Approximating Quasi-Stationary Behaviour in Network-Based SIS Dynamics View Full Text


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Article Info

DATE

2021-11-20

AUTHORS

Christopher E. Overton, Robert R. Wilkinson, Adedapo Loyinmi, Joel C. Miller, Kieran J. Sharkey

ABSTRACT

Deterministic approximations to stochastic Susceptible–Infectious–Susceptible models typically predict a stable endemic steady-state when above threshold. This can be hard to relate to the underlying stochastic dynamics, which has no endemic steady-state but can exhibit approximately stable behaviour. Here, we relate the approximate models to the stochastic dynamics via the definition of the quasi-stationary distribution (QSD), which captures this approximately stable behaviour. We develop a system of ordinary differential equations that approximate the number of infected individuals in the QSD for arbitrary contact networks and parameter values. When the epidemic level is high, these QSD approximations coincide with the existing approximation methods. However, as we approach the epidemic threshold, the models deviate, with these models following the QSD and the existing methods approaching the all susceptible state. Through consistently approximating the QSD, the proposed methods provide a more robust link to the stochastic models. More... »

PAGES

4

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11538-021-00964-7

DOI

http://dx.doi.org/10.1007/s11538-021-00964-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1142711324

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/34800180


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