This paper presents a non-linear model to simulate and predict the spreading of the newly discovered disease caused by a new series of a Novel Coronavirus (COVID-19). The mathematical modeling in this study is based on the Susceptible Infected Recovery (SIR) model, where key controlling parameters are considered, namely: human contact factor b, transmit factor (a), health medication factor (m) and initial infected (I0). The simulation results show the effect of these parameters, and their role in spreading the COVID-19. The results also show that by keeping a high medication factor and a low contact factor, the spreading of COVID-19 will slow down. The medication health factor depends on the infrastructure of a country, and it is difficult to improve it instantly. On the other hand, the contact factor can be easily controlled. Enforcing the physical social distancing, drastically decreases the contact factor. Hence, slow down the spreading of the virus. Also, the effect of medication factor on the number deaths caused by COVID-19 is studied. The results show that as medication factor increases the number of deaths decreases.

中文翻译：

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Corona COVID-19 传播-非线性建模和模拟

本文提出了一个非线性模型来模拟和预测由一系列新型冠状病毒 (COVID-19) 引起的新发现疾病的传播。本研究中的数学模型基于易感感染恢复 (SIR) 模型，其中考虑了关键控制参数，即：人类接触因素 b、传播因素 (a)、健康药物因素 (m) 和初始感染 (I0) . 模拟结果显示了这些参数的影响，以及它们在传播 COVID-19 中的作用。结果还表明，通过保持较高的药物因素和较低的接触因素，COVID-19 的传播将减慢。药物健康因素取决于一个国家的基础设施，很难立即改善。另一方面，接触系数可以很容易地控制。加强身体上的社交距离，大大降低了接触因素。因此，减缓病毒的传播。此外，还研究了药物因素对 COVID-19 造成的死亡人数的影响。结果表明，随着药物因素的增加，死亡人数减少。