When should restrictive measures be taken to contain the COVID-19 pandemic explosion? An important role for interpreting the pandemic data in a fully rational manner, and thus proactively supporting the political decision makers, is played by signal processing tools. In this paper, we exploit quickest-detection theory applied to pandemic time-series to predict the explosion of COVID-19 infection on a large scale. The focus of the work is to develop a version of the celebrated Page's CUSUM test, specifically tailored to pandemic data. Its application to the publicly-available sequence of new positive individuals per day from different countries is briefly illustrated .
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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When should restrictive measures be taken to contain the COVID-19 pandemic explosion? An important role for interpreting the pandemic data in a fully rational manner, and thus proactively supporting the political decision makers, is played by signal processing tools. In this paper, we exploit
This paper develops an easily-implementable version of Page's CUSUM
R
theory applied to pandemic time-series to predict the explosion of COVID-19 infection on a large scale. The focus of the work is to develop a version of the celebrated Page's CUSUM test, specifically tailored to pandemic data. Its application to the
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
R
sequence of new positive individuals per day from different countries is briefly illustrated
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