Justin Lessler, Johns Hopkins - What we know and don't about the Coronavirus

Justin Lessler, Johns Hopkins
What we know and don't about the Coronavirus


When you first saw the ocean, did you count the waves?  I did, for a while, and then I stopped. Because counting the waves as they splash or crash on shore is a waste of time.

So is the counting of waves of COVID-19.  Is this the first wave, or the second, and when we come into colder weather and flu season should that be counted as another new “winter” wave?

Or is it all the same Coronavirus ocean?  With waves of infection, whose amplitude and duration are as related to human behavior as climate change

For a while the waves of new COVID-19 cases in America came, in March, April and May, at a rate of 20 and 30 thousand a day. Then came Memorial Day, Americans took a holiday from family bubbles and personal separations and two weeks later the sea level started to rise – 40, 50, 60,000 new cases a day until they peaked just above 75,000, two weeks after the Fourth of July. Then, American caseloads slowly subsided. But only to the point where September’s best days would have been considered among the worst days in April, May and June.

And this week’s bad days will look good in December according to a well-respected computer model developed at the University of Washington.  The model predicts a “huge surge” in COVID-19 cases to start in October “and accelerate in November and December. There’s a real risk that winter surge has already started in Europe,” says one of the Washington modelers, “Cases are exploding there. So, we know it’s coming and we expect it to hit the U.S. pretty soon.”

Colder weather driving more people indoors is one factor cited to explain the expected surge, the other is bubble fatigue, people reverting to old, now dangerous, social habits.

The latest rise in COVID cases began a couple of weeks after Labor Day, and its old-fashioned family and holiday gatherings may have again spread the disease. But there is perhaps another factor: schools reopened.   The post-Labor Day rise in COVID-19 cases among children has been even sharper than the one noted for adults.

Not only has the percentage of children testing positive for COVID-19 close to doubled since the Spring, so has the percentage of cases serious enough to send children into hospitals.

Many of the infected children, around four out of 10 by one recent study, are asymptomatic. They don’t know they’re sick and neither do the people around them, and reopening schools exponentially increase the number of children around one another. So how much does that increase the risk for classmates, teachers and older folks at home?

And how much does keeping schools closed and kids at home increase the risk of domestic violence and economic disruption?

And how might governments design measures and standards to determine when risks have gotten too high?

For answers to these questions, more and more governments are turning to epidemiologists for guidance on how best to protect public health.  Here in the U.S. one of the most frequently turned-to epidemiologists is our guest today, Justlin Lessler, of the Johns Hopkins Bloomberg School of Public Health.



Justin Lessler is an Associate Professor of Epidemiology at the Johns Hopkins Bloomberg School of Public Health.
















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