Using a novel, sequential analysis combined with daily COVID-19 case data across 24 countries, the research suggests early warning signals (EWSs) can predict COVID-19 waves. The team found that warnings were regularly detectable prior to exponential cases changes. but the reliability of these signals depended on the amount of time between successive waves of infection and the mathematical likelihood of a critical transition, Consequently, EWSs showed highest accuracy for waves that experienced a suppressed R number over a long period before the outbreak.
As the ongoing COVID-19 pandemic has shown, being able to identify rapid increases in cases before they occur is important for people to modify their behaviours, and to inform government actions.
Read the full University of Bristol press release
'Early warning signal reliability varies with COVID-19 waves' by Duncan A. O’Brien and Christopher F. Clements in Biology Letters