Mobility matrix evolution for an SIS epidemic patch model

Intercommunity disease spread can be modeled using a collection of discrete community “patches” with continuous population flow between them. In a susceptible–infected–susceptible (SIS) model residents of a community may either be classified as susceptible or infected. Infected individuals may heal and become susceptible again but are not permitted to die or become immune. The spread of disease can be controlled by modifying the rate and direction of resident movement across patch boundaries. In this work we use genetic algorithms to evolve optimal connections between patch boundaries such that the total number of infected individuals is minimized.