A simulation model of African Anopheles ecology and population dynamics for the analysis of malaria transmission
Authored by JMO Depinay, CM Mbogo, G Killeen, B Knols, J Beier, J Carlson, J Dushoff, P Billingsley, H Mwambi, J Githure, AM Toure, FE McKenzie
Date Published: 2004
DOI: 10.1186/1475-2875-3-29
Sponsors:
No sponsors listed
Platforms:
C++
Model Documentation:
Other Narrative
Flow charts
Mathematical description
Model Code URLs:
Model code not found
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.
Tags
Habitats
Density
Sensu-stricto diptera
Culicidae
Temperature
Body-size
Western kenya
Gambiae complex
Larval
survival
Arabiensis