Multilayer data-driven models for Early Detection of COVID-19
Dan Yamin (Ph.D. Eng.)1,2
1Department of Industrial Engineering, Tel-Aviv University, Tel-Aviv 69978, Israel
2Center for Combatting Pandemics, Tel Aviv University, Tel Aviv 6997801, Israel
Various efforts for early detection and prompt isolation of the COVID-19 pandemic are pivotal to breaking transmission chains and containing outbreaks. In this talk, I will briefly discuss our four projects that utilize data of a large-scale for early detection of 1) hotspots and regional outbreaks using mobility data from cellphone devices, 2) early signs of infections using wearable devices, 3) positive test outcomes using historical electronic medical records, and 4) deteriorations of hospitalized patients using rich medical data. Then, I will elaborate on one of the projects and its potential applicability for policy determination.
Bio:
Dr. Yamin (Ph.D.) is a faculty member at the Department of Industrial Engineering at Tel Aviv University, and a former faculty member in the Center of Infectious Disease Modeling and Analysis, in the school of public health at Yale University. Dr. Yamin received four research prizes awards and five teaching prizes awards. Dr. Yamin’s studies contributed to impact health policy against influenza in Israel, offered novel strategies to eliminate Ebola that were implemented in Liberia. He received a European Research Council (ERC) grant to pursue research on the early detection of infectious diseases using smartphones. He recently advised the Ministry of Health and the Ministry of Finance to identify hotspots and apply effective strategies against the COVID-19 Pandemic in Israel.
via zoom
https://us02web.zoom.us/j/83307786741
