Fuzzy Modelling of Clinical and Epidemiological Factors for COVID-19

IF 0.7 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

International Journal of System Dynamics Applications Pub Date : 2020-05-18 DOI:10.21203/rs.3.rs-29370/v1

Poonam Mittal, M. Mangla, N. Sharma, Reena, Suneeta Satpathy, S. Mohanty

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引用次数: 4

Abstract

During this pandemic outbreak of COVID-19, the whole world is getting severely affected in respect of population health and economy. This novel virus has brought the whole world including the most developed countries to a standstill in a very short span like never before. The prime reason for this unexpected outburst of COVID-19 is lack of effective medicine and lack of proper understanding of the influencing factors. Here, authors aim to find the effect of epidemiological factors that influence its spread using a fuzzy approach. For the same, a total of 9 factors have been considered which are classified into Risk and Preventive factors. This fuzzy model supports to understand and evaluate the impact of these factors on the spread of COVID-19. Also, the model establishes a basis for understanding the effect of risk factors on preventive factors and vice versa. It is worth mentioning that this is the first attempt to analyze the effect of Clinical and Epidemiological factors with respect to COVID-19 using a fuzzy approach.

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COVID-19临床和流行病学因素的模糊建模

在这次新冠肺炎大流行期间，全球人口健康和经济受到严重影响。这种新型病毒使包括最发达国家在内的整个世界在很短的时间内陷入前所未有的停滞状态。疫情突然爆发的主要原因是缺乏有效的药物和对影响因素的认识不足。本文的目的是利用模糊方法找出影响其传播的流行病学因素的作用。为此，共考虑了9个因素，分为风险因素和预防因素。该模糊模型有助于理解和评价这些因素对COVID-19传播的影响。此外，该模型还为理解风险因素对预防因素的影响以及预防因素对风险因素的影响奠定了基础。值得一提的是，这是首次使用模糊方法分析临床和流行病学因素对新冠肺炎的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of System Dynamics Applications COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

自引率

38.90%

发文量