2026-09-19T08:05:19Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/284372022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
George Verghese.
Livingston, Samantha, 1980-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2005-09-26T20:26:50Z
2005-09-26T20:26:50Z
2004
2004
http://hdl.handle.net/1721.1/28437
57003130
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (p. 37).
In this thesis, I looked at an extension of the Reed-Frost epidemic model which had two-sub-populations. By setting up a Markov chain to model the epidemic and finding the transition probabilities of that chain, MATLAB could be used to solve for the expected number of susceptibles and the expected duration. I simulated the model with more tan two sub-populations to find the average number of susceptibles and reviewed previously solved stochastic spatial models to understand how to solve the multiple-population Reed-Frost model on a network.
by Samantha Livingston.
M.Eng.
37 p.
1298003 bytes
1299861 bytes
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Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Stochastic models for epidemics on networks
Thesis
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