Transmissibility of the highly pathogenic avian influenza virus, subtype H5N1 in domestic poultry: a spatio-temporal estimation at the global scale

Submitted: 17 December 2014
Accepted: 17 December 2014
Published: 1 November 2012
Abstract Views: 1190
PDF: 726
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The highly pathogenic avian influenza virus (HPAIV), subtype H5N1 poses a serious threat not only to the poultry industry and wild birds but also to humans. Despite a large number of studies conducted on various aspects of this virus, its transmissibility is still poorly understood. This study quantifies the basic reproductive number (R0) of the global HPAIV H5N1 spread within domestic poultry during December 2003 to December 2009. Three different approaches were applied to estimate R0 for HPAIV H5N1: (i) epidemic doubling time; (ii) spatial distance-based nearest neighbour; and (iii) spatiotemporal distance-based nearest neighbour. These three approaches represent temporal (tR0), spatial (sR0) and spatio-temporal transmissibility (stR0), respectively. The joint application of these three approaches provides a more complete profile by characterising the transmissibility traits of infectious diseases from different perspectives. Estimates of tR0 gradually decreased over the six sequential epidemic waves (EWs) examined, suggesting that the implemented control measures were effective in reducing the number of outbreaks. However, sR0 and stR0 increased from EW1, peaked in EW3 and then gradually decreased during EW4-EW6, reflecting different aspects of disease transmissibility compared to tR0. The application of all three methods in the final EW6 showed R0 >1, suggesting that the control measures implemented did not completely interrupt the transmission cycle, and hence were insufficient to eliminate HPAIV H5N1. Close monitoring of HPAIV H5N1 outbreaks and enhanced control policies is advised.

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Zhang, Z., Chen, D., Ward, M. P., & Jiang, Q. (2012). Transmissibility of the highly pathogenic avian influenza virus, subtype H5N1 in domestic poultry: a spatio-temporal estimation at the global scale. Geospatial Health, 7(1), 135–143. https://doi.org/10.4081/gh.2012.112

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