The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Simulated Epidemics in an Empirical Spatiotemporal Network of 50,185 Sexual Contacts
Open accessAbstract
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.
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Cites
Dynamics and Control of Diseases in Networks with Community Structure
Salathé, M., & Jones, J. H. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000736 · Cited by 586
Cited by
Epidemic processes in complex networks
Pastor-Satorras, R., Castellano, C., Van Mieghem, P., & Vespignani, A. (2015) · Reviews of Modern Physics · doi:10.1103/revmodphys.87.925 · Cited by 3,697
Holme, P., & Saramäki, J. (2012) · Physics Reports · doi:10.1016/j.physrep.2012.03.001 · Cited by 2,736
“Thus one can go straight from the raw data to simulations of spreading processes (or some other dynamics), and analyze the role of the temporal and topological structure by comparing the results to referencemodels [155].”
BackgroundResultSelf-citationStatistical physics of vaccination
Wang, Z., Bauch, C. T., Bhattacharyya, S., d'Onofrio, A., Manfredi, P., Perc, M., Perra, N., Salathé, M., & Zhao, D. (2016) · Physics Reports · doi:10.1016/j.physrep.2016.10.006 · Cited by 872
Modern temporal network theory: a colloquium
Holme, P. (2015) · The European Physical Journal B · doi:10.1140/epjb/e2015-60657-4 · Cited by 734
Self-citationMathematical modeling of infectious disease dynamics
Siettos, C. I., & Russo, L. (2013) · Virulence · doi:10.4161/viru.24041 · Cited by 466
Metadata
- Authors
- Rocha, L. E. C., Liljeros, F., & Holme, P.
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2011-03-17
- Volume
- 7
- Issue
- 3
- Pages
- e1001109
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- OpenAlex
- W1975443659
- Cited by
- 322
- References
- 1
- FWCI
- 23.23
- Type
- journal article
- Language
- en
- Open access
- gold
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- Rocha, L. E. C., Liljeros, F., & Holme, P. (2011). Simulated Epidemics in an Empirical Spatiotemporal Network of 50,185 Sexual Contacts. PLoS Computational Biology. https://doi.org/10.1371/journal.pcbi.1001109
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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