Abstract
This paper describes an agent-based simulation model of the spread of HIV/AIDS in the Sub-Saharan region. The model is part of our studying social complexity in the Sekhukhune district of the Limpopo province in South Africa. The model presents a coherent framework and identifies the essential factors agent-based modellers need to take into account when modelling HIV spread. The necessary empirical data are drawn from the villagers’ accounts during our fieldtrip to the case study region and reports from the available epidemiological and demographic literature. The results presented here demonstrate how agent-based simulation can aid in a better understanding of this complex interplay of various factors responsible for the spread of the epidemic. Although the model is specific to the case study area, the general framework described in this paper can easily be extended and adapted for other regions.
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References
Alam, S.J., Meyer, R., Ziervogel, G., Moss, S.: The Impact of HIV/AIDS in the Context of Socioeconomic Stressors: An Evidence-driven Approach. Journal of Artificial Societies and Social Simulation 10(4), 7 (2007), http://jasss.soc.surrey.ac.uk/10/4/7.html
Billari, F., Prskawetz, A., Fürnkranz, J.: The evolution of social norms: age norms on marriage. Max Planck Institute for Demographic Research, Rostock, Germany (2005)
Helleringer, S., Kohler, H.-P.: Sexual Network Structure and the Spread of HIV in Africa: Evidence from Likoma Island, Malawi. AIDS 21(17), 2323–2332 (2007)
Jin, E.M., Girvan, M., Newman, M.E.J.: Structure of growing social networks. Phys. Rev. E. 64.4 (2001)
Koopman, J.S., et al.: The role of early HIV infection in the spread of HIV through populations. J. Acq Imm. Def. Syn. Hum. Retroviral 14, 249–258 (1997)
Kossinets, G.: Effects of missing data in social networks. Social Networks 28 (2006)
Liljeros, F., Edling, C.R., Amaral, L.A.N.: Sexual networks: implications for the transmission of sexually transmitted infections. Microsbes Infect., 189–196 (2003)
Liljeros, F., et al.: The Web of Human Sexual Contacts. Nature 411, 908–909 (2001)
Merli, M.G., et al.: Modelling the spread of HIV/AIDS in China: The role of sexual transmission. Population Studies 60(1), 1–22 (2006)
Newell, M., et al.: Mortality of infected and uninfected infants born to HIV-infected mothers in Africa: a pooled analysis. The Lancet. 364, 1236–1243 (2004)
Nordvik, M.K., Liljeros, F.: Number of Sexual Encounters Involving Intercourse and the Transmission of Sexually Transmitted Infections. Sex. Trans Dis. 33(6), 342–349 (2006)
Rauner, M.S., et al.: Use of Discrete-Event Simulation to Evaluate Strategies for the Prevention of Mother-to-Child Transmission of HIV in Developing Countries. J. Operational Research Society 56, 222–233 (2005)
Rhee, A.: An Agent-based Approach to HIV/AIDS Modelling: A Case Study of Papua New Guinea. Master of Science Thesis. Massachusetts Institute of Technology (2006)
Schmitt, D.P.: Sociosexuality from Argentina to Zimbabwe: A 48-nation study of sex, culture, and strategies of human mating. Behavioral and Brain Sciences 28(2), 247–311 (2005)
Simão, J., Todd, P.M.: Emergent Patterns of Mate Choice in Human Populations. Artificial Life 9(4), 403–417 (2003)
Sumodhee, C., et al.: Impact of Social Behaviors on HIV Epidemic: A Computer Simulation View. In: Proc. Intl. Conference on Computational Intelligence for Modelling, Control and Automation, pp. 550–556. IEEE Press, Los Alamitos (2005)
Wawer, M.J., et al.: Rates of HIV-1 Transmission per Coital Act, by Stage of HIV-1 Infection, in Rakai, Uganda. Journal of Infectious Diseases 191, 1403–1409 (2005)
Watts, D.J., Strogatz, S.: Collective Dynamics of ‘small world’ networks. Nature 393, 440–442 (1998)
Heuveline, P., Sallach, D., Howe, T.: The Structure of an Epidemic: Modelling AIDS Transmission in Southern Africa. In: Papers from Symposium on Agent-based Computational Modelling, Vienna, Austria (2003)
Alam, S.J., Edmonds, B., Meyer, R.: Identifying Structural Changes in Networks Generated from Agent-based Social Simulation Models. In: Proc. 10th Pacific RIM International Workshop on Multi-agent Systems (2007)
Kretzschmar, M., Morris, M.: Measures of concurrency in networks and the spread of infectious disease. Math. Biosci. 133(2), 165–195 (1996)
Bearman, P.S., Moody, J., Stovel, K.: Chains of Affection: The Structure of Adolescent Romantic and Sexual Networks. American Journal of Sociology 110(1), 44–91 (2004)
Ziervogel, G., Taylor, A.: Feeling Stressed: Integrating Climate Adaptation with Other Priorities in South Africa. Environment 50(2), 32–41 (2008)
Tawfik, A.Y., Farag, R.R.: Modeling the Spread of Preventable Diseases: Social Culture and Epidemiology. In: Proc. IFIP International Federation for Information Processing; Artificial Intelligence and Practice II, vol. 276, pp. 277–286. Springer, Boston (2008)
North, M.J., Collier, N.T., Vos, J.R.: Experiences Creating Three Implementations of the Repast Agent Modeling Toolkit. ACM Transactions on Modeling and Computer Simulation 16(1) (2006)
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Alam, S.J., Meyer, R., Norling, E. (2009). A Model for HIV Spread in a South African Village. In: David, N., Sichman, J.S. (eds) Multi-Agent-Based Simulation IX. MABS 2008. Lecture Notes in Computer Science(), vol 5269. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01991-3_3
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DOI: https://doi.org/10.1007/978-3-642-01991-3_3
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