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

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 S...

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Bibliographic Details
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
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Summary: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.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1001109