Project Snapshot
Surveillance Pillar
A Bayesian Network Model to Explore Management Options for Environmental AMR Control
Project Key Words: Campylobacter, enterococci, E. coli, Risk Assessment, Integrated Assessment Model, Bayes Net
Principal Investigator: Nicholas Ashbolt, PhD
Co-Investigator(s): Simon Otto, PhD; Richard Reid-Smith, DVSc; Carolee Carson, PhD; Colleen Murphy, PhD; Ben Smith; Ainsley Otten; Tim McAllister, PhD; Sylvia Checkley, PhD; Scott McEwen, DVSc, DipACVP; Lynora Saxinger; Eduardo Taboada; Doug Inglis
Trainees: Mariem Oloraso, MSc candidate; Gabriela Paulus, PhD candidate; Qiaozhi Li, PhD; Nancy Price, PhD
The Aim
The aim of this project is to quantify the efficacy of available control strategies for managing environmental risks of AMR in fluoroquinolone-resistant Campylobacter, vancomycin-resistant E. faecalis & ESBL E. coli to humans.
Why is This Important?
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The environment represents both a source and place of exchange in AMR between environmental bacteria and human pathogens, and water-based pathways are not considered at the system level for AMR management, but could dominate exposure risks. |
Outcomes
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New quantitative modeling tools to understand the relative risk reductions of AMR transmission/health burden through management interventions. |
Research Questions
What is the relative risk of waterborne vs. foodborne transmission of AMR from poultry and beef production to humans via fluoroquinolone resistant Campylobacter, macrolide-resistant enterococci, and ESBL E. coli?
Our Approach
We will use various models and networks to follow intervention scenarios and parameter values. Priorities to management options will be described and discussed with other WP leads using probabailities of infection, health burden (DALYs), and economic measures to compare between scenarios for the three AMR pathogen representatives.