The distorting lens of human mobility data

TL;DR

This paper compares human mobility datasets from seven sources across 145 countries, revealing significant differences in mobility patterns and their impact on epidemic modeling, emphasizing the need for transparency and standardized practices.

Contribution

It provides an unprecedented large-scale comparison of human mobility data sources, highlighting variability and its effects on modeling outcomes.

Findings

Wide differences in mobility networks across datasets

Displacement distribution varies significantly between sources

Impacts on epidemic spreading models

Abstract

The description of complex human mobility patterns is at the core of many important applications ranging from urbanism and transportation to epidemics containment. Data about collective human movements, once scarce, has become widely available thanks to new sources such as Phone CDR, GPS devices, or Smartphone apps. Nevertheless, it is still common to rely on a single dataset by implicitly assuming that it is a valid instance of universal dynamics, regardless of factors such as data gathering and processing techniques. Here, we test such an overarching assumption on an unprecedented scale by comparing human mobility datasets obtained from 7 different data-sources, tracing over 500 millions individuals in 145 countries. We report wide quantifiable differences in the resulting mobility networks and, in particular, in the displacement distribution previously thought to be universal. These variations -- that do not necessarily imply that the human mobility is not universal -- also impact processes taking place on these networks, as we show for the specific case of epidemic spreading. Our results point to the crucial need for disclosing the data processing and, overall, to follow good practices to ensure the robustness and the reproducibility of the results.