Giuseppe
Emeritus
[Source: PLoS ONE, full page: (LINK). Abstract, edited.]
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Model to Track Wild Birds for Avian Influenza by Means of Population Dynamics and Surveillance Information
Anna Alba<SUP>1</SUP><SUP>*</SUP>, Dominique J. Bicout<SUP>2</SUP>, Francesc Vidal<SUP>3</SUP>, Antoni Curc?<SUP>3</SUP>, Alberto Allepuz<SUP>1</SUP><SUP>,</SUP><SUP>4</SUP>, Sebasti?n Napp<SUP>1</SUP>, Ignacio Garc?a-Bocanegra<SUP>1</SUP><SUP>,</SUP><SUP>5</SUP>, Taiana Costa<SUP>4</SUP>, Jordi Casal<SUP>1</SUP><SUP>,</SUP><SUP>4</SUP>
<SUP></SUP>
1 Centre de Recerca en Sanitat Animal, Universitat Aut?noma de Barcelona-IRTA, Campus de la Universitat Aut?noma de Barcelona, Barcelona, Spain, 2 Unit? BioMath?matiques et Epid?miologie ? Environnement et Pr?diction de la Sant? des Populations TIMC, Centre national de la recherche scientifique. VetAgro Sup, Marcy l?Etoile, France, 3 Parc Natural del Delta de l?Ebre, Departament de Medi Ambient i Habitatge, Deltebre, Tarragona, Spain, 4 Departament de Sanitat i Anatomia Animals, Universitat Aut?noma de Barcelona, Barcelona, Spain, 5 Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad de C?rdoba, C?rdoba, Spain
Abstract
Design, sampling and data interpretation constitute an important challenge for wildlife surveillance of avian influenza viruses (AIV). The aim of this study was to construct a model to improve and enhance identification in both different periods and locations of avian species likely at high risk of contact with AIV in a specific wetland. This study presents an individual-based stochastic model for the Ebre Delta as an example of this appliance. Based on the Monte-Carlo method, the model simulates the dynamics of the spread of AIV among wild birds in a natural park following introduction of an infected bird. Data on wild bird species population, apparent AIV prevalence recorded in wild birds during the period of study, and ecological information on factors such as behaviour, contact rates or patterns of movements of waterfowl were incorporated as inputs of the model. From these inputs, the model predicted those species that would introduce most of AIV in different periods and those species and areas that would be at high risk as a consequence of the spread of these AIV incursions. This method can serve as a complementary tool to previous studies to optimize the allocation of the limited AI surveillance resources in a local complex ecosystem. However, this study indicates that in order to predict the evolution of the spread of AIV at the local scale, there is a need for further research on the identification of host factors involved in the interspecies transmission of AIV.
Citation: Alba A, Bicout DJ, Vidal F, Curc? A, Allepuz A, et al. (2012) Model to Track Wild Birds for Avian Influenza by Means of Population Dynamics and Surveillance Information. PLoS ONE 7(8): e44354. doi:10.1371/journal.pone.0044354
Editor: Justin David Brown, University of Georgia, United States of America
Received: August 14, 2010; Accepted: August 6, 2012; Published: August 30, 2012
Copyright: ? 2012 Alba et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work has been supported by the Department of Agriculture, Livestock, Fisheries, Food and Environment (DAAM) of the Catalan Government (Spain) as part of Surveillance Program for Avian Influenza in Catalonia, financing the expenses of technical personnel. URL: http://www20.gencat.cat/portal/site/DAR. The funders accepted the publication of this work and had no role in its design, data analysis, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
* E-mail: ana.alba@cresa.uab.es
-Anna Alba<SUP>1</SUP><SUP>*</SUP>, Dominique J. Bicout<SUP>2</SUP>, Francesc Vidal<SUP>3</SUP>, Antoni Curc?<SUP>3</SUP>, Alberto Allepuz<SUP>1</SUP><SUP>,</SUP><SUP>4</SUP>, Sebasti?n Napp<SUP>1</SUP>, Ignacio Garc?a-Bocanegra<SUP>1</SUP><SUP>,</SUP><SUP>5</SUP>, Taiana Costa<SUP>4</SUP>, Jordi Casal<SUP>1</SUP><SUP>,</SUP><SUP>4</SUP>
<SUP></SUP>
1 Centre de Recerca en Sanitat Animal, Universitat Aut?noma de Barcelona-IRTA, Campus de la Universitat Aut?noma de Barcelona, Barcelona, Spain, 2 Unit? BioMath?matiques et Epid?miologie ? Environnement et Pr?diction de la Sant? des Populations TIMC, Centre national de la recherche scientifique. VetAgro Sup, Marcy l?Etoile, France, 3 Parc Natural del Delta de l?Ebre, Departament de Medi Ambient i Habitatge, Deltebre, Tarragona, Spain, 4 Departament de Sanitat i Anatomia Animals, Universitat Aut?noma de Barcelona, Barcelona, Spain, 5 Departamento de Sanidad Animal, Facultad de Veterinaria, Universidad de C?rdoba, C?rdoba, Spain
Abstract
Design, sampling and data interpretation constitute an important challenge for wildlife surveillance of avian influenza viruses (AIV). The aim of this study was to construct a model to improve and enhance identification in both different periods and locations of avian species likely at high risk of contact with AIV in a specific wetland. This study presents an individual-based stochastic model for the Ebre Delta as an example of this appliance. Based on the Monte-Carlo method, the model simulates the dynamics of the spread of AIV among wild birds in a natural park following introduction of an infected bird. Data on wild bird species population, apparent AIV prevalence recorded in wild birds during the period of study, and ecological information on factors such as behaviour, contact rates or patterns of movements of waterfowl were incorporated as inputs of the model. From these inputs, the model predicted those species that would introduce most of AIV in different periods and those species and areas that would be at high risk as a consequence of the spread of these AIV incursions. This method can serve as a complementary tool to previous studies to optimize the allocation of the limited AI surveillance resources in a local complex ecosystem. However, this study indicates that in order to predict the evolution of the spread of AIV at the local scale, there is a need for further research on the identification of host factors involved in the interspecies transmission of AIV.
Citation: Alba A, Bicout DJ, Vidal F, Curc? A, Allepuz A, et al. (2012) Model to Track Wild Birds for Avian Influenza by Means of Population Dynamics and Surveillance Information. PLoS ONE 7(8): e44354. doi:10.1371/journal.pone.0044354
Editor: Justin David Brown, University of Georgia, United States of America
Received: August 14, 2010; Accepted: August 6, 2012; Published: August 30, 2012
Copyright: ? 2012 Alba et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work has been supported by the Department of Agriculture, Livestock, Fisheries, Food and Environment (DAAM) of the Catalan Government (Spain) as part of Surveillance Program for Avian Influenza in Catalonia, financing the expenses of technical personnel. URL: http://www20.gencat.cat/portal/site/DAR. The funders accepted the publication of this work and had no role in its design, data analysis, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
* E-mail: ana.alba@cresa.uab.es
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