Volume 8 • Issue 1 • PP: 40-46 • 2022
COVID-19 vaccine choice using the multi-criteria decision making method under uncertainty
Abstract
COVID-19, a coronavirus pandemic unlike any seen before, is in a state of flux over the planet. Since the COVID-19 pandemic now poses a serious danger to all nations, it is critical that policymakers find the most effective response possible. The coronavirus is difficult to eradicate, however the COVID-19 vaccination may help with that. Everyone is wondering which vaccination would be best for them. Multi-criteria decision-making (MCDM) is an excellent method for assessing this maze. As a result, we have suggested a cutting-edge MCDM method for choosing COVID-19 vaccinations. The primary objective of this work is to deliver a technique for MCDM. In this investigation, we present a unique hybrid model that combines the strengths of the neutrosophic Analytic Hierarchy Process (N-AHP) and the neutrosophic VIKOR technique. Using the N-AHP, we can quantify the importance of the criterion, and using the N-VIKOR method, we can prioritize our options for interventions.
Keywords
References
[1] I. M. Hezam, M. K. Nayeem, A. Foul, and A. F. Alrasheedi, “COVID-19 Vaccine: A neutrosophic MCDM
approach for determining the priority groups,” Results in physics, vol. 20, p. 103654, 2021.
[2] C. Kahraman, B. Oztaysi, and S. Cevik Onar, “Single & interval-valued neutrosophic AHP methods:
Performance analysis of outsourcing law firms,” Journal of Intelligent & Fuzzy Systems, vol. 38, no. 1,
pp. 749–759, 2020.
[3] M. Junaid, Y. Xue, M. W. Syed, J. Z. Li, and M. Ziaullah, “A neutrosophic ahp and topsis framework for
supply chain risk assessment in automotive industry of Pakistan,” Sustainability, vol. 12, no. 1, p. 154,
2019.
[4] L. Yang et al., “COVID-19: immunopathogenesis and Immunotherapeutics,” Signal transduction and
targeted therapy, vol. 5, no. 1, pp. 1–8, 2020.
[5] T. T. Le et al., “The COVID-19 vaccine development landscape,” Nat Rev Drug Discov, vol. 19, no. 5,
pp. 305–306, 2020.
[6] K. Yuki, M. Fujiogi, and S. Koutsogiannaki, “COVID-19 pathophysiology: A review,” Clinical
immunology, vol. 215, p. 108427, 2020.
[7] T. P. Velavan and C. G. Meyer, “The COVID‐19 epidemic,” Tropical medicine & international health,
vol. 25, no. 3, p. 278, 2020.
[8] Z. Andreadakis, A. Kumar, R. G. Román, S. Tollefsen, M. Saville, and S. Mayhew, “The COVID-19
vaccine development landscape,” Nat Rev Drug Discov, vol. 19, no. 5, pp. 305–306, 2020.
[9] M. Ciotti, M. Ciccozzi, A. Terrinoni, W.-C. Jiang, C.-B. Wang, and S. Bernardini, “The COVID-19
pandemic,” Critical reviews in clinical laboratory sciences, vol. 57, no. 6, pp. 365–388, 2020.
[10] X. Cao, “COVID-19: immunopathology and its implications for therapy,” Nature reviews immunology,
vol. 20, no. 5, pp. 269–270, 2020.
[11] J. H. Beigel et al., “Remdesivir for the treatment of Covid -19,” New England Journal of Medicine, vol.
383, no. 19, pp. 1813–1826, 2020.
[12] A. Sotoudeh-Anvari, “The applications of MCDM methods in COVID-19 pandemic: A state of the art
review,” Applied Soft Computing, p. 109238, 2022.
[13] P.-H. Nguyen, J.-F. Tsai, T.-T. Dang, M.-H. Lin, H.-A. Pham, and K.-A. Nguyen, “A hybrid spherical
fuzzy MCDM approach to prioritize governmental intervention strategies against the COVID -19
pandemic: A case study from Vietnam,” Mathematics, vol. 9, no. 20, p. 2626, 2021.
[14] R. Ghosh and F. N. Saima, “Resilience of commercial banks of Bangladesh to the shocks caused by
COVID-19 pandemic: an application of MCDM-based approaches,” Asian Journal of Accounting
Research, 2021.
[15] M. A. Alsalem et al., “Multi-criteria decision-making for coronavirus disease 2019 applications: A
theoretical analysis review,” Artificial Intelligence Review, pp. 1–84, 2022.
[16] N. Ahmad, M. G. Hasan, and R. K. Barbhuiya, “Identification and prioritization of strategies to tackle
COVID-19 outbreak: A group-BWM based MCDM approach,” Applied soft computing, vol. 111, p.
107642, 2021.
[17] C.-L. Lin, J. K. C. Chen, and H.-H. Ho, “BIM for smart hospital management during COVID-19 Using
MCDM,” Sustainability, vol. 13, no. 11, p. 6181, 2021.
[18] N. Aydin and S. Seker, “Determining the location of isolation hospitals for COVID‐19 via Delphi‐based
MCDM method,” International Journal of Intelligent Systems, vol. 36, no. 6, pp. 3011–3034, 2021.
[19] J. Hu, L. Pan, and X. Chen, “An interval neutrosophic projection-based VIKOR method for selecting
doctors,” Cognitive Computation, vol. 9, no. 6, pp. 801–816, 2017.
[20] J. Wang, G. Wei, and M. Lu, “An extended VIKOR method for multiple criteria group decision making
with triangular fuzzy neutrosophic numbers,” Symmetry, vol. 10, no. 10, p. 497, 2018.
[21] Y.-H. Huang, G.-W. Wei, and C. Wei, “VIKOR method for interval neutrosophic multiple attribute group
decision-making,” Information, vol. 8, no. 4, p. 144, 2017.
[22] H. Eroğlu and R. Şahin, “A neutrosophic VIKOR method-based decision-making with an improved
distance measure and score function: case study of selection for renewable energy alternatives,” Cognitive
Computation, vol. 12, no. 6, pp. 1338–1355, 2020.
[23] E. Bolturk and C. Kahraman, “A novel interval-valued neutrosophic AHP with cosine similarity measure,”
Soft Computing, vol. 22, no. 15, pp. 4941–4958, 2018.
[24] M. Yucesan and M. Gul, “Failure modes and effects analysis based on neutrosophic analytic hierarchy
process: method and application,” Soft Computing, vol. 25, no. 16, pp. 11035–11052, 2021.
[25] N. M. Radwan, M. B. Senousy, and M. R. Alaa El Din, Neutrosophic AHP multi criteria decision making
method applied on the selection of learning management system. Infinite Study, 2016.
Cite This Article
Choose your preferred format