Confronting models with data: the challenges of estimating disease spillover.

ABSTRACT: For pathogens known to transmit across host species, strategic investment in disease control requires knowledge about where and when spillover transmission is likely. One approach to estimating spillover is to directly correlate observed spillover events with covariates. An alternative is to mechanistically combine information on host density, distribution and pathogen prevalence to predict where and when spillover events are expected to occur. We use several case studies at the wildlife-livestock disease interface to highlight the challenges, and potential solutions, to estimating spatio-temporal variation in spillover risk. Datasets on multiple host species often do not align in space, time or resolution, and may have no estimates of observation error. Linking these datasets requires the

SUBMITTER: Cross PC 

PROVIDER: S-EPMC6711303 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature