title: Using evolution to generate sustainable malaria control with spatial repellents.
abstract: Evolution persistently undermines vector control programs through insecticide resistance. Here we propose a novel strategy which instead exploits evolution to generate and sustain new control tools. Effective spatial repellents are needed to keep vectors out of houses. Our approach generates such new repellents by combining a high-toxicity insecticide with a candidate repellent initially effective against only part of the vector population. By killing mosquitoes that enter treated properties the insecticide selects for vector phenotypes deflected by the repellent, increasing efficacy of the repellent against the target vector population and in turn protecting the insecticide against the spread of insecticide resistance. Using such evolved spatial repellents offers an evolutionarily sustainable, 'double-dip' system of disease control combining mortality and repellence. We formalize this idea using models which explore vector population genetics and disease transmission probabilities and show that using evolved spatial repellents is theoretically achievable, effective and sustainable.
authors: Department of Biosciences, University of Exeter, Cornwall Campus, Penryn, United Kingdom.
authors: Penelope Anne
authors: 0000-0002-0486-8507
authors: PA
authors: Lynch
authors: Department of Biosciences, University of Exeter, Cornwall Campus, Penryn, United Kingdom.|Department of Integrative Biology, University of California, Berkeley, United States.
authors: Mike
authors: M
authors: Boots
mesh_terms: D018562:Disease Transmission, Infectious / Q000517:prevention & control*; D006801:Humans; D007302:Insect Repellents / Q000494:pharmacology*; D007306:Insecticides / Q000494:pharmacology*; D008288:Malaria / Q000517:prevention & control* / Q000635:transmission; D009032:Mosquito Control / Q000379:methods*
chemical_list: D007302:Insect Repellents; D007306:Insecticides
keywords: Anopheles; IRS; bednets; epidemiology; evolutionary biology; genomics; global health; insecticide resistance; modeling; none; vector evolution