Quantifying transmission of emerging zoonoses: Using mathematical models to maximize the value of surveillance data

Monique R. Ambrose; Adam J. Kucharski; Pierre Formenty; Jean-Jacques Muyembe-Tamfum; Anne W. Rimoin; James O. Lloyd-Smith

To examine how assuming different broader contact zones would affect inference results, 1331 we compared parameter estimates obtained under three choices of broader contact zones for data 1332 simulated under two inter-locality transmission rules. We simulated disease spread in a system 1333 where localities were placed in the same arrangement as seen in 178 localities with GPS 1334 coordinates included in the monkeypox surveillance system, district and region arrangement 1335 were the same as in the 1980s surveillance, and human-to-human transmission could occur either 1336 between a locality and its five closest neighbors or between localities located within 30 km of 1337 one another. Inference results again showed increasing estimates of R and decreasing estimates 1338 of spillover rate as the size of the assumed broader contact zone increased (S4 and S5 Table) . 1339 1340 . CC-BY 4.0 International license is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the author/funder.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 https://doi.org/10.1101/677021 doi: bioRxiv preprint The copyright holder for this preprint (which was not peer-reviewed) is the author/funder.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 S1 The expected number of new infections that become symptomatic on day t in locality v caused by an infectious individual who became symptomatic on day s in locality w