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Model behavior

ASU computational modelers unleash the power of mathematics and data science to help Arizona in the fight against COVID-19

October 22, 2021

From your smartphone’s weather app telling you it will rain on Friday to the “check engine” light in your car to the safety of the airplane you’re about to board, computational modeling touches your life every day. 

What is it? Combining the power of mathematics, physics and computer science, researchers replicate real-world events using computer simulations. The computers can then predict what’s happening — or could happen — in complex situations, from weather forecasting and aircraft flight to earthquakes and pandemics.

Unleashing data to curb a pandemic

A recent surge in the COVID-19 outbreak in Arizona and throughout the country has left people gripped with uncertainty as they confront countless questions, from whether breakthrough cases are now the norm to when booster shots might be needed. Without concrete answers amid a new wave of the virus, public policy makers, health care leaders and corporate executives struggle to formulate plans on whether to renew mask mandates, roll back reopenings or stay the course.

Filling the information void is Arizona State University’s COVID-19 modeling task force, Modeling Emerging Threats for Arizona (METAz). Led by Timothy Lant, director of program development at ASU’s Biodesign Institute, the task force includes Megan Jehn, associate professor in the School of Human Evolution and Social Change who teaches courses in epidemiology, global health and quantitative research methods; Anna R. Muldoon, co-author of “COVID-19 Conspiracy Theories” and graduate student in the School for the Future of Innovation in Society; and Heather M. Ross, a clinical associate professor who holds a joint appointment in the School for the Future of Innovation in Society and the Edson College of Nursing and Health Innovation

The experts in epidemiological modeling have emerged as leading providers of data about the coronavirus and its rapid spread in the state, helping government, businesses and individuals make informed decisions on how best to protect human health and well-being. 

The task force’s data feeds an online interactive dashboard that has become the state’s go-to site for COVID-19 trends. It informs public officials of hot spots and hospital capacity and citizens about the virus’ trajectory in Arizona, allowing users to compare statewide data to the nation and look at transmission rates county-by-county as well as new vaccines by gender, age and ethnicity. 

Using epidemiological modeling to save lives

“One of the big things we focused on with our models was hospital capacity,” Ross says. “We were able to let public officials and health care officials know what they would need in terms of COVID beds and nurses to care for patients. Hospitals were then able to make adjustments, such as canceling elective surgeries, and the public stayed away from the emergency room for things that weren’t true emergencies. By making some of those adjustments, we were able to make sure that everyone who needed an ICU bed in the state of Arizona was able to get an ICU bed.” 

The team also warned of the dangers of eliminating mask mandates too soon as Gov. Doug Ducey granted local governments autonomy to establish their own health and safety measures to fight rising COVID-19 cases last summer.

“I’m confident that our model helped some public officials retain their masking policies,” Ross says. “And we know that those masking policies helped save some people’s lives.”

We were able to make sure that everyone who needed an ICU bed in the state of Arizona was able to get an ICU bed.”

ASU Clinical Associate Professor Heather M. Ross

“Similarly, we were able to raise the alarm around Thanksgiving, when our epidemiological model showed that household gatherings where people were unmasked in closed spaces would lead to an even bigger surge,” she adds. “And, indeed, that’s exactly what happened.” 

A glimpse into the future

ASU’s COVID-19 pandemic modeling efforts revealed important lessons for the future, such as the need for a better public health data infrastructure for health officials to identify hot spots and inform reopening decisions. 

“We really need to close some of the gaps to get better at our public health surveillance and reporting at the state and county level so that we have real-time data that’s feeding these models to make them more accurate,” Jehn says. 

Meanwhile, pandemic modeling tools and data dashboards developed at ASU will prove to be as useful in the future as today. Lant reminds us that “we really have no reason to anticipate that COVID-19 is going to go away because there’s so much evidence to the contrary.” 

What’s next? METAz is now taking a look at the future endemic phase of the coronavirus, when the virus will be continually present but affecting a relatively small number of people.

As scientists hone more powerful algorithms for disease forecasting, Lant foresees the day you’ll be able to check an app to monitor infectious diseases in your community — much like using a weather app that predicts sunny skies, rainfall and humidity. 

“The National Weather Service has evolved into a global system of weather forecasting that includes sensors, computer models and high-performance computing infrastructure,” Lant says. “Researchers have taken science and brought it to the point that we get weather reports in our homes by watching TV or checking an app. Likewise, the understanding infectious diseases could advance to the point that we could check an app to see how much disease is around.”

Top image by Jason Drees

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