How did COVID-19 affect the financial markets of the world’s leading economies? How did restrictions to stop the spread of the disease change the way people traveled earlier this year? And, is there any correlation between a population’s dietary habits and how each country managed to control the outbreak?

These are some of the questions that students who participated in a virtual hackathon hosted by Northeastern’s Seattle campus sought to explore this summer. Grouped into teams, graduate students from the Seattle, San Francisco Bay Area, and Vancouver campuses in fields such as data analytics, engineering, and project management pooled their talents and skills to create interactive dashboards, chatbots, and visualizations. 

Led by Patrick Chidsey, the associate director of career services and experiential learning at the Seattle campus, the hackathon culminated in a final showcase held via Zoom last month that allowed each team an opportunity to present their months-long work and address questions from an audience of their peers and the public.

“This is a difficult and complicated topic for so many different reasons and it hits us personally in a lot of different ways,” Chidsey remarked. “I know we’re looking at data and graphs and fancy dashboards today, but we all know there’s the human element behind all this information, so I appreciated a lot of the teams calling that out.”

The top prize was awarded to Dong Quoc Tuong, Sreelakshmi Sneha Mulukutla, Krishna Prakash Sankaramanchi, and Charita Madduri for developing a chatbot tool to answer questions related to COVID-19. Designed to respond to users in 23 different languages and pulling the latest data from Johns Hopkins University, they demonstrated that their chatbot can screen for symptoms and spit out information about the pandemic in real-time, as well as information about local testing sites. The chatbot can be integrated into websites and social platforms, the team said.

Finishing runner-up was a team that sought to understand how different modes of transportation, as well as travel and commuting patterns, were affected by the pandemic over time. For their project, team members Sukanya Aswini Dutta, Chen Liang, Nickyta Manishkumar Patel, Rohith Reddy Narra, and Tiezhou Duan built a website that serves as a prediction tool for analyzing airline travel and ridership trends in metropolitan areas such as New York City.

They found that ridership fell in the Big Apple and that most airlines recorded significant drops in air travel and fuel consumption in April. The team also determined that while cars were the safest way to travel, rideshares and taxis posed the highest risk, as did subways, buses, and other modes of public transportation. Visible safety measures, such as physical distancing, face masks, and touchless payment systems helped make passengers feel safer, the team said. 

Another team developed a dashboard that analyzed the fiscal impact of COVID-19 on the financial markets of the world’s richest countries, and took into consideration factors such as the availability of hospital beds and free COVID-19 tests. The dashboard also compared the countries’ gross domestic product, their health budget, and how much they spent combating the viral outbreak.

“It’s not just the amount of money countries are diverting to the crisis but the timeline affects the recovery metric,” said Arjun Malhotra.

A correlation between food patterns and global recovery rates was the subject of investigation for another team. The members created a website to analyze the widespread impact of the public health crisis and then separately looked at dietary habits.

Something to consider, suggested Prachi Mate, a member of the team, is that one of the reasons why the United States has been hit the hardest by COVID-19 could be because of the nation’s dietary choices. But, she reminded, while this might be a contributing factor, it’s not the sole factor.

Another team built a tool for looking at the relationship between COVID-19 related hashtags on Twitter and the prevalence of cases around the U.S. In order to do this, the team had to first request access to data from the social media company, then they used interactive data visualization software to analyze it. 

One member of the team, Robert Zipp, said that they wanted to know whether the topics people were tweeting about might be directly affecting the rate of COVID-19 cases and deaths. He said that eventually the tool he and his team built has the potential to reveal which hashtags are fueling real-life trends and patterns.

“I really do want to know if misinformation makes health outcomes worse or if there isn’t that much of a relationship,” he said.

In a similar vein, another team analyzed YouTube comments to gain insight into the conversations happening online around the pandemic. Gaining access to data from YouTube for their project, the team members created a word cloud generator based on the words most frequently used by users. ‘Vaccine,’ for example, started popping up in May, the team found.

Team member Jingyan Qiao made an astute observation. Despite the devastation caused by the COVID-19 crisis, she said, the word cloud was replete with positive words.

“We believe people still live with hope and love, and treat others with care and a grateful heart,” she said.

Qiao was one of 25 students who participated in the hackathon. The six teams began working on their projects in mid-June based on available data. Along the way, Chidsey said, students enrolled in an experiential-learning course through Blackboard and tracked their insights through Northeastern’s Self-Authored Integrated Learning platform.

Judging was conducted by a panel that included faculty members from the Khoury College of Computer Sciences and researchers from the Fred Hutchinson Cancer Research Center and Pacific Northwest National Laboratory, along with developers from Mapbox, a mapping platform for websites and applications.  

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