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Quickest Detection of COVID-19 Pandemic Onset
- Source :
- IEEE Signal Process Lett
- Publication Year :
- 2021
-
Abstract
- This paper develops an easily-implementable version of Page's CUSUM quickest-detection test, designed to work in certain composite hypothesis scenarios with time-varying data statistics. The decision statistic can be cast in a recursive form and is particularly suited for on-line analysis. By back-testing our approach on publicly-available COVID-19 data we find reliable early warning of infection flare-ups, in fact sufficiently early that the tool may be of use to decision-makers on the timing of restrictive measures that may in the future need to be taken.<br />Accepted to be published in IEEE Signal Processing Letters
- Subjects :
- Signal Processing (eess.SP)
2019-20 coronavirus outbreak
Physics - Physics and Society
Coronavirus disease 2019 (COVID-19)
Computer science
FOS: Physical sciences
COVID-19 pandemic
MAST
CUSUM
02 engineering and technology
Physics and Society (physics.soc-ph)
Machine learning
computer.software_genre
Article
Pandemic
0202 electrical engineering, electronic engineering, information engineering
FOS: Electrical engineering, electronic engineering, information engineering
Electrical and Electronic Engineering
Electrical Engineering and Systems Science - Signal Processing
Quantitative Biology - Populations and Evolution
Statistic
Warning system
business.industry
Applied Mathematics
Populations and Evolution (q-bio.PE)
020206 networking & telecommunications
Recursive form
pandemic waves
Test (assessment)
FOS: Biological sciences
Signal Processing
quickest detection
Artificial intelligence
business
computer
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- IEEE Signal Process Lett
- Accession number :
- edsair.doi.dedup.....89a43b9ae85acfbc52d6277855ebfda4