epinowcast-package | R Documentation |
Tools to enable flexible and efficient hierarchical nowcasting of right-truncated epidemiological time-series using a semi-mechanistic Bayesian model with support for a range of reporting and generative processes. Nowcasting, in this context, is gaining situational awareness using currently available observations and the reporting patterns of historical observations. This can be useful when tracking the spread of infectious disease in real-time: without nowcasting, changes in trends can be obfuscated by partial reporting or their detection may be delayed due to the use of simpler methods like truncation. While the package has been designed with epidemiological applications in mind, it could be applied to any set of right-truncated time-series count data.
Maintainer: Sam Abbott contact@samabbott.co.uk (ORCID)
Authors:
Adrian Lison adrian.lison@bsse.ethz.ch (ORCID)
Sebastian Funk sebastian.funk@lshtm.ac.uk
Carl Pearson carl.ab.pearson@gmail.com (ORCID)
Hugo Gruson hugo.gruson@normalesup.org (ORCID)
Felix Guenther felixguenther1@gmx.de (ORCID)
Michael DeWitt me.dewitt.jr@gmail.com (ORCID)
James Mba Azam james.azam@lshtm.ac.uk (ORCID)
Jessalyn Sebastian jessalynsebastian@gmail.com (ORCID)
Other contributors:
Hannah Choi hannah.choi1@lshtm.ac.uk [contributor]
Pratik Gupte pratik.gupte@lshtm.ac.uk (ORCID) [contributor]
Joel Hellewell joel@ebi.ac.uk (ORCID) [contributor]
Luis Rivas luisnicolasrivas@gmail.com [contributor]
Sang Woo Park swp2@princeton.edu (ORCID) [contributor]
Nathan McIntosh natemcintosh@gmail.com [contributor]
Kath Sherratt katharine.sherratt@lshtm.ac.uk (ORCID) [contributor]
Nikos Bosse nikos.bosse@lshtm.ac.uk (ORCID) [contributor]
Adam Howes adamthowes@gmail.com (ORCID) [contributor]
Kaitlyn Johnson johnsonkaitlyne9@gmail.com (ORCID) [contributor]
Useful links:
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.