Antimicrobial resistance surveillance: can we estimate resistance in bloodstream infections from other types of specimen?

Synopsis Background Antimicrobial resistance (AMR) surveillance of bloodstream infections is challenging in low- and middle-income countries (LMICs), limited laboratory capacity preventing routine patient-level susceptibility testing. Other specimen types could provide an effective approach to surveillance. Objectives Our study aims to systematically evaluate the relationship between resistance prevalence in non-sterile sites and bloodstream infections. Methods Associations between resistance rates in Escherichia coli and Staphylococcus aureus isolates from blood and other specimens were estimated in Oxfordshire, UK, 1998-2018, comparing proportions resistant in each calendar year using time series cross-correlations and across drug-years. We repeated analysis across publicly-available data from four high-income and 12 middle-income countries, and in three hospitals/programmes in LMICs. Results 8102 E. coli bloodstream infections, 322087 E. coli urinary tract infections, 6952 S. aureus bloodstream infections and 112074 S. aureus non-sterile site cultures were included from Oxfordshire. Resistance trends over time in blood versus other specimens were strongly correlated (maximum cross-correlation 0.51-0.99, strongest associations in the same year for 18/27 pathogen-drug combinations). Resistance prevalence was broadly congruent across drug-years for each species. 276/312 (88%) species-drug-years had resistance prevalence in other specimen types within ±10% of that blood isolates. Results were similar across multiple countries and hospitals/programmes in high/middle/low income-settings. Conclusions Resistance in bloodstream and less invasive infections are strongly related over time, suggesting the latter could be a surveillance tool for AMR in LMICs. These infection sites are easier to sample and cheaper to obtain the necessary numbers of susceptibility tests, providing more cost-effective evidence for decisions including empiric antibiotic recommendations.