Agent-Based Stochastic Simulations of Shipboard Disease Outbreaks

摘要

Infectious diseases aboard naval ships may rapidly spread within shipboard populations and severely disrupt operational activities. In this paper we present Gryphon, an agent-based stochastic modeling and simulation platform for characterizing the spread of shipboard infectious diseases. We discuss the stochastic process of disease transmission, features of the Gryphon system for decision support and the emergent dynamics of observed epidemics. We focus on the sensitivity analysis of stochastic simulations for shipboard disease outbreaks and document the results across various population sizes and seeded infections. Our results show that the dynamics of a disease outbreak can be successfully predicted with a reasonable variance when the number of seeded infections and the population size become relatively high. We discuss the implications of various behaviors exhibited by the stochastic simulation engine and conclude with several possible improvements to the development of Gryphon platform.