Computer Science COVID-19 Data Presented at Anthropology Conference

April 9, 2021

Photo of Gil Gallegos

Gil Gallegos

Las Vegas, N.M. – New Mexico Highlands University faculty and students presented their findings on using artificial intelligence and machine learning to model the spread of COVID-19 on the Navajo Nation at the Society for Applied Anthropology Annual Conference in March.

The ongoing research project was featured in the prestigious Anthony Paredes Plenary Session at the international conference, which highlights and explores issues in contemporary Native American research.

“Our major finding to date is that the fact that the Navajo Nation was very proactive in enforcing strict quarantines and other safety policies on the reservation helped drive the curve down on the spread of the coronavirus,” said Gil Gallegos, a Highlands computer science professor and lead researcher. “There’s a direct correlation between following policy and saving lives.”

Gallegos said another important finding was that the language barrier on the Navajo Nation led to misconceptions about the seriousness of the coronavirus.

“This language barrier led some Navajo people to believe COVID-19 was more like the flu or a bad cold, which influenced some people to not adhere as closely to some of the safety measures like social distancing, mask wearing and frequent hand washing,” Gallegos said.

In May 2020, the National Science Foundation awarded Highlands a “rapid response” $187,094 grant to study COVID-19 cases on the Navajo Nation using machine learning and artificial intelligence.

“Machine learning is using computer algorithms for calculations used to analyze, predict and classify complex data sets, such as those found in COVID-19 data. Artificial intelligence, sometimes called deep learning, gave us more horsepower to really dig into the data,”  Gallegos said.

Gallegos, who chairs the Computer and Mathematical Sciences Department at Highlands, led the team of researchers at the university that delved into the public COVID-19 data from the Navajo Nation and the New Mexico Department of Health. Other faculty team members include Orit Tamir, anthropology professor, and Tatiana Timofeeva, chemistry professor.

In addition, five Highlands computer science graduate students participated in the research including Fernando Sarracino, who is a member of the Navajo Nation, Viktor Glebov, Jesse Ibarra, Svetlana Ryabova and Christopher Torres. Manuel Steele from St. Mary’s College was also part of the student team.

“My students are self-starters who did a fantastic job of developing mathematical computer models for virus spread and combined them with machine learning algorithms, which are step by step workflows to solve a problem. The professors on the project gave the students guidance and they rose to the occasion. I’m very proud of what the students accomplished,” Gallegos said.

The students presented a PowerPoint depiction of their computer models at the anthropology conference.

Tamir worked on correspondence and communication with the Navajo Nation and Navajo friends with whom she has developed close ties through her cultural anthropology research for more than three decades.

Tamir said that many factors contributed to the initial rapid spread of COVID-19 on the Navajo Nation, such as multigenerational Navajo households and infrastructure problems.

“Shocking infrastructure woes on the Navajo Nation contributed to the horrific spread of COVID-19 early on,” Tamir said. “For instance, depending on the season, 30% to 40% of Navajo homes do not have running water or indoor plumbing. This made following CDC and Navajo Nation guidance regarding hand washing very challenging,” Tamir said.

Tamir said she was in touch through phone calls and via texts with members of the extended Navajo family she lived with for almost three years while doing ethnographic anthropology fieldwork a number of years ago.

“Their daily descriptions of people getting sick, and the struggles to get food, soap, diapers and so on, were very worrisome. They also texted about exhausted staff in reservation hospitals, and about mobilizing relatives to make hospital gowns and face masks that reservation hospital staff desperately needed,” Tamir said.