A decline in infection numbers – no matter how steep or steady – does not mean it is safe to ease coronavirus restrictions, two mathematicians have warned.
A peer-reviewed algorithm developed by Nick James and Max Menzies reveals what health authorities should look for before making a decision on when to open back up.
The pair analysed COVID-19 infection rates in all 50 US states plus the District of Columbia for the seven-month period from January 21 to July 31.
“In some of the worst-performing states, it seems that policymakers have looked for plateauing or slightly declining infection rates,” said Mr James, a PhD student in the School of Mathematics and Statistics at the University of Sydney.
“Instead, health officials should look for identifiable local maxima and minima, showing when surges reach their peak and when they are demonstrably over.”
The same algorithm that was used to assess US infection rates was applied to infection rates in all Australian states and territories.
“What the Victorian data shows is that cases are still coming down and the turning point – the local minimum – has not occurred yet,” said Dr Menzies, from the Yau Mathematical Sciences Center at Tsinghua University in Beijing.
He said a true turning point is when cases have legitimately downturned and not just exhibiting stable fluctuations, adding that from a mathematical perspective at least, Victoria should “stay the course”.
“Our approach allows for careful identification of the most and least successful US states at managing COVID-19,” Dr Menzies said.
Mr James said that aggressively pushing infection rates down to a minimum seemed the best way to defeat a second surge.
He said their algorithm was not meant to be used to make predictions.
Rather policymakers should see it as an “analytical tool” to determine “demonstrable turning points in COVID infections”, he said.