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Background: In recent years, Europe has experienced several outbreaks of West Nile Virus (WNV), a mosquito-borne pathogen. This study aims to quantify the impact of weekly mean temperature and cumulative precipitation on human cases of West Nile Neuroinvasive Disease (WNND), to assess the feasibility of climate-informed early warning systems for severe forms of WNV infection.

Methods: Using a space-time-stratified case-crossover design, the short-term effects of meteorological factors on WNND cases reported in Europe from 2014 to 2022 were examined. Distributed lag nonlinear models were implemented in conditional logistic regressions to assess the delayed and nonlinear effects of temperature and precipitation on WNND risk as well as to estimate the Attributable Fraction (AF) of cases to extreme values of the two meteorological factors.

Findings: Between 2014 and 2022, Europe reported 3437 WNND cases. Both meteorological factors recorded in the 8 weeks before symptom onset showed positive and delayed effects on WNND risk. The strongest effect was found for weekly mean temperatures at 2 weeks lag (Odds Ratio (OR): 1.15; 95% Confidence Interval (CI) 1.12–1.19) and for weekly cumulative precipitation at 3 weeks lag (OR: 1.12; 95% CI 1.09–1.16). Of all WNND cases analyzed, 36.4% (95% CI, 31.3%–40.3%) could be attributed to weekly mean temperatures exceeding the 25 °C, while 13.1% (95% CI, 9.5%–16.4%) to weekly cumulative precipitations exceeding 40 mm.

Interpretation: These findings emphasize the significance of short-term variations in temperature and precipitation in driving WNND incidence in Europe. Meteorological factors can be used to operationalize early warning systems to reduce the disease burden from WNV infections, which are continually increasing across the continent.