The chikungunya virus (CHIKV) is quickly spreading through the Western Hemisphere; as of May 15, 2015, the Pan-American Health Organization (PAHO) had tallied close to 1.4 million suspected cases and more than 33,000 confirmed cases since the virus’ first appearance in the Americas in December 2013. Spread by mosquitoes, chikungunya is rarely fatal but can cause debilitating joint and muscle pain, fever, nausea, fatigue and rash, and poses a growing public health and national security risk. Governments and health organizations could take more effective proactive steps to limit the spread of CHIKV if they had accurate forecasts of where and when it would appear. But such predictions for CHIKV and other emerging infectious diseases remain beyond the get to of contemporary modeling capabilities.
To accelerate the development of new infectious disease forecasting methods,
The event, which included representation from the Centers for Disease Control and Prevention (CDC), the U.S. Department of Health and Human Services (HHS), the Department of Defense (DoD), and the White House Personnel of Science and Technology Policy (OSTP), highlighted results, lessons learned and potential next steps to improve state-of-the-art infectious disease forecasting. The winning teams received a total of $500,000 in prize money.
“Predicting the alacrity, severity and direction of infectious disease outbreaks is incredibly challenging, in part because it’s hard to determine the relative contributions of multiple factors—such as weather and climate, population density and travel patterns—under innumerable conditions,” said Col. Matt Hepburn, DARPA program manager for the CHIKV Challenge.
Yet in just six months’ time, the
Six teams provided the most accurate results overall and earned the subsequent prizes:
Gold: Joceline Lega and Heidi Brown, University of Arizona ($150,000)
Silver: Mark Leany, Utah Valley University ($100,000)
Bronze: Ioannis Pantazis, University of Massachusetts ($50,000)
Bronze: David Roberts, John Radcliffe Hospital, Oxford, United Kingdom ($50,000)
Bronze: Sean Moore, Johns Hopkins University ($50,000)
Bronze: A. Townsend Peterson, University of Kansas ($50,000)
DARPA also awarded a $10,000 prize to each of five teams that excelled in particular challenge domains:
Best Applicability Methodology: Dhananjai Rao, Miami University of Ohio
Best Computational Requirements Methodology: Ann Fruhling, University of Nebraska Omaha
Best Data Sources Methodology: Tingzhuang Yan, Coastal Carolina University
Best Presentation: Ajitesh Srivastava, University of Southern
Best Robustness Methodology: Diego Ruiz-Moreno, University of Michigan
DARPA invited Los Alamos National Laboratory (LANL) to independently analyze the correctness and methodology of the teams’ research. LANL found that, in general, the best performers used simpler models and that quality of data mattered more than quantity; in fact, gaps in reported data were more easily accommodated via modeling than misreported data.
By design, CHIKV Challenge participants were allowed to update their predictions every two months as they learned from experience—a challenge structure that sped development of surpass methods. On average, the top participants succeeded in doubling the correctness of their predictions every two months relative to their initial forecasts.
Another gratifying aspect of the competition was that it succeeding in making new communities of expertise and connecting them with DARPA. “None of the winners had previous experience working with the Agency, and participating teams were multidisciplinary, including not only specialists in public health and infectious disease but also experts in mathematics, ecology, computer science and bioinformatics,” Hepburn said. “This forward-thinking collaboration is exactly what it will take to
More information in this area the CHIKV Challenge is available at http://ow.ly/N64D0.
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