Refining epidemiological forecasts with simple scoring rules-Reference-Cited by-同舟云学术

Refining epidemiological forecasts with simple scoring rules

Published:2022-08-15 Issue:2233 Volume:380 Page:
ISSN:1364-503X
Container-title:Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
language:en
Short-container-title:Phil. Trans. R. Soc. A.

Author:

Moore Robert E.¹^ORCID,Rosato Conor¹^ORCID,Maskell Simon¹

Affiliation:

1. Department of Electrical Engineering and Electronics, University of Liverpool, Brownlow Hill, Liverpool L69 3GJ, UK

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’.

Funder

Engineering and Physical Sciences Research Council

Publisher

The Royal Society

Subject

General Physics and Astronomy,General Engineering,General Mathematics

Link

https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2021.0305

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