Overall Winner of the DengueHack Hackathon: DatAsset

Dengue, the most important arbovirus (arthropod borne virus, viruses such as yellow fever and Zika) is spreading rapidly, and half of the world’s population is at risk of contracting it.

In the last half of a century, the number of people affected by dengue has increased 30-fold (say whaat!?), and it threatens to invade Europe and the United States.

We were happy to stumble upon the DengueHack.org project, so we gathered together an AI kid, a monsieur docteur, and a happy bunch of data wizards to stop this ominous prospect by hacking the heck out of Dengue. In data we trust! Together, as data scientists, we embarked upon this epic 36-hour journey.

Ideas for approaching this project were manifold, and we wanted to really use our team’s diverse set of skills. Eventually, we settled on three goals to work toward: building a predictive incidence model for Sri-Lanka, one of the more heavily impacted countries by Dengue in South-Asia, building a cool visual representation of past and predicted data, and exploring the possibilities of our approach from a public health perspective.

For our model, we experimented with included important national socio-economic and environmental data, with the goal of ultimately applying it to different countries as a next step.

Why building a predictive model is so important: If an outbreak is predicted in a late stage, intervention measures are decreasingly effective. If an epidemic can be detected earlier or even predicted before occurring, the number of cases avoided increases (as can be seen in the image below).

The value of outbreak prediction

Who needs sleep? Even during the few hours of rest we had, our models were running in our brains. With concerted effort, at the end of the thirty-six hours, we’ve arrive at a nice final presentation for you to enjoy. Feedback is most welcome!

Thanks so much to the organizers for this wonderful event, you’ve made us realize that there’s so much common ground and cause between the worlds of data science and public health. Data for good has a bright future!


The DatAsset team, Klaas Michael Pieter Andreas Joren

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