Literature DB >> 22819637

Using egg production data to quantify within-flock transmission of low pathogenic avian influenza virus in commercial layer chickens.

J L Gonzales1, A R W Elbers, J A van der Goot, D Bontje, G Koch, J J de Wit, J A Stegeman.   

Abstract

Even though low pathogenic avian influenza viruses (LPAIv) affect the poultry industry of several countries in the world, information about their transmission characteristics in poultry is sparse. Outbreak reports of LPAIv in layer chickens have described drops in egg production that appear to be correlated with the virus transmission dynamics. The objective of this study was to use egg production data from LPAIv infected layer flocks to quantify the within-flock transmission parameters of the virus. Egg production data from two commercial layer chicken flocks which were infected with an H7N3 LPAIv were used for this study. In addition, an isolate of the H7N3 LPAIv causing these outbreaks was used in a transmission experiment. The field and experimental estimates showed that this is a virus with high transmission characteristics. Furthermore, with the field method, the day of introduction of the virus into the flock was estimated. The method here presented uses compartmental models that assume homogeneous mixing. This method is, therefore, best suited to study transmission in commercial flocks with a litter (floor-reared) housing system. It would also perform better, when used to study transmission retrospectively, after the outbreak has finished and there is egg production data from recovered chickens. This method cannot be used when a flock was affected with a LPAIv with low transmission characteristics (R(0)<2), since the drop in egg production would be low and likely to be confounded with the expected decrease in production due to aging of the flock. Because only two flocks were used for this analysis, this study is a preliminary basis for a proof of principle that transmission parameters of LPAIv infections in layer chicken flocks could be quantified using the egg production data from affected flocks.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 22819637     DOI: 10.1016/j.prevetmed.2012.06.010

Source DB:  PubMed          Journal:  Prev Vet Med        ISSN: 0167-5877            Impact factor:   2.670


  6 in total

1.  Estimating the introduction time of highly pathogenic avian influenza into poultry flocks.

Authors:  Peter H F Hobbelen; Armin R W Elbers; Marleen Werkman; Guus Koch; Francisca C Velkers; Arjan Stegeman; Thomas J Hagenaars
Journal:  Sci Rep       Date:  2020-07-24       Impact factor: 4.379

2.  Quantifying the effect of swab pool size on the detection of influenza A viruses in broiler chickens and its implications for surveillance.

Authors:  Amos Ssematimba; Sasidhar Malladi; Peter J Bonney; Cristian Flores-Figueroa; Jeannette Muñoz-Aguayo; David A Halvorson; Carol J Cardona
Journal:  BMC Vet Res       Date:  2018-09-03       Impact factor: 2.741

3.  Genetic analysis identifies potential transmission of low pathogenic avian influenza viruses between poultry farms.

Authors:  Saskia A Bergervoet; Rene Heutink; Ruth Bouwstra; Ron A M Fouchier; Nancy Beerens
Journal:  Transbound Emerg Dis       Date:  2019-04-25       Impact factor: 5.005

4.  Inferring within-flock transmission dynamics of highly pathogenic avian influenza H5N8 virus in France, 2020.

Authors:  Timothée Vergne; Simon Gubbins; Claire Guinat; Billy Bauzile; Mattias Delpont; Debapriyo Chakraborty; Hugo Gruson; Benjamin Roche; Mathieu Andraud; Mathilde Paul; Jean-Luc Guérin
Journal:  Transbound Emerg Dis       Date:  2021-07-27       Impact factor: 4.521

5.  Bayesian inference of epidemiological parameters from transmission experiments.

Authors:  Ben Hu; Jose L Gonzales; Simon Gubbins
Journal:  Sci Rep       Date:  2017-12-01       Impact factor: 4.379

6.  Characterization of immunogenicity of avian influenza antigens encapsulated in PLGA nanoparticles following mucosal and subcutaneous delivery in chickens.

Authors:  Tamiru Negash Alkie; Alexander Yitbarek; Khaled Taha-Abdelaziz; Jake Astill; Shayan Sharif
Journal:  PLoS One       Date:  2018-11-01       Impact factor: 3.240

  6 in total

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