Blog 8: HPAIV

The article I chose to discuss was Risk-based surveillance for avian influenza control along poultry market chains in South China: The value of social network analysis by Martin et al. (2011). As the title states, the authors were performing a surveillance for avian influenza viral spread (HPAIV) since poultry markets are so concentrated throughout certain areas in China. What makes this a public health issue is how pathogenic the avian virus is in these Chinese markets. Martin et al. utilized social network analysis to provide a network-based tactic to offer new perceptions on disease transmission dynamics.

The research question asked if an association existed between poultry trade network characteristics in southern China and HPAIV infection status by the occurrence of poultry outbreaks. They collected their data by sending surveys to thirty live bird markets in South China in Hunan and Yunnan provinces and Guanxi autonomous region. The survey asked questions in regard to hygiene and trade-related indicators of each market. In their network, the nodes were the source markets and the edges were the connections between the markets.

In this study, the K-core is a network metric that measures the centrality of a node within the network of live bird markets. Markets with a higher k-core value (ex. 4) play a greater role in the maintenance of HPAIV. The results yielded that China has had successful control in HPAIV outbreaks, as no outbreaks were reported in 2010. What I really like about this study is the way Martin et al. displayed their social network analysis data. They took the traditional method of creating an SNA graph using k-cores as categorical colors and placed them on the map. I had not thought about combining the talents of an SNA visualization software like Gephi with the likes of geographic Information system (GIS) software. The result turned out beautifully as seen in the figure below.

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