The COVID Computational Challenge seeks to create an innovative solution to determine the risk of exposure to COVID-19 in locations in and around the City of Los Angeles. This two-week challenge will provide ideas and concepts to help deepen our understanding of the issues that may increase or decrease COVID-19 exposure risks, how to calculate these risks, while being respectful of data privacy. Projects will be reviewed by a panel of judges from the City of LA, LA County Department of Public Health, Chamber of Commerce, and academia.
In the next two weeks you will determine the risk of exposure to COVID-19 in locations in and around the City of Los Angeles.
- Features that may increase or decrease COVID-19 exposure risks
- Assist with the transition to re-open by predicting location-based risk scores
- Proposed methodology to implement risk score assessment
- Actionable steps for risk mitigation and to improve risk score
Participants are highly encouraged to use the open data resources highlighted below. If proprietary data is used, it must be documented for our judges to understand and reproduce your work. The datasets below contain both static and time varying spatial-temporal features related to COVID-19, documentation included on site.
Open Data Portals:
To get started, you can begin with these datasets. View Dataset
Free training on epidemiology, spatial analytics, data science, and more:
- Analytical Workflow Guidebook
- Intro to epidemiology
- Data Science Fundamentals
- Ethics and Bias in AI Systems
- Big Data Applications in COVID-19
- Intro to Mobility Data in COVID-19
- Webinar Series Data Science and COVID-19
- Risk forecasting for UK
- Detecting Suspected Epidemic Cases Using Trajectory Big Data
- Zip your documents together and upload the zip file. Naming convention should be COVIDchallenge_yourTeamName.zip
1. Source code required
2. README file explaining how to run your codes. If you use Java or C++, please also include the commands you use to compile your code (we should be able to compile, and if necessary, run your code and see the output files generated)
3. Technical Report in PDF with names of all team members and team name required
- Your report should include the following sections: Introduction, Data, Methodology, Result, Implementation Proposal, Risk Mitigation Recommendations, Acknowledgement, and Reference. Please refer to the Problem Statement to check that your solution answers the prompt.
4. CSV of your results with the location and location-base risk score
- Optional is presentation and demo recording