#Mobility #Mobile phone data #Data Science #food #nutrition #accessibility #environments #Human behavior

You are where you eat: Effect of mobile food environments on fast food visits

Authors: Bernardo Garcia-Bulle, Abigail L. Horn, Brooke M. Bell, Mohsen Bahrami, Burcin Bozkaya, Alex Pentland, Kayla de la Haye, and Esteban Moro Publication: medRxiv 2022.09.20.22280128. LINK Abstract: Poor diets, including those high in fast food, are a leading cause of morbidity and mortality. Exposure to low-quality food environments, such as ‘food swamps’ saturated with fast food outlets (FFO), is hypothesized to negatively impact diet and related disease. However, research linking such exposure to diet and health outcomes has generated mixed findings and led to unsuccessful policy interventions. ...

#Mobile phone data #Urban Science

Rhythm of the streets: a street classification framework based on street activity patterns

Authors: Tianyu Su , Maoran Sun, Zhuangyuan Fan, Ariel Noyman, Alex Pentland, and Esteban Moro Publication: EPJ Data Science 11, 43 (2022). Link Abstract: As the living tissue connecting urban places, streets play significant roles in driving city development, providing essential access, and promoting human interactions. Understanding street activities and how these activities vary across different streets is critical for designing both efficient and livable streets. However, current street classification frameworks primarily focus on either streets’ functions in transportation networks or their adjacent land uses rather than actual activity patterns, resulting in coarse classifications. ...

#covid19 #Mobile phone data #epidemics

Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas

Authors: Alberto Aleta, David Martín-Corral, Michiel A.Bakker, Ana Pastore y Piontti, Marco Ajelli, Maria Litvinova , Matteo Chinazzi, Natalie E. Dean, M. Elizabeth Halloran,Ira M. Longini,Jr, Alex Pentland, Alessandro Vespignani, Yamir Moreno, and Esteban Moro. Publication: PNAS (2022). Link Abstract: Detailed characterization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission across different settings can help design less disruptive interventions. We used real-time, privacy-enhanced mobility data in the New York City, NY and Seattle, WA metropolitan areas to build a detailed agent-based model of SARS-CoV-2infection to estimate the where, when, and magnitude of transmission events during thepandemic’s first wave. ...

#Mobile Phone Data #Privacy #Deep Learning

Generating synthetic mobility data for a realistic population with RNNs to improve utility and privacy

Authors: Alex Berke, Ronan Doorley, Kent Larson, Esteban Moro Publication: arXiv preprint arXiv:2201.01139 (2022). Link Abstract: Location data collected from mobile devices represent mobility behaviors at individual and societal levels. These data have important applications ranging from transportation planning to epidemic modeling. However, issues must be overcome to best serve these use cases: The data often represent a limited sample of the population and use of the data jeopardizes privacy. ...

#inequality #Social Media #Mobile Phone Data

News or social media? Socio-economic divide of mobile service consumption

Authors: Iñaki Ucar, Marco Gramaglia, Marco Fiore, Zbigniew Smoreda, and Esteban Moro Publication: J. R. Soc. Interface (2021). Link Abstract: Reliable and timely information on socio-economic status and divides is critical to social and economic research and policing. Novel data sources from mobile communication platforms have enabled new cost-effective approaches and models to investigate social disparity, but their lack of interpretability, accuracy or scale has limited their relevance to date. ...