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Permanent link (DOI): https://doi.org/10.7939/R3G94T

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Spatio-temporal prediction modeling of clusters of influenza cases Open Access

Descriptions

Other title
Subject/Keyword
influenza prediction
multivariate Pearson Type VII family
cross-validation
pseudo-likelihood
generalized linear mixed model
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Qiu, Weiyu
Supervisor and department
Yasui, Yutaka (Public Health Sciences)
Examining committee member and department
Martinez, Jose Miguel (Department of Experimental and Health Sciences)
Dinu, Irina (Public Health Sciences)
Zhang, Peng (Mathematical and Statistical Sciences)
Department
Department of Public Health Sciences
Specialization

Date accepted
2011-08-31T14:13:33Z
Graduation date
2011-11
Degree
Master of Science
Degree level
Master's
Abstract
Timely, accurate predictions of potential influenza epidemics are essential for healthcare providers and policy makers as the epidemics can result in heavy demands for health services. Current statistical modeling of surveillance data has limited prediction abilities and often fails to respond effectively to the outbreaks. The first part of this thesis, a collaboration with Alberta Health Services, aims at predicting clusters of influenza cases in Edmonton weeks in advance, using real-time data collected from emergency-department visits by Alberta Real Time Syndromic Surveillance Net. The 2004-2009 data are analyzed by spatio-temporal modeling and predictions are cross-validated. In the second part of this thesis, a related theoretical work on multivariate modeling, with spatio-temporal modeling as a potential application, is presented, proving that every conditional second moment is linear in the empirical second moment of the conditioning vector if and only if the distribution belongs to the multivariate Pearson type VII family.
Language
English
DOI
doi:10.7939/R3G94T
Rights
License granted by Weiyu Qiu (weiyu@ualberta.ca) on 2011-08-31T06:59:54Z (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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