Encyclopedia of Complexity and Systems Science

Living Edition
| Editors: Robert A. Meyers

Human Sexual Networks

  • Fredrik Liljeros
Living reference work entry
DOI: https://doi.org/10.1007/978-3-642-27737-5_275-2

Definition

Human sexual networks are the network structures that emerge when individuals have sexual contact with each other. In general, use of the term “sexual contact” is restricted in this entry to mean vaginal or anal intercourse or oral sex – contacts by which sexually transmitted infections (STIs) can be transmitted. Sexual networks are important because an understanding of their structure and how they facilitate the spread of infection can help us understand how the spread of this type of infection can best be prevented.

Introduction

Although the type of contact that spreads STIs occurs less frequently than is the case for most other types of contact that spread disease, the spread of STIs has turned out to be surprisingly hard to limit. The difficulties in getting STIs under control have led to an interest in sexual contact patterns (Liljeros et al. 2003; Morris 2004; Morris et al. 2007). In this entry, we discuss a variety of explanations related to the structural properties...

Keywords

Sexual Contact Line Graph Preferential Attachment Infected Person Contact Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in to check access.

Bibliography

  1. Anderson R, May RM (1991) Infectious diseases of humans. Oxford University Press, OxfordGoogle Scholar
  2. Barabási AL, Albert R (1999) Emergence of scaling in random networks. Science 286(5439):509–512ADSCrossRefMathSciNetGoogle Scholar
  3. Bearman PS, Moody J et al (2004) Chains of affection: the structure of adolescent romantic and sexual networks. Am J Sociol 110(1):44–91CrossRefGoogle Scholar
  4. Brewer DD, Potterat JJ, Garrett SB, Muth SQ, Roberts JM, Kazprzyk D, Montano DE, Darrow WW (2000) Prostitution and the sex discrepancy in reported number of sexual partners. Proc Natl Acad Sci U S A 97:12385–12388ADSCrossRefGoogle Scholar
  5. Colgate SA, Stanley EA et al (1989) Risk behavior-based model of the cubic growth of acquired immunodeficiency syndrome in the United States. Proc Natl Acad Sci U S A 86(12):4793–4797ADSCrossRefGoogle Scholar
  6. Dezso Z, Barabasi AL (2002) Halting viruses in scale-free networks. Phys Rev E Stat Nonlin Soft Matter Phys 65(5 Pt 2):055103ADSCrossRefGoogle Scholar
  7. Diekman O, Heesterbeek JAP (2000) Mathematical epidemiology of infectious disease. Wiley, ChichesterGoogle Scholar
  8. Foulkes MA (1998) Advances in HIV/AIDS statistical methodology over the past decade. Stat Med 17(1):1–25CrossRefMathSciNetGoogle Scholar
  9. Frank O (1971) Statistical inference in graphs. FOA, StockholmGoogle Scholar
  10. Freiesleben de Blasio B, Svensson B et al (2007) Preferential attachment in sexual networks. Proc Natl Acad Sci U S A 104(26):10762–10767CrossRefGoogle Scholar
  11. Handcock MS, Jones JH (2004) Likelihood-based inference for stochastic models of sexual network formation. Theor Popul Biol 65(4):413–422CrossRefzbMATHGoogle Scholar
  12. Harary F (1969) Graph theory. Addison-Wesley, ReadingGoogle Scholar
  13. Hethcote H, Yorke JA (1984) Gonorrhea transmission dynamics and control. Springer, New YorkCrossRefzbMATHGoogle Scholar
  14. Hiltunen-Back E, Haikala O et al (2003) Nationwide increase of Chlamydia trachomatis infection in Finland – highest rise among adolescent women and men. Sex Transm Dis 30(10):737–741CrossRefGoogle Scholar
  15. Holme P, Edling CR et al (2004) Structure and time evolution of an internet dating community. Soc Netw 26(2):155–174CrossRefGoogle Scholar
  16. Johnson AM, Mercer CH et al (2001) Sexual behaviour in Britain: partnerships, practices, and HIV risk behaviours. Lancet 358(9296):1835–1842CrossRefGoogle Scholar
  17. Jones JH, Handcock MS (2003a) An assessment of preferential attachment as a mechanism for human sexual network formation. Proc Biol Sci 270(1520):1123–1128CrossRefGoogle Scholar
  18. Jones JH, Handcock MS (2003b) Social networks: sexual contacts and epidemic thresholds. Nature 423(6940):605–606, discussion 606ADSCrossRefGoogle Scholar
  19. Klovdahl AS (1985) Social networks and the spread of infectious diseases: the AIDS example. Soc Sci Med 21(11):1203–1216CrossRefGoogle Scholar
