The convergence epidemic volatility index(cEVI)as an alternative early warning tool for identifying waves in an epidemic

This manuscript introduces the convergence Epidemic Volatility Index(cEVI),a modifi-cation of the recently introduced Epidemic Volatility Index(EVI),as an early warning tool for emerging epidemic waves.cEVI has a similar architectural structure as EVI,but with an optimization process inspired by a Geweke diagnostic-type test.Our approach triggers an early warning based on a comparison of the most recently available window of data samples and a window based on the previous time frame.Application of cEVI to data from the COVID-19 pandemic data revealed steady performance in predicting early,intermediate epidemic waves and retaining a warning during an epidemic wave.Furthermore,we present two basic combinations of EVI and cEVI:(1)their disjunction cEVI+that respectively identifies waves earlier than the original index,(2)their conjunction cEVIthat results in higher accuracy.Combination of multiple warning systems could potentially create a surveillance umbrella that would result in early implementation of optimal outbreak interventions.