The Texas Pandemic Flu Forecasting tool predicts hospitalizations regionally and state-wide based on various indicators including ILI surveillance data, Google flu trends, absolute humidity and school calendar data. Watch the Texas Pandemic Flu Toolkit video on YouTube.
In 2009, the H1N1 pandemic infected millions and killed more than 18,000 worldwide, according to the World Health Organization. The pandemic highlighted the threat of deadly viruses emerging from animals into humans, and the importance of quick and effective public health intervention.
To help better prepare for the next pandemic, The University of Texas at Austin’s Lauren Ancel Meyers has developed the Texas Pandemic Flu Toolkit, a Web-based service that simulates the spread of pandemic flu through the state, forecasts the number of flu hospitalizations, and determines where and when to place ventilators to minimize fatalities.
“While the forecasts will not be exact, they give a rough idea of how many people will be hospitalized around the state and when an epidemic may peak. Such information can lead to more timely and effective control measures,” said Meyers.
In a globalized world, the probability of a severe pandemic striking is high, says Meyers, an expert in infectious disease epidemiology and professor in the College of Natural Sciences.
A biologist by training, Meyers applies mathematical models and computer programs to understand, analyze and predict the transmission of diseases based on a large number of factors. She worked with a team of university researchers from biology, mathematics, statistics, engineering and the Texas Advanced Computing Center (TACC) to develop the Texas Pandemic Flu Toolkit.
Public health officials can use the toolkit to guide real-time decision-making in emergency situations, for example, determining when a pandemic might crest and what its magnitude will be. This information can then be communicated to local authorities.
The toolkit can also be used proactively to develop scenarios of probable pandemics and to see how they might affect different locations, age groups and demographics.
Potential interventions such as anti-virals, vaccines and public health announcements can be put into the forecasts to determine their effect at different stages in the pandemic’s evolution.
Meyers and her colleagues unveiled the toolkit in late 2011 to state officials who have already begun using it.
“The toolkit allows us to respond more effectively by providing the ability to quickly adjust predictive variables as we gather information. We can use this information to focus response efforts and optimize resources,” said Bruce Clements, director of community preparedness with the Texas Department of State Health Services. “These same tools may be used in training and exercises to better prepare our public health workforce.”
A significant fraction of influenza patients infected during a pandemic require ventilators. However, no one knows whether the strategic national stockpile of ventilators — about 6,000 — is enough.
David Morton, a professor in the university’s Cockrell School of Engineering, led the Texas ventilator-stockpiling portion of the toolkit, which projects where ventilators should be optimally placed to limit mortality.
“If we have a mild or moderate pandemic, then we have ample ventilators. But if we have a severe pandemic, then we’re grossly short,” Morton said. “Officials knew that, but the thing they valued here was that we could actually quantify how short are we.”
In the case of a pandemic, Texas would need all 6,000 ventilators. Ten times as many would be required nationwide.
Meyers worked closely with TACC, a leading advanced computing center located at The University of Texas at Austin. TACC’s powerful supercomputers allow data to be processed, crunched and distributed to a large number of stakeholders simultaneously.
“Our methods often require rapid evaluation of a large number of possible solutions, which would be intractable without high-performance computers,” Meyers explained.
TACC staff members also collaborated on the project. Greg P. Johnson, a research associate at TACC, converted the researchers’ algorithms into a Web-based interface that provides information-rich data visualizations directly to a user’s desktop.
“Greg did a phenomenal job of translating our ideas into extremely user-friendly and transparent tools that surpassed all of our expectations,” Meyers said.
Meyers and her team recently received four grants from the state to extend the toolkit.
Such data-driven science is a big deal these days. The U.S. government recently committed hundreds of millions of dollars toward enabling new applications that can harness data streams effectively. The Texas Pandemic Flu Toolkit shows how this new paradigm will affect public health decision-making. For now, it remains one of the few pandemic-fighting tools available to public health officials.
Said Meyers: “We’ve just scratched the surface in terms of developing quantitative tools that improve our ability to track and control infectious disease outbreaks.”