论文标题
一个简单的SIR模型，具有大量无症状感染
A simple SIR model with a large set of asymptomatic infectives
论文作者
论文摘要
越来越多的证据表明，试图控制正在进行的Covid-19的流行病最困难的问题之一是存在大量无症状感染。考虑到无症状或未被发现的感染性的存在，我们开发了一个sir型模型，并且这些花费的时间很长，而不是孤立的。我们讨论基于早期数据的基于SIR的流行病学预测如何考虑到大量无症状感染的存在将给出错误的估计，例如对医院床的需求，流行病峰的时间，以及第一波造成的危险中的危险中的危险。在注释的第二部分中，我们将模型应用于意大利的Covid-19流行病。我们与流行病学数据达成了良好的一致性；根据该模型的流行病学数据的最佳拟合，意大利只有10％的感染是有症状的。
There is increasing evidence that one of the most difficult problems in trying to control the ongoing COVID-19 epidemic is the presence of a large cohort of asymptomatic infectives. We develop a SIR-type model taking into account the presence of asymptomatic, or however undetected, infective, and the substantially long time these spend being infective and not isolated. We discuss how a SIR-based prediction of the epidemic course based on early data but not taking into account the presence of a large set of asymptomatic infectives would give wrong estimate of very relevant quantities such as the need of hospital beds, the time to the epidemic peak, and the number of people which are left untouched by the first wave and thus in danger in case of a second epidemic wave. In the second part of the note, we apply our model to the COVID-19 epidemics in Italy. We obtain a good agreement with epidemiological data; according to the best fit of epidemiological data in terms of this model, only 10\% of infectives in Italy is symptomatic.
