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Automated detection of outbreaks of antimicrobial-resistant bacteria in Japan

A Tsutsui1, K Yahara1, A Clark2

  • 1Antimicrobial Resistance Research Center, National Institute of Infectious Diseases, Tokyo, Japan.

The Journal of Hospital Infection
|October 16, 2018
PubMed
Abstract

Insights

Automatic detection of antimicrobial-resistant (AMR) bacteria outbreaks in hospitals is crucial. A new framework using WHONET-SaTScan successfully identified unrecognized AMR clusters, enabling early intervention before widespread outbreaks occur.

Area of Science:

  • Healthcare epidemiology
  • Infectious disease surveillance
  • Medical informatics

Background:

  • Hospital-acquired infections pose a significant threat.
  • Early detection and control of antimicrobial-resistant (AMR) bacteria outbreaks are essential for patient safety.
  • Existing surveillance systems may not capture all emerging AMR threats.

Purpose of the Study:

  • To develop and evaluate a framework for the automatic detection of AMR outbreaks in hospitals.
  • To assess the utility of WHONET and SaTScan software for AMR surveillance.
  • To identify AMR clusters that may be missed by traditional surveillance methods.

Main Methods:

  • Utilized data from the Japan Nosocomial Infections Surveillance (JANIS) database (2011-2016).
  • Employed WHONET software for data management and SaTScan for cluster detection.
  • Analyzed data from 1031 hospitals, with in-depth validation in 10 representative institutions.

Main Results:

  • The WHONET-SaTScan framework automatically detected AMR clusters in 1031 hospitals.
  • Approximately 80% of detected clusters involved pathogens not on routine surveillance priority lists.
  • In some cases, clusters of more susceptible isolates were identified prior to outbreaks of highly resistant pathogens.

Conclusions:

  • WHONET-SaTScan provides an effective automated method for detecting AMR outbreaks based on isolate resistance profiles.
  • This framework can identify epidemiologically related patient clusters beyond high-priority pathogens.
  • Detecting clusters of less resistant bacteria may enable proactive infection control interventions, preventing future outbreaks of more resistant strains.
Keywords:
Antimicrobial resistanceAutomated outbreak detectionJANISOutbreakWHONET-SaTScan

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