The great circle epidemic model

Frank Ball, Peter Neal

    Research output: Contribution to journalArticlepeer-review

    Abstract

    We consider a stochastic model for the spread of an epidemic among a population of n individuals that are equally spaced around a circle. Throughout its infectious period, a typical infective, i say, makes global contacts, with individuals chosen independently and uniformly from the whole population, and local contacts, with individuals chosen independently and uniformly according to a contact distribution centred on i. The asymptotic situation in which the local contact distribution converges weakly as n→∞ is analysed. A branching process approximation for the early stages of an epidemic is described and made rigorous as n→∞ by using a coupling argument, yielding a threshold theorem for the model. A central limit theorem is derived for the final outcome of epidemics that take off, by using an embedding representation. The results are specialised to the case of a symmetric, nearest-neighbour local contact distribution. © 2003 Elsevier B.V. All rights reserved.
    Original languageEnglish
    Pages (from-to)233-268
    Number of pages35
    JournalStochastic Processes and their Applications
    Volume107
    Issue number2
    DOIs
    Publication statusPublished - 1 Oct 2003

    Keywords

    • Branching process
    • Central limit theorems
    • Coupling
    • Epidemic process
    • Small-world models
    • Weak convergence

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