论文标题
异质性和对牛群免疫的超级效果
Heterogeneity and Superspreading Effect on Herd Immunity
论文作者
论文摘要
我们考虑到感染性和敏感性的异质性以及这两个参数之间的相关性，并计算出达到群疫苗所必需的感染人群的比例。我们表明，这些导致有效的繁殖数量更快地降低，因此对必须达到疾病的必要人群百分比具有巨大影响。当有效的繁殖数量降低到1以下与患有该疾病的最终人群的最终分数时，我们量化了感染人群的大小之间的差异。这阐明了畜群免疫与疾病末端之间的重要区别，并突出了即使我们计划自然达到牛群免疫，也强调了限制疾病传播的重要性。我们分析了各种锁定场景对被感染人群最终部分的影响。我们讨论了对Covid-19和其他流行学的影响，并将我们的理论结果与基于人群的模拟进行了比较。我们考虑疾病的依赖性扩散到传染性图的结构上，并分析了不同的图形体系结构和图形模型的局限性。
We model and calculate the fraction of infected population necessary to reach herd immunity, taking into account the heterogeneity in infectiousness and susceptibility, as well as the correlation between those two parameters. We show that these cause the effective reproduction number to decrease more rapidly, and consequently have a drastic effect on the estimate of the necessary percentage of the population that has to contract the disease for herd immunity to be reached. We quantify the difference between the size of the infected population when the effective reproduction number decreases below 1 vs. the ultimate fraction of population that had contracted the disease. This sheds light on an important distinction between herd immunity and the end of the disease and highlights the importance of limiting the spread of the disease even if we plan to naturally reach herd immunity. We analyze the effect of various lock-down scenarios on the resulting final fraction of infected population. We discuss implications to COVID-19 and other pandemics and compare our theoretical results to population-based simulations. We consider the dependence of the disease spread on the architecture of the infectiousness graph and analyze different graph architectures and the limitations of the graph models.
