The importance of modelling the spread of insecticide resistance in a heterogeneous environment: the example of adding synergists to bed nets

BACKGROUND: Insecticides are an effective and practical tool for reducing malaria transmission but the development of resistance to the insecticides can potentially compromise controls efforts. In this study a mathematical model was developed to explore the effects on mosquito populations of spatial heterogeneous deployment of insecticides. This model was used to identify important parameters in the evolution of insecticide resistance and to examine the contribution of new generation long-lasting insecticidal bed nets, that incorporate a chemical synergist on the roof panel, in delaying insecticide resistance. METHODS: A genetic model was developed to predict changes in mosquito fitness and resistance allele frequency. Parameters describing insecticide selection, fitness cost and the additional use of synergist were incorporated. Uncertainty and sensitivity analysis were performed followed by investigation of the evolution of resistance under scenarios of fully effective or ineffective synergists. RESULTS: The spread of resistance was most sensitive to selection coefficients, fitness cost and dominance coefficients while mean fitness was most affected by baseline fitness levels. Using a synergist delayed the spread of resistance but could, in specific circumstances that were thoroughly investigated, actually increase the rate of spread. Different spread dynamics were observed, with simulations leading to fixation, loss and most interestingly, equilibrium (without explicit overdominance) of the resistance allele. CONCLUSIONS: This strategy has the potential to delay the spread of resistance but note that in an heterogeneous environment it can also lead to the opposite effect, i.e., increasing the rate of spread. This clearly emphasizes that selection pressure acting inside the house cannot be treated in isolation but must be placed in context of overall insecticide use in an heterogeneous environment.