The COVID-19 pandemic has crippled the world population. Our present work aims to formulate a model to analyze the change in normal health conditions due to COVID-19 infection. For this purpose, we have collected data of seven parameters, namely, age, systolic pressure (SP), diastolic paper (DP), respiratory distress (RD), fasting blood sugar (FBS), cholesterol (CHL), and insomnia (INS) of 156 persons of Birnagar municipality, Nadia, India; before and after COVID-19 infection. Ultimately, using an adaptive neuro-fuzzy inference system (ANFIS), we have formulated our desired model, a Takagi–Sugeno fuzzy inference system. Further, with the help of this model, we have established one’s change in health condition with age due to COVID-19 infection. Finally, we have derived that older people are more affected by COVID-19 infection than younger people.

COVID-19大流行使世界人口瘫痪。我们目前的工作旨在建立一个模型来分析由于 COVID-19 感染引起的正常健康状况的变化。为此，我们收集了七个参数的数据，即年龄、收缩压（SP）、舒张压（DP）、呼吸窘迫（RD）、空腹血糖（FBS）、胆固醇（CHL）和失眠（INS） ) 156 人的 Birnagar 市，纳迪亚，印度；在感染 COVID-19 之前和之后。最终，使用自适应神经模糊推理系统 (ANFIS)，我们制定了我们想要的模型，即 Takagi-Sugeno 模糊推理系统。此外，在该模型的帮助下，我们确定了由于 COVID-19 感染而导致的健康状况随年龄的变化。最后，我们得出结论，老年人比年轻人更容易受到 COVID-19 感染的影响。