With about one third of humanity in some degree of lockdown, we see it critical to quantify physical distancing and its secondary impacts. In this project, we investigate how human mobility changes over time, bringing together wide arrays of data sets (e.g. flight reservation, bike sharing service, carrier/telecommunication, and social data) and analyze from a global as well as local perspective, particularly NYC, Tokyo and Barcelona.
Throughout the four research topics we address, we aim to develop a physical distancing risk index to monitor the risk in areas with high population density and probability of contraction. We expect that our physical distancing index is computed by using multiple data sources including global-level mobility data, travel restriction data, city-level mobility data using bike sharing systems and public transportation, aggregated and anonymized mobile data, and crowd-sourced data on social networking platforms. The index is formulated in a way that it becomes higher if people are ordered or recommended to stay at home and all non-essential businesses and shops are closed - while it becomes smaller if regulations revert back to pre-COVID-19 situations. While COVID-19 transmission slows down and policy restrictions become relaxed, we still must monitor transmission rates as well as social data. Therefore, we aim to provide our physical distancing risk index to inform policy and decision making through visualization and correlation with infected cases and various economic indices during this project.
To learn more about each research topic
- UNDERSTANDING GLOBAL MOBILITY USING FLIGHT DATA
- CHANGES IN MOBILITY (TOKYO)
- CHANGES IN MOBILITY (NEW YORK CITY)
- MOBILITY CHANGES (BARCELONA)
- PHYSICAL DISTANCING POSTS ON INSTAGRAM