Epidemic spreading in random rectangular networks

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Estrada, Ernesto and Meloni, Sandro and Sheerin, Matthew and Moreno, Yamir (2016) Epidemic spreading in random rectangular networks. Physical Review E, 94 (5). 052316. ISSN 2470-0053 (https://doi.org/10.1103/PhysRevE.94.052316)

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Abstract

The use of network theory to model disease propagation on populations introduces important elements of reality to the classical epidemiological models. The use of random geometric graphs (RGG) is one of such network models that allows for the consideration of spatial properties on disease propagation. In certain real-world scenarioslike in the analysis of a disease propagating through plantsthe shape of the plots and fields where the host of the disease is located may play a fundamental role on the propagation dynamics. Here we consider a generalization of the RGG to account for the variation of the shape of the plots/fields where the hosts of a disease are allocated. We consider a disease propagation taking place on the nodes of a random rectangular graph (RRG) and we consider a lower bound for the epidemic threshold of a Susceptible-Infected- Susceptible (SIS) or Susceptible-Infected-Recovered (SIR) model on these networks. Using extensive numerical simulations and based on our analytical results we conclude that (ceteris paribus) the elongation of the plot/field in which the nodes are distributed makes the network more resilient to the propagation of a disease due to the fact that the epidemic threshold increases with the elongation of the rectangle. These results agree with accumulated empirical evidence and simulation results about the propagation of diseases on plants in plots/fields of the same area and different shapes.

ORCID iDs

Estrada, Ernesto ORCID logoORCID: https://orcid.org/0000-0002-3066-7418, Meloni, Sandro, Sheerin, Matthew ORCID logoORCID: https://orcid.org/0000-0001-5708-7555 and Moreno, Yamir;
  • Item type:Article
    ID code:59390
    Dates:
    Date
    Event
    28 November 2016
    Published
    9 November 2016
    Accepted
    Subjects:Science > Physics
    Department:Faculty of Science > Mathematics and Statistics
    Depositing user: Pure Administrator
    Date deposited:11 Jan 2017 13:27
    Last modified:11 Nov 2024 11:35
    URI:https://strathprints.strath.ac.uk/id/eprint/59390
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