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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Main Authors: Luis E C Rocha, Fredrik Liljeros, Petter Holme
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2011-03-01
Series:PLoS Computational Biology
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21445228/pdf/?tool=EBI
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spelling doaj-77af69691c534a8c833be094554b87f02021-04-21T15:29:43ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582011-03-0173e100110910.1371/journal.pcbi.1001109Simulated epidemics in an empirical spatiotemporal network of 50,185 sexual contacts.Luis E C RochaFredrik LiljerosPetter HolmeSexual 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.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21445228/pdf/?tool=EBI
collection DOAJ
language English
format Article
sources DOAJ
author Luis E C Rocha
Fredrik Liljeros
Petter Holme
spellingShingle Luis E C Rocha
Fredrik Liljeros
Petter Holme
Simulated epidemics in an empirical spatiotemporal network of 50,185 sexual contacts.
PLoS Computational Biology
author_facet Luis E C Rocha
Fredrik Liljeros
Petter Holme
author_sort Luis E C Rocha
title Simulated epidemics in an empirical spatiotemporal network of 50,185 sexual contacts.
title_short Simulated epidemics in an empirical spatiotemporal network of 50,185 sexual contacts.
title_full Simulated epidemics in an empirical spatiotemporal network of 50,185 sexual contacts.
title_fullStr Simulated epidemics in an empirical spatiotemporal network of 50,185 sexual contacts.
title_full_unstemmed Simulated epidemics in an empirical spatiotemporal network of 50,185 sexual contacts.
title_sort simulated epidemics in an empirical spatiotemporal network of 50,185 sexual contacts.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2011-03-01
description 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.
url https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21445228/pdf/?tool=EBI
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