Modeling malaria as a complex adaptive system

M. A. Janssen, W. J.M. Martens

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

As the resistance of the malaria parasite to antimalarial drugs continues to increase, as does that of the malarial mosquito to insecticides, the efficacy of efforts to control malaria in many tropical countries is diminishing. This trend, together with the projected consequences of climate change, may prove to exacerbate substantially the significance of malaria in the coming decades. In this article we introduce the use of an evolutionary modeling approach to simulate the adaptation of mosquitoes and parasites to the available pesticides and drugs. By coupling genetic algorithms with a dynamic malaria-epidemiological model, we derive a complex adaptive system capable of simulating adapting and evolving processes within both the mosquito and the parasite populations. This approach is used to analyze malaria management strategies appropriate to regions of higher and lower degrees of endemicity. The results suggest that adequate use of insecticides and drugs may reduce the occurrence of malaria in regions of low endemicity, although increased efforts would be necessary in the event of a climate change. However, our model indicates that in regions of high endemicity the use of insecticides and drugs may lead to an increase in incidence due to enhanced resistance development. Projected climate change, on the other hand, may lead to a limited reduction of the occurrence of malaria due to the presence of a higher percentage of immune persons in the older age class.

Original languageEnglish (US)
Pages (from-to)213-236
Number of pages24
JournalArtificial Life
Volume3
Issue number3
DOIs
StatePublished - 1997
Externally publishedYes

Keywords

  • Adaptation
  • Climate change
  • Genetic algorithms
  • Infectious diseases
  • Resistance development

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology
  • Artificial Intelligence

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