title: A Two-Locus Model of the Evolution of Insecticide Resistance to Inform and Optimise Public Health Insecticide Deployment Strategies.
abstract: We develop a flexible, two-locus model for the spread of insecticide resistance applicable to mosquito species that transmit human diseases such as malaria. The model allows differential exposure of males and females, allows them to encounter high or low concentrations of insecticide, and allows selection pressures and dominance values to differ depending on the concentration of insecticide encountered. We demonstrate its application by investigating the relative merits of sequential use of insecticides versus their deployment as a mixture to minimise the spread of resistance. We recover previously published results as subsets of this model and conduct a sensitivity analysis over an extensive parameter space to identify what circumstances favour mixtures over sequences. Both strategies lasted more than 500 mosquito generations (or about 40 years) in 24% of runs, while in those runs where resistance had spread to high levels by 500 generations, 56% favoured sequential use and 44% favoured mixtures. Mixtures are favoured when insecticide effectiveness (their ability to kill homozygous susceptible mosquitoes) is high and exposure (the proportion of mosquitoes that encounter the insecticide) is low. If insecticides do not reliably kill homozygous sensitive genotypes, it is likely that sequential deployment will be a more robust strategy. Resistance to an insecticide always spreads slower if that insecticide is used in a mixture although this may be insufficient to outperform sequential use: for example, a mixture may last 5 years while the two insecticides deployed individually may last 3 and 4 years giving an overall 'lifespan' of 7 years for sequential use. We emphasise that this paper is primarily about designing and implementing a flexible modelling strategy to investigate the spread of insecticide resistance in vector populations and demonstrate how our model can identify vector control strategies most likely to minimise the spread of insecticide resistance.
authors.affiliation: Department of Parasitology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.
authors.forename: Bethany
authors.identifier: 0000-0002-6371-8744
authors.initials: B
authors.lastname: Levick
authors.affiliation: Independent consultant, Norwich, United Kingdom.
authors.forename: Andy
authors.identifier: 0000-0003-4051-6135
authors.initials: A
authors.lastname: South
authors.affiliation: Department of Parasitology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.
authors.forename: Ian M
authors.identifier: 0000-0002-1332-742X
authors.initials: IM
authors.lastname: Hastings
mesh_terms: D000818:Animals; D005075:Biological Evolution; D003198:Computer Simulation; D003465:Culex / Q000187:drug effects* / Q000235:genetics*; D006291:Health Policy; D006801:Humans; D007305:Insecticide Resistance / Q000235:genetics*; D007306:Insecticides / Q000008:administration & dosage*; D008288:Malaria / Q000469:parasitology / Q000517:prevention & control*; D008957:Models, Genetic
chemical_list: D007306:Insecticides