Greedy Algorithms in Economic Epidemiology

Economic issues are central to the control of disease because of the limited funds available for public health everywhere in the world, even in the wealthiest nations. These economic issues are closely related to issues of individual human behavior, as well as to fundamental disease processes and their relation to the environment. While mathematical formulation of epidemiological processes is an old discipline, combining such formulations with economic, behavioral, and environmental formalisms is relatively new, and has come to define the field of “Economic Epidemiology.” Many problems in Economic Epidemiology can be formulated as optimization problems. The simplest approach to solving such a problem is often a greedy algorithm, one that always chooses the best available (cheapest, highest rated, ...) alternative at each step. We review some classical operations research problems arising in Economic Epidemiology for which the greedy algorithm in fact gives an optimal solution, and others for which it can be guaranteed to be reasonably close. We then present two examples from our own work. Examples will be chosen from: assigning workers to health care tasks; choosing medical supplies to maximize value and minimize cost; locating a health care facility so as to minimize the travel times of users; and reopening flooded roads to allow the passage of emergency vehicles. Other examples will include optimal strategies for vaccination given a limited supply; and optimal strategies for sequencing medical tests or public health interventions in order to minimize costs and