Scientists are developing a model to determine which US states are in a second wave of coronavirus

Scientists have developed a mathematical model to determine whether or not US states are in a ‘second wave period’ of coronavirus infections.

Researchers at the University of Sydney, Australia, looked at data and determined that any state with a ‘second peak’ less than one-fifth of the first is not a true second wave because it is too small.

Using this methodology, they determined that at least 31 states, such as Florida, Ohio and Pennsylvania, were in their second wave by the end of July.

About 13 states, including California, Texas, and Georgia, had seen infection rates level off just a little and didn’t go down, so they were still in their first waves.

Meanwhile, New York and New Jersey had completely smoothed out their respective curves, and their first wave was ‘completely over’ with no second wave in sight.

The team says the findings could help local and state lawmakers determine when to ease restrictions by seeing the difference between stable or insufficiently declining infection rates and rates on a down trajectory.

“In some of the worst-performing states, policymakers seem to have looked for decreasing or slightly decreasing infection rates,” said study co-author Dr. Nick James, a PhD student at the University of Sydney’s School of Mathematics and Statistics.

Instead, health officials should look for identifiable local maximums and minimums that show when peaks are reaching their peak and when they are demonstrably over.

For the study, published in the journal Chaos, the team looked at data from all 50 US states and the District of Columbia from January 21, 2020 to July 31, 2020.

Researchers adjusted the raw daily case totals to account for low totals that typically occur on weekends and negative counts on the day when counties correct errors.

After the data is smoothed, the mathematical model looks for peaks and troughs and identifies a turning point.

A turning point was identified as the trajectory of upward curves that suddenly descend, or downward curves that peak.

Peak highs and lows must also vary by a certain amount.

For example, a second wave with less than a fifth of the number of cases in the first does not qualify as a second wave because it is simply too small, the researchers say.

Thirteen states, including California, Georgia, Mississippi, North Carolina, and Texas, had an increasing number of cases over the entire seven-month period.

Because of this they are are considered to be still in their first wave with a single increasing wave of infection.

Researchers assigned 31 states, including Florida, Ohio and Pennsylvania, to the TPTP series, meaning there are no cases for a first spike, then another trough and a spike after that.

This means that these states are currently in their second wave which is a first wave followed by decreasing infections and then a second wave.

Meanwhile, New York and New Jersey flattened their respective curves in late July, experiencing only one wave each.

The remaining four states, Arizona, Utah, Maine, and Vermont, are still working on their first peaks (the first two states) and the second (the last two states) peaks.

“This is not a predictive model,” said James.

‘It is an analytical tool that should help policymakers determine demonstrable turning points in COVID infections.’

Co-author Dr. Max Menzies, of the Yau Mathematical Sciences Center at Tsinghua University in Beijing, said the analysis shows how reducing constraints when curves have just smoothed out and not gone down can lead to a deadly second wave.

“The real moral of this article is that COVID-19 is highly contagious and very difficult to combat,” he said.

A true turning point, where new cases are legitimately in a downturn and not just showing stable fluctuations, must be observed before any restrictions are relaxed