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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;
Background:
The validity of surveillance systems has rarely been a topic of investigation.
Objective:
To assess potential biases that may influence the validity of contemporary antimicrobial-resistant (AMR) pathogen surveillance systems.
Methods:
In 2008, reports of laboratory-based AMR surveillance systems were identified by searching Medline. Surveillance systems were appraised for six different types of bias. Scores were assigned as '2' (good), '1' (fair) and '0' (poor) for each bias.
Results:
A total of 22 surveillance systems were included. All studies used appropriate denominator data and case definitions (score of 2). Most (n=18) studies adequately protected against case ascertainment bias (score = 2), with three studies and one study scoring 1 and 0, respectively. Only four studies were deemed to be free of significant sampling bias (score = 2), with 17 studies classified as fair, and one as poor. Eight studies had explicitly removed duplicates (score = 2). Seven studies removed duplicates, but lacked adequate definitions (score = 1). Seven studies did not report duplicate removal (score = 0). Eighteen of the studies were considered to have good laboratory methodology, three had some concerns (score = 1), and one was considered to be poor (score = 0).
Conclusion:
Contemporary AMR surveillance systems commonly have methodological limitations with respect to sampling and multiple counting and, to a lesser degree, case ascertainment and laboratory practices. The potential for bias should be considered in the interpretation of surveillance data.
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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Bias
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...