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Using evolutionary costs to enhance the efficacy of malaria control via genetically manipulated mosquitoes

Published online by Cambridge University Press:  24 January 2008

JACOB C. KOELLA*
Affiliation:
Imperial College London, Silwood Park Campus, Ascot SL5 7PY, United Kingdom
LAMIA ZAGHLOUL
Affiliation:
Laboratoire Joliot-Curie, ENS Lyon, 46, allée d'Italie 69364 Lyon Cedex 07, France
*
*Corresponding author: Jacob Koella, Imperial College London, Silwood Park Campus, Ascot SL5 7PY, United Kingdom. Tel: +44 2070542254. E-mail: jkoella@imperial.ac.uk

Summary

An earlier mathematical model exploring the use of genetically manipulated mosquitoes for malaria control suggested that the prevalence of malaria is reduced significantly only if almost all mosquitoes become completely resistant to malaria. Central to the model was the ‘cost of resistance’: the reduction of a resistant mosquito's evolutionary fitness in comparison with a sensitive one's. Here, we consider the possibility of obtaining more optimistic outcomes by taking into account the epidemiological (in addition to the evolutionary) consequences of a cost of resistance that decreases the life-span of adult mosquitoes (the most relevant parameter for the parasite's epidemiology). There are two main results. First, if despite its cost, resistance is fixed in the population, increasing the cost of resistance decreases the intensity of transmission. However, this epidemiological effect is weak if resistance is effective enough to be considered relevant for control. Second, if the cost of resistance prevents its fixation, increasing it intensifies transmission. Thus, the epidemiological effect of the cost of resistance cannot compensate for the lower frequency of resistant mosquitoes in the population. Overall, our conclusion remains pessimistic: so that genetic manipulation can become a promising method of malaria control, we need techniques that enable almost all mosquitoes to be almost completely resistant to infection.

Type
Research Article
Copyright
Copyright © 2008 Cambridge University Press

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