An epidemic model to address the spread of plant pests. The case of Xylella fastidiosa in almond trees

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Título: An epidemic model to address the spread of plant pests. The case of Xylella fastidiosa in almond trees
Autor/es: Signes Pont, María Teresa | Cortés-Plana, José Juan | Mora, Higinio | Mollá Sirvent, Rafael Alejandro
Grupo/s de investigación o GITE: Informática Industrial y Redes de Computadores | Arquitecturas Inteligentes Aplicadas (AIA)
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Tecnología Informática y Computación
Palabras clave: Xylella fastidiosa | Computational modeling | Disease expansion | Insect vector | Neighborhood pattern | Space time framework | Update rules
Área/s de conocimiento: Arquitectura y Tecnología de Computadores
Fecha de publicación: 28-dic-2020
Editor: Emerald
Cita bibliográfica: Kybernetes. 2021, 50(10): 2943-2955. https://doi.org/10.1108/K-05-2020-0320
Resumen: Purpose – The purpose of this paper is to present a discrete compartmental susceptible-asymptomatic-infected-dead (SAID) model to address the expansion of plant pests. The authors examined the case of Xylella fastidiosa in almond trees in the province of Alicante (Spain) to define the best eradication/contention protocol depending on the environmental parameters such as climatic factors, distance between trees, isolation of the plots, etc. Design/methodology/approach – This approach considers the expansion of the disease among the almond trees orchards by means of a grid model. The cells of the grid represent a tree (or even a group of trees) that can be susceptible (healthy), asymptomatic (infected by the bacterium but without symptoms), infected or dead. When time passes, the status of the cells is determined by binary rules that update following both a neighborhood and a delay pattern. The model assumes that the environmental parameters have a crucial impact on the expansion of the disease, so a grid is assigned to each parameter to model the single effect caused by this parameter. The expansion is then the weighted sum of all the grids. Findings – This proposal shows how the grid architecture, along with an update rule and a neighborhood pattern, is a valuable tool to model the pest expansion. This model has already been analyzed in previous works and has been compared with the corresponding continuous models solved by ordinary differential equations, coming to find the homologous parameters between both approaches. Thus, it has been possible to prove that the combination neighborhood-update rule is responsible for the rate of expansion and recovering/death of the illness. The delays (between susceptible and asymptomatic, asymptomatic and infected, infected and recovered/dead) may have a crucial impact on both the peak of infected and the recovery/death rate. This theoretical model has been successfully tested in the case of the dissemination of information through mobile social networks and is also currently under study in the case of expansion of COVID-19. Originality/value – This work develops a new approach for the analysis of expansion of plant pests. This approach provides both behavioral variability at the cell level (by its capability to modify the neighborhood and/or the update rule and/or the delays) and modularity (by easy scaling the number of grids). This provides a wide range of possibilities to deal with realistic scenarios.
Patrocinador/es: This work was supported by the Spanish Research Agency (AEI) and the European Regional Development Fund (ERDF) under project CloudDriver4Industry TIN2017-89266-R, and by the Conselleria of Innovation, Universities, Science and Digital Society, of the Community of Valencia, Spain, under project AICO/2020/206.
URI: http://hdl.handle.net/10045/119339
ISSN: 0368-492X (Print) | 1758-7883 (Online)
DOI: 10.1108/K-05-2020-0320
Idioma: eng
Tipo: info:eu-repo/semantics/article
Derechos: © Emerald Publishing Limited
Revisión científica: si
Versión del editor: https://doi.org/10.1108/K-05-2020-0320
Aparece en las colecciones:INV - I2RC - Artículos de Revistas
INV - AIA - Artículos de Revistas

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