论文标题
超级宣传者在SARS-COV-2建模中的作用
The role of super-spreaders in modeling of SARS-CoV-2
论文作者
论文摘要
在传染病的随机建模中，已经确定感染性的变化会影响重大爆发的可能性，但在重大暴发期间曲线的形状不影响曲线的形状，这是通过确定性模型预测的[Diekmann等，2012]。但是，此类结论是在理想化的假设下得出的，例如趋向于无穷大的人口规模，并且仅取决于感染性的差异。在本文中，我们表明，在代表中等大小的城市的有限种群中，相同的结论是正确的，在该城市中，感染程度取决于后代分布，我们试图对SARS-COV-2尽可能地实现。特别是，我们考虑使用脂肪尾巴的分布，以结合超级宣传者的存在。我们还为随机模型的收敛提供了新的理论结果，该结果允许将任何后代分布与有限差异合并。
In stochastic modeling of infectious diseases, it has been established that variations in infectivity affect the probability of a major outbreak, but not the shape of the curves during a major outbreak, which is predicted by deterministic models [Diekmann et al., 2012]. However, such conclusions are derived under idealized assumptions such as the population size tending to infinity, and the individual degree of infectivity only depending on variations in the infectiousness period. In this paper we show that the same conclusions hold true in a finite population representing a medium size city, where the degree of infectivity is determined by the offspring distribution, which we try to make as realistic as possible for SARS-CoV-2. In particular, we consider distributions with fat tails, to incorporate the existence of super-spreaders. We also provide new theoretical results on convergence of stochastic models which allows to incorporate any offspring distribution with a finite variance.
