Central Bank of Chile, Santiago, Chile.
Humboldt University of Berlin, Berlin, Germany.
PLoS One. 2021 Jan 13;16(1):e0244474. doi: 10.1371/journal.pone.0244474. eCollection 2021.
We develop a new method for estimating the effective reproduction number of an infectious disease ([Formula: see text]) and apply it to track the dynamics of COVID-19. The method is based on the fact that in the SIR model, [Formula: see text] is linearly related to the growth rate of the number of infected individuals. This time-varying growth rate is estimated using the Kalman filter from data on new cases. The method is easy to implement in standard statistical software, and it performs well even when the number of infected individuals is imperfectly measured, or the infection does not follow the SIR model. Our estimates of [Formula: see text] for COVID-19 for 124 countries across the world are provided in an interactive online dashboard, and they are used to assess the effectiveness of non-pharmaceutical interventions in a sample of 14 European countries.
我们开发了一种新的方法来估计传染病的有效繁殖数（[公式：见正文]），并将其应用于追踪 COVID-19 的动态。该方法基于这样一个事实，即在 SIR 模型中，[公式：见正文]与感染人数的增长率呈线性关系。通过从新病例数据中使用卡尔曼滤波器来估计这个时变增长率。该方法易于在标准统计软件中实现，即使感染人数的测量不完美，或者感染不符合 SIR 模型，它也能很好地工作。我们为全球 124 个国家提供了 COVID-19 的[公式：见正文]的估计值，并在一个交互式在线仪表板中提供了这些值，我们还使用这些值评估了 14 个欧洲国家样本中的非药物干预措施的有效性。
