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MODELS: a six-step framework for developing an infectious disease model.

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This study introduces the MODELS framework to help users understand and create reliable COVID-19 epidemic models. It guides researchers in developing dependable models for public health decision-making.

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Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Public Health

Background:

  • The COVID-19 pandemic spurred numerous modeling studies.
  • Many models exhibit methodological flaws, hindering reliable interpretation.
  • Navigating the complex landscape of epidemic models presents challenges for various stakeholders.

Purpose of the Study:

  • To introduce a structured framework, named MODELS, for developing dependable epidemic models.
  • To assist novices, healthcare workers, and policymakers in understanding and utilizing COVID-19 models.
  • To provide direction for researchers in epidemic modeling endeavors.

Main Methods:

  • Development of a structured framework (MODELS) for epidemic modeling.
  • Focus on essential steps and considerations for creating dependable models.
  • Guidance tailored for researchers, healthcare professionals, and policymakers.

Main Results:

  • A comprehensive framework (MODELS) for constructing reliable epidemic models.
  • Identification of key considerations to ensure model dependability.
  • Facilitation of informed decision-making through improved model understanding.

Conclusions:

  • The MODELS framework offers a structured approach to enhance the quality and reliability of epidemic models.
  • Effective modeling is crucial for informed public health strategies during pandemics.
  • Standardized frameworks improve the utility of modeling for diverse audiences.