论文标题
超级传播者和高方差传染病
Superspreaders and High Variance Infectious Diseases
论文作者
论文摘要
诸如Covid-19之类的大流行病的众所周知的特征是感染传播中高水平的传播异质性：并非所有受感染的个体都以相同的速度传播疾病，而某些人（超级公民）则负责大多数感染。为了量化这一现象，需要分析变异的影响和感染分布的较高力矩。在随机分支过程的框架中工作，我们得出了一个近似的分析公式，该公式是在感染分布的高方差状态下爆发的概率，对其进行数值验证并在各种示例中分析其有效性方案。我们表明，即使基本的繁殖数$ r_0 $大于一个，并讨论了我们对Covid-19和其他大流行的含义，即使基本的繁殖数量$ r_0 $大于一个爆发，也可能不会发生在高方差制度中。
A well-known characteristic of pandemics such as COVID-19 is the high level of transmission heterogeneity in the infection spread: not all infected individuals spread the disease at the same rate and some individuals (superspreaders) are responsible for most of the infections. To quantify this phenomenon requires the analysis of the effect of the variance and higher moments of the infection distribution. Working in the framework of stochastic branching processes, we derive an approximate analytical formula for the probability of an outbreak in the high variance regime of the infection distribution, verify it numerically and analyze its regime of validity in various examples. We show that it is possible for an outbreak not to occur in the high variance regime even when the basic reproduction number $R_0$ is larger than one and discuss the implications of our results for COVID-19 and other pandemics.
