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Stochastic Methodology for the Study of an Epidemic Decay Phase, Based on a Branching Model
Joint Authors
Jacob, Christine
Pénisson, Sophie
Source
International Journal of Stochastic Analysis
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-32, 32 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-12-04
Country of Publication
Egypt
No. of Pages
32
Main Subjects
Abstract EN
We present a stochastic methodology to study the decay phase of an epidemic.
It is based on a general stochastic epidemic process with memory, suitable to model the spread in a large open population with births of any rare transmissible disease with a random incubation period and a Reed-Frost type infection.
This model, which belongs to the class of multitype branching processes in discrete time, enables us to predict the incidences of cases and to derive the probability distributions of the extinction time and of the future epidemic size.
We also study the epidemic evolution in the worst-case scenario of a very late extinction time, making use of the Q-process.
We provide in addition an estimator of the key parameter of the epidemic model quantifying the infection and finally illustrate this methodology with the study of the Bovine Spongiform Encephalopathy epidemic in Great Britain after the 1988 feed ban law.
American Psychological Association (APA)
Pénisson, Sophie& Jacob, Christine. 2012. Stochastic Methodology for the Study of an Epidemic Decay Phase, Based on a Branching Model. International Journal of Stochastic Analysis،Vol. 2012, no. 2012, pp.1-32.
https://search.emarefa.net/detail/BIM-484030
Modern Language Association (MLA)
Pénisson, Sophie& Jacob, Christine. Stochastic Methodology for the Study of an Epidemic Decay Phase, Based on a Branching Model. International Journal of Stochastic Analysis No. 2012 (2012), pp.1-32.
https://search.emarefa.net/detail/BIM-484030
American Medical Association (AMA)
Pénisson, Sophie& Jacob, Christine. Stochastic Methodology for the Study of an Epidemic Decay Phase, Based on a Branching Model. International Journal of Stochastic Analysis. 2012. Vol. 2012, no. 2012, pp.1-32.
https://search.emarefa.net/detail/BIM-484030
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-484030