Incorporating Fuzzy Cognitive Inference for Vaccine Hesitancy Measuring

Vaccine hesitancy plays a key role in vaccine delay and refusal, but its measurement is still a challenge due to multiple intricacies and uncertainties in factors. This paper attempts to tackle this problem through fuzzy cognitive inference techniques. Firstly, we formulate a vaccine hesitancy deter...

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Bibliographic Details
Published in:Sustainability 2022-07, Vol.14 (14), p.8434
Main Authors: Sun, Kun, Zhao, Tian-Fang, Wu, Xiao-Kun, Lai, Kai-Sheng, Chen, Wei-Neng, Zhang, Jin-Sheng
Format: Article
Language:English
Subjects:
Cognitive maps
Cognitive models
Coronaviruses
COVID-19 vaccines
Decision making
Developing countries
Immunization
Inference
LDCs
Medical research
Pandemics
Personal health
Questionnaires
Severe acute respiratory syndrome coronavirus 2
Sustainability
Uncertainty
Vaccines
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Summary:Vaccine hesitancy plays a key role in vaccine delay and refusal, but its measurement is still a challenge due to multiple intricacies and uncertainties in factors. This paper attempts to tackle this problem through fuzzy cognitive inference techniques. Firstly, we formulate a vaccine hesitancy determinants matrix containing multi-level factors. Relations between factors are formulated through group decision-making of domain experts, which results in a fuzzy cognitive map. The subjective uncertainty of linguistic variables is expressed by fuzzy numbers. A double-weighted method is designed to integrate the distinguished decisions, in which the subjective hesitancy is considered for each decision. Next, three typical scenarios are constructed to identify key and sensitive factors under different experimental conditions. The experimental results are further discussed, which enrich the approaches of vaccine hesitancy estimation for the post-pandemic global recovery.
ISSN:2071-1050
2071-1050
DOI:10.3390/su14148434