An eco-epidemiological model supporting rational disease management of Xylella fastidiosa. An application to the outbreak in Apulia (Italy)

Knowledge on the dynamics of Xylella fastidiosa infection is an essential element for the effective management of new foci. In this study, we propose an Eco-epidemiological Model (XEM) describing the infection dynamics of X. fastidiosa outbreaks. XEM can be applied to design disease management strategies and compare their level of efficacy. XEM is a spatial explicit mechanistic model for short-range spread of X. fastidiosa considering: i) the growth of the bacterium in the host plant, ii) the acquisition of the pathogen by the vector and its transmission to host plants, iii) the vector population dynamics, iv) the dispersal of the vector. The model is parametrized based on data acquired on the spread of X. fastidiosa subsp. pauca in olive groves in the Apulia region. Four epide-miological scenarios were considered combining host susceptibility and vector abundance. Eight management strategies were compared testing several levels of vector control efficacy, plant cutting radius, time to detection and intervention. Simulation results showed that the abundance of the vector is the key factor determining the spread rate of the pathogen. Vector control efficacy and time to detection and intervention emerged as the key factors for an effective eradication strategy. XEM proved to be a suitable tool to support decision making for the drafting and management of emergency plans related to new outbreaks.

Automated summary

In this study, an Eco-epidemiological Model (XEM) was proposed to describe the infection dynamics of X. fastidiosa outbreaks. The model considers various factors such as host plant growth, pathogen acquisition and transmission by vectors, vector population dynamics, and vector dispersal. Simulation results showed that vector abundance is the key factor determining the spread rate of the pathogen, and vector control efficacy and time to detection and intervention are crucial for effective eradication strategies. XEM proved to be a suitable tool for decision making in emergency plans related to new outbreaks.