Ghanbari Behzad
Department of Engineering Science, Kermanshah University of Technology, Kermanshah, Iran.
Department of Mathematics, Faculty of Engineering and Natural Sciences, Bahçeşehir University, 34349 Istanbul, Turkey.
Chaos Solitons Fractals. 2020 Nov;140:110176. doi: 10.1016/j.chaos.2020.110176. Epub 2020 Jul 28.
One of the common misconceptions about COVID-19 disease is to assume that we will not see a recurrence after the first wave of the disease has subsided. This completely wrong perception causes people to disregard the necessary protocols and engage in some misbehavior, such as routine socializing or holiday travel. These conditions will put double pressure on the medical staff and endanger the lives of many people around the world. In this research, we are interested in analyzing the existing data to predict the number of infected people in the second wave of out-breaking COVID-19 in Iran. For this purpose, a model is proposed. The mathematical analysis corresponded to the model is also included in this paper. Based on proposed numerical simulations, several scenarios of progress of COVID-19 corresponding to the second wave of the disease in the coming months, will be discussed. We predict that the second wave of will be most severe than the first one. From the results, improving the recovery rate of people with weak immune systems via appropriate medical incentives is resulted as one of the most effective prescriptions to prevent the widespread unbridled outbreak of the second wave of COVID-19.
关于新冠疫情，常见的误解之一是认为在第一波疫情消退后不会出现复发情况。这种完全错误的认知导致人们无视必要的防控措施，做出一些不当行为，比如日常社交或节假日出行。这些情况会给医护人员带来双重压力，并危及世界各地许多人的生命。在本研究中，我们有兴趣分析现有数据，以预测伊朗第二波新冠疫情爆发时的感染人数。为此，我们提出了一个模型。本文还包含了与该模型对应的数学分析。基于所提出的数值模拟，将讨论未来几个月与第二波疫情相对应的几种新冠疫情发展情景。我们预测第二波疫情将比第一波更严重。从结果来看，通过适当的医疗激励措施提高免疫系统较弱人群的康复率，是预防第二波新冠疫情大规模肆意爆发的最有效药方之一。
