Quantifying uncertainty about future antimicrobial resistance: Comparing structured expert judgment and statistical
Abigail R Colson1,2, Itamar Megiddo1,2, Gerardo Alvarez-Uria3
1Department of Management Science, University of Strathclyde, Glasgow, Scotland, United Kingdom.
Plos One
|July 6, 2019
Summary
Structured expert judgment forecasts future antibiotic resistance rates, showing key pathogen-antibiotic resistance likely remaining below 50% in several European countries by 2026.
Area of Science:
- Microbiology
- Public Health
- Epidemiology
Background:
- Antibiotic resistance is a growing global health crisis.
- Predicting future resistance trends is vital for public health strategies.
- Current surveillance and statistical models have limitations in forecasting resistance.
Purpose of the Study:
- To elicit and validate expert projections of antibiotic resistance rates through 2026.
- To quantify uncertainty in future antibiotic resistance trends.
- To compare expert judgment forecasts with statistical models.
Main Methods:
- Utilized the Classical Model of structured expert judgment.
- Elicited projections for nine pathogen-antibiotic pairs in four European countries.
- Validated expert assessments using calibration questions and compared with EARS-Net data.
Main Results:
- Expert projections indicated resistance for priority pathogens (e.g., E. coli, K. pneumoniae, MRSA) likely below 50% in France, Spain, and UK by 2026.
- Italian projections suggested sustained or improved resistance rates, with some credible ranges exceeding 50%.
- Expert forecasts differed from statistical models and incorporated factors not easily captured by data alone.
Conclusions:
- Structured expert judgment offers a valuable tool for understanding and projecting future antibiotic resistance.
- Expert insights provide crucial context beyond statistical forecasting for public health decision-making.
- This approach aids in guiding investments in antibiotic development and resistance control strategies.
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