Malaria Journal (Jul 2004)

A simulation model of African <it>Anopheles </it>ecology and population dynamics for the analysis of malaria transmission

  • Billingsley Peter,
  • Dushoff Jonathan,
  • Carlson John,
  • Beier John,
  • Knols Bart,
  • Killeen Gerry,
  • Mbogo Charles M,
  • Depinay Jean-Marc O,
  • Mwambi Henry,
  • Githure John,
  • Toure Abdoulaye M,
  • Ellis McKenzie F

DOI
https://doi.org/10.1186/1475-2875-3-29
Journal volume & issue
Vol. 3, no. 1
p. 29

Abstract

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Abstract Background Malaria is one of the oldest and deadliest infectious diseases in humans. Many mathematical models of malaria have been developed during the past century, and applied to potential interventions. However, malaria remains uncontrolled and is increasing in many areas, as are vector and parasite resistance to insecticides and drugs. Methods This study presents a simulation model of African malaria vectors. This individual-based model incorporates current knowledge of the mechanisms underlying Anopheles population dynamics and their relations to the environment. One of its main strengths is that it is based on both biological and environmental variables. Results The model made it possible to structure existing knowledge, assembled in a comprehensive review of the literature, and also pointed out important aspects of basic Anopheles biology about which knowledge is lacking. One simulation showed several patterns similar to those seen in the field, and made it possible to examine different analyses and hypotheses for these patterns; sensitivity analyses on temperature, moisture, predation and preliminary investigations of nutrient competition were also conducted. Conclusions Although based on some mathematical formulae and parameters, this new tool has been developed in order to be as explicit as possible, transparent in use, close to reality and amenable to direct use by field workers. It allows a better understanding of the mechanisms underlying Anopheles population dynamics in general and also a better understanding of the dynamics in specific local geographic environments. It points out many important areas for new investigations that will be critical to effective, efficient, sustainable interventions.