The challenge was to analyze environmental and geographic data in order to understand what happens in the environment in the face of pandemics. The solution fits due to obtaining data such as population density and CO2, and seeking the generation of predictive model to estimate the chances of new pandemical and/or epidemiological outbreaks.
Data mining has enabled the generation of new insights for a quick response to future pandemics.That’s why it is one of the motivations for the challenge. In the chosen approach we have developed a platform to generate insights regarding the connection between environmental care and disease to predict future pandemics and/or epidemics. To estimate these values we used data from “SEDAC - NASA” to search demographic information and “Earth Observatory”, to capture geographic data. During the project development, Photoshop and Miro were used to prototype the idea and build the platform interface. The main problems were on finding official documentation to export the data and perform integration with systems using programming languages.
Photoshop, Miro, Google Docs, Discord, Sony Vegas;
https://sedac.ciesin.columbia.edu/mapping/popest/covid-19/
https://earthobservatory.nasa.gov/images/89117/satellite-detects-human-contribution-to-atmospheric-co2