Mapping the Spread of Contagions with Social Network Analysis [SNA]

A contagion passed by human contact, such as SARS or TB, spreads through human networks based on how infectious and susceptible each party is. Multiple contacts with infectious others play a role in the probability of infection. Contagions that flow through human-based networks can be good(ideas and innovations) or bad(disease, gossip).

Public health officials perform contact tracing to map the spread of infections and manage their diffusion. The network map above, created at the epidemiology unit of The Centers for Disease Control [CDC], shows the spread of an airborne infectious disease. The map was created using actual contact data from the community in which the outbreak was happening.

Black nodes are persons with clinical disease (and are potentially infectious), pink nodes represent exposed persons with incubating (or dormant) infection and are not infectious, green represent exposed persons with no infection and are not infectious. The infection status is unknown for the grey nodes -- they are still to be tested.

Unfortunately the 'social butterfly' in this community, the black node in the center of the graph, is also the most infectious -- a super spreader.

Current procedures focus on inoculating the vulnerable -- often the very young and the very old. Network analysis tells us that it may be smarter, and more efficient, to focus on the spreaders -- those with many contacts to many groups, the bridges in the network.

For more information on how social network analysis [SNA] assists health care professionals to manage and discover contagious disease outbreaks, see...

  • "Transmission Network Analysis to Complement Routine Tuberculosis Contact Investigations" by McKenzie Andre, Kashef Ijaz, Jon D. Tillinghast, Valdis E. Krebs, Lois A. Diem, Beverly Metchock, Theresa Crisp, Peter D. McElroy [Abstract] [Pre-Print PDF]
  • Application of Social Network Analysis to Understanding HIV Transmission by Centers for Disease Control [PDF]
  • Applying Positive Deviance and Social Network Analysis to reducing hospital-born infections such as MRSA. "Embracing collaboration: A novel strategy for reducing bloodstream infections in outpatient hemodialysis centers" by Curt Lindberg, Gemma Downham, Prucia Buscell, Erin Jones, Pamela Peterson, Valdis Krebs [PDF]

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