A complex fuzzy decision model for analysing the post-pandemic immuno-sustainability

Area of Science:

• Women's Health
• Public Health
• Medical Decision Making

Background:

• The COVID-19 pandemic and subsequent vaccination campaigns have led to varied post-vaccination effects.
• These effects significantly impact women's physical, psychological, social, and economic well-being.
• There is a critical need for comprehensive risk assessment of these post-vaccination anomalies in women.

Purpose of the Study:

• To develop a robust framework for assessing the multifaceted post-vaccination effects on women.
• To introduce a novel decision-making approach utilizing complex bipolar spherical fuzzy ℵ-soft sets.

Main Methods:

• Application of complex bipolar spherical fuzzy ℵ-soft sets to handle ambiguous and parametric data.
• Utilizing the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for decision optimization.
• Demonstrating the efficacy through a real-world application and comparative analysis.

Main Results:

• The proposed method effectively assesses complex post-vaccination effects on women.
• The TOPSIS approach within the fuzzy set environment optimizes decision-making outcomes.
• The methodology shows significant credibility and integrity compared to existing techniques.

Conclusions:

• A novel decision-making framework is established for evaluating post-vaccination effects on women's health.
• The study highlights the importance of tailored risk assessments considering socioeconomic and biological factors.
• The developed approach offers a reliable tool for safeguarding women's well-being in the post-pandemic era.