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)

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 Science and Engineering > School of Computing Science; College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
• 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