Antimicrobial Resistance in South East Asia: A Participatory Systems Modelling Approach

Abstract

Purpose: Our study purpose was to identify (1) the underlying causal system of factors influencing antimicrobial resistance (AMR) development and spread in South East Asia (SEA) and (2) places to intervene by integrating diverse perspectives to find context-specific solutions. Methods & Materials: Using a complex adaptive systems lens and participatory, qualitative, systems modelling approach, we conducted 2 participatory workshops and 2 interviews involving AMR experts and other disciplinary experts to brainstorm factors influencing AMR and identify leverage points for intervention. Transcripts were thematically analyzed for factors, connections, and leverage points for interventions, which were then transcribed into a causal loop diagram (CLD) using Vensim 8.0.4 and validated via participant feedback. Results: Seventeen participants representing diverse perspectives across the One Health spectrum (e.g., animal welfare, pharmaceutical industry, food industry, water and sanitation, pest control) constructed a CLD that identified 98 factors, interlinked by 393 arrows, that influenced AMR in SEA. Seven themes explained the AMR dynamics illustrated in the CLD: consumer demand; agricultural food production systems; antimicrobial and pesticide/chemical misuse and AMR spread in the environment; inequitable access to quality antibiotics and health care; poor food safety practices; poor knowledge; and a need for research and innovation. Eight ‘overarching factors’, not included in the CLD because they impact the entire AMR system, emerged as underpinning the AMR dynamics described in each theme: leadership priorities and investments (e.g., privatized health care); poor regulations and enforcement; social and cultural norms; infectious disease prevalence; the drive to survive (e.g., due to food insecurity, poverty); increasing wealth and urbanization; climate change; and the underlying goal of economic prosperity that drives system behaviour. Fifteen leverage points representing different ‘overarching’ and CLD factors were identified as places to intervene with potential to change AMU and AMR directly (e.g., via setting AMU standards) or indirectly (e.g., via improving food security) in SEA. Conclusion: Our study illustrates AMR as the product of actions across the One Health spectrum and identifies the need for multi-pronged and multi-level interventions, including actions relevant to achieving the sustainable development goals, to transform our reliance on AMU and mitigate AMR sustainably.