Network-Based Analysis of Beijing SARS Data

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

“…Methods initially developed in the social sciences can be applied to epidemiology to assist identifying persistence of infection or points of concentration along poultry market chains. Among these techniques, value chain analysis and social network analysis are playing an increasing role in describing infectious disease transmission patterns and guiding control policies elaborated by health authorities (Kobayashi, 2007;Yi-Da et al, 2007;Zheng et al, 2008;Kitsak et al, 2010). Value chain analysis, originally developed in economics and managerial science, provides an analytical framework that allows characterization of an entire poultry industry as well as inter-linkages among various actors in the industry (Kaplinsky, 2004;Reardon, 2006;Humphrey and Napier, 2005).…”

“…More recently, it was used to explain the patterns of the severe acute respiratory syndrome (SARS) transmission taking into account transmission modes in clustered populations (Chen, 2007;Fearnley, 2009) that epidemiological models based on the mean field assumption (equal probability of transmission between all hosts) failed to explain. A public health implication of this finding is that a traditional disease control approach based on random immunization may not be effective (Zheng et al, 2008). In veterinary epidemiology, the application of SNA techniques is much more recent.…”

Social influence and spread dynamics in social networks

“…However, recent massive empirical studies on real-world social networks have shown that the distribution P(k) of these networks follows a power-law shaped distribution, P(k) ∼ k −α , which significantly deviates from that of traditional research. Examples include: traditional epidemic social networks [15], online social networks [18,43,44], Internet news [45], and mobile communication networks [46]. This demonstrates that in these networks there exist a few nodes linking to many other nodes, and a large number of nodes with poorly connected elements.…”

“…In the past few years, with the development of the social network research domain, more complex and feasible network construction methods have been developed. For instance, we can construct social networks in which nodes belong to two different types and links are both directed and weighted [15][16][17][18]. In these networks, nodes may represent people of different genders, occupations, locations, or ages and links represent different friendships, communications, or enmities [3,19,20].…”

“…These five basic network construction methods are compared in Table 2. [5,15,22,23]. For an unweighted network, this difference can be characterized by the degree distribution P(k), which gives the probability that a randomly selected node has exactly k edges.…”