Utilizing mobility data during COVID-19 outbreak to Asses Applied Policy

Via Zoom click here

Abstract:

The COVID-19 pandemic (coronavirus pandemic) has emerged into our life in 2019 and affected our everyday life in many aspects, the main one is mobility. Since the disease transmission has been linked to mobility and close-contact people gathering, countries around the world applied different regimes restricting the movement in order to fight the spread of pandemic such as lockdowns, home schooling/work from home, travel restrictions, cancelling events or allowing limited amount of people gathering. Examining and analyzing how the population move when applying such policies can help governments understand their performances, and if is it required making changes or to be better enforce. In recent years massive amount of data is available, and specifically mobility data, which can be Utilize for application of mobility analysis. In this study we use cellular aggregated data of users location in level of neighborhoods and cities during the first months of the pandemic in Israel. We define the optimization problem of discovering most compatible movements factor which represent the actual movement during segregation when comparing the regular movement to the movement during the pandemic. We also examined how to best cluster neighborhoods when having multiple objectives using the mobility data and the geographical information. We evaluate multiple clustering methods and present sensitivity analysis. Finally, we present a usecase of using such analysis method

Bio:

Or Volkamir is an MSc student in Lambda, the laboratory of AI, Machine Learning, Business & Data Analytics in the faculty of engineering in Tel Aviv University. Or has an experience as data scientists for several years, worked in past in Moovit and now working in fintech company named Lili

Contact:

• E-Mail: orwolkomir@mail.tau.ac.il

• Linkedin: https://www.linkedin.com/in/or-wolkomir-32a161115/