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A comparison of aggregation methods for probabilistic forecasts of COVID-19 mortality in the United States

Abstract:

The COVID-19 pandemic has placed forecasting models at the forefront of health policy making. Predictions of mortality and hospitalization help governments meet planning and resource allocation challenges. In this paper, we consider the weekly forecasting of the cumulative mortality due to COVID-19 at the national and state level in the U.S. Optimal decision-making requires a forecast of a probability distribution, rather than just a single point forecast. Interval forecasts are also importan...

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Publication status:
Not published
Peer review status:
Not peer reviewed

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Publication website:
https://arxiv.org/abs/2007.11103v2

Authors


More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Primary Care Health Sciences
Role:
Author
ORCID:
0000-0001-6589-5456
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Saïd Business School
Role:
Author
Publisher:
Cornell University Publisher's website
Journal:
arXiv Journal website
Publication date:
2020-07-21
Language:
English
Keywords:
Pubs id:
1123687
Local pid:
pubs:1123687
Deposit date:
2020-09-16

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