AUSTIN (KXAN) — They’re predictions about the pandemic that have guided public policy, warned hospital systems of surges and have been reported on extensively at KXAN as a way to inform the public about what is to come. A new study published in the Proceedings of the National Academy of Sciences shows those predictions have been some of the most accurate in the country during turbulent surges and declines, and likely saved lives.

In 2020, the University of Texas COVID-19 Modeling Consortium was tasked with helping local leaders predict the outcome of the COVID-19 pandemic with enough advance that hospital and ICU surges wouldn’t become overwhelming. By predicting surges a few weeks out, local leaders could plead with the public with enough evidence to change behavior.

“When COVID-19 was emerging, we were already thinking about how best to forecast COVID-19 dynamics and track the pandemic,” Dr. Spencer Fox, the associate director of the UT COVID-19 Modeling Consortium, said. “So the first thing we did was figure out what data we’re going to power the model.”

Fox said the consortium looked towards two sources of data to create reliable predictions: epidemiological data and behavioral data.

The most reliable form of epidemiological data, Fox said, was hospital admissions. It’s a data set the City of Austin and Travis County have also highlighted as a metric for which risk-based guidelines stage the area is in.

But in March of 2020, how to measure behavioral data was less obvious — testing was not widely available and best practices were just emerging for much of the public. That’s why researchers turned to what you carry around in your pocket.

The UT modeling consortium was one of the first to include public movement data in their models, according to UT, even before the well-known Institute for Health Metrics and Evaluation modeled by the University of Washington.

Researchers plugged anonymous cell phone data from SafeGraph into their projections, and it showed how much time people spent in their own household versus school, work, restaurants and other public spaces. It filled a data gap that many other models couldn’t fill.

“That behavioral cellphone mobility data has allowed us to kind of understand how behaviors are changing in our community with the goal of providing a one to two week lead time and what will happen in terms of our healthcare needs,” Fox said. “So what we found in the study specifically was that overall our forecasts predictions were very reliable up to three, even four weeks out in some cases.”

But just collecting the data wouldn’t be enough to warn the public of what was to come. For those predictions to be intuitive to the community, it needed to be presented in a way that everyone at home could understand. That’s why researchers at UT turned to a model of public forecasting already well established — spaghetti lines from hurricane forecasting, paired with easy-to-read graphics.

Those predictions and data were published on a public-facing dashboard, which if you’ve followed KXAN’s pandemic coverage, you’ve likely heard about. We use that dashboard on a regular basis.

“I think this report that we just had published really gives, you can think of a schematic of how to actually respond to a pandemic,” Fox said. “It walks through how to collaborate with local public health officials, elected leaders, and healthcare systems, what data sources are useful for actually making these types of forecasts and it gives a model structure and framework for doing that.”

When it comes to this pandemic though, other parts of the country won’t have to build their own forecast dashboards from scratch. Researchers at UT are working to roll out a dashboard similar to the one we use in Austin for every metropolitan region in the country.

“Over the next few weeks, few months, we should have a dashboard that will actually let you look at what our projections are for Albuquerque,” Fox said. “You’ll be able to select any metropolitan region in the country.”