Back to the Future: Using Historical Dengue Data to Predict the Next Epidemic
What would you do if you could see the future? What would change? If you asked CDC biologist Michael Johansson, he would tell you he’d like to know what kind of summer it’s going to be in Puerto Rico – how bad will this year’s dengue season be?
Dengue is a mosquito-transmitted viral disease affecting millions of people every year, including U.S. travelers and residents of the tropical regions of the U.S. like Puerto Rico. Experts estimate that around 390 million dengue infections occur worldwide each year, including about 500,000 severe cases – mostly children -- requiring hospitalization. Case counts are climbing as the disease moves into new areas. Dengue is now endemic in more than 100 countries and several U.S. territories. In endemic areas, major epidemics occur roughly every 3-5 years overwhelming medical services, so anticipating epidemics has the potential to save lives. The risk to U.S. travelers is on the rise, and in recent years, local dengue outbreaks have struck the continental United States where the Aedes vector mosquitoes are endemic.
Accurate dengue predictions would help public health workers, like Johansson, and people around the world take steps to reduce the impact of these epidemics. But predicting dengue is a hefty task that calls for the consolidation of different data sets on disease incidence, weather, and the environment.
Several departments in the U.S. Federal Government (Department of Health and Human Services, Department of Defense, and Department of Commerce) have joined together, with the support of the National Science and Technology Council (NSTC), to design an infectious disease forecasting project with the aim of galvanizing efforts to predict local epidemics of dengue.
This project launches on June 5, 2015, when the U.S. Government will provide access to datasets for developing forecast models to anyone/team interested in participating. Participants will have access to new data, a chance to test their modeling capabilities, and an opportunity to improve public health.
After the data are released, participants will have two months to develop forecasting models given the datasets and forecasting targets tied to public health decisions. More information about forecasts format, requirements, and evaluation criteria will be provided at http://DengueForecasting.NOAA.gov.
Individuals or teams must submit preliminary forecasts in early August and final forecasts by early September. Representatives from the organizing U.S. Departments will evaluate the submissions based on the established evaluation criteria. Subsequently, the NSTC Pandemic Prediction and Forecasting Science and Technology (PPFST) Working Group will convene a meeting in Washington, D.C. with project participants to review lessons learned and potential next steps in strengthening infectious disease forecasting.
For more information about how to become involved, please contact Predict@CDC.Gov, and see the following website http://DengueForecasting.NOAA.gov.
Background on the Predict the Next Pandemic (PtNP) Initiative
In 2013, President Obama’s Science and Technology Advisor Dr. John Holdren stood in support of the Data to Knowledge to Action event, where different U.S. Government agencies encouraged increased collaboration towards data-intensive discoveries. The goal was to spur scientists to come together and share their data to create new and interesting advancements.
In honor of this goal, Dr. Holdren launched the Predict the Next Pandemic (PtNP) Initiative, which aims to develop predictive capabilities from the data-sharing project. It was designed to anticipate disease emergence, identify early indications of disease emergence, to determine the pandemic potential of a disease, and forecast impacts and effects of mitigation on disease progression. The NSTC established the PPFST to achieve these goals.
To date, the PPFST Working Group has focused on projecting the likely progression of infectious disease outbreaks. With all of the great work the program is spurring, the PPFST realized there was a new way for the academic community, and possibly the public generally, to get involved in big data for infectious disease forecasting.
Dylan George is Senior Policy Advisor for Biological Threat Defense at the White House Office of Science and Technology Policy.
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