Author: Monique R. Ambrose; Adam J. Kucharski; Pierre Formenty; Jean-Jacques Muyembe-Tamfum; Anne W. Rimoin; James O. Lloyd-Smith
Title: Quantifying transmission of emerging zoonoses: Using mathematical models to maximize the value of surveillance data Document date: 2019_6_19
ID: f14u2sz5_66
Snippet: To illustrate how highly structured and non-homogeneous spillover could bias parameter 1287 estimates, we simulated an extreme case of a zoonotic epidemic traveling through time and 1288 space. We imagined that disease dynamics in the reservoir would occur in a single location for 1289 25 days before moving to a new spot, in an extreme form of a traveling zoonotic epidemic. For 1290 each 25 day period, three localities (selected to be in the same.....
Document: To illustrate how highly structured and non-homogeneous spillover could bias parameter 1287 estimates, we simulated an extreme case of a zoonotic epidemic traveling through time and 1288 space. We imagined that disease dynamics in the reservoir would occur in a single location for 1289 25 days before moving to a new spot, in an extreme form of a traveling zoonotic epidemic. For 1290 each 25 day period, three localities (selected to be in the same district when possible) would be 1291 selected to experience all of the spillover in the entire system. Aside from this extreme spillover 1292 pattern, the simulation followed the district-level model. 1293
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