气候变化领域集成服务门户(CCPortal): Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions

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DOI	10.1126/science.abb9789
	Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions
	Dehning J.; Zierenberg J.; Spitzner F.P.; Wibral M.; Neto J.P.; Wilczek M.; Priesemann V.
发表日期	2020
ISSN	0036-8075
卷号	369 期号:6500
英文摘要	As coronavirus disease 2019 (COVID-19) is rapidly spreading across the globe, short-term modeling forecasts provide time-critical information for decisions on containment and mitigation strategies. A major challenge for short-term forecasts is the assessment of key epidemiological parameters and how they change when first interventions show an effect. By combining an established epidemiological model with Bayesian inference, we analyzed the time dependence of the effective growth rate of new infections. Focusing on COVID-19 spread in Germany, we detected change points in the effective growth rate that correlate well with the times of publicly announced interventions. Thereby, we could quantify the effect of interventions and incorporate the corresponding change points into forecasts of future scenarios and case numbers. Our code is freely available and can be readily adapted to any country or region. © 2020 American Association for the Advancement of Science. All rights reserved.
英文关键词	disease spread; epidemiology; growth rate; infectious disease; viral disease; virus; Article; coronavirus disease 2019; epidemic; geographic distribution; human; illness trajectory; incidence; infection control; infection rate; intervention study; priority journal; virus transmission; Bayes theorem; Coronavirus infection; forecasting; Germany; pandemic; social distance; virus pneumonia; Germany; Coronavirus; Bayes Theorem; Coronavirus Infections; Forecasting; Germany; Humans; Pandemics; Pneumonia, Viral; Social Distance
语种	英语
来源期刊	Science
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/243502
作者单位	Max Planck Institute for Dynamics and Self-Organization, Göttingen, 37077, Germany; Campus Institute for Dynamics of Biological Networks, University of Göttingen, Göttingen, 37075, Germany; Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, 37077, Germany; Bernstein Center for Computational Neuroscience, Göttingen, 37075, Germany
推荐引用方式 GB/T 7714	Dehning J.,Zierenberg J.,Spitzner F.P.,et al. Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions[J],2020,369(6500).
APA	Dehning J..,Zierenberg J..,Spitzner F.P..,Wibral M..,Neto J.P..,...&Priesemann V..(2020).Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions.Science,369(6500).
MLA	Dehning J.,et al."Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions".Science 369.6500(2020).