论文标题
COVID-19的流行病的概率和平均场模型具有用户移动性和触点跟踪
Probabilistic and mean-field model of COVID-19 epidemics with user mobility and contact tracing
论文作者
论文摘要
我们提出了COVID-19流行病的详细离散时间模型，有两种口味，平均场和概率。主要贡献在于基本模型的几个扩展，这些模型捕获i）用户移动性 - 区分路由，即居住的变化，与通勤，即每日移动性 - 和ii）接触跟踪程序。我们将此模型与关于日常住院的公共数据进行，并讨论其应用以及基本估计程序。
We propose a detailed discrete-time model of COVID-19 epidemics coming in two flavours, mean-field and probabilistic. The main contribution lies in several extensions of the basic model that capture i) user mobility - distinguishing routing, i.e. change of residence, from commuting, i.e. daily mobility - and ii) contact tracing procedures. We confront this model to public data on daily hospitalizations, and discuss its application as well as underlying estimation procedures.
