ArticleJournal of the Royal Society, Interface2012
Influence of network dynamics on the spread of sexually transmitted diseases.
Article in Journal of the Royal Society, Interface, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Coupling dynamics of epidemic spreading and information diffusion on complex networks.Applied mathematics and computation · 2018Article
- Molecular epidemiology of Neisseria gonorrhoeae strains circulating in Indonesia using multi-locus variable number tandem repeat analysis (MLVA) and Neisseria gonorrhoeae multi-antigen sequence typing (NG-MAST) techniques.BMC infectious diseases · 2018Article
- Predicting and controlling infectious disease epidemics using temporal networks.F1000prime reports · 2013Article
- Epidemics scenarios in the "Romantic network".PloS one · 2012Article
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1 author.
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Abstract
Network epidemiology often assumes that the relationships defining the social network of a population are static. The dynamics of relationships is only taken indirectly into account by assuming that the relevant information to study epidemic spread is encoded in the network obtained, by considering numbers of partners accumulated over periods of time roughly proportional to the infectious period of the disease. On the other hand, models explicitly including social dynamics are often too schematic to provide a reasonable representation of a real population, or so detailed that no general conclusions can be drawn from them. Here, we present a model of social dynamics that is general enough so its parameters can be obtained by fitting data from surveys about sexual behaviour, but that can still be studied analytically, using mean-field techniques. This allows us to obtain some general results about epidemic spreading. We show that using accumulated network data to estimate the static epidemic threshold lead to a significant underestimation of that threshold. We also show that, for a dynamic network, the relative epidemic threshold is an increasing function of the infectious period of the disease, implying that the static value is a lower bound to the real threshold. A practical example is given of how to apply the model to the study of a real population.
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