Human mobility patterns in Mexico City and their links with socioeconomic variables during the COVID-19 pandemic
Year: 2022
Type: preprint
Abstract: The availability of cellphone geolocation data provides a remarkable opportunity to study human mobility patterns and how these patterns are affected by the recent pandemic. Two simple centrality metrics allow us to measure two different aspects of mobility in origin-destination networks constructed with this type of data: variety of places connected to a certain node (degree) and number of people that travel to or from a given node (strength). In this contribution, we present an analysis of node degree and strength in daily origin-destination networks for Greater Mexico City during 2020. Unlike what is observed in many complex networks, these origin-destination networks are not scale free. Instead, there is a characteristic scale defined by the distribution peak; centrality distributions exhibit a skewed two-tail distribution with power law decay on each side of the peak. We found that high mobility areas tend to be closer to the city center, have higher population and better socioeconomic conditions. Areas with anomalous behavior are almost always on the periphery of the city, where we can also observe qualitative difference in mobility patterns between east and west. Finally, we study the effect of mobility restrictions due to the outbreak of the COVID-19 pandemics on these mobility patterns.
Source: Research Square
Authors: Oscar Fontanelli, Dulce Valdivia, Guillermo Romero, Oliver Medina, Wentian Li, Maribel Hernández-Rosales
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W4293582008