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Quantifying uncertainty about future antimicrobial resistance: Comparing structured expert judgment and statistical

Abigail R Colson1,2, Itamar Megiddo1,2, Gerardo Alvarez-Uria3

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Summary
This summary is machine-generated.

Structured expert judgment forecasts future antibiotic resistance rates, showing key pathogen-antibiotic resistance likely remaining below 50% in several European countries by 2026.

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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.