Literature DB >> 29738720

Epidemics on plants: Modeling long-range dispersal on spatially embedded networks.

Juddy H Arias1, Jesus Gómez-Gardeñes2, Sandro Meloni3, Ernesto Estrada4.   

Abstract

Here we develop an epidemic model that accounts for long-range dispersal of pathogens between plants. This model generalizes the classical compartmental models-Susceptible-Infected-Susceptible (SIS) and Susceptible-Infected-Recovered (SIR)-to take into account those factors that are key to understand epidemics in real plant populations. These ingredients are the spatial characteristics of the plots and fields in which plants are embedded and the effect of long-range dispersal of pathogens. The spatial characteristics are included through the use of random rectangular graphs which allow to consider the effects of the elongation of plots and fields, while the long-range dispersal is implemented by considering transformations, such as the Mellin and Laplace transforms, of a generalization of the adjacency matrix of the geometric graph. Our results point out that long-range dispersal favors the propagation of pathogens while the elongation of plant plots increases the epidemic threshold and decreases dramatically the number of affected plants. Interestingly, our model is able of reproducing the existence of patchy regions of infected plants and the absence of a clear propagation front centered in the initial infected plants, as it is observed in real plant epidemics.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Keywords:  Plant diseases; Spatial networks; Susceptible-Infected- Susceptible; Susceptible-Infected-Recovered

Year:  2018        PMID: 29738720     DOI: 10.1016/j.jtbi.2018.05.004

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  2 in total

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Authors:  Alfonso Allen-Perkins; Ernesto Estrada
Journal:  Proc Math Phys Eng Sci       Date:  2019-06-19       Impact factor: 2.704

2.  Mathematical Modeling Suggests Cooperation of Plant-Infecting Viruses.

Authors:  Joshua Miller; Tessa M Burch-Smith; Vitaly V Ganusov
Journal:  Viruses       Date:  2022-03-31       Impact factor: 5.818

  2 in total

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