Abstract
Background Antimicrobial resistance (AMR) is a major global health threat, but there is scarcity of laboratory surveillance data linked to clinical information to determine burden and inform interventions, especially from low-income and middle-income countries. The ACORN2 study sought to address this through prospective case-based surveillance in 19 hospitals across Africa and Asia to characterise drug-resistant infections by origin, clinical syndrome, patient age, outcome, and geographical location.
Methods Patients were enrolled on selected wards and clinical data were collected daily for community-acquired infections (CAIs). Point prevalence surveys for hospital-acquired infections (HAIs) were conducted weekly. Mortality was assessed at discharge and after 28 days. Linked microbiology data were extracted from local laboratory databases. Primary descriptive analyses focused on WHO Global Antimicrobial Resistance and Use Surveillance System pathogen (target organism) bloodstream infections (BSIs). Comparisons were adjusted for clustering by site using random effects models.
Findings Over 31 months, 41 907 infections were characterised from 41 032 admissions. Two-thirds were children (19 351; 47·2%) or neonates (6649; 16·2%). There were marked differences in pathogen incidence and antibiotic resistance when clinical infections were stratified by patient age category and infection origin (CAI/HAI). The highest rates of target organism AMR BSI were third-generation cephalosporin-resistant (3GC-R) Escherichia coli (718·56/100 000 blood cultured infection episodes), meticillin-resistant Staphylococcus aureus (586·89/100 000 blood cultured infection episodes), and 3GC-R Klebsiella pneumoniae (364·92/100 000 blood cultured infection episodes). In-hospital mortality was 13·1% (166/1265) in patients with target organism BSI versus 6·2% (1357/21 845) in those with negative blood cultures, p<0·0001.
Interpretation ACORN2 has shown practical implementation of collecting linked clinical-laboratory AMR data in low-income and middle-income countries and identified a significant burden of WHO GLASS BSI. Adoption of the ACORN2 approach at scale might enhance use of diagnostic microbiology and improve the volume of clinical data included in national and global AMR surveillance datasets.
| Original language | English |
|---|---|
| Article number | 101228 |
| Journal | The Lancet Microbe |
| Volume | 7 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 8 Dec 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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