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Refining epidemiological forecasts with simple scoring rules.
- Source :
- Philosophical Transactions of the Royal Society A: Mathematical, Physical & Engineering Sciences; 10/3/2022, Vol. 380 Issue 2233, p1-13, 13p
- Publication Year :
- 2022
-
Abstract
- Estimates from infectious disease models have constituted a significant part of the scientific evidence used to inform the response to the COVID-19 pandemic in the UK. These estimates can vary strikingly in their bias and variability. Epidemiological forecasts should be consistent with the observations that eventually materialize. We use simple scoring rules to refine the forecasts of a novel statistical model for multisource COVID-19 surveillance data by tuning its smoothness hyperparameter. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'. [ABSTRACT FROM AUTHOR]
- Subjects :
- COVID-19 pandemic
COMMUNICABLE diseases
STATISTICAL models
COVID-19
EPIDEMICS
Subjects
Details
- Language :
- English
- ISSN :
- 1364503X
- Volume :
- 380
- Issue :
- 2233
- Database :
- Complementary Index
- Journal :
- Philosophical Transactions of the Royal Society A: Mathematical, Physical & Engineering Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 158586139
- Full Text :
- https://doi.org/10.1098/rsta.2021.0305