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.
Highlights
Spatiotemporal heterogeneities in sexual contact patterns are thought to influence the spread of sexually transmitted infections (STIs)
By understanding the structure of this system we can better understand the dynamics of STIs
There has been much focus on the static network structure of sexual contacts. We extend this approach and address temporal effects in a special type of sexual network—that of Internet-mediated prostitution
Summary
Spatiotemporal heterogeneities in sexual contact patterns are thought to influence the spread of sexually transmitted infections (STIs). Since epidemics can be a society-wide phenomenon, and sexual contact patterns can have structure at all scales, we need population-level sexual network data to understand STI epidemics. It is hard to collect sexual contact data on that large a scale. Small surveys and contact tracing risk missing large-scale structures [13] and emergent phenomena. An alternative way of gather information about sexual contact patterns, which covers a large number of people and explicitly maps their connections, is to use Internet data. We used a dataset of claimed sexual contacts between Brazilian escorts (high-end prostitutes) and sex buyers [14]. Contact patterns of commercial sex cannot be generalized to a whole population, but they do contain relevant information that can be used to study possible transmission pathways within a social group. Our dataset has information about the time and location of sexual contacts covering six years and 16,748 individuals
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
