Abstract
Sexual contact patterns, both in their temporal and network structure, can influence the spread of sexually transmitted infections (STI). Most previous literature has focused on effects of network topology; few studies have addressed the role of temporal structure. We simulate disease spread using SI and SIR models on an empirical temporal network of sexual contacts in high-end prostitution. We compare these results with several other approaches, including randomization of the data, classic mean-field approaches, and static network simulations. We observe that epidemic dynamics in this contact structure have well-defined, rather high epidemic thresholds. Temporal effects create a broad distribution of outbreak sizes, even if the per-contact transmission probability is taken to its hypothetical maximum of 100%. In general, we conclude that the temporal correlations of our network accelerate outbreaks, especially in the early phase of the epidemics, while the network topology (apart from the contact-rate distribution) slows them down. We find that the temporal correlations of sexual contacts can significantly change simulated outbreaks in a large empirical sexual network. Thus, temporal structures are needed alongside network topology to fully understand the spread of STIs. On a side note, our simulations further suggest that the specific type of commercial sex we investigate is not a reservoir of major importance for HIV.
Original language | English |
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Pages (from-to) | e1001109 |
Journal | PLOS Computational Biology |
Volume | 7 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2011 |
Keywords
- Brazil
- Computer Simulation
- Disease Outbreaks
- Female
- Humans
- Internet
- Male
- Models, Biological
- Models, Statistical
- Prostitution
- Sexual Partners
- Sexually Transmitted Diseases