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

Acta Trop. 2024 Aug:256:107261. doi: 10.1016/j.actatropica.2024.107261. Epub 2024 May 19.

Abstract

The post-effects of the COronaVIrus Disease (COVID-19) vary depending on socioeconomic and biological factors. Similarly, the effects of vaccination on people's immunity vary across several factors. After the pandemic, real-life post-vaccination anomalies significantly impact women's health, access to medical treatments and medications, mental well-being, and daily physical activities. However, there has been scant investigation into the physical, psychological, social, and economic ramifications of vaccine effects on women in the post-pandemic era. Therefore, conducting a comprehensive risk assessment is crucial to safeguard women from the post-vaccination effects.To address this issue, the research encompasses complex bipolar spherical fuzzy ℵ-soft set, which has two-sided periodic ambiguous data due to its parametric properties as an adaptable ℵ-soft set and distinguishing criteria as a complex bipolar spherical fuzzy set. In addition, some fundamental operations and properties are presented in a complex bipolar spherical fuzzy ℵ-soft environment. Furthermore, the robust assessment of a real-world application demonstrate the efficacy of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach to optimise the decision result. Finally, the provided decision-making approach is compared with existing techniques to illustrate their remarkable credibility and integrity.

Keywords: Decision-making; Fuzzy set; Risk analysis; The effects of post-pandemic; Vaccine outbreak; Women health.

MeSH terms

  • COVID-19 Vaccines / administration & dosage
  • COVID-19 Vaccines / immunology
  • COVID-19* / epidemiology
  • COVID-19* / prevention & control
  • Female
  • Fuzzy Logic*
  • Humans
  • Pandemics / prevention & control
  • Risk Assessment
  • SARS-CoV-2* / immunology
  • Vaccination

Substances

  • COVID-19 Vaccines