A Spatially Explicit Approach to Modeling the Optimal Control of Cholera Epidemics

Abstract

Mathematical models can provide key insights into the optimal control of infectious disease outbreaks. In this thesis, I study the role that such modeling could have played if it had been applied to the ongoing cholera epidemic in Haiti that began in October 2010. I integrate a spatially explicit model of cholera transmission with the decision framework of a social planner who seeks the optimal allocation of fixed resources across a variety of preventive and therapeutic cholera control measures. Knowing the spatio-temporal dynamics of the spread of diseases across an interconnected region can inform policy-makers on the interventions that maximize health impact while economizing on resources and cost. I find that, in the case of Haiti, public health officials should have emphasized treatment from the very beginning and phased in intermediate levels of sanitation and vaccination once the prevalence of disease had been sufficiently tamed. I also conclude that the cost structures of interventions lead to interior solutions to the optimization problem only when the marginal cost of infection is comparable to that of an intervention. Although the prevalence of cholera in Haiti has declined naturally over the last 3 years, letting the disease run its course instead of intervening is not a socially optimal strategy. Preparedness and prevention might have averted hundreds of thousands of severe cases of cholera and saved millions of dollars in government spending. This research confirms the critical role modeling can play in informing public health decision-making at the aggregate level.