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Confronting Models With Data: The Challenges Of Estimating Disease Spillover, Paul C. Cross, Diann J. Prosser, Andrew M. Ramey, Ephraim M. Hanks, Kim M. Pepin
Confronting Models With Data: The Challenges Of Estimating Disease Spillover, Paul C. Cross, Diann J. Prosser, Andrew M. Ramey, Ephraim M. Hanks, Kim M. Pepin
USDA Wildlife Services: Staff Publications
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 spatiotemporal variation in spillover risk. Datasets on multiple host species often do not align in space, time or resolution, …
Board Invited Review: Prospects For Improving Management Of Animal Disease Introductions Using Disease-Dynamic Models, Ryan S. Miller, Kim M. Pepin
Board Invited Review: Prospects For Improving Management Of Animal Disease Introductions Using Disease-Dynamic Models, Ryan S. Miller, Kim M. Pepin
USDA Wildlife Services: Staff Publications
Management and policy decisions are continually made to mitigate disease introductions in animal populations despite often limited surveillance data or knowledge of disease transmission processes. Science-based management is broadly recognized as leading to more effective decisions yet application of models to actively guide disease surveillance and mitigate risks remains limited. Disease-dynamic models are an efficient method of providing information for management decisions because of their ability to integrate and evaluate multiple, complex processes simultaneously while accounting for uncertainty common in animal diseases. Here we review disease introduction pathways and transmission processes crucial for informing disease management and models at the …