Development of Disease‐specific, Context‐specific Surveillance Models: Avian Influenza (H5N1)‐Related Risks and Behaviours in African Countries
Identifieur interne : 001D28 ( Istex/Curation ); précédent : 001D27; suivant : 001D29Development of Disease‐specific, Context‐specific Surveillance Models: Avian Influenza (H5N1)‐Related Risks and Behaviours in African Countries
Auteurs : F. O. Fasina [Afrique du Sud, Pays-Bas] ; P. M. K. Njage [Afrique du Sud] ; A. M. M. Ali [Égypte] ; J. M. Yilma [Égypte] ; D. G. Bwala [Afrique du Sud] ; A. L. Rivas [États-Unis] ; A. J. Stegeman [Pays-Bas]Source :
- Zoonoses and Public Health [ 1863-1959 ] ; 2016-02.
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.
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DOI: 10.1111/zph.12200
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O." last="Fasina">F. O. Fasina</name><affiliation wicri:level="1"><mods:affiliation>Department of Production Animal Studies, Faculty of Veterinary Science, University of Pretoria, Onderstepoort, South Africa</mods:affiliation><country xml:lang="fr">Afrique du Sud</country><wicri:regionArea>Department of Production Animal Studies, Faculty of Veterinary Science, University of Pretoria, Onderstepoort</wicri:regionArea></affiliation><affiliation wicri:level="1"><mods:affiliation>Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Yalenaan, the Netherlands</mods:affiliation><country xml:lang="fr" wicri:curation="lc">Pays-Bas</country><wicri:regionArea>Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Yalenaan</wicri:regionArea></affiliation><affiliation><mods:affiliation>F. O. Fasina. Department of Production Animal Studies, Faculty of Veterinary Science, University of Pretoria, Onderstepoort 0110, South Africa. 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Stegeman</name><affiliation wicri:level="1"><mods:affiliation>Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Yalenaan, the Netherlands</mods:affiliation><country xml:lang="fr" wicri:curation="lc">Pays-Bas</country><wicri:regionArea>Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrecht University, Yalenaan</wicri:regionArea></affiliation></author></analytic><monogr></monogr><series><title level="j" type="main">Zoonoses and Public Health</title><title level="j" type="alt">ZOONOSES AND PUBLIC HEALTH</title><idno type="ISSN">1863-1959</idno><idno type="eISSN">1863-2378</idno><imprint><biblScope unit="vol">63</biblScope><biblScope unit="issue">1</biblScope><biblScope unit="page" from="20">20</biblScope><biblScope unit="page" to="33">33</biblScope><biblScope unit="page-count">14</biblScope><date type="published" when="2016-02">2016-02</date></imprint><idno type="ISSN">1863-1959</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">1863-1959</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="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.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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