MSc Defence: Building a Framework for Assessing Policy Compliance and Efficacy in One Health: Insights From a COVID-19 Case Study

CANDIDATE: Rhiannon Loster

ABSTRACT: In this work, we propose a modeling framework that gives insight to public policy compliance and efficacy for complex One Health issues, and apply it to a case study on nonpharmaceutical interventions (NPIs) compliance in Ontario during the COVID-19 pandemic. Using a stepwise multivariate linear regression analysis, we determine monthly comfort levels with both staying-home and mask-wearing, as well as determine significant indicator variables of each. These comfort values are then used within a decision-making model to determine average estimated compliance to each NPI in Ontario from March 2020 to January 2022. Using SEILR and SEILRV_1,2,3 compartmental models, we fit our simulations to real incidence data to determine the efficacy of staying-home and mask-wearing policies over time. Finally, we explore the applicability of our model to One Health policies, benefits of using the One Health approach, limitations of our work and discuss possible avenues for future work.