A decision-making framework for COVID-19 infodemic management strategies evaluation in spherical fuzzy environment

Abstract

100 years after the Spanish flu, the COVID-19 crisis showed that large-scale epidemics and pandemics do not belong to the past. On the report of the World Health Organization, COVID-19 is the most significant public health problem of the twenty-first century. Like previous epidemics, the current crisis is accompanied by uncertainty, mistrust, doubt and fear, and this has led to an infodemic connection to the epidemic. So not only are we fighting an epidemic, but also, we are brawling an infodemic. To reduce the social and economic consequences and harmful effects of infodemic health, and to overcome it, we need to implement strategies against infodemic. Evaluating strategies based on multiple characteristics can be considered multi-criteria decision-making (MCDM) problem. According to the literature, there is no study that aims on proposing an integrated approach to evaluate infodemic management strategies under uncertain environment. Therefore, in this paper, an integrated framework based on the extended version of best–worst method (BWM) and Combined Compromise Solution (CoCoSo) methods under a spherical fuzzy set (SFS) is developed for the first time to address the COVID-19 infodemic management strategies selection. Initially, the criteria are weighted using the developed SFS BWM which reduces uncertainty in pairwise comparisons. In the next step, the 15 selected strategies are analyzed and ranked using SFS CoCoSo. The outputs of this paper illustrate that online tools for fact checking COVID-19 information and engage and empower communities are placed in the first and second priorities, respectively. The comparison of ranking results SFS-CoCoSo with other MCDM methods demonstrates the performance of the proposed approach and its ranking stability.

Selection of Suitable Cloud Vendors for Health Centre: A Personalized Decision Framework with Fermatean Fuzzy Set, LOPCOW, and CoCoSo

“…Qiyas et al (2022) employed logarithmic picture fuzzy sets along with CoCoSo and used this framework for the drug selection for COVID-19. Jafarzadeh Ghoushchi et al (2023) utilized spherical fuzzy sets and applied the Best-Worst method and CoCoSo to assess strategies for managing the COVID-19 infodemic. Zhang and Wei (2023) employed spherical fuzzy sets and combined CoCoSo and D-CRITIC ("distance correlation criteria importance through inter-criteria correlation") for the location selection of electric vehicle charging stations.…”

Risk Assessment of Green Logistics in Renewable Energy Transition under Spherical Fuzzy Environment

“…1) This method requires fewer pairwise comparisons than the AHP method, which means that several more relevant criteria can be considered (Haseli et al, 2021). 2) Achieving more consistent pairwise comparisons and higher reliable results are other features of the BWM method (Rezaei, 2015, Jafarzadeh Ghoushchi et al,2023.…”

DIBR–DOMBI–FUZZY MAIRCA Model for Strategy Selection in the System of Defense

“…Methods To choose an advertising strategy [17] FAHP, GREY TOPSIS For e-tailers' distribution strategy evaluation [18] DANP with VIKOR To choose a green marketing strategy [19] Fuzzy AHP, fuzzy TOPSIS Choosing a public transport company strategy (Istanbul, Turkey) [20] Interval type-2 fuzzy AHP and TOPSIS Design a marketing strategy [21] Discrete choice analysis (DCA) Selection of government intervention strategies against the COVID-19 pandemic [22] SF-AHP, WASPAS-F Determination of optimal renewable energy growth strategies [23] SWARA, ARAS-Grey In agricultural water management for development strategies [24] AHP, TOPSIS In research related to science park development strategies [25] Fuzzy BWM, fuzzy CoCoSo Green mining strategy selection [26] SWOT-PEST, fuzzy AHP-MARCOS Health tourism strategy selection [27] SWOT, fuzzy linguistic AHP, MABAC Te COVID-19 infodemic management strategies selection [28] BWM, spherical fuzzy set, CoCoSo…”