Meteorological and land-use determinants of Culex pipiens s.l. spatio-temporal dynamics in Northern Italy
Anna Simonetto, Francesco Defilippo, Mattia Calzolari, Ana Maria Moreno Martin, Michele Dottori, Davide Lelli, Davide Monici, Andrea Pintossi, Antonio Lavazza, Gianni GilioliAbstract
Mosquito population dynamics are a key determinant of West Nile virus (WNV) transmission risk in temperate regions, as they regulate the timing, intensity, and spatial distribution of seasonal outbreaks. In Europe, Culex pipiens s.l. is the primary WNV vector, yet a comprehensive understanding of how its populations respond to environmental variability across multiple temporal and spatial scales remains limited. Using a nine-year entomological dataset (2014–2022) from an extensive monitoring network in Northern Italy, we investigated the spatio-temporal dynamics of Cx. pipiens s.l. across the heterogeneous landscapes of the Po Valley, a WNV-endemic area. We applied complementary statistical and machine-learning approaches to characterize between-year trends, within-year (summer) fluctuations, and long-term spatial patterns in mosquito abundance. Results showed strong persistence in population states across both years and months, consistently modulated by hydroclimatic conditions. Precipitation during the pre-activity period emerged as a dominant driver of inter-annual variability, highlighting its potential as an early indicator of summer population build-up. Within seasons, short-term temperature exerted a strong, nonlinear influence on Cx. pipiens s.l. abundance, with declines observed under extreme heat conditions. Spatial analyses identified persistent hotspots associated with irrigated agricultural systems, wetlands, and major river corridors, whereas upland and forest-dominated areas exhibited lower suitability. Overall, this study advances current knowledge of Cx. pipiens s.l. spatio-temporal dynamics and demonstrates how climatically and environmentally driven indicators can be translated into actionable tools for risk assessment and adaptive vector surveillance. These insights support improved early detection and targeted control within integrated One Health surveillance frameworks for WNV.