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Infection in Social Networks: Using Network Analysis to Identify High-Risk Individuals
2005
American Journal of Epidemiology
Simulation studies using susceptible-infectious-recovered models were conducted to estimate individuals' risk of infection and time to infection in small-world and randomly mixing networks. Infection transmitted more rapidly but ultimately resulted in fewer infected individuals in the small-world, compared with the random, network. The ability of measures of network centrality to identify high-risk individuals was also assessed. "Centrality" describes an individual's position in a population;
doi:10.1093/aje/kwi308
pmid:16177140
fatcat:udkwnoovjfedzkq5ecqjopsx74