Total number of WNV-positive pools for each year and cluster.

Total number of WNV-positive pools for each year and cluster.</p

Simulated outbreak frequency of WNV into the mosquito population during the summer season.

Simulated outbreak frequency of WNV into the mosquito population during the summer season.</p

Ranges of <i>R</i>₀ estimates. <i>R</i>₀ values were calculated at 2.5% and 97.5% percentile of parameter estimates for each considered parameter, while others were assumed equal to their estimated average.

Ranges of R0 estimates. R0 values were calculated at 2.5% and 97.5% percentile of parameter estimates for each considered parameter, while others were assumed equal to their estimated average.</p

Outbreak frequency as a function of temperature (10–30°C) and different vector-host ratios.

Outbreak frequency as a function of temperature (10–30°C) and different vector-host ratios.</p

Total number of analysed mosquito pools for each year and cluster.

Total number of analysed mosquito pools for each year and cluster.</p

Supplementary information.

West Nile disease is a vector-borne disease caused by West Nile virus (WNV), involving mosquitoes as vectors and birds as maintenance hosts. Humans and other mammals can be infected via mosquito bites, developing symptoms ranging from mild fever to severe neurological infection. Due to the worldwide spread of WNV, human infection risk is high in several countries. Nevertheless, there are still several knowledge gaps regarding WNV dynamics. Several aspects of transmission taking place between birds and mosquitoes, such as the length of the infectious period in birds or mosquito biting rates, are still not fully understood, and precise quantitative estimates are still lacking for the European species involved. This lack of knowledge affects the precision of parameter values when modelling the infection, consequently resulting in a potential impairment of the reliability of model simulations and predictions and in a lack of the overall understanding of WNV spread. Further investigations are thus needed to better understand these aspects, but field studies, especially those involving several wild species, such as in the case of WNV, can be challenging. Thus, it becomes crucial to identify which transmission processes most influence the dynamics of WNV. In the present work, we propose a sensitivity analysis to investigate which of the selected epidemiological parameters of WNV have the largest impact on the spread of the infection. Based on a mathematical model simulating WNV spread into the Lombardy region (northern Italy), the basic reproduction number of the infection was estimated and used to quantify infection spread into mosquitoes and birds. Then, we quantified how variations in four epidemiological parameters representing the duration of the infectious period in birds, the mosquito biting rate on birds, and the competence and susceptibility to infection of different bird species might affect WNV transmission. Our study highlights that knowledge gaps in WNV epidemiology affect the precision in several parameters. Although all investigated parameters affected the spread of WNV and the modelling precision, the duration of the infectious period in birds and mosquito biting rate are the most impactful, pointing out the need of focusing future studies on a better estimate of these parameters at first. In addition, our study suggests that a WNV outbreak is very likely to occur in all areas with suitable temperatures, highlighting the wide area where WNV represents a serious risk for public health.</div

Effect of different changes in model parameters on the R_t ratio.

Effect of A) fraction of bites on competent birds (f); B) bird competence (p); C) bird susceptibility to infection (pMB); and D) duration of infectious period in birds (νB) on R0 in each sub-region and year of simulation (solid lines). Dotted lines represent the mean value of R0. The grey boxplot provided for each panel visualises the posterior distribution of the parameter investigated. The posterior distribution of parameters is visualised using the same y axis to compare the shown distributions.</p

Capture site division proposed for the Lombardy region.

Red quadrats represent the northern subregion, green quadrats represent the western subregion, and blue quadrats represent the eastern subregion. Black squares, circles and triangles represent mosquito capture sites for 2016, 2017 and 2018, respectively. This map was generated using R 4.1.2 (raster package, http://gadm.org source).</p

WNV outbreak frequency in the mosquito population according to parameters variability.

WNV outbreak frequency in the mosquito population during the summer season depended on the variation in A) fraction of bites on competent birds (f); B) bird competence (p); C) bird susceptibility (pMB) and D) duration of infectious period in birds (νB) estimates. The solid red line represents the outbreak frequency estimated using the mean value of the parameters’ posterior distributions. The red-shaded area shows the outbreak frequency obtained assuming all free parameters but one (allowed to range in the 95%CI) equal to their average.</p

Recorded average entomological captures for each year and cluster.

Recorded average entomological captures for each year and cluster.</p