Programming an Agent-Based Model for Disease Dynamics with Multiple Sources of Infection
Epidemiologists use susceptible, infective, resistant (SIR) models to describe disease dynamics and predict the distribution of infective states within host populations. Many SIR models have been reported in scientific journals; however, models for disease caused by generalist pathogens, where disease-causing organisms infect multiple host species or maintain environmental reservoirs, are not fully accounted for by the fundamental rules of probability. Therefore, probabilistically correct susceptible, infective, resistant (SIR), susceptible, exposed, infective, resistant (SEIR) and susceptible, infective, susceptible (SIS) models for generalist pathogens where more than one infective source exists have been constructed. The models introduced here demonstrate computer code for agent-based disease models in the mathematical programming language R. Examples of code for three models are given that can be easily modified to model other diseases and environments. These models can easily characterize the dynamics of an infectious disease in a host community.