Unrealistic assumptions (baseline scenario: random disease distribution, random sampling) overestimate the detection probability (~ confidence in detecting #CWD). Agent-based framework for wildlife disease surveillance Belsare et. al ow.ly/6U7M30mQFTc #bioRxiv #gganimate
The model was simulated for Franklin County Missouri deer population. Alternate scenario simulates clustering of cases and non-random sampling. Very low prevalence thresholds reflect recent CWD introduction. User-friendly-sliders to set age-sex class specific harvest and testing. 
Can be used to calculate region-specific sample sizes for efficient and sustainable CWD surveillance. Also facilitates inferring negative surveillance outcomes. #AdaptiveManagementApproach
This ABM framework can be readily adapted to other regions as well as other host-pathogen systems (e.g. bTB-deer, brucellosis-elk). Open access models, certified & peer-reviewed ow.ly/xlVM30mQGbn & ow.ly/PXOQ30mQGdE #OpenABM Enquires welcome!@coatiwhisperer
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