ArticleJournal of mathematical biology2015
SI infection on a dynamic partnership network: characterization of R0.
Article in Journal of mathematical biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Modeling outbreak data: Analysis of a 2012 Ebola virus disease epidemic in DRC.Biomath (Sofia, Bulgaria) · 2019Article
- EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks.Journal of statistical software · 2018Article
- Branching process approach for epidemics in dynamic partnership network.Journal of mathematical biology · 2018Article
- Forward reachable sets: Analytically derived properties of connected components for dynamic networks.Network science (Cambridge University Press) · 2017Article
- Pair formation models for sexually transmitted infections: A primer.Infectious Disease Modelling · 2017Review
- Gender asymmetry in concurrent partnerships and HIV prevalence.Epidemics · 2017Article
- Mathematical models of SIR disease spread with combined non-sexual and sexual transmission routes.Infectious Disease Modelling · 2017Article
- Dangerous connections: on binding site models of infectious disease dynamics.Journal of mathematical biology · 2017Article
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3 authors.
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Abstract
We model the spread of an SI (Susceptible → Infectious) sexually transmitted infection on a dynamic homosexual network. The network consists of individuals with a dynamically varying number of partners. There is demographic turnover due to individuals entering the population at a constant rate and leaving the population after an exponentially distributed time. Infection is transmitted in partnerships between susceptible and infected individuals. We assume that the state of an individual in this structured population is specified by its disease status and its numbers of susceptible and infected partners. Therefore the state of an individual changes through partnership dynamics and transmission of infection. We assume that an individual has precisely n 'sites' at which a partner can be bound, all of which behave independently from one another as far as forming and dissolving partnerships are concerned. The population level dynamics of partnerships and disease transmission can be described by a set of (n +1)(n +2) differential equations. We characterize the basic reproduction ratio R0 using the next-generation-matrix method. Using the interpretation of R0 we show that we can reduce the number of states-at-infection n to only considering three states-at-infection. This means that the stability analysis of the disease-free steady state of an (n +1)(n +2)-dimensional system is reduced to determining the dominant eigenvalue of a 3 × 3 matrix. We then show that a further reduction to a 2 × 2 matrix is possible where all matrix entries are in explicit form. This implies that an explicit expression for R0 can be found for every value of n.
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