Mean-field models for non-Markovian epidemics on networks View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2018-02

AUTHORS

Neil Sherborne, Joel C. Miller, Konstantin B. Blyuss, Istvan Z. Kiss

ABSTRACT

This paper introduces a novel extension of the edge-based compartmental model to epidemics where the transmission and recovery processes are driven by general independent probability distributions. Edge-based compartmental modelling is just one of many different approaches used to model the spread of an infectious disease on a network; the major result of this paper is the rigorous proof that the edge-based compartmental model and the message passing models are equivalent for general independent transmission and recovery processes. This implies that the new model is exact on the ensemble of configuration model networks of infinite size. For the case of Markovian transmission the message passing model is re-parametrised into a pairwise-like model which is then used to derive many well-known pairwise models for regular networks, or when the infectious period is exponentially distributed or is of a fixed length. More... »

PAGES

755-778

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00285-017-1155-0

DOI

http://dx.doi.org/10.1007/s00285-017-1155-0

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1090371322

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28685365


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