Antimicrobial resistance surveillance systems: Are potential biases taken into account?

Olivia Rempel1, Johann Dd Pitout, Kevin B Laupland

  • 1O'Brien Centre for the Bachelor of Health Sciences Program, Health Sciences Centre, Faculty of Medicine, University of Calgary;

Abstract

Insights

Contemporary antimicrobial-resistant (AMR) pathogen surveillance systems often have methodological flaws, particularly in sampling and duplicate counting. These biases can impact data validity, requiring careful consideration during interpretation.

Area of Science:

  • Public Health
  • Infectious Disease Surveillance
  • Epidemiology

Background:

  • The reliability of antimicrobial-resistant (AMR) pathogen surveillance systems is seldom examined.
  • Understanding potential biases is crucial for accurate public health assessments.

Purpose of the Study:

  • To evaluate potential biases affecting the validity of current AMR pathogen surveillance systems.
  • To identify common methodological weaknesses in AMR surveillance.

Main Methods:

  • A systematic search of Medline identified laboratory-based AMR surveillance systems from 2008.
  • Surveillance systems were assessed for six bias types using a scoring system (0-2).

Main Results:

  • Twenty-two surveillance systems were analyzed; all used appropriate denominators and case definitions.
  • Significant limitations were found in sampling bias (only 4/22 free of bias) and duplicate counting.
  • Most systems demonstrated good laboratory methodology, but issues with case ascertainment and duplicate removal were noted.

Conclusions:

  • Current AMR surveillance systems frequently exhibit methodological limitations, especially concerning sampling and duplicate record management.
  • Biases in case ascertainment and laboratory practices also present challenges.
  • Interpreting surveillance data requires awareness of these potential biases to ensure accuracy.

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