Human mobility from theory to practice: Data, models and applications

The inclusion of tracking technologies in personal devices opened the doors to the analysis of large sets of mobility data like GPS traces and call detail records. This tutorial presents an overview of both modeling principles of human mobility and machine learning models applicable to specific problems. We review the state of the art of five main aspects in human mobility: (1) human mobility data landscape; (2) key measures of individual and collective mobility; (3) generative models at the level of individual, population and mixture of the two; (4) next location prediction algorithms; (5) applications for social good. For each aspect, we show experiments and simulations using the Python library "scikit-mobility" developed by the presenters of the tutorial

Human mobility: Models and applications

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordRecent years have witnessed an explosion of extensive geolocated datasets related to human movement, enabling scientists to quantitatively study individual and collective mobility patterns, and to generate models that can capture and reproduce the spatiotemporal structures and regularities in human trajectories. The study of human mobility is especially important for applications such as estimating migratory flows, traffic forecasting, urban planning, and epidemic modeling. In this survey, we review the approaches developed to reproduce various mobility patterns, with the main focus on recent developments. This review can be used both as an introduction to the fundamental modeling principles of human mobility, and as a collection of technical methods applicable to specific mobility-related problems. The review organizes the subject by differentiating between individual and population mobility and also between short-range and long-range mobility. Throughout the text the description of the theory is intertwined with real-world applications.US Army Research Offic

Network Cosmology

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology

Developing capacity in health informatics in a resource poor setting: lessons from Peru

The public sectors of developing countries require strengthened capacity in health informatics. In Peru, where formal university graduate degrees in biomedical and health informatics were lacking until recently, the AMAUTA Global Informatics Research and Training Program has provided research and training for health professionals in the region since 1999. The Fogarty International Center supports the program as a collaborative partnership between Universidad Peruana Cayetano Heredia in Peru and the University of Washington in the United States of America. The program aims to train core professionals in health informatics and to strengthen the health information resource capabilities and accessibility in Peru. The program has achieved considerable success in the development and institutionalization of informatics research and training programs in Peru. Projects supported by this program are leading to the development of sustainable training opportunities for informatics and eight of ten Peruvian fellows trained at the University of Washington are now developing informatics programs and an information infrastructure in Peru. In 2007, Universidad Peruana Cayetano Heredia started offering the first graduate diploma program in biomedical informatics in Peru

Human Mobility in a Continuum Approach

Human mobility is investigated using a continuum approach that allows to calculate the probability to observe a trip to anyarbitrary region, and the fluxes between any two regions. The considered description offers a general and unified framework, in which previously proposed mobility models like the gravity model, the intervening opportunities model, and the recently introduced radiation model are naturally resulting as special cases. A new form of radiation model is derived and its validity is investigated using observational data offered by commuting trips obtained from the United States census data set, and the mobility fluxesextracted from mobile phone data collected in a western European country. The new modeling paradigm offered by this description suggests that the complex topological features observed in large mobility and transportation networks may be the result of a simple stochastic process taking place on an inhomogeneous landscape.Comment: 13 pages, 3 figure

Mesoscopic structure and social aspects of human mobility

The individual movements of large numbers of people are important in many contexts, from urban planning to disease spreading. Datasets that capture human mobility are now available and many interesting features have been discovered, including the ultra-slow spatial growth of individual mobility. However, the detailed substructures and spatiotemporal flows of mobility - the sets and sequences of visited locations - have not been well studied. We show that individual mobility is dominated by small groups of frequently visited, dynamically close locations, forming primary "habitats" capturing typical daily activity, along with subsidiary habitats representing additional travel. These habitats do not correspond to typical contexts such as home or work. The temporal evolution of mobility within habitats, which constitutes most motion, is universal across habitats and exhibits scaling patterns both distinct from all previous observations and unpredicted by current models. The delay to enter subsidiary habitats is a primary factor in the spatiotemporal growth of human travel. Interestingly, habitats correlate with non-mobility dynamics such as communication activity, implying that habitats may influence processes such as information spreading and revealing new connections between human mobility and social networks.Comment: 7 pages, 5 figures (main text); 11 pages, 9 figures, 1 table (supporting information

REDIENTE: historia clínica odontológica ubicua con indicadores de calidad de servicios y evaluación epidemiológica

