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实时估计 以支持针对 COVID-19 的公共卫生政策。

Real-Time Estimation of for Supporting Public-Health Policies Against COVID-19.

机构信息

Centre for Biotechnology and Bioengineering, Universidad de Chile, Santiago, Chile.

Departamento de Ingeniería Química, Biotecnología y Materiales, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Santiago, Chile.

出版信息

Front Public Health. 2020 Dec 22;8:556689. doi: 10.3389/fpubh.2020.556689. eCollection 2020.

Abstract

In the absence of a consensus protocol to slow down the spread of SARS-CoV-2, policymakers need real-time indicators to support decisions in public health matters. The Effective Reproduction Number ( ) represents the number of secondary infections generated per each case and can be dramatically modified by applying effective interventions. However, current methodologies to calculate from data remain somewhat cumbersome, thus raising a barrier between its timely calculation and application by policymakers. In this work, we provide a simple mathematical formulation for obtaining the effective reproduction number in real-time using only and directly daily official case reports, obtained by modifying the equations describing the viral spread. We numerically explore the accuracy and limitations of the proposed methodology, which was demonstrated to provide accurate, timely, and intuitive results. We illustrate the use of our methodology to study the evolution of the pandemic in different iconic countries, and to assess the efficacy and promptness of different public health interventions.

摘要

在缺乏减缓 SARS-CoV-2 传播的共识协议的情况下,政策制定者需要实时指标来支持公共卫生事务的决策。有效繁殖数( )表示每个病例产生的二次感染数量,可以通过实施有效干预措施显著改变。然而,目前从数据中计算 的方法仍然有些繁琐,从而在其及时计算和政策制定者应用之间造成了障碍。在这项工作中,我们提供了一种简单的数学公式,用于仅使用和直接从官方每日病例报告中实时获取有效繁殖数,这是通过修改描述病毒传播的方程来实现的。我们对所提出的方法的准确性和局限性进行了数值研究,结果表明该方法能够提供准确、及时和直观的结果。我们说明了使用我们的方法来研究不同标志性国家大流行的演变,并评估不同公共卫生干预措施的效果和及时性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c8b1/7783316/3543a261cf6f/fpubh-08-556689-g0001.jpg

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