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Application of social network analysis to communicable disease research

Application of social network analysis to communicable disease research. Sheila McCarthy, MSc PhD student Healthcare and Epi UBC Jan. 21, 2004. Social Network Analysis.

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Application of social network analysis to communicable disease research

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  1. Application of social network analysis to communicable disease research Sheila McCarthy, MSc PhD student Healthcare and Epi UBC Jan. 21, 2004

  2. Social Network Analysis • SNA is a research perspective that focuses on relationships between and among social entities, and on the patterns and implications of these relationships (Wasserman and Faust, 1994) • Both theory and methods

  3. Theory • Relational ties are primary • Attributes of actors are secondary • Actors and their actions are viewed as interdependent • Relational ties are channels for transfer • Different types of relations identify different networks even when imposed on identical people • The structure of relations among individuals and the location of individuals in the network have important consequences both for the individuals and for the system as a whole.

  4. Methods • Distinct from the methods of traditional statistics and data analysis • Data are the function of two interdependent units • Must incorporate social context • i.e. analyze ties and the structure of ties • Software: Pajek, UCInet, Multinet, and more • Multiple levels of analysis: individual, small groups, whole network

  5. Social Network Analysis • SNA is particularly attractive to epidemiologists interested in STIs, bloodborne infections, and TB because these diseases spread directly and indirectly through relational ties • SNA offers new approaches to research, but also to intervention and prevention strategies

  6. Example 1 • Illustrates a sociogram (visual representation of a network) • Components, sub-groups, individuals • Network structures related to disease dynamics • Intervention, prevention

  7. Example 1 from Rothenberg et al.Sociogram HIV/AIDS Colorado Springs, 1982-1999 325 nodes (actors) and their ties (relations, links)

  8. Example 2 • Illustrates matrix algebra • Illustrates the use of social events (in epi, “epidemiologically-relevant places” • Intervention, prevention

  9. Example 2 from Dynamic Social Network Modeling and Analysis:Workshop Summary and Papers (2003)http://books.nap.edu/books/0309089522/html/index.html

  10. Example 2 from Dynamic Social Network Modeling and Analysis:Workshop Summary and Papers (2003)http://books.nap.edu/books/0309089522/html/index.html

  11. Example 2 from Dynamic Social Network Modeling and Analysis:Workshop Summary and Papers (2003)http://books.nap.edu/books/0309089522/html/index.html

  12. Example 2 from Dynamic Social Network Modeling and Analysis:Workshop Summary and Papers (2003)http://books.nap.edu/books/0309089522/html/index.html • Goals: • Study patterns of interactions • Concern with issues related to similarity/dissimilarity • Results: • Two more or less distinct groups • Positions – core/periphery – could also be determined

  13. Conclusions • SNA can be used for • Research into disease dynamics • Intervention and prevention • Based on an assumption of importance of relationships among interacting units • Offers new methods of analysis

  14. References Wasserman and Faust. 1994. Social Network Analysis: Methods and Applications. Breigner, Carley, and Pattison. 2003. Dynamic Social Network Modeling and Analysis. (http://books.nap.edu/books/0309089522/html/index.html)

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