论文标题
COVID-19的两相动态传染模型
A Two-Phase Dynamic Contagion Model for COVID-19
论文作者
论文摘要
在本文中，我们提出了一个连续的随机强度模型，即两相动态传播过程（2P-DCP），用于对Covid-19的流行传播进行建模，并根据Dassios和Zhao（2011）引入的动态传播模型来研究锁定效应。它允许对个体的感染性，而不是标准模型假设的恒定繁殖数。基于各个地区和国家的实际数据，得出和估算了关键的流行病学数量，例如最终流行病的分布和预期的流行持续时间。估计每个国家或地区干预效果的相关时间滞后。我们的结果与最近医学研究发现的Covid-19的孵育时间一致。我们证明，我们的模型可能是Covid-19建模中的有价值工具。更重要的是，提出的2P-DCP模型也可以用作流行病学建模的重要工具，因为这种具有非常简单结构的传染模型足以描述区域流行病和全球大流行的演变。
In this paper, we propose a continuous-time stochastic intensity model, namely, two-phase dynamic contagion process(2P-DCP), for modelling the epidemic contagion of COVID-19 and investigating the lockdown effect based on the dynamic contagion model introduced by Dassios and Zhao (2011). It allows randomness to the infectivity of individuals rather than a constant reproduction number as assumed by standard models. Key epidemiological quantities, such as the distribution of final epidemic size and expected epidemic duration, are derived and estimated based on real data for various regions and countries. The associated time lag of the effect of intervention in each country or region is estimated. Our results are consistent with the incubation time of COVID-19 found by recent medical study. We demonstrate that our model could potentially be a valuable tool in the modeling of COVID-19. More importantly, the proposed model of 2P-DCP could also be used as an important tool in epidemiological modelling as this type of contagion models with very simple structures is adequate to describe the evolution of regional epidemic and worldwide pandemic.
