A Novel Vaccine Selection Decision-Making Model (VSDMM) for COVID-19

Area of Science:

• Healthcare Decision Science
• Vaccinology
• Epidemiology

Background:

• Selecting appropriate vaccines is critical during pandemics, necessitating robust decision-making tools.
• Existing models may not adequately address the multi-criteria nature of vaccine selection in public health emergencies.

Purpose of the Study:

• To propose and develop a novel vaccine selection decision-making model (VSDMM).
• To utilize the analytic hierarchy process (AHP) for multi-criteria vaccine assessment.
• To demonstrate the model's applicability using six coronavirus disease-19 (COVID-19) vaccines.

Main Methods:

• Development of the VSDMM based on the analytic hierarchy process (AHP).
• Selection of six COVID-19 vaccines for a case study.
• Evaluation of vaccines based on six criteria: availability, formula, efficacy, side effects, cost savings, and host factors.
• Expert-based comparative analysis and sensitivity analysis to assess model robustness.

Main Results:

• The VSDMM successfully ranked available COVID-19 vaccines based on expert-defined criteria weights.
• Sensitivity analysis confirmed the model's robustness to changes in criteria weighting.
• The model demonstrated flexibility for incorporating additional vaccines or criteria.

Conclusions:

• The proposed VSDMM provides a structured, flexible framework for vaccine selection in pandemic/epidemic scenarios.
• This is the first report detailing a VSDMM for optimizing vaccine choices in public health crises.
• The model's adaptability allows for application to diverse infectious disease outbreaks.