Complex agent networks explaining the HIV epidemic among homosexual men in Amsterdam

Mathematics and Computers in Simulation

Volumn 80, Issue 5, 2010, Pages 1018-1030

  Mei, Shan ^a,b   Sloot, P M A ^a   Quax, Rick ^a   Zhu, Yifan ^b   Wang, Weiping ^b  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

^b NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

Author keywords

Complex networks (CNs); HIV epidemics; Men who have sex with men (MSM); Multi agent systems (MAS); Scale free

Indexed keywords

AMSTERDAM; CASUAL RELATIONSHIPS; COHORT STUDIES; COMPLEX AGENT; COMPLEX NETWORKS; EPIDEMIC MODELS; HISTORICAL DATA; HUMAN IMMUNODEFICIENCY VIRUS; SCALE-FREE; SIMULATION RESULT; SMALL POPULATION;

COMPLEXATION; COMPUTER VIRUSES; EPIDEMIOLOGY; VIRUSES;

MULTI AGENT SYSTEMS;

EID: 75849154008     PISSN: 03784754     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.matcom.2009.12.008     Document Type: Article

References (32)

1. R.F. Baggaley, N.M. Ferguson, G.P. Garnett, The epidemiological impact of antiretroviral use predicted by mathematical models: a review, Emerging Themes in Epidemiology 2 (2005).
2. Bai W., Zhou T., and Wang B. Interplay between HIV/AIDS epidemics and demographic structures based on sexual contact networks. International Journal of Modern Physics C 18 6 (2007) 1025-1045
3. Bezemer D., De Wolf F., Boerlijst M.C., Van Sighem A., Hollingsworth T.D., Prins M., Geskus R.B., Gras L., Coutinho R.A., and Fraser C. A resurgent HIV-1 epidemic among men who have sex with men in the era of potent antiretroviral therapy. AIDS 22 9 (2008) 1071-1077
4. Boily M.C., Bastos F.I., Desai K., and Masse B. Changes in the transmission dynamics of the HIV epidemic after the wide-scale use of antiretroviral therapy could explain increases in sexually transmitted infections: results from mathematical models. Sexually Transmitted Diseases 31 2 (2004) 100-112
5. Caceres C.F., and Van Griensven G.J.P. Male homosexual transmission of HIV-1. AIDS 8 8 (1994) 1051-1061
6. Davidovich U., De Wit J.B.F., and Stroebe W. Behavioral and cognitive barriers to safer sex between men in steady relationships: Implications for prevention strategies. AIDS Education and Prevention 16 4 (2004) 304-314
7. DeGruttola V., Seage Iii G.R., Mayer K.H., and Horsburgh Jr. C.R. Infectiousness of HIV between male homosexual partners. Journal of Clinical Epidemiology 42 9 (1989) 849-856
8. Dukers N.H.T.M., Goudsmit J., De Wit J.B.F., Prins M., Weverling G.J., and Coutinho R.A. Sexual risk behaviour relates to the virological and immunological improvements during highly active antiretroviral therapy in HIV-1 infection. AIDS 15 3 (2001) 369-378
9. Goodreau S.M. Assessing the effects of human mixing patterns on human immunodeficiency virus-1 interhost phylogenetics through social network simulation. Genetics 172 4 (2006) 2035
10. F. Heylighen, The science of self-organization and adaptivity, in: L.D. Kiel (ed.), Knowledge Management, Organizational Intelligence and Learning, and Complexity, in: The Encyclopedia of Life Support Systems (EOLSS), (Eolss Publishers, Oxford), 2001.
11. Koopman J.S., Jacquez J.A., Welch G.W., Simon C.P., Foxman B., Pollock S.M., Barth-Jones D., Adams A.L., and Lange K. The role of early HIV infection in the spread of HIV through populations. Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology 14 3 (1997) 249-258
12. Leynaert B., Downs A.M., and De Vincenzi I. Heterosexual transmission of human immunodeficiency virus: variability of infectivity throughout the course of infection. American Journal of Epidemiology 148 1 (1998) 88-96
13. S. Luke, C. Cioffi-Revilla, L. Panait, K. Sullivan, Mason: a new multi-agent simulation toolkit, Proceedings of the 2004 SwarmFest Workshop, 2004.
