Enhanced automated detection of outbreaks of a rare antimicrobial-resistant bacterial species.

ABSTRACT: Surveillance of antimicrobial resistance (AMR) is a crucial strategy to combat AMR. Using routine surveillance data, we could detect and control hospital outbreaks of AMR bacteria as early as possible. Previously, we developed a framework for automatic detection of clusters of AMR bacteria using SaTScan, a free cluster detection tool integrated into WHONET. WHONET is a free software used globally for microbiological surveillance data management. We applied this framework to data from the Japan Nosocomial Infections Surveillance (JANIS), one of the world's most comprehensive and largest national AMR surveillance systems. Although WHONET-SaTScan has several cluster detection algorithms, no published studies have compared how different algorithms can produce varying results in cluster detecti

SUBMITTER: Hosaka Y 

PROVIDER: S-EPMC11500894 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature