NobBS: Nowcasting by Bayesian Smoothing
A Bayesian approach to estimate the number of occurred-but-not-yet-reported cases from incomplete, time-stamped reporting data for disease outbreaks. 'NobBS' learns the reporting delay distribution and the time evolution of the epidemic curve to produce smoothed nowcasts in both stable and time-varying case reporting settings, as described in McGough et al. (2019) <doi:10.1101/663823>.
||R (≥ 3.3.0)
||dplyr, rjags, coda, magrittr
||Sarah McGough [aut, cre],
Nicolas Menzies [aut],
Marc Lipsitch [aut],
Michael Johansson [aut]
||Sarah McGough <sfm341 at mail.harvard.edu>
||MIT + file LICENSE
||JAGS (http://mcmc-jags.sourceforge.net/) for
analysis of Bayesian hierarchical models
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