Characterising proximal and distal drivers of antimicrobial resistance: An umbrella review

Abstract

Introduction: Antimicrobial resistance (AMR) is a multifactorial challenge driven by a complex interplay of proximal drivers, such as the overuse and misuse of antimicrobials and the high burden of infectious diseases, and distal factors, encompassing broader societal conditions such as poverty, inadequate sanitation, and healthcare system deficiencies. However, distinguishing between proximal and distal drivers remains a conceptual challenge.

Objectives: We conducted an umbrella review, aiming to systematically map current evidence about proximal and distal drivers of AMR and to investigate their relationships.

Methods: Forty-seven reviews were analysed, and unique causal links were retained to construct a causality network of AMR. To distinguish between proximal and distal drivers, we calculated a 'driver distalness index (Di)', defined as an average relative position of a driver in its causal pathways to AMR.

Results: The primary emphasis of the literature remained on proximal drivers, with fragmented existing evidence about distal drivers. The network analysis showed that proximal drivers of AMR are associated with risks of resistance transmission (Di = 0.49, SD = 0.14) and antibiotic use (Di = 0.58, SD = 0.2), which are worsened by intermediate drivers linked with challenges of antibiotic discovery (Di = 0.62, SD = 0.07), infection prevention (Di = 0.67, SD = 0.14) and surveillance (Di = 0.69, SD = 0.16). Distal drivers, such as living conditions, access to sanitation infrastructure, population growth and urbanisation, and gaps in policy implementation were development and governance challenges, acting as deep leverage points in the system in addressing AMR.

Conclusions: Comprehensive AMR strategies aiming to address multiple chronic AMR challenges must take advantage of opportunities for upstream interventions that specifically address distal drivers.

Keywords: Antimicrobial resistance; DPSIR; Distal drivers; Network analysis; SDGs.