PMID- 35475277 OWN - NLM STAT- MEDLINE DCOM- 20220428 LR - 20230412 IS - 2090-1224 (Electronic) IS - 2090-1232 (Print) IS - 2090-1224 (Linking) VI - 37 DP - 2022 Mar TI - Novel dynamic fuzzy Decision-Making framework for COVID-19 vaccine dose recipients. PG - 147-168 LID - 10.1016/j.jare.2021.08.009 [doi] AB - INTRODUCTION: The vaccine distribution for the COVID-19 is a multicriteria decision-making (MCDM) problem based on three issues, namely, identification of different distribution criteria, importance criteria and data variation. Thus, the Pythagorean fuzzy decision by opinion score method (PFDOSM) for prioritising vaccine recipients is the correct approach because it utilises the most powerful MCDM ranking method. However, PFDOSM weighs the criteria values of each alternative implicitly, which is limited to explicitly weighting each criterion. In view of solving this theoretical issue, the fuzzy-weighted zero-inconsistency (FWZIC) can be used as a powerful weighting MCDM method to provide explicit weights for a criteria set with zero inconstancy. However, FWZIC is based on the triangular fuzzy number that is limited in solving the vagueness related to the aforementioned theoretical issues. OBJECTIVES: This research presents a novel homogeneous Pythagorean fuzzy framework for distributing the COVID-19 vaccine dose by integrating a new formulation of the PFWZIC and PFDOSM methods. METHODS: The methodology is divided into two phases. Firstly, an augmented dataset was generated that included 300 recipients based on five COVID-19 vaccine distribution criteria (i.e., vaccine recipient memberships, chronic disease conditions, age, geographic location severity and disabilities). Then, a decision matrix was constructed on the basis of an intersection of the 'recipients list' and 'COVID-19 distribution criteria'. Then, the MCDM methods were integrated. An extended PFWZIC was developed, followed by the development of PFDOSM. RESULTS: (1) PFWZIC effectively weighted the vaccine distribution criteria. (2) The PFDOSM-based group prioritisation was considered in the final distribution result. (3) The prioritisation ranks of the vaccine recipients were subject to a systematic ranking that is supported by high correlation results over nine scenarios of the changing criteria weights values. CONCLUSION: The findings of this study are expected to ensuring equitable protection against COVID-19 and thus help accelerate vaccine progress worldwide. CI - (c) 2022 The Authors. FAU - Albahri, O S AU - Albahri OS AD - Faculty of Engineering & IT, British University in Dubai, United Arab Emirates. FAU - Zaidan, A A AU - Zaidan AA AD - Faculty of Engineering & IT, British University in Dubai, United Arab Emirates. FAU - Albahri, A S AU - Albahri AS AD - Informatics Institute for Postgraduate Studies (IIPS), Iraqi Commission for Computers and Informatics (ICCI), Baghdad, Iraq. FAU - Alsattar, H A AU - Alsattar HA AD - Faculty of Engineering & IT, British University in Dubai, United Arab Emirates. FAU - Mohammed, Rawia AU - Mohammed R AD - Faculty of Engineering & IT, British University in Dubai, United Arab Emirates. FAU - Aickelin, Uwe AU - Aickelin U AD - School of Computing and Information Systems, University of Melbourne, 700 Swanston Street, Victoria 3010 Australia. FAU - Kou, Gang AU - Kou G AD - School of Business Administration, Faculty of Business Administration, Southwestern University of Finance and Economics, Chengdu 611130, China. FAU - Jumaah, F M AU - Jumaah FM AD - Department of Advanced Applications and Embedded Systems, Intel Corporation, Plot 6 Bayan Lepas Technoplex, 11900, Georgetown, Pulau Pinang, Malaysia. FAU - Salih, Mahmood M AU - Salih MM AD - Department of Computer Science, Computer Science and Mathematics College, Tikrit University, Tikrit, Iraq. FAU - Alamoodi, A H AU - Alamoodi AH AD - Faculty of Engineering & IT, British University in Dubai, United Arab Emirates. FAU - Zaidan, B B AU - Zaidan BB AD - Faculty of Engineering & IT, British University in Dubai, United Arab Emirates. FAU - Alazab, Mamoun AU - Alazab M AD - College of Engineering, IT and Environment, Charles Darwin University, NT, Australia. FAU - Alnoor, Alhamzah AU - Alnoor A AD - School of Management, Universiti Sains Malaysia, Pulau Pinang, Malaysia. FAU - Al-Obaidi, Jameel R AU - Al-Obaidi JR AD - Department of Biology, Faculty of Science and Mathematics, Universiti Pendidikan Sultan Idris, Tanjong Malim, Perak 35900, Malaysia. LA - eng PT - Journal Article PT - Research Support, Non-U.S. Gov't DEP - 20210821 PL - Egypt TA - J Adv Res JT - Journal of advanced research JID - 101546952 RN - 0 (COVID-19 Vaccines) SB - IM EIN - J Adv Res. 2023 Mar;45:193. PMID: 36849218 MH - *COVID-19/prevention & control MH - *COVID-19 Vaccines MH - Decision Making MH - Fuzzy Logic MH - Humans PMC - PMC8378994 OTO - NOTNLM OT - COVID-19 OT - Multicriteria Decision Making OT - PFDOSM OT - PFWZIC OT - Pythagorean Fuzzy OT - Vaccine COIS- 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. EDAT- 2022/04/28 06:00 MHDA- 2022/04/29 06:00 PMCR- 2021/08/21 CRDT- 2022/04/27 06:24 PHST- 2021/03/29 00:00 [received] PHST- 2021/08/09 00:00 [revised] PHST- 2021/08/12 00:00 [accepted] PHST- 2022/04/27 06:24 [entrez] PHST- 2022/04/28 06:00 [pubmed] PHST- 2022/04/29 06:00 [medline] PHST- 2021/08/21 00:00 [pmc-release] AID - S2090-1232(21)00155-7 [pii] AID - 10.1016/j.jare.2021.08.009 [doi] PST - epublish SO - J Adv Res. 2021 Aug 21;37:147-168. doi: 10.1016/j.jare.2021.08.009. eCollection 2022 Mar.