Date of Award

Fall 2014

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Computational Modeling & Simulation Engineering

Program/Concentration

Modeling and Simulation

Committee Director

James F. Leathrum

Committee Member

Frederic D. McKenzie

Committee Member

Yuzhong Shen

Call Number for Print

Special Collections LD4331.E58 G3653 2014

Abstract

This study uses contact probability in an agent-based model to simulate the spread of an infectious disease. In order to perform the study, the agent-based model must first be discretized into events. Each agent in the model is given its own infectious disease state machine taken from the Susceptible-Exposed-Infected-Recovered (SEIR) model. The agents move between squares in a grid environment where each square represents a group. Groups have a contact probability as an attribute that is used to predict whether an agent comes in close contact with another agent. The transitions between the states in the SEIR model are easily translated into Expose, Infect, and Recover events. The Infect and Recover events use the latency period and the infectious period of the disease being modeled. For the Expose event, the contact probability of the group is used to determine what agents the disease is spread to. Due to a lack of available data on the probability of individuals infecting each other, the model output is calibrated to match that of an existing agent-based model as a proof of concept.

Rights

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

DOI

10.25777/5wvd-wr96

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