Risk-based surveillance for avian influenza control along poultry market chains in South China: The value of social network analysis

Abstract

Over the past two decades, the poultry sector in China went through a phase of tremendous growth as well as rapid intensification and concentration. Highly pathogenic avian influenza virus (HPAIV) subtype H5N1 was first detected in 1996 in Guangdong province, South China and started spreading throughout Asia in early 2004. Since then, control of the disease in China has relied heavily on wide-scale preventive vaccination combined with movement control, quarantine and stamping out. This strategy has been successful in drastically reducing the number of outbreaks during the past 5years. However, HPAIV H5N1 is still circulating and is regularly isolated in traditional live bird markets (LBMs) where viral infection can persist, which represent a public health hazard for people visiting them. The use of social network analysis in combination with epidemiological surveillance in South China has identified areas where the success of current strategies for HPAI control in the poultry production sector may benefit from better knowledge of poultry trading patterns and the LBM network configuration as well as their capacity for maintaining HPAIV H5N1 infection. We produced a set of LBM network maps and estimated the associated risk of HPAIV H5N1 within LBMs and along poultry market chains, providing new insights into how live poultry trade and infection are intertwined. More specifically, our study provides evidence that several biosecurity factors such as daily cage cleaning, daily cage disinfection or manure processing contribute to a reduction in HPAIV H5N1 presence in LBMs. Of significant importance is that the results of our study also show the association between social network indicators and the presence of HPAIV H5N1 in specific network configurations such as the one represented by the counties of origin of the birds traded in LBMs. This new information could be used to develop more targeted and effective control interventions.

Fig. 1

Representation of the 2 mode “market–source node” network within the three provinces of southern China. The 2 mode network illustrates the links between market nodes represented by surveyed Live Bird Markets (n = 30) and source nodes (n = 222) from which poultry originate.

Fig. 2

Representation of Network 1 (2 mode market–source) network and the relative geographical position of its 4 components in southern China, composed of a giant weak component (red squares) and secondary components (blue circles, black down-triangles and grey up-triangles). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 3

Representation of the 2 mode “market–source node” network of poultry movement in southern China according to the k-core value. The k-core is a network parameter that measures the centrality of a node within a network. Some Live Bird Markets have a higher k-core than others, especially in Hunan and Guangxi provinces, where some LBMs displayed a maximum k-core value of 4 and could play a greater role in HPAIV maintenance.

Fig. 4

Representation of Network 2 (1 mode source–source) network and the relative geographical position of its 4 components in southern China, composed of a giant weak component (red squares) and secondary components (blue circles, black down-triangles and grey up-triangles).

Fig. 5

Representation of Network 3 (1 mode market-market) network and the relative geographical position of its 4 components in southern China, composed of a giant weak component (red squares) and secondary components (blue circles and grey up-triangles).