ArticleJournal of mathematical biology2017
Dangerous connections: on binding site models of infectious disease dynamics.
Article in Journal of mathematical biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Dynamic shift in the dominant transmission route of clade Ib monkeypox virus across networks with sexual and nonsexual contacts.Science advances · 2026Article
- A stochastic SIR network epidemic model with preventive dropping of edges.Journal of mathematical biology · 2019Article
- Branching process approach for epidemics in dynamic partnership network.Journal of mathematical biology · 2018Article
- The relationships between message passing, pairwise, Kermack-McKendrick and stochastic SIR epidemic models.Journal of mathematical biology · 2017Article
- Article
- Systematic Approximations to Susceptible-Infectious-Susceptible Dynamics on Networks.PLoS computational biology · 2016Article
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2 authors.
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Abstract
We formulate models for the spread of infection on networks that are amenable to analysis in the large population limit. We distinguish three different levels: (1) binding sites, (2) individuals, and (3) the population. In the tradition of physiologically structured population models, the formulation starts on the individual level. Influences from the 'outside world' on an individual are captured by environmental variables. These environmental variables are population level quantities. A key characteristic of the network models is that individuals can be decomposed into a number of conditionally independent components: each individual has a fixed number of 'binding sites' for partners. The Markov chain dynamics of binding sites are described by only a few equations. In particular, individual-level probabilities are obtained from binding-site-level probabilities by combinatorics while population-level quantities are obtained by averaging over individuals in the population. Thus we are able to characterize population-level epidemiological quantities, such as [Formula: see text], r, the final size, and the endemic equilibrium, in terms of the corresponding variables.
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