Does our collective stringency control the virus? Investigating lockdown effectiveness on community mobility data

Facing the global crisis brought by COVID-19, many countries have adopted social distancing or stay-at-home measures to restrict individual mobility to control the virus. Meanwhile, the availability of anonymized and aggregated mobility data provides an opportunity to obtain a deeper understanding of the impact of these measures. In this paper, we utilize an open mobility dataset called Community Mobility Report published by Google on the Internet and other external data sources (e.g., statistics on daily confirmed cases, demographics, etc.) to quantitatively characterize people’s collective responses and model it with a proposed metric called Lockdown Stringency Score (LSS) after the lockdown measures have been taken. Then, by investigating the correlations between LSS and the increase of new confirmed cases across different regions and countries in the world, we explore how people’s collective response in terms of mobility pattern changes affects the control of the virus. The analysis results show that lockdown and social distancing measures do have a positive impact on virus control, and the restriction on different types of Point-of-Interests (PoIs) has different weights (significance) in terms of virus control effectiveness. These results reveal important insights and implication on public health policy making, such as the phased start of the lockdown or reopen of the economy.