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_25
Snippet: Most of the within-locality transmission links detected through epidemiological contact-tracing 503 appear in the locality-level model's tree, though the locality-level tree suggests substantially 504 more human-to-human transmission events than captured in the contact-tracing tree. However, 505 the locality-level tree misses all inter-locality links. The district-level model's tree captures most 506 of the links indicated by the locality-level t.....
Document: Most of the within-locality transmission links detected through epidemiological contact-tracing 503 appear in the locality-level model's tree, though the locality-level tree suggests substantially 504 more human-to-human transmission events than captured in the contact-tracing tree. However, 505 the locality-level tree misses all inter-locality links. The district-level model's tree captures most 506 of the links indicated by the locality-level tree, and also suggests that inter-locality transmission 507 is occurring, though it has low power to determine exactly which case pairs are linked through 508 inter-locality transmission. The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It . https://doi.org/10.1101/677021 doi: bioRxiv preprint
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