Identifying areas for infectious animal disease surveillance in the absence of population data Highly pathogenic avian influenza in wild bird populations of Europe

A large number (n=591) of H5N1 highly pathogenic avian influenza virus (HPAIV) outbreaks have been reported in wild birds of Europe from October 2005 through January 2009. Consequently, prevention and control strategies have been implemented in response to the outbreaks and considerable discussion has taken place regarding the need for implementing surveillance programs in high-risk areas with the objective of early detecting and preventing HPAIV epidemics. However countries ability to define the temporal and spatial extension of the high risk areas has been impaired by the lack of information on the distribution of susceptible wild bird populations in the region. Here, a technique for the detection of time-space disease clustering that does not require information on the distribution of susceptible populations and that has been referred to as the time-space permutation model of the scan statistic was used to identify areas and times of the year in which epidemics of H5N1 HPAIV were most likely to occur in wild bird populations of Europe from October, 2005, through December, 2008. The scan statistic was parameterized considering pre-existing knowledge on the epidemiological and ecological characteristics of the disease in the region. Robustness of the results was assessed using a generalized linear regression model to compare the outcomes of 36 alternative parameterizations of the scan statistic. Ten significant time-space clusters of H5N1 HPAI outbreaks were detected in six European countries. Results were sensitive (P<0.05) to the definition of the maximum spatial size defined for the clusters. Results presented here will help to identify high risk areas for HPAIV surveillance in the European Union. Assumptions, results, and implications of the analytical model are extensively presented and discussed in order to facilitate the use of this approach for the identification of high risk areas for infectious animal disease surveillance in the absence of population data. © 2010 Elsevier B.V.

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Main Authors: Iglesias Martín, Irene, Perez, A. M., De La Torre Reoyo, Ana Isabel, Muñoz, M. J., Martínez, M., Sánchez-Vizcaíno, J. M.
Format: artículo de revisión biblioteca
Language:English
Published: Elsevier 2010
Subjects:Time–space clustering, Surveillance, Avian influenza, Wild birds, Risk areas,
Online Access:http://hdl.handle.net/20.500.12792/2145
http://hdl.handle.net/10261/291946
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spelling dig-inia-es-10261-2919462023-02-20T07:23:55Z Identifying areas for infectious animal disease surveillance in the absence of population data Highly pathogenic avian influenza in wild bird populations of Europe Iglesias Martín, Irene Perez, A. M. De La Torre Reoyo, Ana Isabel Muñoz, M. J. Martínez, M. Sánchez-Vizcaíno, J. M. Time–space clustering Surveillance Avian influenza Wild birds Risk areas A large number (n=591) of H5N1 highly pathogenic avian influenza virus (HPAIV) outbreaks have been reported in wild birds of Europe from October 2005 through January 2009. Consequently, prevention and control strategies have been implemented in response to the outbreaks and considerable discussion has taken place regarding the need for implementing surveillance programs in high-risk areas with the objective of early detecting and preventing HPAIV epidemics. However countries ability to define the temporal and spatial extension of the high risk areas has been impaired by the lack of information on the distribution of susceptible wild bird populations in the region. Here, a technique for the detection of time-space disease clustering that does not require information on the distribution of susceptible populations and that has been referred to as the time-space permutation model of the scan statistic was used to identify areas and times of the year in which epidemics of H5N1 HPAIV were most likely to occur in wild bird populations of Europe from October, 2005, through December, 2008. The scan statistic was parameterized considering pre-existing knowledge on the epidemiological and ecological characteristics of the disease in the region. Robustness of the results was assessed using a generalized linear regression model to compare the outcomes of 36 alternative parameterizations of the scan statistic. Ten significant time-space clusters of H5N1 HPAI outbreaks were detected in six European countries. Results were sensitive (P<0.05) to the definition of the maximum spatial size defined for the clusters. Results presented here will help to identify high risk areas for HPAIV surveillance in the European Union. Assumptions, results, and implications of the analytical model are extensively presented and discussed in order to facilitate the use of this approach for the identification of high risk areas for infectious animal disease surveillance in the absence of population data. © 2010 Elsevier B.V. 2023-02-20T07:23:55Z 2023-02-20T07:23:55Z 2010 artículo de revisión Preventive Veterinary Medicine 96(1-2): 1-8 (2010) 0167-5877 http://hdl.handle.net/20.500.12792/2145 http://hdl.handle.net/10261/291946 10.1016/j.prevetmed.2010.05.002 en none Elsevier
institution INIA ES
collection DSpace
country España
countrycode ES
component Bibliográfico
access En linea
databasecode dig-inia-es
tag biblioteca
region Europa del Sur
libraryname Biblioteca del INIA España
language English
topic Time–space clustering
Surveillance
Avian influenza
Wild birds
Risk areas
Time–space clustering
Surveillance
Avian influenza
Wild birds
Risk areas
spellingShingle Time–space clustering
Surveillance
Avian influenza
Wild birds
Risk areas
Time–space clustering
Surveillance
Avian influenza
Wild birds
Risk areas
Iglesias Martín, Irene
Perez, A. M.
