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COVID-19 Data Challenge Sponsored by West Big Data Innovation Hub & Border Solutions Alliance

While researchers race to develop a COVID-19 vaccine, communities along the U.S.-Mexico border have been hard hit by the pandemic. The West Big Data Innovation Hub recently collaborated with the Border Solutions Alliance to conduct a COVID-19 Data Challenge. Three dozen faculty members and community partners supported the effort, holding office hours, giving lightning talks, and judging the pitch competition. A total of 33 teams composed of students, researchers, and community members from across the U.S. and Mexico participated in four categories: 1) School and Work, 2) Retail and Leisure, 3) Cross-Border, and 4) High School students-only. During the data challenge, teams worked on projects that leveraged data to better understand risk levels in real-time for different situations and communicated them to the public. Over $5,000 in prizes and stipends were awarded to teams.

“Team matching events encouraged diverse team composition,” said event organizer Melissa Floca, who led the effort for the Border Solutions Alliance at UC San Diego. “For example, Mexico-based students partnered with individuals in the private sector in San Diego to work on a project to support response to the twin disasters of fires and COVID-19 and high school students from Tijuana and San Diego came together to use data storytelling and social media to inform Spanish-speaking households on the importance of young people taking precautions to protect older people in multigenerational homes.”

This COVID-19 Risk Calculator asks a series of questions, including occupational information, and then assesses risk for contracting the virus. Developed by UC San Diego students, the project won second place in the Cross-Border section of the COVID-19 Data Challenge.

A quarter of participants were in high school, a third of participants were based in Mexico, and 45 percent of participants were women. Teams addressed a wide variety of topics including using the pandemic as an opportunity to build data literacy in marginalized communities, supporting small shopkeepers, and improving data gathering on COVID-19 in migrant shelters.

Video clips of winning projects are available here.

“Against a backdrop of difficult pandemic news, suffering, and staggering statistics, the data challenge experience itself was a delight and gives me great hope for the future,” said Christine Kirkpatrick, Co-Principal Investigator and Deputy Director of the West Hub. “We had a huge number of high school students from across the U.S. and Mexico, undergraduates and graduate students, medical residents and doctors, epidemiologists, and data scientists. In the West Hub, we focus on the incredible data work happening in the Western U.S., but this challenge brought us in touch with the powerhouse capabilities of data scientists across Mexico, as well as Mexico’s wealth of open data. Teams came up with several thoughtful approaches to improve decision making and to facilitate safety as well as quality of life – often inspired by challenges they’d encountered themselves. They approached the research problems with the utmost ethics, employed creative approaches to assess risk, and produced a tremendous set of new resources for our region.”

In addition to organizing the COVID-19 data challenge with the Border Solutions Alliance, earlier this year, the West Hub co-sponsored the MIT COVID-19 Datathon with partners including the American Civil Liberties Union, COVID-19 Policy Alliance, and USA FACTS, building upon relationships from the 2020 Women in Data Science (WiDS) Datathon focused on intensive care unit health data. Connecting researchers and the broader public through efforts such as the Virus Outbreak Data Network with GO FAIR, CO DATA, and RDA, the COVID Information Commons hosted by the regional Big Data Hubs, and the emerging networks contributing to Rapid Response Data Science and resilience continues to be a priority.

About the Organizers:

Border Solutions Alliance: The Border Solutions Alliance is a partnership that includes research universities from the four U.S. states at the border with Mexico. The coordinating institutions – UC San Diego, the University of Arizona, New Mexico State University, the University of Texas at El Paso, and the University of Texas at San Antonio – have ongoing research projects with Mexican universities and frequently collaborate with community, government, and industry partners. The Alliance works to create a backbone for research grounded in robust public and private sector partnerships by:

● Fostering collaboration between universities and the public and private sectors to contribute to regional sustainability, health and well-being, and productivity

● Bringing together the best and brightest researchers from the four states that border Mexico, with Mexican counterparts, to engage in public impact research focused on use-inspired research questions grounded in the daily challenges faced by service providers, practitioners, and policy makers

● Focusing on data-driven research in science, medicine, and engineering, as well as data science-focused education and workforce development

About West Big Data Innovation Hub: The West Big Data Innovation Hub is one of four regional hubs funded by the National Science Foundation (NSF) to build and strengthen strategic partnerships across industry, academia, nonprofits, and government. The West Hub community aims to catalyze and scale data science for societal needs – connecting research, education, and practice in thematic areas such as natural resources and hazards, metro data science, health, and data-enabled discovery and learning. Coordinated by UC Berkeley’s Division of Computing, Data Science, and Society, the San Diego Supercomputer Center, and the University of Washington, the West Hub region includes contributors and data enthusiasts from Alaska, Arizona, California, Colorado, Hawaii, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, Wyoming, and a global network of partners.

The organizers are supported by the National Science Foundation through awards 1550312, 1550224, 1550328, 1833482, 1916481, 1916573, and 1915774.


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