Decision support for the quickest detection of critical COVID-19 phases

During the course of an epidemic, one most challenging tasks for authorities is to decide what kind restrictive measures introduce and when these should be enforced. In order take informed decisions in a fully rational manner, onset critical regime, characterized by exponential growth contagion, must identified as quickly possible. Providing rigorous quantitative tools detect such represents important contribution from scientific community proactively support political decision makers. this paper, leveraging quickest detection theory, we propose mathematical model COVID-19 pandemic evolution develop rapidly passage controlled regime one. A new sequential test -- referred MAST (mean-agnostic test) presented, demonstrated on publicly available infection data different countries. Then, performance investigated second wave, showing effective trade-off between average delay $\Delta$ risk $R$, where $R$ inversely proportional time required declare need unnecessary measures. Ideally, mechanism react quick possible given level risk. We find that all countries share same behaviour terms detection, specifically scales exponentially with delay, $R \sim \exp{(-\omega \Delta)}$, $\omega$ depends specific nation. For reasonably small level, say, possibility ten thousand (i.e., unmotivated implementation countermeasures every 27 years, average), proposed algorithm detects few days three weeks, much earlier than becomes evident.