UT Toolkit Readies Texas to Fight the Flu
In 2009, the H1N1 virus struck hard, killing millions of people worldwide.
The days of wearing surgical masks at the airport during the swine flu outbreak may be long gone, but the probability of a severe pandemic striking again is still high.
And when it does, Texas will be ready, thanks to developments made by UT researchers.
Lauren Ancel Meyers, a UT professor of integrative biology and director of the Division of Statistics Scientific Computation, and her team of researchers have developed the Texas Pandemic Flu Toolkit, a web-based service to forecast and simulate the spread of pandemic flu throughout the state of Texas.
“This will enable our state public health department to come up with better strategies for preparing for, or responding to, the next major pandemic,” Meyers says, “so that they can ensure that hospitals have the resources needed to effectively treat all cases.”
The toolkit can be used in emergency situations to alert public health officials of infections, forecast pandemic progression, specify deployment of vaccines, and to develop visuals that vividly depict the spread of disease.
Scenarios of probable pandemics can be developed to show how disease may impact different locations, age groups, and demographics. Each time the scenarios are tested, a slightly different outcome is given depending on how quickly the disease may spread, how lethal it is, and where the outbreak began.
The tool will train public health officials to make better decisions by giving them an understanding of the flu’s spread and the best strategies for fighting it, Meyers says.
“When the flu pandemic first starts spreading we usually don’t have vaccines available, and when they become available, there is a lot of demand,” Meyers says. “So officials should know what the best use of vaccines is in order to protect the public and save lives.”
Various intervention methods—such as antivirals, vaccines, and public health announcements—can be inputted into the simulations to determine their effect on the pandemic’s evolution.
During a pandemic, some of the most serious cases of influenza will require medical ventilators to breathe. The stockpiling tool uses information from the forecaster to make sure hospitals have enough ventilators available to treat the most serious cases.
“At the peak of a pandemic, hospitals may experience a large surge of severe cases,” Meyers says. “This tool uses forecasts of flu hospitalizations to estimate how many ventilators Texas should have on hand to effectively treat severe cases.”
The toolkit is designed for the Texas Department of State Health Services, with all models built on Texas data in particular.
If adapted, similar tools could be of value to other states and on a national scale, Meyers says.
Meyers’ efforts to enhance data-driven science were aided by UT’s Texas Advanced Computing Center, which recently published an in-depth story about the toolkit.
Meyers will present her research to the attendees of the Texas Exes Alumni College next week.
Photo courtesy Flickr user Xavier Donat.
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