Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/36417
Title: EpiLPS: a fast and flexible Bayesian tool for near real-time estimation of the time-varying reproduction number
Authors: GRESSANI, Oswaldo 
Wallinga, Jacco
Althaus, Christian
HENS, Niel 
FAES, Christel 
Issue Date: 2021
Abstract: The instantaneous reproduction number R(t) is a key metric that provides important insights into an epidemic outbreak. We present a flexible Bayesian approach called EpiLPS (Epidemi-ological modeling with Laplacian-P-splines) for smooth estimation of the epidemic curve and R(t). Computational speed and absence of arbitrary assumptions on smoothing makes EpiLPS an interesting tool for near real-time estimation of the reproduction number. An R software package is available (https://github.com/oswaldogressani).
Document URI: http://hdl.handle.net/1942/36417
DOI: 10.1101/2021.12.02.21267189
Category: O
Type: Preprint
Appears in Collections:Research publications

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