Mosquito-borne pathogens are responsible for a
massive global burden of disease: they cause approximately 700,000 deaths
annually. Each year more than half of this total mortality is attributed to the
protozoan parasites that transmit malaria. Current control measures range from
anti-parasitic drugs to bed nets, insecticides, and the destruction of vector
habitats.[1] But while such methods have
met with some success to date, drug and insecticide resistance is rising.
Further, the changing precipitation patterns and temperatures brought by global
warming will affect the incidence of malaria. This makes eradication of the
disease unlikely if existing approaches are not augmented.
Fortunately, the advent of functional genetic
engineering technologies such as RNA-guided CRISPR-Cas9 presents novel
possibilities for complementing traditional malaria control methods: the genes
of mosquitoes can be altered to inhibit the spread of malaria-causing pathogens
to humans. This work conducts a study of the optimal release schedule for modified
Aedes Aegypti mosquitoes, building from a mathematical model created by the
Marshall Lab at the University of California, Berkeley.[2] This approach to
vector control employs approximate dynamic programming (DP) methods to achieve
"fixation", here defined as successful propagation of the modified
genotype such that it is inherited by at least 50% of the male population. The
use of HPC would drastically expand the scope of this work and enable
methodological improvements, including through more detailed modelling of the
DP formulation and a better quantification of relevant uncertainties.