seabbs/ecdc-weekly-growth-forecasts

Abbott, SORCID logo and Sherratt, KORCID logo (2022). seabbs/ecdc-weekly-growth-forecasts. [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.7189620
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A Bayesian autoregressive model using weekly incidence data designed to run as a Github action. Both cases and the growth rate are assumed to be AR(1) processes with the growth rate being differenced and scaled by a decay parameter. The model is implemented using the forecast.vocs R package.

Keywords

COVID-19 cases forecasts, COVID-19, Coronavirus

Item Type Dataset
Capture method Other
Date 12 October 2022
Language(s) of written materials English
Creator(s) Abbott, SORCID logo and Sherratt, KORCID logo
LSHTM Faculty/Department Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology (-2023)
Participating Institutions London School of Hygiene & Tropical Medicine, London, United Kingdom
Date Deposited 13 Oct 2022 09:12
Last Modified 13 Oct 2022 09:12
Publisher Zenodo

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