论文标题
表征Covid-19的传播
Characterizing the spread of CoViD-19
论文作者
论文摘要
自流行病开始以来，全世界的Covid-19案件，住院和死亡的日常报告已公开。本文介绍了使用基于离散时间差异方程的新种群建模框架来表征疾病传播的广泛特征，并具有相对较长的恒定传输速率。选择比较参数是因为它们对模型假设的弱依赖性。提出了其点和间隔估计的方法，即案例数据中其他方差的差异来源。这些方法提供了一个基础，可以定量评估使用公开可用数据对社会距离政策的变化的影响。作为示例，使用此框架分析了安大略省和德国州的数据。德国案件数据显示，在2020年5月6日放松锁定规则后，传输率的增加很小。通过将案件和死亡数据结合在一起，估计从感染到死亡的时间的平均和标准偏差。
Since the beginning of the epidemic, daily reports of CoViD-19 cases, hospitalizations, and deaths from around the world have been publicly available. This paper describes methods to characterize broad features of the spread of the disease, with relatively long periods of constant transmission rates, using a new population modeling framework based on discrete-time difference equations. Comparative parameters are chosen for their weak dependence on model assumptions. Approaches for their point and interval estimation, accounting for additional sources of variance in the case data, are presented. These methods provide a basis to quantitatively assess the impact of changes to social distancing policies using publicly available data. As examples, data from Ontario and German states are analyzed using this framework. German case data show a small increase in transmission rates following the relaxation of lock-down rules on May 6, 2020. By combining case and death data from Germany, the mean and standard deviation of the time from infection to death are estimated.
