Filipino team’s winning app in NASA challenge aims to predict dengue hot spots | ABS-CBN

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Filipino team’s winning app in NASA challenge aims to predict dengue hot spots
Filipino team’s winning app in NASA challenge aims to predict dengue hot spots
Kristine Sabillo,
ABS-CBN News
Published Mar 05, 2020 11:00 AM PHT
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Updated Mar 05, 2020 01:09 PM PHT

Massive day today. We started with Animo Labs, and ended with FuturePerfect. Data. Insight. Action. Thank you @dostpcieerd @AnimoLabs @SpaceAppsPHIL pic.twitter.com/8YGMDjBDLu
— Dominic Ligot (@docligot) March 4, 2020
Massive day today. We started with Animo Labs, and ended with FuturePerfect. Data. Insight. Action. Thank you @dostpcieerd @AnimoLabs @SpaceAppsPHIL pic.twitter.com/8YGMDjBDLu
— Dominic Ligot (@docligot) March 4, 2020
MANILA - A group of Filipino data scientists are hoping to get enough support to finance an app that can predict the rise of dengue cases in certain parts of the Philippines.
MANILA - A group of Filipino data scientists are hoping to get enough support to finance an app that can predict the rise of dengue cases in certain parts of the Philippines.
Team AEDES, led by data entrepreneur Dominic Ligot, won the NASA Space Apps Challenge’s Best Use of Data category last January.
Team AEDES, led by data entrepreneur Dominic Ligot, won the NASA Space Apps Challenge’s Best Use of Data category last January.
The app, which zeroes in on stagnant water and other dengue-related factors, was cited for being “the solution that best makes space data accessible, or leverages it to a unique application.”
The app, which zeroes in on stagnant water and other dengue-related factors, was cited for being “the solution that best makes space data accessible, or leverages it to a unique application.”
Team AEDES got its name from the Aedes aegypti mosquito, which is the carrier of the dengue virus. It is also an acronym for Advanced Early Dengue Prediction and Exploration Service (AEDES).
Team AEDES got its name from the Aedes aegypti mosquito, which is the carrier of the dengue virus. It is also an acronym for Advanced Early Dengue Prediction and Exploration Service (AEDES).
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The app uses 3 data sets: imaging data from the satellites Sentinel-2 Copernicus and Landsat, climate data from the Philippine Atmospheric, Geophysical and Astronomical Service Administration (Pagasa) and digital data from Google search trends for dengue and other related terms.
The app uses 3 data sets: imaging data from the satellites Sentinel-2 Copernicus and Landsat, climate data from the Philippine Atmospheric, Geophysical and Astronomical Service Administration (Pagasa) and digital data from Google search trends for dengue and other related terms.
“We were trying to find a way to quicken the response time for dengue (outbreaks),” Ligot, an owner of a data analytics consulting firm, told ABS-CBN News in a phone interview.
“We were trying to find a way to quicken the response time for dengue (outbreaks),” Ligot, an owner of a data analytics consulting firm, told ABS-CBN News in a phone interview.
He said he started working on it with fellow freelancers who are also data analysts or engineers. Among the core member of the team are Claire Tayco who worked on statistical models, Jansen Lopez on geospatial models and Mark Toledo, a data engineer.
He said he started working on it with fellow freelancers who are also data analysts or engineers. Among the core member of the team are Claire Tayco who worked on statistical models, Jansen Lopez on geospatial models and Mark Toledo, a data engineer.
“We thought, ’Is there a way we can get ahead of the reports and predict where dengue will strike?’” Ligot said.
“We thought, ’Is there a way we can get ahead of the reports and predict where dengue will strike?’” Ligot said.
That’s when they thought of correlating dengue reports to other real-time data.
That’s when they thought of correlating dengue reports to other real-time data.
Ligot said they got data from the public domain and the United States’ National Aeronautics and Space Administration (NASA).
Ligot said they got data from the public domain and the United States’ National Aeronautics and Space Administration (NASA).
“They have a lot of free data from satellites. Satellites orbiting the earth. They get spectral data, light reflecting from the ground,” he explained.
“They have a lot of free data from satellites. Satellites orbiting the earth. They get spectral data, light reflecting from the ground,” he explained.
They used those data to see which areas have stagnant water, which is a factor in the proliferation of mosquito's, which carry the disease.
They used those data to see which areas have stagnant water, which is a factor in the proliferation of mosquito's, which carry the disease.
Ligot said they decided to put all of the data in a simple application to “make it painless” and allow even the public to use it.
Ligot said they decided to put all of the data in a simple application to “make it painless” and allow even the public to use it.
He said public health practitioners and local government officials who use it can determine where mosquitoes will be.
He said public health practitioners and local government officials who use it can determine where mosquitoes will be.
“You can start fumigating the area,” he pointed out.
“You can start fumigating the area,” he pointed out.
Ligot said the team eventually noticed a pattern in the dengue spikes, which would help further improve the app’s predictions.
Ligot said the team eventually noticed a pattern in the dengue spikes, which would help further improve the app’s predictions.
The Aedes project website shows predicted mosquito hotspots, dengue data and trends.
The Aedes project website shows predicted mosquito hotspots, dengue data and trends.
He said the app can be used to predict other mosquito-born diseases and can be thought of as something as useful as flood mapping.
He said the app can be used to predict other mosquito-born diseases and can be thought of as something as useful as flood mapping.
The next step for the team is to get funding and support from NASA and to partner with a local government that can help validate their data in real-time.
The next step for the team is to get funding and support from NASA and to partner with a local government that can help validate their data in real-time.
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