XploData are the DengueHack.org’s Hackathon prize winner for Best Storytelling. You can view their presentation from the event here.
Our goal at the DengueHack.org hackathon, was to determine the main factors or variables (climate, population, livestock, vegetation…) that influence both Aedes mosquitos and the Dengue virus. We approached this by building two models, one that would be able to take climate and population data to predict mosquito presence in parts of the world where this data is lacking, and the second model would integrate this new data with climate and population data to predict Dengue outbreaks.
In the process of the hackathon, we faced several problems in creating these models, however, we turned our focus to a different second model. Data on Dengue world-wide is inconsistent: we have reports of countries with Dengue, countries where we can confidently say Dengue is not present, and countries where Dengue may or may not be present. By looking at environmental variables that explain the presence or lack thereof of Dengue, we were able to create a model that could estimate the chance of Dengue being present in the countries where Dengue remains unconfirmed.
The problem we faced in building our first model was that the available data for the mosquitoes was only ‘presence’ data, and lacking real absence data. We therefore added an artificial temperature threshold in this model, to create so-called ‘pseudo-absence’ data of mosquitoes. Of course, this resulted in a model that lacked the sophistication we had hoped for. The future is promising although. For instance, satellites and satellite imaging are constantly improving. With improved imaging technology, we could gather more precise data on vegetation, livestock movement and population movements. Bringing this data together in one table with as many points on earth as possible with climate data, population data, livestock data, vegetation data, the amount of standing water, mosquito data, and Dengue data would greatly improve our predictions on Dengue. After all, the impact of being able to predict presence of Dengue cannot be overstated.
To conclude, we want to thank the organizers for giving us the opportunity to join the Hackathon, discover new technologies and meet interesting people. Also special thanks to the members of TeraData who greatly helped us during our preparations and final building of the models.
 Our team consisted of members of XploData, i4BI, Janssen Pharma and University of Liege, and are scientists, engineers, physicists, and informatics-specialists. We worked multidisciplinary, combining various skills such as data engineering, data science, data modelling and data visualization. Work hard, play hard (Figure 1).
Figure 1: Hacking is fun!