Interventions for avian influenza A (H5N1) risk management in live bird market networks.

Interventions for avian influenza A (H5N1) risk management in live bird market networks.

Fournié, Guillaume;Guitian, Javier;Desvaux, Stéphanie;Cuong, Vu Chi;Dung, Do Huu;Pfeiffer, Dirk Udo;Mangtani, Punam;Ghani, Azra C;
Proceedings of the National Academy of Sciences of the United States of America 2013 Vol. 110 pp. 9177-82
282
fourni2013interventionsproceedings

Abstract

Highly pathogenic avian influenza virus subtype H5N1 is endemic in Asia, with live bird trade as a major disease transmission pathway. A cross-sectional survey was undertaken in northern Vietnam to investigate the structure of the live bird market (LBM) contact network and the implications for virus spread. Based on the movements of traders between LBMs, weighted and directed networks were constructed and used for social network analysis and individual-based modeling. Most LBMs were connected to one another, suggesting that the LBM network may support large-scale disease spread. Because of cross-border trade, it also may promote transboundary virus circulation. However, opportunities for disease control do exist. The implementation of thorough, daily disinfection of the market environment as well as of traders' vehicles and equipment in only a small number of hubs can disconnect the network dramatically, preventing disease spread. These targeted interventions would be an effective alternative to the current policy of a complete ban of LBMs in some areas. Some LBMs that have been banned still are very active, and they likely have a substantial impact on disease dynamics, exhibiting the highest levels of susceptibility and infectiousness. The number of trader visits to markets, information that can be collected quickly and easily, may be used to identify LBMs suitable for implementing interventions. This would not require prior knowledge of the force of infection, for which laboratory-confirmed surveillance would be necessary. These findings are of particular relevance for policy development in resource-scarce settings.

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