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Differentiation of epidemic cases, detection of network properties, and estimation of long-range connectivity in the AI epizoonotic.

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posted on 2012-06-25, 00:03 authored by Ariel L. Rivas, Folorunso O. Fasina, Almira L. Hoogesteyn, Steven N. Konah, José L. Febles, Douglas J. Perkins, James M. Hyman, Jeanne M. Fair, James B. Hittner, Steven D. Smith

Low-scale data revealed that one primary AI case was located close to but outside the connecting structure defined by epidemic nodes (A). In contrast, at or after TC II, most cases were found within epidemic nodes (B). Two clusters of cases were observed (red polygons, B). Some epidemic nodes displayed a much higher proportion of cases than average nodes, e.g., two nodes (nodes # 1 and 2, red pentagon, B) accounted for 46 (or 71%) of all within-node cases. Four road intersection areas, out of 16 (or 25%) included 80% (52/65) of all within-node cases (C). To estimate long-range connectivity, all pairs of epidemic cases were connected with Euclidean lines, conforming a graph of N * (N –1)/2 lines, where N = epidemic case (an infected farm), or (113 * 112)/2 = 6328 infective links (D).


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