Quickest Detection of COVID-19 Pandemic Onset

Paolo Braca, Domenico Gaglione, Stefano Marano, Leonardo M. Millefiori, Peter Willett, Krishna Pattipati

备注：: Accepted to be published in IEEE Signal Processing Letters
DOI：: 10.1109/LSP.2021.3068072

英文摘要：

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.

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