When does a second COVID-19 surge end? Look at the data
New data on US infection rates helps identify COVID-19 turning points


Date:
September 23, 2020
Source:
University of Sydney
Summary:
Using data from all 50 U.S. states plus the District of Columbia,
two mathematicians have developed a new method to analyze COVD-19
rates to help policymakers identify demonstrable turning points
in infection surges.



FULL STORY ========================================================================== Mathematicians have developed a framework to determine when regions enter
and exit COVID-19 infection surge periods, providing a useful tool for
public health policymakers to help manage the coronavirus pandemic.


==========================================================================
The first published paper on second-surge COVID-19 infections from US
states suggests that policymakers should look for demonstrable turning
points in data rather than stable or insufficiently declining infection
rates before lifting restrictions.

Mathematicians Nick James and Max Menzies have published what they believe
is the first analysis of COVID-19 infection rates in US states to identify turning points in data that indicate when surges have started or ended.

The new study by the Australian mathematicians is published today in
the journal Chaos, published by the American Institute of Physics.

"In some of the worst performing states, it seems that policymakers have
looked for plateauing or slightly declining infection rates. Instead,
health officials should look for identifiable local maxima and minima,
showing when surges reach their peak and when they are demonstrably over,"
said Nick James a PhD student in the School of Mathematics and Statistics
at the University of Sydney.

In the study, the two mathematicians report a method to analyse COVID-19
case numbers for evidence of a first or second wave. The authors
studied data from all 50 US states plus the District of Columbia for
the seven-month period from 21 January to 31 July 2020. They found 31
states and the District of Columbia were experiencing a second wave as
of the end of July.



==========================================================================
The two mathematicians have also applied the method to analyse infection
rates in eight Australian states and territories using data from covidlive.com.au.

While the Australian analysis has not been peer-reviewed, it does apply
the peer-reviewed methodology. The analysis clearly identified Victoria
as an outlier, as expected.

"What the Victorian data shows is that cases are still coming down
and the turning point -- the local minimum -- has not occurred yet,"
Dr Menzies said.

He said from a mathematical perspective at least, Victoria should
"stay the course." Dr Menzies, from the Yau Mathematical Sciences
Center at Tsinghua University in Beijing, said: "Our approach allows
for careful identification of the most and least successful US states at managing COVID-19." The results show New York and New Jersey completely flattened their infection curves by the end of July with just a single
surge. Thirteen states, including Georgia, California and Texas, have
a continuing and rising single infection surge. Thirty-one states had
an initial surge followed by declining infection to be followed by a
second surge. These states include Florida and Ohio.

Mr James said: "This is not a predictive model. It is an analytical tool
that should assist policymakers determining demonstrable turning points
in COVID infections." Methodology


==========================================================================
The method smoothes raw daily case count data to eliminate artificial
low counts over weekends and even some negative numbers that occur
when localities correct errors. After smoothing the data, a numerical
technique is used to find peaks and troughs. From this, turning points
can be identified.

Dr Menzies said their analysis shows governments should try not to allow
new cases to increase, nor reduce restrictions when case numbers have
merely flattened.

"A true turning point, where new cases are legitimately in downturn
and not just exhibiting stable fluctuations, should be observed before
relaxing any restrictions." He said that the analysis wasn't just nice mathematics, using a new measure between sets of turning points, the study
also deals with a very topical problem: looking at state-by-state data.

Mr James said that aggressively pushing infection rates down to a minimum seemed the best way to defeat a second surge.

Peaks and Troughs To determine the peaks and troughs, the algorithm
developed by the mathematicians determines that a turning point occurs
when a falling curve surges upward or a rising curve turns downward. Only
those sequences where the peak and trough amplitudes differ by a definite minimum amount are counted.

Fluctuations can occur when a curve flattens for a while but continues to increase without going through a true downturn, so the method eliminates
these false counts.

Both from Australia, the two mathematicians have been best friends for
25 years. "But this year is the first time we have worked on problems together," Mr James said.

Mr James has a background in statistics and has worked for start-ups
and hedge funds in Texas, Sydney, San Francisco and New York City. Dr
Menzies is a pure mathematician, completing his PhD at Harvard in 2019
and his undergraduate mathematics at the University of Cambridge.


========================================================================== Story Source: Materials provided by University_of_Sydney. Note: Content
may be edited for style and length.


========================================================================== Journal Reference:
1. Nick James, Max Menzies. COVID-19 in the United States: Trajectories
and
second surge behavior. Chaos: An Interdisciplinary Journal of
Nonlinear Science, 2020; 30 (9): 091102 DOI: 10.1063/5.0024204 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2020/09/200922112312.htm

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