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Diffusion as a first model of spread of viral infection

机译:扩散作为病毒感染的第一模型

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The appearance of the coronavirus (COVID-19) in late 2019 has dominated the news in the last few months as it developed into a pandemic. In many mathematics and physics classrooms, instructors are using the time series of the number of cases to show exponential growth of the infection. In this manuscript, we propose a simple diffusion process as the mode of spreading infections. This model is less sophisticated than other models in the literature, but it can capture the exponential growth and it can explain it in terms of mobility (diffusion constant), population density, and probability of transmission. Students can change the parameters and determine the growth rate and predict the total number of cases as a function of time. Students are also given the opportunity to add other factors that are not considered in the simple diffusion model.
机译:2019年底冠状病毒(Covid-19)的外观在过去几个月里,在普遍发展到大流行时占据了新闻。 在许多数学和物理教室中,教师正在使用案例数量的时间序列,以表现出感染的指数增长。 在本手稿中,我们提出了一种简单的扩散过程作为传播感染模式。 该模型比文献中的其他模型更复杂,但它可以捕获指数增长,并且它可以在移动性(扩散常数),人口密度和传输概率方面进行解释。 学生可以改变参数并确定增长率并预测作为时间的函数的案例总数。 学生还有机会添加简单的扩散模型中不考虑的其他因素。

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