Ghosh Bappaditya, Biswas Animesh
Department of Mathematics, University of Kalyani, Kalyani 741235, India.
Appl Soft Comput. 2021 Sep;109:107540. doi: 10.1016/j.asoc.2021.107540. Epub 2021 Jun 2.
The outbreak of COVID-19 had already shown its harmful impact on mankind, especially on health sectors, global economy, education systems, cultures, politics, and other important fields. Like most of the affected countries in the globe, India is now facing serious crisis due to COVID-19 in the recent times. The evaluation of the present status of the provinces affected by COVID-19 is very much essential to the government authorities to impose preventive strategies in controlling the spread of COVID-19 and to take necessary measures. In this article, a computational methodology is developed to estimate the present status of states and provinces which are affected due to COVID-19 using a fuzzy inference system. The factors such as population density, number of COVID-19 tests, confirmed cases of COVID-19, recovery rate, and mortality rate are considered as the input parameters of the proposed methodology. Considering positive and negative factors of the input parameters, the rule base is developed using triangular fuzzy numbers to capture uncertainties associated with the model. The application potentiality is validated by evaluating Pearson's correlation coefficient. A sensitivity analysis is also performed to observe the changes of final output by varying the tolerance ranges of the inputs. The results of the proposed method show that some of the provinces have very poor performance in controlling the spread of COVID-19 in India. So, the government needs to take serious attention to deal with the pandemic situation of COVID-19 in those provinces.
新型冠状病毒肺炎（COVID-19）疫情已对人类产生了有害影响，尤其是对卫生部门、全球经济、教育系统、文化、政治及其他重要领域。与全球大多数受影响国家一样，印度近期正因COVID-19面临严重危机。评估受COVID-19影响省份的现状对于政府当局实施预防策略以控制COVID-19传播并采取必要措施至关重要。在本文中，开发了一种计算方法，使用模糊推理系统来估计受COVID-19影响的邦和省份的现状。人口密度、COVID-19检测次数、COVID-19确诊病例数、康复率和死亡率等因素被视为该方法的输入参数。考虑到输入参数的正负因素，使用三角模糊数建立规则库以捕捉与模型相关的不确定性。通过评估皮尔逊相关系数验证了应用潜力。还进行了敏感性分析，以观察通过改变输入的公差范围对最终输出的影响。所提方法的结果表明，印度的一些省份在控制COVID-19传播方面表现非常差。因此，政府需要认真关注这些省份应对COVID-19大流行的情况。
