Reconstructing disease transmission dynamics from animal movements and test data

Enright, J.A. and O'Hare, A. (2017) Reconstructing disease transmission dynamics from animal movements and test data. Stochastic Environmental Research and Risk Assessment, 31(2), pp. 369-377. (doi: 10.1007/s00477-016-1354-z)

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Abstract

Disease outbreaks are often accompanied by a wealth of data, usually in the form of movements, locations and tests. This data is a valuable resource in which data scientists and epidemiologists can reconstruct the transmission pathways and parameters and thus devise control strategies. However, the spatiotemporal data gathered can be both vast whilst at the same time incomplete or contain errors frustrating the effort to accurately model the transmission processes. Fortunately, several techniques exist that can be used to infer the relevant information to help explain these processes. The aim of this article is to provide the reader with a user friendly introduction to the techniques used in dealing with the large datasets that exists in epidemiological and ecological science and the common pitfalls that are to be avoided as well as an introduction to inference techniques for estimating parameter values for mathematical models from spatiotemporal datasets.

Item Type:Articles
Additional Information:The authors gratefully acknowledge funding and data from the Scottish Government as part of EPIC: Scotland’s Centre of Expertise on Animal Disease Outbreaks.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:O'Hare, Dr Anthony and Enright, Dr Jessica
Authors: Enright, J.A., and O'Hare, A.
College/School:College of Medical Veterinary and Life Sciences > Institute of Biodiversity Animal Health and Comparative Medicine
College of Science and Engineering > School of Computing Science
Journal Name:Stochastic Environmental Research and Risk Assessment
Publisher:Springer
ISSN:1436-3240
ISSN (Online):1436-3259
Published Online:16 November 2016
Copyright Holders:Copyright © 2016 The Authors
First Published:First published in Stochastic Environmental Research and Risk Assessment 31(2): 369-377
Publisher Policy:Reproduced under a Creative Commons License

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