iScience· 2026Q1
Network-based characterization of latent co-testing patterns in antimicrobial susceptibility testing
- 0citations
- Q1SCImago
- 2026year
Short summary
This study introduces 'shadow antibiograms' – the latent structures of antibiotic co-testing patterns – revealing that networks of antibiotic co-testing in Germany (n≈13 million isolates) consistently form 3-4 dominant communities, with Jaccard similarity proving most effective for analysis.
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Key points
- Introduced 'shadow antibiograms' to describe the empirical structures of antibiotic co-testing in susceptibility testing.
- Analyzed ~13 million bacterial isolates from Germany (2019-2023) to construct co-testing networks.
- Identified 3-4 dominant co-testing communities consistently across different cohorts and specimen types.
- Jaccard similarity was found to be the most effective metric for network analysis, balancing multiple evaluation criteria.
AI-generated from the title and abstract; the full text is not read.
Abstract
Antimicrobial resistance (AMR) surveillance depends on antimicrobial susceptibility testing, yet antibiotic panels vary by pathogen cohort, specimen, year, ward, and care setting. We term these empirically reconstructed testing architectures shadow antibiograms: structures that shape which susceptibility results enter surveillance datasets and which resistance relationships can be observed. We analyzed approximately 13 million bacterial isolates from Germany's National Antibiotic Resistance Surveillance system (2019–2023) across six WHO BPPL-aligned operational cohorts. Co-testing networks were constructed using Jaccard, Dice, cosine, and phi-coefficient similarity, evaluated with Fisher's exact tests and Benjamini-Hochberg correction, and partitioned with multi-resolution Louvain community detection. Networks contained three to four dominant co-testing communities; false discovery rate (FDR) retention ranged from 89 to 100% across cohorts and specimen types. Jaccard provided the best balance of coherence, stability, antimicrobial-class alignment, interpretability, and edge retention. This work provides one of the first national-scale empirical characterizations of shadow antibiogram structure, supporting diagnostic stewardship and bias-aware AMR surveillance interpretation.
The authors' abstract, as published at the source. iScience, 2026 · DOI ↗
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Field: Clinical Biochemistry
Clinical BiochemistryBiochemistry, Genetics and Molecular Biology