2026-09-18T19:51:48Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/331482022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Adam Szpiro and Lucila Ohno-Machado.
McLean, Cory Y. (Cory Yuen Fu)
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2006-06-19T17:45:21Z
2006-06-19T17:45:21Z
2004
2004
http://hdl.handle.net/1721.1/33148
62256284
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.
Includes bibliographical references (p. 119-121).
Infectious disease models predict the impact of outbreaks. Discrepancies between model predictions stem from both the disease parameters used and the underlying mathematics of the models. Smallpox has been modeled extensively in recent years to determine successful response guidelines for a future outbreak. Five models, which range in fidelity, were created for this thesis in an attempt to reveal the differences inherent in the mathematical techniques used in the models. The disease parameters were standardized across all models. Predictions for various outbreak scenarios are given, and the strengths and weaknesses of each modeling technique are discussed. The mixing strategy used greatly affects the predictions of the models. The results gathered indicate that mass vaccination should be considered as a primary response technique in the event of a future smallpox outbreak.
by Cory Y. McLean.
M.Eng.
121 p.
5681061 bytes
5688592 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Epidemic modeling techniques for smallpox
Thesis
application/pdf
false
Publication
unknown
unknown
<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="6ca07828-92dc-4300-b3f3-ad704bb0940d">
<Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type>
<Language>eng</Language>
<Title>Epidemic modeling techniques for smallpox</Title>
<PublishedIn>
<Publication>
</Publication>
</PublishedIn>
<PublicationDate>2004</PublicationDate>
<Authors>
<Author>
<DisplayName>McLean, Cory Y. (Cory Yuen Fu)</DisplayName>
<Affiliation>
<OrgUnit>
</OrgUnit>
</Affiliation>
</Author>
</Authors>
<Editors>
</Editors>
<Publishers>
<Publisher>
<DisplayName>Massachusetts Institute of Technology</DisplayName>
<OrgUnit />
</Publisher>
</Publishers>
<License>http://dspace.mit.edu/handle/1721.1/7582</License>
<Keyword>Electrical Engineering and Computer Science.</Keyword>
<Abstract>Infectious disease models predict the impact of outbreaks. Discrepancies between model predictions stem from both the disease parameters used and the underlying mathematics of the models. Smallpox has been modeled extensively in recent years to determine successful response guidelines for a future outbreak. Five models, which range in fidelity, were created for this thesis in an attempt to reveal the differences inherent in the mathematical techniques used in the models. The disease parameters were standardized across all models. Predictions for various outbreak scenarios are given, and the strengths and weaknesses of each modeling technique are discussed. The mixing strategy used greatly affects the predictions of the models. The results gathered indicate that mass vaccination should be considered as a primary response technique in the event of a future smallpox outbreak.</Abstract>
<Access xmlns="http://purl.org/coar/access_right"
>
</Access>
</Publication>