An Individual-Based Spatial Epidemiological Model for the Spread of Plant Diseases
Martina Cendoya (),
Ana Navarro-Quiles,
Antonio López-Quílez,
Antonio Vicent and
David Conesa
Additional contact information
Martina Cendoya: Institut Valencià d’Investigacions Agràries
Ana Navarro-Quiles: Universitat de València
Antonio López-Quílez: Universitat de València
Antonio Vicent: Institut Valencià d’Investigacions Agràries
David Conesa: Universitat de València
Journal of Agricultural, Biological and Environmental Statistics, 2025, vol. 30, issue 3, No 2, 618-637
Abstract:
Abstract In the study of plant disease epidemics, the state of each individual in the population and their spatial location should be considered when modeling disease spread. We present a model to describe the spread of plant diseases, where the infection of a susceptible individual depends on the transmission rate of infected individuals and the spatial correlation. This latter is introduced through the Matérn correlation function, accounting for spatial dependence based on distance. Almond leaf scorch disease, caused by the bacterium Xylella fastidiosa, was used as a case study to test the behavior of the model parameters and the variability due to the characteristics and location of initial disease introduction using a proposed simulation algorithm. The greatest variability in the results depended on the range parameter of the Matérn correlation, i.e., the distance at which two observations can be considered spatially uncorrelated, and the initial introduction. The spatial distribution of individuals also had a strong influence on disease spread, highlighting that areas without trees acted as barriers when their extent was greater than the range parameter. It should be stressed that this individual-based model can be applied to other plant diseases, adapting the parameter values to their particular epidemiological characteristics.
Keywords: Individual-based models; Matérn correlation; Simulation; Spatial epidemic model (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13253-024-00604-2
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