(ASPOT39) Antimicrobial Resistance of Escherichia coli and Anti-diabetics: A Multi-year Geospatial Analysis

Background: Previous studies have shown geospatial variation in antimicrobial resistance (AMR) among community-dwelling populations. Antibiotic use and comorbid diabetes have been identified as risk factors for Escherichia coli (E. coli) AMR.

Objectives: The aim of this research is to investigate the geospatial association between antibiotic use, comorbid diabetes and E. coli AMR in a community-dwelling population.

Methods: For this study, prescription medicine use from the Australian reimbursement data (PBS) and microbiology data on E. coli resistance was geospatially linked at the local community level from 2013 to 2018. The proportion of claims (antibiotics: ATC J01, J04AB and A07AA and diabetes: ATC A10A, A10B) per amount of people and proportion of resistance (amoxicillin, amoxicillin-clavulanate, cephalexin, norfloxacin, and trimethoprim) each year per area was analyzed using multi-level logistic regression.

Results: An increased risk of E. coli resistance rates over time was observed for amoxicillin with clavulanic acid, cefalexin and norfloxacin. Association between risk factors and resistance varied per antibiotic type. Areas with higher areal antibiotic use showed a decreased risk of norfloxacin resistance. Areas with a higher prevalence of comorbid diabetes showed a higher risk of trimethoprim (OR = 1.21, 95% CI: 1.03–1.41) and amoxicillin resistance (OR = 1.23, 95% CI: 1.03–1.47).

Conclusions: Using a geospatial analysis method to investigate risk factors and E. coli resistance in the community enables a solid basis for identifying local drivers for resistance. This research shows the complexity around risk factors for resistance in the local community that differed per antibiotic type.