighbouring countries. Multi-model selection and inference were used to gain a consensus from multiple linear mixed models. Climate and landscape were key predictors of WNF outbreaks (specifically, high precipitation in late winter/early spring, high summer temperatures, summer drought, occurrence of irrigated croplands and highly fragmented forests). Identification of the environmental conditions associated with WNF outbreaks is key to enabling public health bodies to properly focus surveillance and mitigation of West Nile virus impact, but more work needs to be done to enable accurate predictions of WNF risk.

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BackgroundWest Nile Virus (WNV) is an emerging global health threat. Transmission risk is strongly related to the abundance of mosquito vectors, typically Culex pipiens in Europe. Early-warning predictors of mosquito population dynamics would therefore help guide entomological surveillance and thereby facilitate early warnings of transmission risk.MethodsWe analysed an 11-year time series (2001 to 2011) of Cx. pipiens mosquito captures from the Piedmont region of north-western Italy to determine the principal drivers of mosquito population dynamics. Linear mixed models were implemented to examine the relationship between Cx. pipiens population dynamics and environmental predictors including temperature, precipitation, Normalized Difference Water Index (NDWI) and the proximity of mosquito traps to urban areas and rice fields.ResultsWarm temperatures early in the year were associated with an earlier start to the mosquito season and increased season length, and later in the year, with decreased abundance. Early precipitation delayed the start and shortened the length of the mosquito season, but increased total abundance. Conversely, precipitation later in the year was associated with a longer season. Finally, higher NDWI early in the year was associated with an earlier start to the season and increased season length, but was not associated with abundance. Proximity to rice fields predicted higher total abundance when included in some models, but was not a significant predictor of phenology. Proximity to urban areas was not a significant predictor in any of our models. Predicted variations in start of the season and season length ranged from one to three weeks, across the measured range of variables. Predicted mosquito abundance was highly variable, with numbers in excess of 1000 per trap per year when late season temperatures were low (average 21°C) to only 150 when late season temperatures were high (average 30°C).ConclusionsClimate data collected early in the year, in conjunction with local land use, can be used to provide early warning of both the timing and magnitude of mosquito outbreaks. This potentially allows targeted mosquito control measures to be implemented, with implications for prevention and control of West Nile Virus and other mosquito borne diseases.