14. Newman M.E.J. The structure and function of complex networks. SIAM Review 45 2 (2003) 167-256
15. J. O'Madadhain, D. Fisher, P. Smyth, S. White, Y.-B. Boey, Analysis and visualization of network data using jung, Journal of Statistical Software (2005).
16. Overview of the Amsterdam cohort studies among homosexual men and drug users (2006). http://www.amsterdamcohortstudies.org/menu/reports/ACSoverview2006.pdf.
17. Panait L., and Luke S. Cooperative multi-agent learning: the state of the art. Autonomous Agents and Multi-Agent Systems 11 3 (2005) 387-434 doi:10.1007/s10458-005-2631-2
18. Pautasso M., and Jeger M.J. Epidemic threshold and network structure: the interplay of probability of transmission and of persistence in small-size directed networks. Ecological Complexity 5 1 (2008) 1-8
19. Reed W.J. A stochastic model for the spread of a sexually transmitted disease which results in a scale-free network. Mathematical Biosciences 201 1-2 (2006) 3-14
20. Schneeberger A., Nat R., Mercer C.H., Gregson S.A.J., Ferguson N.M., Nyamukapa C.A., Anderson R.M., Johnson A.M., and Garnett G.P. Scale-free networks and sexually transmitted diseases: a description of observed patterns of sexual contacts in britain and zimbabwe. Sexually Transmitted Diseases 31 6 (2004) 380-387
21. Semple S.J., Patterson T.L., and Grant I. HIV-positive gay and bisexual men: predictors of unsafe sex. AIDS Care-Psychological and Socio-Medical Aspects of AIDS/HIV 15 1 (2003) 3-15
22. Sloot P.M.A., Boukhanovsky A.V., Keulen W., Tirado-Ramos A., and Boucher C.A. A grid-based HIV expert system. Journal of Clinical Monitoring and Computing 19 4-5 (2005) 263-278
23. P.M.A. Sloot, P. Coveney, M.T. Bubak, A.-M. Vandamme, B. Nuallain, Dvd. Vijver, C. Boucher, Virolab: a collaborative decision support system in viral disease treatment, Reviews in Antiviral Therapy 3 (2008).
24. Sloot P.M.A., Ivanov S.V., Boukhanovsky A.V., Van De Vijver D.A.M.C., and Boucher C.A.B. Stochastic simulation of HIV population dynamics through complex network modelling. International Journal of Computer Mathematics 85 8 (2008) 1175-1187
25. Teweldemedhin E., Marwala T., and Mueller C. Agent-based modelling: a case study in HIV epidemic. Proceedings-HIS'04: 4th International Conference on Hybrid Intelligent Systems (2005) 154-159
26. The Amsterdam cohort studies on HIV infection annual report 2006 (2006). http://www.amsterdamcohortstudies.org/menu/reports/ACSannualreport2006.pdf.
27. M. van Veen, F. Koedijk, I. vanden Broek, E. op de Coul, I. de Boer, A van Sighem, M. vander Sande, Sexually transmitted infections in the Netherlands in 2006 (2006), http://rivm.openrepository.com/rivm/bitstream/10029/16495/1/210261003.pdf.
28. Vittinghoff E., Douglas J., Judson F., McKirnan D., Macqueen K., and Buchbinder S.R. Per-contact risk of human immunodeficiency virus transmission between male sexual partners. American Journal of Epidemiology 150 3 (1999) 306-311
29. In: Wooldridge M. (Ed). An Introduction to MultiAgent Systems (2002), John Wiley & Sons Ltd.
30. Xiridou M., Geskus R., De Wit J., Coutinho R., and Kretzschmar M. The contribution of steady and casual partnerships to the incidence of HIV infection among homosexual men in Amsterdam. AIDS 17 7 (2003) 1029-1038
31. Xiridou M., Geskus R., De Wit J., Coutinho R., and Kretzschmar M. Primary HIV infection as source of HIV transmission within steady and casual partnerships among homosexual men. AIDS 18 9 (2004) 1311-1320
32. H. Xuan, L. Xu, L. Li, A CA-based epidemic model for HIV/AIDS transmission with heterogeneity, Annals of Operations Research capital 168 (1) (2008) 81-99.