论文标题
在感染指示器之间的平均时间测量COVID-19的扩散速度
Measuring COVID-19 spreading speed through the mean time between infections indicator
论文作者
论文摘要
我们建议利用从最近引入的非均匀马尔可夫随机模型获得的感染（MTBI）度量之间的平均时间。进行了不同类型的参数校准。我们使用来自不同时间窗口和整个阶段历史记录的数据来估算MTBI，并比较结果。为了检测输入数据中的波和阶段，应用了预处理滤波技术。显示了将该指标应用于Covid-19报告的结果，该指标报告了阿根廷，德国和美国的感染数据。我们发现，MTBI相对于不同的数据输入的行为相似，而模型参数完全改变了其行为。还显示了参数和MTBI指标的演变。我们展示的证据支持以下说法：MTBI是一个相当不错的指标，以衡量流行病的传播速度，无论输入数据大小如何，都具有相似的值。
We propose to use the mean time between infections (MTBI) metric as obtained from a recently introduced non-homogeneous Markov stochastic model. Different types of parameter calibration are performed. We estimate the MTBI using data from different time windows and from the whole stage history and compare the results. In order to detect waves and stages in the input data, a preprocessing filtering technique is applied. The results of applying this indicator to the COVID-19 reported data of infections from Argentina, Germany and the United States are shown. We find that the MTBI behaves similarly with respect to the different data inputs, whereas the model parameters completely change their behaviour. Evolution over time of the parameters and the MTBI indicator is also shown. We show evidence to support the claim that the MTBI is a rather good indicator in order to measure the spreading speed of an epidemic, having similar values whatever the input data size.
