Background COVID-19 poses a severe threat worldwide. This study analyzes its
propagation and evaluates statistically the effect of mobility restriction policies on the spread …

As countries in the world review interventions for containing the pandemic of coronavirus
disease 2019 (COVID-19), important lessons can be drawn from the study of the full …

We employ the Google and Apple mobility data to identify, quantify and classify different
degrees of social distancing and characterise their imprint on the first wave of the COVID-19 …

Human mobility is an important driver of geographic spread of infectious pathogens.
Detailed information about human movements during outbreaks are, however, difficult to …

While large scale mobility data has become a popular tool to monitor the mobility patterns
during the COVID-19 pandemic, the impacts of non-compulsory measures in Tokyo, Japan …

We combine COVID-19 case data with mobility data to estimate a modified susceptible-
infected-recovered (SIR) model in the United States. In contrast to a standard SIR model, we …

Understanding dynamic human mobility changes and spatial interaction patterns at different
geographic scales is crucial for assessing the impacts of non-pharmaceutical interventions …

Background Governments have implemented population-wide physical distancing
measures to control COVID-19, but metrics evaluating their effectiveness are not readily …

In response to the COVID-19 pandemic, countries have sought to control SARS-CoV-2
transmission by restricting population movement through social distancing interventions …

Disease transmission is notoriously heterogeneous, and SARS-CoV-2 is no exception. A
skewed distribution where few individuals or events are responsible for the majority of …