title: Influence of network dynamics on the spread of sexually transmitted diseases.
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.
authors: Consejo Nacional de Investigaciones Científicas y Técnicas, Centro Atómico Bariloche, 8400 San Carlos de Bariloche, Argentina. srisau@cab.cnea.gov.ar
authors: Sebastián
authors: S
authors: Risau-Gusman
mesh_terms: D003198:Computer Simulation; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D015995:Prevalence; D012749:Sexually Transmitted Diseases / Q000453:epidemiology*; D012944:Social Support