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Digital Library

of the European Council for Modelling and Simulation

 

Title:

An Agent-Based Model For The Control Of Malaria Using

Genetically Modified Vectors

Authors:

Ana Maria Reyes, Hernando Diaz, Andrés Olarte

Published in:

 

(2012).ECMS 2012 Proceedings edited by: K. G. Troitzsch, M. Moehring, U. Lotzmann. European Council for Modeling and Simulation. doi:10.7148/2012 

 

ISBN: 978-0-9564944-4-3

 

26th European Conference on Modelling and Simulation,

Shaping reality through simulation

Koblenz, Germany, May 29 – June 1 2012

 

Citation format:

Reyes, A. M., Diaz, H., & Olarte, A. (2012). An Agent-Based Model For The Control Of Malaria Using Genetically Modified Vectors. ECMS 2012 Proceedings edited by: K. G. Troitzsch, M. Moehring, U. Lotzmann (pp. 31-36). European Council for Modeling and Simulation. doi:10.7148/2012-0031-0036

DOI:

http://dx.doi.org/10.7148/2012-0031-0036

Abstract:

An agent-based model was developed to assess the use of Genetically Modified Mosquitoes (GMMs) as a control strategy for the Malaria epidemic. Mosquitoes responsible for the transmission of Malaria (vectors) have been modified genetically so that the probability of transmitting the parasite causing the disease when biting a human being is reduced with respect to wild type vectors. Our model represents the population dynamics of the introduction of a transgenic strain of malaria vectors of the species Anopheles Gambiae. In the model three different types of agents were included: wild type, homozygous and heterozygous transgenic mosquitoes. Each agent is characterized by a fitness parameter that represents a reproduction rate, relative to the wild type population. The model considers specific biological processes such as: gonotrophic cycle (the average interval between successive blood meals), egg maturation time and life cycle of the vector. Additionally, some spatial aspects such as: biting zones (human settlements) and water zones (breeding places) were included in the model to consider the influence of environmental conditions. Through simulations it was observed that the model represents adequately the dynamics of Malaria vectors. These results may be used to evaluate different control strategies considering spatial and environmental features.

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