The University of Southampton
University of Southampton Institutional Repository

H7N9 and H5N1 avian influenza suitability models for China: accounting for new poultry and live-poultry markets distribution data

H7N9 and H5N1 avian influenza suitability models for China: accounting for new poultry and live-poultry markets distribution data
H7N9 and H5N1 avian influenza suitability models for China: accounting for new poultry and live-poultry markets distribution data
Risk maps are one of several sources used to inform risk-based disease surveillance and control systems, but their production can be hampered by lack of access to suitable disease data. In such situations, knowledge-driven spatial modeling methods are an alternative to data-driven approaches. This study used multicriteria decision analysis (MCDA) to identify areas in Asia suitable for the occurrence of highly pathogenic avian influenza virus (HPAIV) H5N1 in domestic poultry. Areas most suitable for H5N1 occurrence included Bangladesh, the southern tip and eastern coast of Vietnam, parts of north-central Thailand and large parts of eastern China. The predictive accuracy of the final model, as determined by the area under the receiver operating characteristic curve (ROC AUC), was 0.670 (95% CI 0.667-0.673) suggesting that, in data-scarce environments, MCDA provides a reasonable alternative to the data-driven approaches usually used to inform risk-based disease surveillance and control strategies.
1436-3240
1-10
Artois, Jean
3343be37-bdde-44cd-b5bd-d9be5b483b1f
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Feng, Luzhao
5842cd78-bfa7-40d1-ae76-92ca4bf70c4d
Jiang, Hui
fecd6868-9358-49c6-99a6-e6dbc9cf9f3e
Zhou, Hang
e6311e21-1708-41e9-ac9b-bfdd834102b9
Li, Xiangping
c8693668-7685-4d41-bc9c-aed81d1de122
Dhingra, Madhur S.
2d5e985f-b45f-4f25-b913-c490ad46eb77
Linard, Catherine
231a1de7-72c2-4dc1-bc4e-ea30ed444856
Nicolas, Gaëlle
f99c5657-8c71-42cb-824b-5321fd65cb4d
Xiao, Xiangming
bb32f3da-c0b6-49d7-b69f-362eeac33026
Robinson, Timothy P.
c668ca6e-11b6-4624-8dfc-942a439701d8
Yu, Hongjie
f6a43c0c-0da8-4124-bd15-cd832d6fee7c
Gilbert, Marius
c7b7a250-9ec8-47ea-8f08-3b847f0c576c
Artois, Jean
3343be37-bdde-44cd-b5bd-d9be5b483b1f
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Feng, Luzhao
5842cd78-bfa7-40d1-ae76-92ca4bf70c4d
Jiang, Hui
fecd6868-9358-49c6-99a6-e6dbc9cf9f3e
Zhou, Hang
e6311e21-1708-41e9-ac9b-bfdd834102b9
Li, Xiangping
c8693668-7685-4d41-bc9c-aed81d1de122
Dhingra, Madhur S.
2d5e985f-b45f-4f25-b913-c490ad46eb77
Linard, Catherine
231a1de7-72c2-4dc1-bc4e-ea30ed444856
Nicolas, Gaëlle
f99c5657-8c71-42cb-824b-5321fd65cb4d
Xiao, Xiangming
bb32f3da-c0b6-49d7-b69f-362eeac33026
Robinson, Timothy P.
c668ca6e-11b6-4624-8dfc-942a439701d8
Yu, Hongjie
f6a43c0c-0da8-4124-bd15-cd832d6fee7c
Gilbert, Marius
c7b7a250-9ec8-47ea-8f08-3b847f0c576c

Artois, Jean, Lai, Shengjie, Feng, Luzhao, Jiang, Hui, Zhou, Hang, Li, Xiangping, Dhingra, Madhur S., Linard, Catherine, Nicolas, Gaëlle, Xiao, Xiangming, Robinson, Timothy P., Yu, Hongjie and Gilbert, Marius (2016) H7N9 and H5N1 avian influenza suitability models for China: accounting for new poultry and live-poultry markets distribution data. Stochastic Environmental Research and Risk Assessment, 1-10. (doi:10.1007/s00477-016-1362-z).

Record type: Article

Abstract

Risk maps are one of several sources used to inform risk-based disease surveillance and control systems, but their production can be hampered by lack of access to suitable disease data. In such situations, knowledge-driven spatial modeling methods are an alternative to data-driven approaches. This study used multicriteria decision analysis (MCDA) to identify areas in Asia suitable for the occurrence of highly pathogenic avian influenza virus (HPAIV) H5N1 in domestic poultry. Areas most suitable for H5N1 occurrence included Bangladesh, the southern tip and eastern coast of Vietnam, parts of north-central Thailand and large parts of eastern China. The predictive accuracy of the final model, as determined by the area under the receiver operating characteristic curve (ROC AUC), was 0.670 (95% CI 0.667-0.673) suggesting that, in data-scarce environments, MCDA provides a reasonable alternative to the data-driven approaches usually used to inform risk-based disease surveillance and control strategies.

Text
2016- Stoch Environ Res Risk Assess - H7N9 and H5N1 avian influenza suitability models for China.pdf - Version of Record
Available under License Creative Commons Attribution.
Download (3MB)

More information

Accepted/In Press date: 25 November 2016
e-pub ahead of print date: 5 December 2016
Organisations: WorldPop, Population, Health & Wellbeing (PHeW)

Identifiers

Local EPrints ID: 405108
URI: https://eprints.soton.ac.uk/id/eprint/405108
ISSN: 1436-3240
PURE UUID: fb530e4b-3d3c-425d-8823-cd825aff5a79
ORCID for Shengjie Lai: ORCID iD orcid.org/0000-0001-9781-8148

Catalogue record

Date deposited: 27 Jan 2017 09:50
Last modified: 08 Mar 2019 01:21

Export record

Altmetrics

Contributors

Author: Jean Artois
Author: Shengjie Lai ORCID iD
Author: Luzhao Feng
Author: Hui Jiang
Author: Hang Zhou
Author: Xiangping Li
Author: Madhur S. Dhingra
Author: Catherine Linard
Author: Gaëlle Nicolas
Author: Xiangming Xiao
Author: Timothy P. Robinson
Author: Hongjie Yu
Author: Marius Gilbert

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×