More testing, more culling?: accounting for imperfect detection in disease management strategies of Mycoplasmopsis bovis in North American Bison

Authors: DALEO, MARIS - University Of Illinois; BRAGG, TOM - Turner Institute For Ecoagriculture, Inc; Kaplan, Bryan; MALMBERG, JENNIFER - Animal And Plant Health Inspection Service (APHIS); MARTIN, KELSEY - State Of Montana; BUTTKE, DANIELLE - Us National Park Service

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 7/26/2026
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: North American bison (Bison bison) restoration increasingly relies on translocation among herds to preserve genetic diversity, raising concern about pathogen spread, particularly for Mycoplasmopsis bovis, which can persist in asymptomatic carriers. Current test-and-remove strategies rely heavily on PCR diagnostics, yet imperfect detection may allow for infected individuals to persist and seed future outbreaks. We developed hierarchical occupancy models for M. bovis using PCR data from 2022-2026 from six bison herds to estimate detection probability, pathogen persistence, and optimal sampling strategies while accounting for herd-specific variation and irregular sampling intervals. Monthly PCR sensitivity was lower than expected, while specificity remained high (false-positive rate <2%). Persistence analyses indicated strong month-to-month retention of infection status, with most positive individuals remaining positive in subsequent months. Detection probability varied among herds, with some populations requiring more than twice the sampling effort to achieve comparable confidence in detection. At the individual level, a single negative PCR result left significant residual infection risk, whereas consecutive monthly negatives markedly improved confidence in clearance. Following outbreak periods, infection risk declined rapidly but still required repeated annual testing to reach residual-risk thresholds. These findings indicate that single-test clearance protocols may underestimate infection risk and highlight the importance of sequential surveillance for translocation decisions. Our framework provides a quantitative, adaptable approach for designing wildlife management strategies that account for imperfect diagnostic detection and pathogen persistence. As wildlife translocations accelerate globally, failure to account for detection uncertainty threatens to turn conservation tools into inadvertent networks for pathogen dispersal.