Texas A&M predicting COVID-19 spread with deep-learning model

Researchers at Texas A&M University have recently begun using artificial intelligence to forecast the growth of COVID-19 cases in communities across the country. The university is using a deep-learning model, a method of machine-learning that relies on large amounts of data, to process data related to population activities and mobility to help predict the spread of COVID-19 at a county level. Ali Mostafavi, the project's lead researcher, said this work could help lawmakers make informed policy decisions to protect residents and mitigate spread of the virus. "Significant opportunities exist using these big data and AI to contain the existing pandemic and also better prepare and mitigate the future pandemics," said Mostafavi, an associate professor of civil and environmental engineering. According to an announcement from the university last week, data fed into the model included the movement of people within communities, census data, social-distancing data, past case count growth and social demographics.