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Development of Disease‐specific, Context‐specific Surveillance Models: Avian Influenza (H5N1)‐Related Risks and Behaviours in African Countries

Identifieur interne : 001D28 ( Istex/Corpus ); précédent : 001D27; suivant : 001D29

Development of Disease‐specific, Context‐specific Surveillance Models: Avian Influenza (H5N1)‐Related Risks and Behaviours in African Countries

Auteurs : F. O. Fasina ; P. M. K. Njage ; A. M. M. Ali ; J. M. Yilma ; D. G. Bwala ; A. L. Rivas ; A. J. Stegeman

Source :

RBID : ISTEX:ECC4FA68208188DB15A841D99AC04C493922A29F

Abstract

Avian influenza virus (H5N1) is a rapidly disseminating infection that affects poultry and, potentially, humans. Because the avian virus has already adapted to several mammalian species, decreasing the rate of avian–mammalian contacts is critical to diminish the chances of a total adaptation of H5N1 to humans. To prevent the pandemic such adaptation could facilitate, a biology‐specific disease surveillance model is needed, which should also consider geographical and socio‐cultural factors. Here, we conceptualized a surveillance model meant to capture H5N1‐related biological and cultural aspects, which included food processing, trade and cooking‐related practices, as well as incentives (or disincentives) for desirable behaviours. This proof of concept was tested with data collected from 378 Egyptian and Nigerian sites (local [backyard] producers/live bird markets/village abattoirs/commercial abattoirs and veterinary agencies). Findings revealed numerous opportunities for pathogens to disseminate, as well as lack of incentives to adopt preventive measures, and factors that promoted epidemic dissemination. Supporting such observations, the estimated risk for H5N1‐related human mortality was higher than previously reported. The need for multidimensional disease surveillance models, which may detect risks at higher levels than models that only measure one factor or outcome, was supported. To develop efficient surveillance systems, interactions should be captured, which include but exceed biological factors. This low‐cost and easily implementable model, if conducted over time, may identify focal instances where tailored policies may diminish both endemicity and the total adaptation of H5N1 to the human species.

Url:
DOI: 10.1111/zph.12200

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ISTEX:ECC4FA68208188DB15A841D99AC04C493922A29F

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<p>
<b>Appendix S1.</b>
Schematic risk pathways and detailed contributors to each stage of the infection pathways for influenza A (H5N1).</p>
<p>
<b>Appendix S2.</b>
Complete Table of the Review of data from 174 Nigerian markets to assess the risk of Influenza A (H5N1) food‐borne infection.</p>
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<p>Avian influenza virus (H5N1) is a rapidly disseminating infection that affects poultry and, potentially, humans. Because the avian virus has already adapted to several mammalian species, decreasing the rate of avian–mammalian contacts is critical to diminish the chances of a total adaptation of H5N1 to humans. To prevent the pandemic such adaptation could facilitate, a biology‐specific disease surveillance model is needed, which should also consider geographical and socio‐cultural factors. Here, we conceptualized a surveillance model meant to capture H5N1‐related biological and cultural aspects, which included food processing, trade and cooking‐related practices, as well as incentives (or disincentives) for desirable behaviours. This proof of concept was tested with data collected from 378 Egyptian and Nigerian sites (local [backyard] producers/live bird markets/village abattoirs/commercial abattoirs and veterinary agencies). Findings revealed numerous opportunities for pathogens to disseminate, as well as lack of incentives to adopt preventive measures, and factors that promoted epidemic dissemination. Supporting such observations, the estimated risk for H5N1‐related human mortality was higher than previously reported. The need for multidimensional disease surveillance models, which may detect risks at higher levels than models that only measure one factor or outcome, was supported. To develop efficient surveillance systems, interactions should be captured, which include but exceed biological factors. This low‐cost and easily implementable model, if conducted over time, may identify focal instances where tailored policies may diminish both endemicity and the total adaptation of H5N1 to the human species.</p>
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<affiliation>F. O. Fasina. Department of Production Animal Studies, Faculty of Veterinary Science, University of Pretoria, Onderstepoort 0110, South Africa. Tel.: +27 84 958 0042; Fax: +27 12 529 8396; E‐mail:</affiliation>
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<abstract>Avian influenza virus (H5N1) is a rapidly disseminating infection that affects poultry and, potentially, humans. Because the avian virus has already adapted to several mammalian species, decreasing the rate of avian–mammalian contacts is critical to diminish the chances of a total adaptation of H5N1 to humans. To prevent the pandemic such adaptation could facilitate, a biology‐specific disease surveillance model is needed, which should also consider geographical and socio‐cultural factors. Here, we conceptualized a surveillance model meant to capture H5N1‐related biological and cultural aspects, which included food processing, trade and cooking‐related practices, as well as incentives (or disincentives) for desirable behaviours. This proof of concept was tested with data collected from 378 Egyptian and Nigerian sites (local [backyard] producers/live bird markets/village abattoirs/commercial abattoirs and veterinary agencies). Findings revealed numerous opportunities for pathogens to disseminate, as well as lack of incentives to adopt preventive measures, and factors that promoted epidemic dissemination. Supporting such observations, the estimated risk for H5N1‐related human mortality was higher than previously reported. The need for multidimensional disease surveillance models, which may detect risks at higher levels than models that only measure one factor or outcome, was supported. To develop efficient surveillance systems, interactions should be captured, which include but exceed biological factors. This low‐cost and easily implementable model, if conducted over time, may identify focal instances where tailored policies may diminish both endemicity and the total adaptation of H5N1 to the human species.</abstract>
<note type="additional physical form">Appendix S1. Schematic risk pathways and detailed contributors to each stage of the infection pathways for influenza A (H5N1). Appendix S2. Complete Table of the Review of data from 174 Nigerian markets to assess the risk of Influenza A (H5N1) food‐borne infection.</note>
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