Statistical Science

Evidence Synthesis for Stochastic Epidemic Models

Paul J. Birrell, Daniela De Angelis, and Anne M. Presanis

Full-text: Open access

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.

Article information

Source
Statist. Sci., Volume 33, Number 1 (2018), 34-43.

Dates
First available in Project Euclid: 2 February 2018

Permanent link to this document
https://projecteuclid.org/euclid.ss/1517562023

Digital Object Identifier
doi:10.1214/17-STS631

Mathematical Reviews number (MathSciNet)
MR3757502

Zentralblatt MATH identifier
07031388

Keywords
Evidence synthesis state-space models epidemic modelling mechanistic modelling

Citation

Birrell, Paul J.; De Angelis, Daniela; Presanis, Anne M. Evidence Synthesis for Stochastic Epidemic Models. Statist. Sci. 33 (2018), no. 1, 34--43. doi:10.1214/17-STS631. https://projecteuclid.org/euclid.ss/1517562023


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