1. A complex fuzzy decision model for analysing the post-pandemic immuno-sustainability.
- Author
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Pragathi S, Narayanamoorthy S, Dhivya S, Saraswathy R, Pamucar D, Simic V, and Kang D
- Subjects
- Humans, Female, Vaccination, COVID-19 Vaccines administration & dosage, COVID-19 Vaccines immunology, Risk Assessment, Pandemics prevention & control, COVID-19 prevention & control, COVID-19 epidemiology, Fuzzy Logic, SARS-CoV-2 immunology
- 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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)
- Published
- 2024
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