AI improved the state’s COVID tracking and response

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IBJ used Adobe Firefly to generate art from the prompt “a medical professional administering a Covid test on another person, both isolated on a white background” using a pencil drawing tag. (AI image/Adobe Firefly)

Josh Martin had his first child on March 15, 2020, just as the pandemic was taking root in the United States. Two days later, the state’s chief data officer and director of the Indiana Management Performance Hub received a phone call: Could he come back to work?

The state needed to quickly develop a system that could provide real-time information to state and local public health officials, the U.S. Centers for Disease Control and Prevention and the public. Until then, the Indiana Department of Health—and many state health agencies—were set up to report and evaluate information after the fact.

For the next two months, Martin and his team used machine learning—a subfield of AI that focuses on algorithms that help computers define models for complex relationships or patterns—to create a real-time health data dashboard that tracked COVID testing results throughout the state.

“We started doing more forecasting, providing as much information [as possible] to the governor and his team on what we were seeing from a testing standpoint,” Martin recalled. “We got into contact tracing, anything that we could to support the decision-making efforts while also providing all that data to the public.”

Developments in AI during the pandemic greatly improved the COVID-19 screening, diagnostics and prediction process, according to a 2021 study by the National Institutes of Health.

Working with the Indiana Office of Technology, the Indiana MPH also worked to deploy chatbots—or generative AI systems—on the Health Department’s website, allowing Hoosiers to get some of their questions about COVID answered when phone lines were down or tied up.•

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