Efficient detection of contagious outbreaks in massive metropolitan encounter networks

Physical contact remains difficult to trace in large metropolitan networks, though it is a key vehicle for the transmission of contagious outbreaks. Co-presence encounters during daily transit use provide us with a city-scale time-resolved physical contact network, consisting of 1 billion contacts among 3 million transit users. Here, we study the advantage that knowledge of such co-presence structures may provide for early detection of contagious outbreaks. We first examine the "friend sensor" scheme --- a simple, but universal strategy requiring only local information --- and demonstrate that it provides significant early detection of simulated outbreaks. Taking advantage of the full network structure, we then identify advanced "global sensor sets", obtaining substantial early warning times savings over the friends sensor scheme. Individuals with highest number of encounters are the most efficient sensors, with performance comparable to individuals with the highest travel frequency, exploratory behavior and structural centrality. An efficiency balance emerges when testing the dependency on sensor size and evaluating sensor reliability; we find that substantial and reliable lead-time could be attained by monitoring only 0.01% of the population with the highest degree.Comment: 4 figure

DATASET2050 D5.2 - Assessment execution

Over recent years there has been an increasing effort to enhance European door-to-door mobility. Several initiatives have focused on improving the seamlessness, effectiveness and predictability of the European transport system through improving the related systems, technologies, concepts or processes. In an effort to establish a concrete methodology for assessing the system's current performance, this document describes a data-driven model centred on the current and future performance of European mobility. Included in this study, but not restricted to, is data and insight related to the Flightpath 2050 goal that states "90% of travellers within Europe [will be] able to complete their journey, door-to-door within four hours" where this journey includes at least one leg by air. In this report, the current door-to-door times and prices are quantified, dis-aggregated by passenger profile, door-to-door phase (door-kerb-gate-gate-kerb-door) and airport considered. In addition, major bottlenecks are identified that are hindering the 4-hour goal

Representative time use data and new harmonised calibration of the American Heritage Time Use Data (AHTUD) 1965-1999

Representative and reliable individual time use data, in connection with a proper set of socio-economic back-ground variables, are essential elements for the empirical foundation and evaluation of existing and new theories in general and in particular for time use analyses. Within the international project Assessing Time Use Survey Datasets several potentially useful individual US time use heritage datasets have been identified for use in de-veloping an historical series of non-market accounts. In order to evaluate the series of American Heritage Time Use Data (AHTUD) (1965, 1975, 1985, 1992-94, 1998-99) this paper analyses the representativeness of this data when using given weights and provides a new harmonised calibration of the AHTUD for sound time use analyses. Our calibration procedure with its ADJUST program package is theoretically founded on information theory, consistent with a simultaneous weighting including hierarchical data, ensures desired positive weights, and is well-suited and available for any time use data calibration of interest. We present the calibration approach and provide new harmonised weights for all AHTUD surveys based on a substantially driven calibration frame-work. To illustrate the various application possibilities of a calibration, we finally disentangle demographic vs. time use behavioural changes and developments by re-calibrating all five AHTUD surveys using 1965 popula-tion totals as a benchmark.Representative time use data, calibration (adjustment re-weighting) of microdata, information theory, minimum information loss principle, American Heritage Time Use Data (AHTUD), ADJUST program package

Doctor of Philosophy

dissertationRecent years' advancements in sensing technology have generated an enormous amount of data in various fields and industries, including transportation. Public transportation systems, as a critical component within the transportation ecosystem, have also been experiencing much data growth. The availability of big data not only improves traditional transit service monitoring, but also enables high-resolution transit performance analysis that guides decision making. However, the potential of these datasets is not fully explored yet due to several challenges such as residing noises in data records and limited computational power. This dissertation tries to address three of those challenges: how to incorporate and analyze missing data due to lack of electronic footage, how to enable high-resolution performance measurements that require extensive computation, and how to interpret the high-resolution results? The first challenge was addressed in a quest to find missing data on the different fare payment methods without electronic footage, and their impact (among other factors) on bus Dwell Time (DT). Integrating information from multiple data sources, a combined approach of optimization and regression analysis was developed that offers a data-driven evaluation of existing fare payment structures and their individual effects on DT. Using the 35M bus rapid transit line operated by the Utah Transit Authority as a case study, the method demonstrates the robustness and strong predictive power in DT modeling. Then we introduce a new algorithm that is computationally elegant and mathematically efficient to address the second challenge of run-time reduction. An open-source toolbox written in C++ is developed to implement the algorithm. The toolbox is tested on the City of St. George's transit network to showcase dynamic transit accessibility analysis. The experimental evidence shows significant reduction on computational time. To address challenge three on interpreting the high-resolution transit accessibility results, the algorithm in the previous study was applied to the Salt Lake City's network to compute travel times at multiple departure times throughout the day. A series of indicators that are intuitive to interpret were developed to determine the varying causes of poor transit accessibility and identify areas with immediate needs for service improvements. This dissertation manifested that utilizing newly available datasets not only improves the resolution and accuracy of the transit service assessments, but also takes a step further to enable a comprehensive study of various factors (stop characteristics) impacting transit service efficiency and quantifying critical decision-making indices unveiling transit service effectiveness that were not possible before. Findings from this research are expected to lead to methodological advancements in data-driven approaches in public transit studies, and help transform the transit management mindset into a model of data-driven, sensing, and smart urban systems

Changes in the use of time and the state of health of the Russian population in the 1980s-1990s

This is an attempt to answer a question about how changes in the time use and in health the population relate to each other, what connection exists between duration and character of work and the state of health. The paper draws on the data from two rounds of time budget surveys of: 1) families who kept record of their incomes and expenditures (the RF Goskomstat, 1977-1990 – over 28 thous. families), 2) the rural population of the Novosi-birsk region (IEIE SB RAS, 1975-1999, 1400-1100 persons in each). In these rounds the “previous day” ap-proach was used. Used were also the data of questionnaire surveys and official statistics. Last 20 years are a unique period in the Russian modern history reflected in most different forms on all aspects of life, including time use, everyday activity and health of population. The analysis of relationship between time use and health was made at macro levels. Health is presented by life expectancy. Time use is presented by aggregated structure of average time budget, respectively. The assessment by respondents of changes in living conditions and in their own state is seen as a measure of social-psychological well-being of the population. The direction and degree of influence between “time use – state of health” depend on macro and micro life conditions, on social-psychological well-being of the society and individual, on the “initial’ state of health of the individuals.Time budget, everyday activity, living conditions, life expectancy, social changes

Children and Parents Time Use: Empirical Evidence on Investment in Human Capital in France, Italy and Germany

We analyze a mechanism that has been disregarded in the literature on parental investment in children, as little attention has been devoted to the choices made by children themselves. We model directly time use by youngsters into activities related to the acquisition of human capital, considering not just the decision on study time, but also on socialization/networking at young age, which can enhance personal interaction skills. We provide new empirical evidence for three European countries (France, Italy and Germany) on the link between time allocation by parents and time allocation by youngsters, highlighting country-specific patterns as well as cross-country differences. We run fractional regression models and double hurdle models on multi-member household micro data on time use. Countries diverge concerning the association between parents and youngsters allocation of time to socializing and to reading and studying activities, with Italy standing out as the country where that association, in particular between youngster and mother, is strongest. Our results are consistent with different mechanisms: parental role model directly influencing children behavior, intergenerational transmission of preferences, or network effects, as individuals adapt their behavior to social patterns.study time, socializing, networking, youth, intergenerational transmission of preferences, fractional regression models, double hurdle models