Simulated epidemics in an empirical spatiotemporal network of 50,185 sexual contacts

• Published in: PLoS computational biology 2011-03, Vol.7 (3), p.e1001109-e1001109
• Main Authors: Rocha, Luis E C, Liljeros, Fredrik, Holme, Petter
• Format: Article
• Language: English
• Subjects: Behavior; Brazil - epidemiology; Computer Simulation; Disease Outbreaks; Disease transmission; Distribution; Epidemics; Female; Fysik; Health aspects; Humans; Infectious Diseases/Sexually Transmitted Diseases; Internet; Male; Models, Biological; Models, Statistical; NATURAL SCIENCES; NATURVETENSKAP; Physics; Physics/Interdisciplinary Physics; Prostitution; Public Health and Epidemiology/Epidemiology; Public Health and Epidemiology/Infectious Diseases; Sex; Sex Work - statistics & numerical data; Sexual Partners; Sexually transmitted diseases; Sexually Transmitted Diseases - epidemiology; Social aspects; South Korea; Studies
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1001109

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.