Analyzing Mobility Patterns at Scale in Pandemic Scenarios Leveraging the Mobile Network Ecosystem

Abstract

The ubiquity and pervasiveness of mobile network technologies has made them so deeply ingrained in our everyday lives that by interacting with them for very simple purposes (e.g., messaging or browsing the Internet), we produce an unprecedented amount of data that can be analyzed to understand our behavior. While this practice has been extensively adopted by telcos and big tech companies in the last few years, this condition, which was unimaginable just 20 years ago, has only been mildly exploited to fight the COVID-19 pandemic. In this paper, we discuss the possible alternatives that we could leverage in the current mobile network ecosystem to provide regulators and epidemiologists with the right understanding of our mobility patterns, to maximize the efficiency and extent of the introduced countermeasures. To validate our analysis, we dissect a fine-grained dataset of user positions in two major European countries severely hit by the pandemic. The potential of using these data, harvested employing traditional mobile network technologies, is unveiled through two exemplary cases that tackled macro and microscopic aspects.