Tyler O'Neal, Staff Editor MANUFACTURING

When what-if scenarios turn real: CSU pandemic modeler providing new COVID-19 insights

Analyzing the toll that long-term school closures may have on US health care providers

As a Yale University postdoctoral researcher, economist Jude Bayham studied the potential consequences of a global pandemic that could shutter schools, close businesses, and strain hospitals. That was back in 2013.

Now, as the world grapples with the coronavirus, the Colorado State University economist and a multi-institutional team are turning those prescient modeling exercises into real insights for policymakers.

"We're repurposing models we had done a while back that frankly at the time, people didn't really care about," said Bayham, assistant professor in the Department of Agricultural and Resource Economics. "It's an 'I told you so' moment. I'm not happy about it. It's unfortunate." {module INSIDE STORY}

In the last several weeks, Bayham and Yale collaborator Eli Fenichel have run a series of analyses illustrating the toll that long-term school closures may have on U.S. health care providers. They're now fielding inquiries from all over the world, from state governments to child care needs assessment professionals, who think the economists' work could help them navigate the here and now. In the last two weeks, the researchers created an interactive dashboard for drilling down statistics on child care needs by state, city and industry sector. Their data were published in The Lancet Public Health on April 3.

Bayham and Fenichel have also created another dashboard for viewing COVID-19 complication risk factors in the workforce.

A third of health workers care for young children

For their health care worker analysis, the researchers used data from the U.S. Current Population Survey to show that about a third of health care workers - doctors, nurses, hospital staff - care for children ages 3-12. Fifteen percent of those households don't have other adults or older children who can help with child care.

At the time they did their original analysis, long-term school closure was a far-off hypothetical. Now, as school districts nationwide shutter for weeks or months, Bayham's work of yore takes on new significance, and the team is scrambling to update it with current figures.

School closures are intended to slow the transmission of the virus. But Bayham and Fenichel find that the toll school closures take on health care workers could potentially negate any mortality benefits from the closures. Their calculations indicate that if the health care workforce declines by 15 percent, due to the workers now having to care for their children, it could lead to an increase in coronavirus deaths because the workers aren't there to care for sick people. Specifically, they report that assuming a 15 percent loss of the health care labor force, a coronavirus infection mortality rate increase of just 0.35 percentage points would net a greater number of deaths than would be prevented by the closures.

These calculations are just that - calculations, which don't take into account, for example, the potential rollout of state or federal programs to offer child care relief to workers. And the estimates aren't perfect; the researchers don't claim to know, down to a precise number, what one health care worker's absence portends.

"We don't know, in terms of a productivity measure, the estimate of one nurse saving this many lives or reducing mortality," Bayham said. "But we think it's not zero. So essentially we are getting at how productive they need to be for us to be concerned about how school closures would undermine the goal of saving lives."

The work is a sobering reminder of the societal and public-health tradeoffs of large-scale disruptions like long-term school closures.

Forming networks

As the pandemic continues to unfold, Bayham and colleagues at Yale, Northwestern University and other institutions have quickly formed a network of economists and epidemiologists to continue this and other lines of work. They hope to help inform decisionmakers on questions not only of tradeoffs of school closures, but also, strategies for peeling back such restrictive measures when the time is right.

As researchers all over the world converge their expertise around the pandemic, Bayham and colleagues are also jumping into other projects to help. For example, Bayham is serving on a U.S. Forest Service task force that will examine potential outcomes of coronavirus on firefighters as fire season returns.

And along with department colleagues Becca Jablonski and Dawn Thilmany, Rebecca Clary, Rebecca Hill and Alexandra Hill, he is also serving on a Colorado Department of Agriculture-focused task force looking at effects of social distancing measures on food supply chain issues. CSU's vice president for engagement and extension, Blake Naughton, established the CSU Task Force on Colorado Food Supply to conduct research on several key areas: food access and security; designating food retail establishments as "essential services;" food supply chain workforce readiness; and consumer expenditure and farm market access.

ESA supports hypersonic surfing

Tyler O'Neal, Staff Editor MANUFACTURING

The European Space Agency has been simulating the test flight of a hypersonic glider, which is being developed through the international HEXAFLY-INT collaboration, involving partners across Europe, Russia, Australia, and Brazil and supported by the European Commission and ESA.

The aim of the project is to develop and fly a wave rider-based vehicle above seven times the speed of sound, designed to surf on the shock waves generated by its own high-speed flight. HEXAFLY-INT’s Experimental Flight Test Vehicle (EFTV) will be launched by a Brazilian sounding rocket before being deployed for its test glide. Hypersonic surfing pillars{module INSIDE STORY}

At 3.29 m long, and 1.24 m wide, the EFTV is slightly smaller than a compact car, with a flat nose tip and wings. A detailed study of its aerodynamic performance was recently performed by Italy’s Centro Italiano Ricerche Aerospaziali, funded through ESA’s Technology Development Element.

Danish AI predicts corona-patients' risk of needing ventilators

Tyler O'Neal, Staff Editor MANUFACTURING

As coronavirus patients are hospitalized, it is difficult for doctors to predict which of them will require intensive care and a respirator. Many different factors come into play, some yet to be fully understood by doctors .

As such, computer scientists at the University of Copenhagen are now developing supercomputer models based on artificial intelligence that calculate the risk of an individual patient's need for a ventilator or intensive care. The new initiative is being conducted in a collaboration with Rigshospitalet and Bispebjerg Hospital.

"With these models, hospitals will be able to know - for example - that 40 percent of their 300 hospitalized patients will probably require a ventilator within one week. This allows them to plan and deploy their resources in the best possible way," explains Professor and Department Head Mads Nielsen of the University of Copenhagen's Department of Computer Science. {module INSIDE STORY}

What do the seriously ill have in common?

Algorithms will harvest vast amounts of data from multiple sources. First, they will find patterns in data from Danish coronavirus patients who have been through the system up until now. In doing so, doctors hope to identify shared traits among the most severely affected patients. This may turn out to be the number of white blood cells, the use of certain pharmaceuticals or something else.

"We are aware of certain things that increase risk, such as age, smoking, asthma and heart problems, but there are other factors involved. After all, we hear about young people who end up on ventilators, and older people who do well without understanding why. So let's get the computer to find patterns that we aren't able to see ourselves," says Chief Physician Espen Solem of Bispebjerg and Frederiksberg Hospitals.

These patterns will be compared with information from newly hospitalized patients. The data consists of X-rays, tests and measurements taken of patients at the time of their admittance to hospital, along with their electronic health records.

"All data will go to a supercomputer where, within minutes, our model calculates how likely a specific patient is to require a ventilator, and how many days will go by before such a need arises. That's our goal," says Mads Nielsen.

First models ready in two to three weeks

Although the models will not be used as a basis for treating individual patients, they will be used as a planning tool that can still make a big difference for hospital staff. According to Espen Solem:

"It will be a great help if we know from the outset whether an individual patient is someone who we need to pay extra attention to, and reserve capacity for. Danish hospitals are still able to keep up, but the situation could change."

Work on the computer models is underway this week, and Mads Nielsen expects the first, rough models to be ready in two to three weeks.

"We hope that our models will be able to be used during this initial wave of coronavirus infections - otherwise, they will be beneficial during the second wave that we anticipate in autumn. Perhaps the models can also be taken to countries where the pandemic has yet to spread as widely as it has in Denmark," says Mads Nielsen.