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Title: Modelling optimal strategies for novel genetics-based pest management
Author: Alphey, Nina
ISNI:       0000 0004 2743 6808
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2009
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Genetic transformation techniques for pest insects have enabled the development of novel methods to mitigate the enormous harm done by insects to human health (through transmission of diseases) and to agriculture (through damage to crops or livestock). I use mathematical modelling to analyse strategies using autocidal genetic constructs (dominant lethal genes that are repressible during mass-rearing); in parallel several research groups are developing the strains and the laboratory and field experimental work. Engineered insects would be released in large numbers and compete for mates, and their progeny would inherit one copy of a dominant lethal gene and die. The lethal mechanism can be made stage- or sex-specific. The aim is to reduce the number of pest insects in a population, suppressing numbers to a less harmful level or local elimination. I examine the evolutionary, ecological, and economic cost and benefit aspects of these novel interventions. I consider application of this genetic technology against agricultural pest insects, combined with genetically modified crop plants engineered to produce insecticidal toxins, to which field-evolved resistance is emerging. Using a theoretical framework, I analyse the gene frequency evolution of resistant alleles and show that strategies using genetic constructs that are selectively lethal only to females could help to manage both pests and resistance. I investigate potential resistance to the lethal mechanism of the genetic construct itself. I use population genetics and population dynamics models to explore the impact of heritable biochemically-based resistance on the effectiveness of genetic strategies for reducing populations of important pests in agriculture or public health. Released insects are homozygous for susceptibility to the lethal construct; this has an inherent element of resistance dilution. Finally, I analyse genetic vector control methods to reduce the transmission of human disease. I combine vector population dynamics and epidemiological models with techniques for assessing cost-effectiveness of a genetic strategy for controlling a vector mosquito, and show that disease elimination is feasible on a practical timescale and economically beneficial.
Supervisor: Bonsall, Michael B.; Alphey, Luke Sponsor: Biotechnology and Biological Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Ecology (zoology) ; Disease (zoology) ; Agriculture ; mathematical modelling