TAU Researcher Fights Epidemics Both Viral and Virtual
Dan Yamin can detect any kind of contagious outbreak
TAU’s Dr. Dan Yamin has developed a data tracking system applicable both to infectious diseases like coronavirus and to anti-Israel bias on social media. He cites human behavior as a key factor in the transmission of both. Yamin, who heads the Lab for Epidemic Modeling and Analysis at TAU’s Fleischman Faculty of Engineering, says that his approach is based on what traditional epidemiology lacks – data on human behavior. “At the core of any transmission process lies contact mixing patterns,” explains Yamin. “These patterns represent the social interactions of individuals,” adding that, when it comes to the spread of diseases, “whoever doesn’t consider these elements misses the point completely”. Together with Prof. Irad Ben-Gal, head of TAU’s Laboratory of AI, Machine Learning, Business & Data Analytics (LAMBDA), Yamin developed a tool for predicting transmission dynamics based on people’s movements tracked on their mobile phones. When COVID-19 broke out in Israel, Yamin consulted for Israel’s Health Ministry, predicting local outbreaks with this phone data system. “The tool is not only helpful for local detection of the virus but also for creating simulations of the virus’ spread, telling us what will happen if one policy is replaced with another,” he says. For example, Yamin’s team recommended to the Health Ministry that daycare centers should re-open, based on data they collected. Additionally, Yamin found that targeted lockdowns for high-risk groups and localized infection clusters are up to 5 times more efficient in reducing mortality as opposed to a nationwide lockdown strategy. This finding led the Israeli government to adopt its current targeted lockdown approaches. Now, months later, Yamin and his team are developing a tool for early detection of COVID-19 infection based on mobile phone sensors which measure step counts, sleeping habits and other parameters.