Blue Banana| Human Factors

Human Factors

The emergence and spread of infectious diseases, like COVID-19, are on the rise. Can you identify patterns between population density and COVID-19 cases and identify factors that could help predict hotspots of disease spread?

ACES - Automated Coronavirus Exploration Software

Summary

Our project, ACES (Automated Coronavirus Exploration Software) is built to offer predictive capabilities for researchers and policymakers in the midst of the COVID19 epidemic by using trend correlation from Google search data. We using Machine Learning methods and leverage the amount of data generated by global use of the Google search engine. Our main goal and hope is that we can provide a useful tool for governments and medical institutions to rapidly test hypotheses and deploy solutions.

How We Addressed This Challenge

Our solution is based on statistical tests, as well as the measure of data trends in the from of time-series. We measure statistical correlations between different COVID statistics and Google search trends to provide useful insights. The central idea of our challenge is the use of data to understand the COVID pandemic, our solution does just that. We leverage crowd sourcing and to generate and crunch that data, thus, providing a self sustaining system.

How We Developed This Project

We decided to go for this approach due to the centralized source of data from Google Trends, so we can have a sense of the world's interest on a keyword with the least trouble. We coded a web app to display that information on a friendly way. Our app is built on python flask (for the backend and API), and Javascript react for the display of the charts and webpage design.

This Hackathon proved to be a challenging experience, as we had to learn various features of the programming languages mencioned above in limited time. Overall, it has been a huge success and learning experience for us.

Project Demo

https://youtu.be/X7j4fqOae_0

Project Code
Data & Resources

Google Trends Data

Census Bureau Data for COVID-19, American Community Survey

https://sedac.ciesin.columbia.edu/mapping/popest/covid-19/

https://earthdata.nasa.gov/learn/pathfinders/covid-19

https://github.com/microsoft/Bing-COVID-19-Data/raw/master/data/Bing-COVID19-Data.csv


Tags
#data #prediction #trends #covid
Global Judging
This project was submitted for consideration during the Space Apps Global Judging process.