Mathematical Models of Genetic Strategies for Controlling the Dengue Vector, Aedes aegypti

Because traditional efforts for controlling the primary mosquito vector of dengue fever, Aedes aegypti, have not led to significant decreases in disease cases, attention has turned to the development of novel methods of control, including genetic strategies. In genetic strategies, strains of genetically modified (i.e. transgenic) insects are released that are engineered to either have fewer viable offspring or to be less capable of transmitting disease pathogens, leading to either reduction of a wild-type population or replacement of a vector-competent population with one that cannot transmit disease pathogens. Significant progress in developing transgenic strains has been made in recent years, and the release of transgenic insects to control native populations is becoming more plausible; however, cautious evaluation, testing, and planning must occur before these measures are implemented on a large scale.Mathematical models are valuable tools that are used throughout the development of genetic strategies, particularly in the evaluation, testing, and planning stages. In this work, different types of models are utilized to study genetic strategies at different stages in the development process. With a stochastic model designed to study cage experiments for testing a female-killing (FK) population reduction strategy, we underscore the utility of mathematical models in designing and evaluating experiments.We show that fitness disadvantages associated with transgenes can go undetected in experiments in which large numbers of transgenic individuals are released and that studying small population densities in cage experiments could be complicated by extinction that occurs as a result of the experimental design.We also illustrate how the model can be used to propose and explore experiments that have not previously been considered. Utilizing an optimal control model, we explore integrated control programs that include FK releases.We showthat optimal releases lead to lower costs of control than similar constant releases that have previously been studied.We show that integrated control approaches can be more cost-effective than corresponding programs that involve single control strategies. We also explore the influence of costs of control on the total cost of integrated programs. Employing a relatively simple deterministic model, we propose and evaluate a Reduce and Replace (R&R) strategy that aims to cause simultaneous population reduction and replacement by combining FK genes with anti-pathogen (AP) genes.We show that R&R releases are more effective in reducing competent vector densities long-term than similar FK releases. We show that releases including R&R females lead to greater reduction in competent vector density than male-only releases. Overall, the magnitude of reduction in total and competent vectors depends upon the release ratio, release duration, and whether females are included in releases. With the same modeling framework, we evaluate an R&R strategy against AP-only and FK-only strategies, along with three hybrid strategies that combine FK, AP, and R&R releases. In most scenarios, we find that AP-only and R&R followed by AP strategies lead to the most reduction in competent vectors. While R&R releases often cause the most reduction while releases are being conducted, they are not as effective in reducing competent vectors long termin part due to the effects of linkage disequilibrium when population densities are low. We show that if fitness disadvantages are associated with the AP gene, fewer AP-only releases are needed to maintain low competent vector densities following an initial release period than similar R&R or FK-only releases. The insights from the studies included in this dissertation can be and have been used to guide the development of genetic strategies in the laboratory, aid in the design and evaluation of experiments aimed at testing these strategies, and provide a general framework for guiding eventual release programs involving transgenic strains of Ae. aegypti..