Mobility

Authors: Fengli Xu, Qi Wang, Esteban Moro, Arianna Salazar Miranda, Marta C. González, Chaoming Song, Carlo Ratti, Luis Bettencourt, James Evans Publication: Nature Human Behavior (2025) LINK Abstract: The lived experience of urban life is shaped by personal mobility through dynamic relationships and resources, marked not only by access and opportunity, but also inequality and segregation. The recent availability of fine-grained mobility data and context attributes ranging from venue type to demographic mixture offer researchers a deeper understanding of experienced inequalities at scale, and pose many new questions. ...

Authors: Oriol Cabanas-Tirapu, Lluís Danús, Esteban Moro, Marta Sales-Pardo & Roger Guimerà Publication: Nature Communications 16, 1336 (2025). LINK Abstract: Modeling human mobility is critical to address questions in urban planning, sustainability, public health, and economic development. However, our understanding and ability to model flows between urban areas are still incomplete. At one end of the modeling spectrum we have gravity models, which are easy to interpret but provide modestly accurate predictions of flows. ...

Authors: Takahiro Yabe, Massimiliano Luca, Kota Tsubouchi, Bruno Lepri, Marta C. Gonzalez & Esteban Moro Publication: Nature Computational Science (2024). doi: 10.1038/s43588-024-00650-3 LINK Abstract: Human mobility research intersects with various disciplines, with profound implications for urban planning, transportation engineering, public health, disaster management, and economic analysis. Here, we discuss the urgent need for open and standardized datasets in the field, including current challenges and lessons from other computational science domains, and propose collaborative efforts to enhance the validity and reproducibility of human mobility research. ...

Authors: Shenhao Wang, Yunhan Zheng, Guang Wang, Takahiro Yabe, Esteban Moro & Alex ‘Sandy’ Pentland Publication: Nature Cities 10.1038/s44284-024-00051-7. LINK Abstract: Many studies have revealed the predictive power of the most frequent, regular and habitual mobility patterns. However, it remains unclear which components of the mobility patterns contain the most informative signals for predicting disparate economic development across urban areas. Here we use machine learning to predict economic outcomes by analyzing the heterogeneous mobility networks of 687 activities from more than 560,000 anonymized users in Boston, Chicago and Miami. ...

Authors: Bernardo Garcia-Bulle, Abigail L. Horn, Brooke M. Bell, Mohsen Bahrami, Burcin Bozkaya, Alex Pentland, Kayla de la Haye, and Esteban Moro Publication: Nature Communications 15, article number: 2291. LINK Abstract: Poor diets are a leading cause of morbidity and mortality. Exposure to low-quality food environments saturated with fast food outlets is hypothesized to negatively impact diet. However, food environment research has predominantly focused on static food environments around home neighborhoods and generated mixed findings. ...

Authors: Marco Pangallo, Alberto Aleta, R. Maria del Rio-Chanona, Anton Pichler, David Martin-Corral, Matteo Chinazzi, Francois Lafond, Marco Ajelli, Esteban Moro, Yamir Moreno, Alessandro Vespignani, J. Doyne Farmer Publication: Nature Human Behavior, Nov 16th, (2023) LINK Abstract: Despite the global impact of the coronavirus disease 2019 pandemic, the question of whether mandated interventions have similar economic and public health effects as spontaneous behavioural change remains unresolved. Addressing this question, and understanding differential effects across socioeconomic groups, requires building quantitative and fine-grained mechanistic models. ...