Factors that antimicrobial resistance in food systems: a participatory modelling approach. (30th September 2020) - Majowicz, S; Lambraki, I; Cousins, M; Parmley, E J; Carson, C
Abstract: Background: Antimicrobial resistance (AMR) emerges from a complex web of factors; understanding their dynamics is key to determining sustainable solutions. Thus, we aimed to create a model of the diverse factors influencing AMR in two food systems and model the impacts of interventions. Methods: We built a causal loop diagram (CLD) of the factors driving AMR in the food chain via 4 participatory workshops (2 in Sweden; 2 in Malaysia) with diverse stakeholders. The CLD became the structure of a compartmental model, which was populated using data from multiple sources (e.g., interviews, surveillance data). Using fuzzy set theory, quantitative and qualitative data were converted to categorical variables. The compartmental model was created in AnyLogic and was used to test how expert-selected solutions (e.g., taxation) might impact AMR under different scenarios. Results: Factors identified as influencing AMR across Europe and Southeast Asia clustered around key themes: on-farm (e.g., biosecurity); social (e.g., consumer demand); research (e.g., alternatives to antimicrobials [AMs]); economic (e.g., agricultural production levels); policy (e.g., trade agreements); and environment (e.g., waste management). Differences were identified between regions, for example, regulations and standards regarding imports or food safety were more relaxed in Southeast Asia than in Europe. Identified interventions included: AMR education in schools, training diverse stakeholders in AM stewardship, increased on-farm biosecurity measures to limit disease and the need for AMs, and taxing AM-containing products. Conclusions: Our model captured a range of multi-level, interlinked factors that impact AMR in the European and Southeast Asian food system contexts. Preliminary findings suggest that different principles need to be cultivated (e.g., polycentric governance, cross-sector partnerships) to ensure that interventions addressing AMR are sustainable over time. Key messages: Our study visually characterized the interlinked factors that impact AMR transmission and emergence in food systems. Our approach provides a tool to model impacts of potential interventions.