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February 2018 Evidence Synthesis for Stochastic Epidemic Models
Paul J. Birrell, Daniela De Angelis, Anne M. Presanis
Statist. Sci. 33(1): 34-43 (February 2018). DOI: 10.1214/17-STS631

Abstract

In recent years, the role of epidemic models in informing public health policies has progressively grown. Models have become increasingly realistic and more complex, requiring the use of multiple data sources to estimate all quantities of interest. This review summarises the different types of stochastic epidemic models that use evidence synthesis and highlights current challenges.

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Paul J. Birrell. Daniela De Angelis. Anne M. Presanis. "Evidence Synthesis for Stochastic Epidemic Models." Statist. Sci. 33 (1) 34 - 43, February 2018. https://doi.org/10.1214/17-STS631

Information

Published: February 2018
First available in Project Euclid: 2 February 2018

zbMATH: 07031388
MathSciNet: MR3757502
Digital Object Identifier: 10.1214/17-STS631

Keywords: Epidemic modelling , evidence synthesis , mechanistic modelling , state-space models

Rights: Copyright © 2018 Institute of Mathematical Statistics

Vol.33 • No. 1 • February 2018
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