Facial reconstruction

Search LJMU Research Online

Browse Repository | Browse E-Theses

Complete hierarchies of SIR models on arbitrary networks with exact and approximate moment closure

Sharkey, KJ and Wilkinson, RR (2015) Complete hierarchies of SIR models on arbitrary networks with exact and approximate moment closure. Mathematical Biosciences, 264. pp. 74-85. ISSN 0025-5564

[img]
Preview
Text
Complete hierarchies of SIR models on arbitrary networks with exact and approximate moment closure.pdf - Published Version
Available under License Creative Commons Attribution.

Download (799kB) | Preview

Abstract

We first generalise ideas discussed by Kiss et al. (2015) to prove a theorem for generating exact closures (here expressing joint probabilities in terms of their constituent marginal probabilities) for susceptible-infectious-removed (SIR) dynamics on arbitrary graphs (networks). For Poisson transmission and removal processes, this enables us to obtain a systematic reduction in the number of differential equations needed for an exact ‘moment closure’ representation of the underlying stochastic model. We define ‘transmission blocks’ as a possible extension of the block concept in graph theory and show that the order at which the exact moment closure representation is curtailed is the size of the largest transmission block. More generally, approximate closures of the hierarchy of moment equations for these dynamics are typically defined for the first and second order yielding mean-field and pairwise models respectively. It is frequently implied that, in principle, closed models can be written down at arbitrary order if only we had the time and patience to do this. However, for epidemic dynamics on networks, these higher-order models have not been defined explicitly. Here we unambiguously define hierarchies of approximate closed models that can utilise subsystem states of any order, and show how well-known models are special cases of these hierarchies.

Item Type: Article
Uncontrolled Keywords: 01 Mathematical Sciences, 06 Biological Sciences
Subjects: Q Science > QA Mathematics
Divisions: Applied Mathematics
Publisher: Elsevier BV
Date Deposited: 03 Jul 2019 10:11
Last Modified: 03 Jul 2019 10:15
DOI or Identification number: 10.1016/j.mbs.2015.03.008
URI: http://researchonline.ljmu.ac.uk/id/eprint/10967

Actions (login required)

View Item View Item