Since 2020, the coronavirus has infected more than 627 million people and caused more than 6.5 million to lose their lives, according to the World Health Organization. COVID-19 has put a strain on almost every country in the world, fundamentally altering their economies and health care systems worldwide.
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 illnesses like the coronavirus are expected to arise more frequently. The study estimates the yearly likelihood of severe disease outbreaks could increase by 300% in the decades to come.
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 and a professor in the School of Electrical, Computer and Energy Engineering, part of the Ira A. Fulton Schools of Engineering at ASU, the team brings together computational, biological and social science experts to develop modeling tools that can adapt to predict the spread of both new and existing pathogens to inform legislative and health care responses to pandemics.