Mapping out a One Health model of antimicrobial resistance in the context of the Swedish food system: A literature scan

Abstract

Abstract Background: Antimicrobial resistance (AMR) causes worsening health, environmental, and financial burdens. Modeling complex issues such as AMR can help clarify the behaviour of the system and assess the impacts of interventions. While models exist for specific AMR contexts (e.g. on-farm, in hospital), due to inadequate collaboration and data availability, how well such models cover the broader One Health system is unknown. Our study aimed to identify models of AMR across the One Health system with a focus on the Swedish food system (objective 1), and data to parameterize the models (objective 2), to ultimately inform future development of a comprehensive model of possible AMR emergence and transmission across the entire system. Methods: Using a previously developed causal loop diagram (CLD) of factors identified as important in the emergence and transmission of AMR in the Swedish food system, an extensive literature scan was performed to identify models and data from peer-reviewed and grey literature sources. Articles were searched using Google, Google Scholar, and Pubmed, screened for relevance, and the models and data were extracted and categorized in an Excel database. Visual representations of the models and data were overlayed on the existing CLD to illustrate coverage. Results: A total of 126 articles were identified, describing 106 models in various parts of the One Health system; 54 were AMR specific. Four articles described models with an economic component (e.g. cost-effectiveness of interventions, cost-analysis of disease outbreaks). Most models were limited to one sector (n=60, 57%) and were compartmental (n=73, 69%); half were deterministic (n=53, 50%). Few multi-level, multi-sector models, and models of AMR within the animal and environmental sectors, were identified. A total of 414 articles were identified that contained data to parameterize the models. There were major data gaps for factors related to the environment, wildlife, and broad, ill-defined, or abstract ideas (e.g. human experience and knowledge). Conclusions: There were no models that addressed the entire system and few that addressed the issue of AMR beyond one context or sector. Existing models have the potential to be integrated to create a mixed-methods model, provided that data gaps can be addressed.