Meet the Participants for the Hackathon
January 25-30, 2021 Students from the University of California, Irvine Paul
Merage School of Business took on the COVID-19 Hackathon Challenge.

Meet the participants in the COVID-19 Hackathon competition!
Meet the Winners
Team 10 - Project Vax-The-Nation
Team Members: Harshal Vaza, Swathi Mudhelli, Mira Daya, Xueting (Lexi) Li

1st Place Best Modeling
$10,000 in Amazon Activate Credits

We found that there are 156,836 vaccines that have gone to waste. This is months of research, billions of dollars, and the potential for an individual immunity being thrown away. Because it is so important for vaccines to be administered at the right time and temperature, every vaccine must be administered in a timely manner. It is important that they reach people and that they are willing to take it.

Goal: To identify individuals based on demographic information, centrality, and distance to an available vaccine through an automatic alert system.

Our hackathon project was to help fight COVID-19 with social network theory. Our assumptions is that the R0 or reproduction number is above 1 and vaccination efforts aim to bring it below 1. The problem is that we must optimize and maximize vaccine readiness (willingness). This is important because the vaccine is limited in supply, high in holding cost, and very time sensitive. Our proposed solution is to identify individuals willing to get vaccinated, develop alert system to notify select individuals of vaccine availability, and maximize/optimize vaccine delivery to as many people as possible
Other Teams
Here are the other teams that participated:
Team 8
Project Wellness
2nd Place Best Idea / Innovation
$3,000 in Google Cloud Credits

Marianna Carini
Abishek Karimpuzha Devarajan
Azaan Barlas

Team 6
Ready Now
3rd Place Best Visualization
$2,000 in Bubble Credits / $1,000 in Miro credits

Dylan Nguyen
Caesar Phan
Ping-Chun Liu
Edward Shih-Yu Chung
Kabeer Bahl

Team 9
Health Alert
Chia-Jo Chen
Mariella Dela Cruz
Smitha Kannanaikkal
Team 7
Sentiment Analysis and Prediction
Pei Liu
Yang Sheng
Bowen Yang
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