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Center for Nonlinear Studies |
A conceptualization of Network Theory operationalized by Geographical Information Systems (GIS) is described. Using spatially and temporally explicit data from the 2006 Nigerian Avian Influenza epidemic (caused by the H5N1 strain), the role of road intersections and road networks in epidemic is evaluated. It will be shown that most AI cases occurred near major roads and, in addition, near major road intersections. Disease clusters defined epidemic phases: the early phase (3 epidemic weeks) was characterized by a ratio of cases within clusters/cases outside clusters greater than 2; profile that, two weeks before the epidemic peak, was replaced by a phase within which non-clustered cases represented a higher percentage. Combining transmissibility assessments with GIS data, it will be shown that, as early as epidemic day 4, a cost-benefit based decision could have been made to prevent the further spread of this epidemic.These concepts and tools may apply to fields where spatial networks influence diffusion processes.