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Modeling Malaria with Multi-Agent Systems

Author

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  • Fatima Rateb

    (University of Granada, Spain)

  • Bernard Pavard

    (Institut de Recherche en Informatique de Toulouse, France)

  • Narjes Bellamine-BenSaoud

    (University of Tunis, Tunisia)

  • J.J. Merelo

    (University of Granada, Spain)

  • M.G. Arenas

    (University of Granada, Spain)

Abstract

Malaria is a vector-borne disease that greatly affects social and economic development. We adopt the complex system paradigm in our analysis of the problem. Our aim is to assess the impact of education on malaria healthcare. Multi-agent systems are employed to model the spread of malaria in Haiti, where we introduce malaria education as a possible way of regulating deaths due to the parasite. We launch three experiments, each with environment modifications: three hospitals; three hospitals and 20 schools; and five hospitals and 20 schools. The results of running 10 simulations for each experiment show that there is a reduction in malaria deaths not only when including schools, but in combination with increasing the number of hospitals.

Suggested Citation

  • Fatima Rateb & Bernard Pavard & Narjes Bellamine-BenSaoud & J.J. Merelo & M.G. Arenas, 2005. "Modeling Malaria with Multi-Agent Systems," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 1(2), pages 17-27, April.
    • Handle: RePEc:igg:jiit00:v:1:y:2005:i:2:p:17-27
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    Cited by:

    1. James E. Gentile & Gregory J. Davis & Samuel S. C. Rund, 2012. "Verifying agent-based models with steady-state analysis," Computational and Mathematical Organization Theory, Springer, vol. 18(4), pages 404-418, December.

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