Topics in Bayesian Inference and Model Assessment for Partially Observed Stochastic Epidemic Models
Author: Georgios Aristotelous
Publisher:
Published: 2020
Total Pages:
ISBN-13:
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Author: Georgios Aristotelous
Publisher:
Published: 2020
Total Pages:
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DOWNLOAD EBOOKAuthor: Panayiota Touloupou
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Published: 2016
Total Pages: 510
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DOWNLOAD EBOOKAuthor: P. D. O'Neill
Publisher:
Published: 1997
Total Pages: 12
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DOWNLOAD EBOOKAuthor: Theodore Kypraios
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Published: 2007
Total Pages: 0
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DOWNLOAD EBOOKAuthor: Jonathan Fintzi
Publisher:
Published: 2018
Total Pages: 357
ISBN-13:
DOWNLOAD EBOOKEpidemic count data reported by public health surveillance systems reflect the incidence or prevalence of an infectious agent as it spreads through a population. They are a primary source of information for shaping response strategies and for predicting how an outbreak will evolve. Incidence and prevalence counts are often the only source of information about historical outbreaks, or outbreaks in resource limited settings, which are of interest for researchers seeking to develop an understanding of disease transmission during ``peace time", with an eye on preparing for future outbreaks. The absence of subject--level information and the systematic underreporting of cases complicate the task of disentangling whether the data arose from a severe outbreak, observed with low fidelity, or a mild outbreak were most cases were detected. The magnitude of the missing data and the high dimensional state space of the latent epidemic process present challenges for fitting epidemic models that appropriately quantify the stochastic aspects of the transmission dynamics. In this dissertation, we develop computational algorithms for fitting stochastic epidemic models to partially observed incidence and prevalence data. Our algorithms are not specific to particular model dynamics, but rather apply to a broad class of commonly used stochastic epidemic models, including models that allow for time--inhomogeneous transmission dynamics. We use our methods to analyze data from an outbreak of influenza in a British boarding school, the 2014--2015 outbreak of Ebola in West Africa, and the 2009--2011 A(H1N1) influenza pandemic in Finland.
Author: Tom Britton
Publisher: Springer Nature
Published: 2019-11-30
Total Pages: 474
ISBN-13: 3030309002
DOWNLOAD EBOOKFocussing on stochastic models for the spread of infectious diseases in a human population, this book is the outcome of a two-week ICPAM/CIMPA school on "Stochastic models of epidemics" which took place in Ziguinchor, Senegal, December 5–16, 2015. The text is divided into four parts, each based on one of the courses given at the school: homogeneous models (Tom Britton and Etienne Pardoux), two-level mixing models (David Sirl and Frank Ball), epidemics on graphs (Viet Chi Tran), and statistics for epidemic models (Catherine Larédo). The CIMPA school was aimed at PhD students and Post Docs in the mathematical sciences. Parts (or all) of this book can be used as the basis for traditional or individual reading courses on the topic. For this reason, examples and exercises (some with solutions) are provided throughout.
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Published: 2006
Total Pages: 240
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Published: 2008
Total Pages: 3
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DOWNLOAD EBOOKAuthor: Hola Kwame Adrakey
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Published: 2016
Total Pages:
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DOWNLOAD EBOOKAuthor: Andrea Kraus
Publisher:
Published: 2013
Total Pages: 228
ISBN-13:
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