Atangana Abdon, İğret Araz Seda
Institute for Groundwater Studies, Faculty of Natural and Agricultural Sciences, University of the Free State, Bloemfontein, South Africa.
Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan.
Adv Differ Equ. 2020;2020(1):659. doi: 10.1186/s13662-020-03095-w. Epub 2020 Nov 25.
A comprehensive study about the spread of COVID-19 cases in Turkey and South Africa has been presented in this paper. An exhaustive statistical analysis was performed using data collected from Turkey and South Africa within the period of 11 March 2020 to 3 May 2020 and 05 March and 3 of May, respectively. It was observed that in the case of Turkey, a negative Spearman correlation for the number of infected class and a positive Spearman correlation for both the number of deaths and recoveries were obtained. This implied that the daily infections could decrease, while the daily deaths and number of recovered people could increase under current conditions. In the case of South Africa, a negative Spearman correlation for both daily deaths and daily infected people were obtained, indicating that these numbers may decrease if the current conditions are maintained. The utilization of a statistical technique predicted the daily number of infected, recovered, and dead people for each country; and three results were obtained for Turkey, namely an upper boundary, a prediction from current situation and lower boundary. The histograms of the daily number of newly infected, recovered and death showed a sign of lognormal and normal distribution, which is presented using the Bell curving method parameters estimation. A new mathematical model COVID-19 comprised of nine classes was suggested; of which a formula of the reproductive number, well-poseness of the solutions and the stability analysis were presented in detail. The suggested model was further extended to the scope of nonlocal operators for each case; whereby a numerical method was used to provide numerical solutions, and simulations were performed for different non-integer numbers. Additionally, sections devoted to control optimal and others dedicated to compare cases between Turkey and South Africa with the aim to comprehend why there are less numbers of deaths and infected people in South Africa than Turkey were presented in detail.
本文介绍了一项关于新冠疫情在土耳其和南非传播情况的综合研究。分别使用2020年3月11日至5月3日以及3月5日至5月3日期间从土耳其和南非收集的数据进行了详尽的统计分析。研究发现,在土耳其的案例中,感染病例数呈现负斯皮尔曼相关性,而死亡数和康复数均呈现正斯皮尔曼相关性。这意味着在当前情况下,每日新增感染数可能会减少,而每日死亡数和康复人数可能会增加。在南非的案例中,每日死亡数和每日感染人数均呈现负斯皮尔曼相关性,这表明如果维持当前状况,这些数字可能会下降。运用统计技术预测了每个国家每日的感染、康复和死亡人数;土耳其得出了三个结果,即上限、基于当前情况的预测以及下限。每日新增感染、康复和死亡人数的直方图呈现出对数正态分布和正态分布的迹象,这是通过钟形曲线方法参数估计得出的。提出了一个由九个类别组成的新冠疫情新数学模型;详细给出了繁殖数公式、解的适定性和稳定性分析。针对每个案例,将所提出的模型进一步扩展到非局部算子的范围;采用数值方法提供数值解,并针对不同的非整数进行了模拟。此外,还详细介绍了控制优化部分以及旨在比较土耳其和南非情况以理解为何南非的死亡和感染人数少于土耳其的其他部分。