Predict future pandemic trends

Predict future pandemic trends

November 18, 2022

Since 2020, the coronavirus has infected more than 627 million people and killed more than 6.5 million, according to the World Health Organization. COVID-19 has put a strain on almost every country in the world, fundamentally altering their economies and healthcare systems around the world.

A study published in the Proceedings of the National Academy of Sciences that analyzed data from pandemics dating back to 1600 reports that future pandemics caused by diseases like the coronavirus are expected to occur more frequently. The study estimates that the annual probability of serious epidemics could increase by 300% in the coming decades.
Close-up view of a coronavirus particle on a black background.
Machine learning expert Professor Pavan Turaga leads an interdisciplinary research team studying the use of machine learning to reduce the societal impacts of future pandemics. Photo courtesy Unsplash
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With the growing threat looming, a team of 17 researchers from Arizona State University is looking to minimize the impact of these future pandemics through the power of machine learning.

Led by machine learning expert Pavan Turaga, director of the School of Arts, Media and Engineering at the Herberger Institute for Design and the Arts and professor in the School of Electrical, Computer and energy, which is part of the Ira A. Fulton Schools of Engineering at ASU, the team brings together experts in computer science, biology, and social sciences to develop modeling tools that can adapt to predict the spread of new and existing pathogens to inform legislative and health responses to pandemics.

The team was awarded one of 26 grants from the National Science Foundation’s (NSF) Predictive Intelligence for Pandemic Prevention program to advance their project.

Turaga says current mathematical models used to predict the spread of pathogens are based on designs from decades ago that don’t account for nuances such as socioeconomic conditions and climatic factors like extreme heat. These factors are also known as compound effects.

“We still don’t have a reliable model that can reliably predict any pandemic spread,” Turaga says. “The grant is not intended to develop another narrow model, but rather to perform an ‘analysis’ of factors that are not currently considered and new techniques that can be used versus those that have been used before. .”

Collaborating to defeat pandemics through research

Initially, the researchers included teams working on projects funded by three different grants to study and model the spread of the coronavirus under the NSF Rapid Response Grants research program in 2020. The research teams remained connected with each other, discovered Predictive Intelligence Pandemic Prevention and came together under the new 18-month research grant as one large, interdisciplinary team, led by Turaga and four co-principal investigators.

Gautam Dasarathy, an assistant professor of electrical engineering, is a co-principal investigator leading machine learning efforts for modeling pandemic spread.

“I am extremely honored and thrilled to be part of this research,” Dasarathy said. “It brings together a truly diverse team of researchers with expertise ranging from virology, sequencing and wastewater analysis to data science, controls and cryptography, to name a few. “

Another Co-Principal Investigator, Patricia Solis, Executive Director of Knowledge Exchange for Resilience in ASU’s School of Geographic Sciences and Urban Planning, leads a team examining how behavioral and socio-economic factors human economics affect the patterns of pandemic spread. Solis’ goal is to connect with community leaders making pandemic response decisions and determine what criteria were considered for both the pandemic phase of COVID-19 and the phase during from which the world learns to live with disease.

“What kinds of data, models, information, and insights are being used, and what else is needed for better decision-making?” Solis asks. “We aim to bring that back into conversations with our ASU scientists about how to design better models that are not only robust, but also truly serve public interest research, consistent with our ASU charter.”

Giulia Pedrielli, another co-principal investigator and associate professor of computer science and industrial engineering in the School of Computing and Augmented Intelligence, part of the Fulton Schools, lends her expertise in detecting mobile activity while respecting user privacy to determine how best to allocate pandemic response resources.

Pedrielli believes that researchers’ consideration of additional factors to inform pandemic response decisions will lead to better outcomes for society.

“We hope that including behavior in testing and resource allocation decisions will make resource distribution more equitable, taking into account multiple and diverse aspects of the effect of policies not only on the mechanisms of propagation of the pandemic, but also on behavior,” she says.

Visar Berisha, an associate professor of electrical engineering at the Fulton Schools with a dual appointment at the College of Health Solutions, is a co-principal investigator leading a team that uses machine learning to analyze numerical parameter patterns using biological samples taken from blood, saliva and wastewater.

Berisha hopes that the research on the biological samples can be used for an easily accessible dashboard that will constantly search for new pathogens, such as new variants of the coronavirus or entirely new diseases.

“Based on different regions of the United States with different socioeconomic cohorts, the idea is to develop on-the-fly precision interventions to inform people of the risks of these pathogens,” he says. “By providing actionable insights into what they can do to protect themselves and those around them, we can reduce the spread and improve outcomes.”

This actionable information could include public health advice such as encouraging people with weakened immune systems or who work in high-risk environments to wear masks, or advising those most vulnerable to the worst effects of COVID-19. to get additional booster shots.

With a little help from research friends

While only ASU researchers will initially be involved in the project, the team aims to forge partnerships with outside organizations to support its efforts. These include Creative Testing Solutions, which analyzes blood samples collected from the ASU community by Berisha’s research group, and Cowper Sciences Inc., which analyzes biological samples to determine how the immune system responds to pathogens.

In addition to ASU’s team of experts, students will have the opportunity to gain hands-on research experience by participating in the project.

Berisha says the project demonstrates the benefit of basing the work at ASU because of the variety of expertise and the range and depth of investigation that its researchers can contribute to the effort.

“You have people who wear very different hats on a daily basis and are now coming together under the same roof to work on a very important issue,” he says.

In addition to Pavan Turaga, Visar Berisha, Giulia Pedrielli, Gautam Dasarathy, and Patricia Solis, the research group includes other Fulton Schools scholars: Daniel Riveraprofessor of chemical engineering at School of Materials, Transport and Energy Engineering; Rolf Haldedirector of the Biodesign Center for Environmental Health Engineering and Professor of Civil and Environmental Engineering at School of Sustainable Engineering and the Built Environment; Lalitha Sankar, associate professor of electrical engineering in the School of Electrical, Computer and Energy Engineering; and Ni Trieu, assistant professor of computer science in the School of Computing and Augmented Intelligence.

The group also includes Erik Johnsonacting deputy director and professor at ASU School for the Future of Innovation in Society; Michel Simeonassociate research professor at ASU School of sustainability and the Global Initiative on Biosocial Complexity; Timothy Lantthe Director of Program Development for ASU Knowledge business; Wenwen LiProfessor of Geographic Information Science in the School of Geographic Sciences and Urban Planning at ASU; Laimonas Kelbauskasa research scientist from the ASU Knowledge Enterprise; Efrem Limassociate professor of microbiology at ASU School of Life Sciences; Matthew Bouman, professor and director of ASU’s College of Health Solutions; and Neal Woodburyvice president and chief science and technology officer of ASU’s knowledge business.

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