  20. Kretzschmar M, Morris M (1996) Measures of concurrency in networks and the spread of infectious disease. Math Biosci 133(2):165–195CrossRefzbMATHGoogle Scholar
  21. Laumann EO, Gagnon JH et al (1994) The social organization of sexuality. University of Chicago Press, ChicagoGoogle Scholar
  22. Lewin B (ed) (2000) Sex in Sweden. The Swedish National Institute of Public Health, StockholmGoogle Scholar
  23. Liljeros F, Edling CR et al (2001) The web of human sexual contacts. Nature 411(6840):907–908ADSCrossRefGoogle Scholar
  24. Liljeros F, Edling CR et al (2003) Sexual networks: implications for the transmission of sexually transmitted infections. Microbes Infect 5(2):189–196CrossRefGoogle Scholar
  25. Lloyd AL, May RM (2001) Epidemiology. How viruses spread among computers and people. Science 292(5520):1316–1317CrossRefGoogle Scholar
  26. Moody J (2002) The importance of relationship timing for diffusion. Soc Forces 81(1):25–56CrossRefGoogle Scholar
  27. Morris M (1993) Telling tails explain the discrepancy in sexual partner reports. Nature 365(6445):437–440ADSCrossRefGoogle Scholar
  28. Morris M (ed) (2004) Network epidemiology: a handbook for survey design and data collection. Oxford University Press, New YorkGoogle Scholar
  29. Morris M, Kretzschmar M (1995) Concurrent partnerships and transmission dynamics in networks. Soc Netw 17(3–4):299–318CrossRefGoogle Scholar
  30. Morris M, Kretzschmar M (1997) Concurrent partnerships and the spread of HIV. Aids 11(5):641–648CrossRefGoogle Scholar
  31. Morris M, Goodreau S et al (2007) Sexual networks, concurrency, and STD/HIV. In: Holmes KK, Sparling PF, Stamm WE (eds) Sexually transmitted diseases. McGraw-Hill, New YorkGoogle Scholar
  32. Newman MEJ (2002) Assortative mixing in networks. Phys Rev Lett 89(20):1–4CrossRefGoogle Scholar
  33. Newman MEJ (2003a) Mixing patterns in networks. Phys Rev E 67(2):1–13Google Scholar
  34. Newman MEJ (2003b) Properties of highly clustered networks. Phys Rev E 68(2):026121ADSCrossRefGoogle Scholar
  35. Nordvik MK, Liljeros F (2006) Number of sexual encounters involving intercourse and the transmission of sexually transmitted infections. Sex Transm Dis 33(6):342–349CrossRefGoogle Scholar
  36. Nordvik MK, Liljeros F et al (2007) Spatial bridges and the spread of Chlamydia: the case of a county in Sweden. Sex Transm Dis 34(1):47–53CrossRefGoogle Scholar
  37. Pastor-Satorras R, Vespignani A (2001a) Epidemic dynamics and endemic states in complex networks. Phys Rev E 63(066117):1–8Google Scholar
  38. Pastor-Satorras R, Vespignani A (2001b) Epidemic spreading in scale-free networks. Phys Rev Lett 86:3200–3203ADSCrossRefGoogle Scholar
  39. Pastor-Satorras R, Vespignani A (2002) Epidemic dynamics in finite size scale-free networks. Phys Rev E Stat Nonlin Soft Matter Phys 65(3 Pt 2A):035108ADSCrossRefGoogle Scholar
  40. Potterat JJ, Woodhouse DE et al (2004) Network dynamism: history and lessons of the Colorado Springs study. In: Morris M (ed) Network epidemiology: a handbook for survey design and data collection. Oxford University Press, New York, pp 87–114Google Scholar
  41. Price DJ (1976) A general theory of bibliometric and other cumulative advantage processes. J Am Soc Inf Sci 27:292–306CrossRefGoogle Scholar
  42. Riolo CS, Koopman JS et al (2001) Methods and measures for the description of epidemiologic contact networks. J Urban Health 78(3):446–457CrossRefGoogle Scholar
  43. Schneeberger A, Mercer CH et al (2004) Scale-free networks and sexually transmitted diseases: a description of observed patterns of sexual contacts in Britain and Zimbabwe. Sex Transm Dis 31(6):380–387CrossRefGoogle Scholar
  44. Simon HA (1955) On a class of skew distribution functions. Biometrika 42:425–440CrossRefzbMATHMathSciNetGoogle Scholar
  45. Szendroi B, Csányi G (2004) Polynomial epidemics and clustering in contact networks. Proc Biol Sci Aug 7(271 Suppl 5):S364–S366CrossRefGoogle Scholar
  46. Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393(6684):440–442ADSCrossRefGoogle Scholar
  47. Wylie JL, Jolly A (2001) Patterns of chlamydia and gonorrhea infection in sexual networks in Manitoba, Canada. Sex Transm Dis 28(1):14–24CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2011

Authors and Affiliations

  1. 1.Department of SociologyStockholm UniversityStockholmSweden