De La Torre Reoyo, Ana Isabel
Muñoz, M. J.
Martínez, M.
Sánchez-Vizcaíno, J. M.
Identifying areas for infectious animal disease surveillance in the absence of population data Highly pathogenic avian influenza in wild bird populations of Europe
description A large number (n=591) of H5N1 highly pathogenic avian influenza virus (HPAIV) outbreaks have been reported in wild birds of Europe from October 2005 through January 2009. Consequently, prevention and control strategies have been implemented in response to the outbreaks and considerable discussion has taken place regarding the need for implementing surveillance programs in high-risk areas with the objective of early detecting and preventing HPAIV epidemics. However countries ability to define the temporal and spatial extension of the high risk areas has been impaired by the lack of information on the distribution of susceptible wild bird populations in the region. Here, a technique for the detection of time-space disease clustering that does not require information on the distribution of susceptible populations and that has been referred to as the time-space permutation model of the scan statistic was used to identify areas and times of the year in which epidemics of H5N1 HPAIV were most likely to occur in wild bird populations of Europe from October, 2005, through December, 2008. The scan statistic was parameterized considering pre-existing knowledge on the epidemiological and ecological characteristics of the disease in the region. Robustness of the results was assessed using a generalized linear regression model to compare the outcomes of 36 alternative parameterizations of the scan statistic. Ten significant time-space clusters of H5N1 HPAI outbreaks were detected in six European countries. Results were sensitive (P<0.05) to the definition of the maximum spatial size defined for the clusters. Results presented here will help to identify high risk areas for HPAIV surveillance in the European Union. Assumptions, results, and implications of the analytical model are extensively presented and discussed in order to facilitate the use of this approach for the identification of high risk areas for infectious animal disease surveillance in the absence of population data. © 2010 Elsevier B.V.
format artículo de revisión
topic_facet Time–space clustering
Surveillance
Avian influenza
Wild birds
Risk areas
author Iglesias Martín, Irene
Perez, A. M.
De La Torre Reoyo, Ana Isabel
Muñoz, M. J.
Martínez, M.
Sánchez-Vizcaíno, J. M.
author_facet Iglesias Martín, Irene
Perez, A. M.
De La Torre Reoyo, Ana Isabel
Muñoz, M. J.
Martínez, M.
Sánchez-Vizcaíno, J. M.
author_sort Iglesias Martín, Irene
title Identifying areas for infectious animal disease surveillance in the absence of population data Highly pathogenic avian influenza in wild bird populations of Europe
title_short Identifying areas for infectious animal disease surveillance in the absence of population data Highly pathogenic avian influenza in wild bird populations of Europe
title_full Identifying areas for infectious animal disease surveillance in the absence of population data Highly pathogenic avian influenza in wild bird populations of Europe
title_fullStr Identifying areas for infectious animal disease surveillance in the absence of population data Highly pathogenic avian influenza in wild bird populations of Europe
title_full_unstemmed Identifying areas for infectious animal disease surveillance in the absence of population data Highly pathogenic avian influenza in wild bird populations of Europe
title_sort identifying areas for infectious animal disease surveillance in the absence of population data highly pathogenic avian influenza in wild bird populations of europe
publisher Elsevier
publishDate 2010
url http://hdl.handle.net/20.500.12792/2145
http://hdl.handle.net/10261/291946
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