Spatial and temporal regularization to estimate COVID-19 reproduction number R(t): Promoting piecewise smoothness via convex optimization

Among the different indicators that quantify the spread of an epidemic such as the on-going COVID-19, stands first the reproduction number which measures how many people can be contaminated by an infected person. In order to permit the monitoring of the evolution of this number, a new estimation pro...

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Veröffentlicht in:	PloS one 2020-08, Vol.15 (8), p.e0237901-e0237901, Article 0237901
Hauptverfasser:	Abry, Patrice, Pustelnik, Nelly, Roux, Stephane, Jensen, Pablo, Flandrin, Patrick, Gribonval, Remi, Lucas, Charles-Gerard, Guichard, Eric, Borgnat, Pierre, Garnier, Nicolas
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Betacoronavirus Computer and Information Sciences Computer Science Computer simulation Convex analysis Convexity Coronavirus Infections - epidemiology Coronavirus Infections - transmission Coronavirus Infections - virology Coronaviruses COVID-19 Databases, Factual Disease transmission Disease Transmission, Infectious - statistics & numerical data Earth Sciences Engineering and Technology Epidemics Evolution France France - epidemiology Humans Inverse problems Medical supplies Medicine and Health Sciences Methods Models, Statistical Multidisciplinary Sciences Optimization Pandemics Parameter estimation People and places Physical Sciences Pneumonia, Viral - epidemiology Pneumonia, Viral - transmission Pneumonia, Viral - virology Poisson Distribution Regularization Reproduction Research and Analysis Methods Risk factors SARS-CoV-2 Science & Technology Science & Technology - Other Topics Sentinel surveillance Signal and Image Processing Smoothness Software Spatio-Temporal Analysis Statistics
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