Nandi Sandip, Granata Giuseppe, Jana Subrata, Ghorui Neha, Mondal Sankar Prasad, Bhaumik Moumita
Institute of Business Management & Research, Kolkata, WB, India.
Department of Economics University Mercatorum of Rome, Italy.
Socioecon Plann Sci. 2023 Aug;88:101614. doi: 10.1016/j.seps.2023.101614. Epub 2023 Jun 5.
The breakout of the pandemic COVID-19 has affected numerous countries and territories worldwide. As COVID-19 specific medicines yet to be invented, at present the treatment is case specific, hence identification and evaluation of different prevalent treatment options based on various criteria and attributes are very important not only from the point of view of present pandemic but also for futuristic pandemic preparedness. The present study focuses on identifying, evaluation and ranking of treatment options using Multi Criteria Decision Making (MCDM). In this regard, the existing literature, doctors and scientist were interviewed to know the current treatment options in vogue and the scale of their importance with respect to the criteria. The criteria taken are side effect, regime cost, treatment duration, plasma stability, plasma turnover, time of suppression, ease of application, drug-drug interaction, compliance, fever, pneumonia, intensive care, organ failure, macrophage activation syndrome, hemophagocytic syndrome, pregnancy, kidney problem, age. This study extended Hesitant Fuzzy Set (HFS) to Generalized Hesitant Fuzzy Sets (GHFS). Generalized Hesitant Pentagonal Fuzzy Number (GHPFN) is developed. The properties of GHPFN are demonstrated. Two types of GHPFN has been described. The GHPFN (2nd type) along with MCDM tool Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been applied to rank the treatment options. The result of the study ranked 'Hydroxychloroquine' as the first alternative followed by, 'Plasma Exchange', 'Tocilizumab', 'Remdesivir' and 'Favipravir'. To check the robustness and steadiness of the proposed methodology, comparative analysis and sensitivity analysis has been conducted.
新型冠状病毒肺炎疫情的爆发已经影响了全球众多国家和地区。由于针对新冠病毒的特效药物尚未发明,目前的治疗是针对具体病例的,因此,基于各种标准和属性来识别和评估不同的流行治疗方案,不仅从当前疫情的角度来看非常重要,而且对于未来的疫情防范也很重要。本研究的重点是使用多准则决策方法(MCDM)来识别、评估治疗方案并进行排序。在这方面,我们采访了现有文献、医生和科学家,以了解当前流行的治疗方案以及它们相对于各项标准的重要程度。所采用的标准包括副作用、治疗方案成本、治疗持续时间、血浆稳定性、血浆周转率、抑制时间、应用便利性、药物相互作用、依从性、发热、肺炎、重症监护、器官衰竭、巨噬细胞活化综合征、噬血细胞综合征、妊娠、肾脏问题、年龄。本研究将犹豫模糊集(HFS)扩展为广义犹豫模糊集(GHFS)。提出了广义犹豫五边形模糊数(GHPFN)。证明了GHPFN的性质。描述了两种类型的GHPFN。将第二类GHPFN与多准则决策工具理想解相似排序法(TOPSIS)一起应用于对治疗方案进行排序。研究结果将“羟氯喹”列为首选,其次是“血浆置换”、“托珠单抗”、“瑞德西韦”和“法匹拉韦”。为了检验所提方法的稳健性和稳定性,进行了对比分析和敏感性分析。