REDIENTE es un registro clínico en una base de datos accesible en internet, con vocación nacional y manejo local por parte de los odontólogos en sus consultorios individuales o en instituciones. Un carnet REDIENTE con copia de la historia clínica queda en poder del paciente que une todos los eventos en un hilo documental coherente. Las variables de la Historia Clínica Odontológica (HCO) son las indispensables para certificar una buena atención. Los indicadores de REDIENTE sobre poblaciones permiten describir situaciones de salud bucal, evaluar calidad de atención y hacer el seguimiento docente. REDIENTE respeta la legislación sobre protección de datos personales del paciente.REDIENTE is an interdisciplinary solution for a multifaceted problem: standardization of dental care documentation, creation of a teaching supervision tool and designing a management application for dental care quality assurance. Distribution of data and information are addressed by giving the patient a copy of the basic record, the Dental Clinical Record (HCO for the Spanish “Historia Clínica Odontológica”) and by designing a web application. HCO contains the skeleton of dental care record including items of procedures performed, complications, office dates and periodic odontogram. REDIENTE displays quality of care and learning indicators as selective queries to the database. www.rediente.org.uy.Sociedad Argentina de Informática e Investigación Operativ

Emergence of structural and dynamical properties of ecological mutualistic networks

Mutualistic networks are formed when the interactions between two classes of species are mutually beneficial. They are important examples of cooperation shaped by evolution. Mutualism between animals and plants plays a key role in the organization of ecological communities. Such networks in ecology have generically evolved a nested architecture independent of species composition and latitude - specialists interact with proper subsets of the nodes with whom generalists interact. Despite sustained efforts to explain observed network structure on the basis of community-level stability or persistence, such correlative studies have reached minimal consensus. Here we demonstrate that nested interaction networks could emerge as a consequence of an optimization principle aimed at maximizing the species abundance in mutualistic communities. Using analytical and numerical approaches, we show that because of the mutualistic interactions, an increase in abundance of a given species results in a corresponding increase in the total number of individuals in the community, as also the nestedness of the interaction matrix. Indeed, the species abundances and the nestedness of the interaction matrix are correlated by an amount that depends on the strength of the mutualistic interactions. Nestedness and the observed spontaneous emergence of generalist and specialist species occur for several dynamical implementations of the variational principle under stationary conditions. Optimized networks, while remaining stable, tend to be less resilient than their counterparts with randomly assigned interactions. In particular, we analytically show that the abundance of the rarest species is directly linked to the resilience of the community. Our work provides a unifying framework for studying the emergent structural and dynamical properties of ecological mutualistic networks.Comment: 10 pages, 4 figure

REDIENTE: historia clínica odontológica ubicua con indicadores de calidad de servicios y evaluación epidemiológica

REDIENTE es un registro clínico en una base de datos accesible en internet, con vocación nacional y manejo local por parte de los odontólogos en sus consultorios individuales o en instituciones. Un carnet REDIENTE con copia de la historia clínica queda en poder del paciente que une todos los eventos en un hilo documental coherente. Las variables de la Historia Clínica Odontológica (HCO) son las indispensables para certificar una buena atención. Los indicadores de REDIENTE sobre poblaciones permiten describir situaciones de salud bucal, evaluar calidad de atención y hacer el seguimiento docente. REDIENTE respeta la legislación sobre protección de datos personales del paciente.REDIENTE is an interdisciplinary solution for a multifaceted problem: standardization of dental care documentation, creation of a teaching supervision tool and designing a management application for dental care quality assurance. Distribution of data and information are addressed by giving the patient a copy of the basic record, the Dental Clinical Record (HCO for the Spanish “Historia Clínica Odontológica”) and by designing a web application. HCO contains the skeleton of dental care record including items of procedures performed, complications, office dates and periodic odontogram. REDIENTE displays quality of care and learning indicators as selective queries to the database. www.rediente.org.uy.Sociedad Argentina de Informática e Investigación Operativ

REDIENTE: historia clínica odontológica ubicua con indicadores de calidad de servicios y evaluación epidemiológica

REDIENTE es un registro clínico en una base de datos accesible en internet, con vocación nacional y manejo local por parte de los odontólogos en sus consultorios individuales o en instituciones. Un carnet REDIENTE con copia de la historia clínica queda en poder del paciente que une todos los eventos en un hilo documental coherente. Las variables de la Historia Clínica Odontológica (HCO) son las indispensables para certificar una buena atención. Los indicadores de REDIENTE sobre poblaciones permiten describir situaciones de salud bucal, evaluar calidad de atención y hacer el seguimiento docente. REDIENTE respeta la legislación sobre protección de datos personales del paciente.REDIENTE is an interdisciplinary solution for a multifaceted problem: standardization of dental care documentation, creation of a teaching supervision tool and designing a management application for dental care quality assurance. Distribution of data and information are addressed by giving the patient a copy of the basic record, the Dental Clinical Record (HCO for the Spanish “Historia Clínica Odontológica”) and by designing a web application. HCO contains the skeleton of dental care record including items of procedures performed, complications, office dates and periodic odontogram. REDIENTE displays quality of care and learning indicators as selective queries to the database. www.rediente.org.uy.Sociedad Argentina de Informática e Investigación Operativ