ArticleApplied soft computing2021
Evaluation of government strategies against COVID-19 pandemic using q-rung orthopair fuzzy TOPSIS method.
Article in Applied soft computing, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Decision Support Frameworks in Public Health Emergencies: A Systematic Review of Dynamic Models in Complex Contexts.International journal of environmental research and public health · 2023Pooled it
- A soft computing TOPSIS framework with fractional orthopair fuzzy sine aggregation for robust model evaluation in data science.Scientific reports · 2026Article
- A novel generalized orthopair fuzzy CURLI MCDM framework for smart art communication integrating emotional intelligence.Scientific reports · 2026Article
- A multi-phase, multi-method assessment of national COVID-19 vaccination performance with equity analysis.Scientific reports · 2026Article
- Assessing three-decade HIV testing transformation: TOPSIS-radar evaluation of tiered health system performance in rural-urban Southwestern China.BMC public health · 2025Article
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- Identifying and prioritizing resilient health system units to tackle the COVID-19 pandemic.Socio-economic planning sciences · 2023Article
- GeneralizedArtificial intelligence review · 2023Article
- A county-level analysis of association between social vulnerability and COVID-19 cases in Khuzestan Province, Iran.International journal of disaster risk reduction : IJDRR · 2023Article
- Design of multimodal hub-and-spoke transportation network for emergency relief under COVID-19 pandemic: A meta-heuristic approach.Applied soft computing · 2023Article
- Risk assessment approach for analyzing risk factors to overcome pandemic using interval-valued q-rung orthopair fuzzy decision making method.Applied soft computing · 2023Article
- A Multi-Criteria Decision-Making Model with Interval-Valued Intuitionistic Fuzzy Sets for Evaluating Digital Technology Strategies in COVID-19 Pandemic Under Uncertainty.Arabian journal for science and engineering · 2023Article
- Multi-criteria decision making of COVID-19 vaccines (in India) based on ranking interpreter technique under single valued bipolar neutrosophic environment.Expert systems with applications · 2022Article
- The applications of MCDM methods in COVID-19 pandemic: A state of the art review.Applied soft computing · 2022Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The COVID-19 outbreak, which emerged in China and continues to spread rapidly all over the world, has brought with it increasing numbers of cases and deaths. Governments have suffered serious damage and losses not only in the field of health but also in many other fields. This has directed governments to adopt and implement various strategies in their communities. However, only a few countries succeed partially from the strategies implemented while other countries have failed. In this context, it is necessary to identify the most important strategy that should be implemented by governments. A decision problem based on the decisions of many experts, with some contradictory and multiple criteria, should be taken into account in order to evaluate the multiple strategies implemented by various governments. In this study, this decision process is considered as a multi-criteria decision making (MCDM) problem that also takes into account uncertainty. For this purpose, q-rung orthopair fuzzy sets (q-ROFSs) are used to allow decision-makers to their assessments in a wider space and to better deal with ambiguous information. Accordingly, two different Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approaches are recommended under the q-ROFS environment and applied to determine the most appropriate strategy. The results of the proposed approaches determine the A1 -
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.