117 research outputs found
Predicting human mobility through the assimilation of social media traces into mobility models
Predicting human mobility flows at different spatial scales is challenged by
the heterogeneity of individual trajectories and the multi-scale nature of
transportation networks. As vast amounts of digital traces of human behaviour
become available, an opportunity arises to improve mobility models by
integrating into them proxy data on mobility collected by a variety of digital
platforms and location-aware services. Here we propose a hybrid model of human
mobility that integrates a large-scale publicly available dataset from a
popular photo-sharing system with the classical gravity model, under a stacked
regression procedure. We validate the performance and generalizability of our
approach using two ground-truth datasets on air travel and daily commuting in
the United States: using two different cross-validation schemes we show that
the hybrid model affords enhanced mobility prediction at both spatial scales.Comment: 17 pages, 10 figure
The impact of news exposure on collective attention in the United States during the 2016 Zika epidemic
How search engine data enhance the understanding of determinants of suicide in India and inform prevention: Observational study
Gender gaps in urban mobility
Abstract Mobile phone data have been extensively used to study urban mobility. However, studies based on gender-disaggregated large-scale data are still lacking, limiting our understanding of gendered aspects of urban mobility and our ability to design policies for gender equality. Here we study urban mobility from a gendered perspective, combining commercial and open datasets for the city of Santiago, Chile. We analyze call detail records for a large cohort of anonymized mobile phone users and reveal a gender gap in mobility: women visit fewer unique locations than men, and distribute their time less equally among such locations. Mapping this mobility gap over administrative divisions, we observe that a wider gap is associated with lower income and lack of public and private transportation options. Our results uncover a complex interplay between gendered mobility patterns, socio-economic factors and urban affordances, calling for further research and providing insights for policymakers and urban planners
High temperature stability of Terphenyl based thermal oils
Thermal oils are nowadays widely used as heat transfer fluids or cooling media in industrial and energy production plants. Currently, very few data are available about their thermal stability in function of the operating temperatures, which is a crucial parameter to estimate oil structural changes and their possible effects the maximum fluids lifetime.
The present work is concerned with ageing tests on a commercially used thermal oil at temperatures higher than the nominal working ones, including a full post-test characterization.
At this aim, a dedicated experimental set-up was designed and constructed to study the degradation kinetics, and to qualitatively and quantitatively analyze the released gases. As a result, the kinetic parameters were estimated, along with the related changes in the oil thermos-physical properties
Evaluation of a candidate breast cancer associated SNP in ERCC4 as a risk modifier in BRCA1 and BRCA2 mutation carriers. Results from the Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA)
Background: In this study we aimed to evaluate the role of a SNP in intron 1 of the ERCC4 gene (rs744154), previously reported to be associated with a reduced risk of breast cancer in the general population, as a breast cancer risk modifier in BRCA1 and BRCA2 mutation carriers. Methods: We have genotyped rs744154 in 9408 BRCA1 and 5632 BRCA2 mutation carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and assessed its association with breast cancer risk using a retrospective weighted cohort approach. Results: We found no evidence of association with breast cancer risk for BRCA1 (per-allele HR: 0.98, 95% CI: 0.93–1.04, P=0.5) or BRCA2 (per-allele HR: 0.97, 95% CI: 0.89–1.06, P=0.5) mutation carriers. Conclusion: This SNP is not a significant modifier of breast cancer risk for mutation carriers, though weak associations cannot be ruled out. A Osorio1, R L Milne2, G Pita3, P Peterlongo4,5, T Heikkinen6, J Simard7, G Chenevix-Trench8, A B Spurdle8, J Beesley8, X Chen8, S Healey8, KConFab9, S L Neuhausen10, Y C Ding10, F J Couch11,12, X Wang11, N Lindor13, S Manoukian4, M Barile14, A Viel15, L Tizzoni5,16, C I Szabo17, L Foretova18, M Zikan19, K Claes20, M H Greene21, P Mai21, G Rennert22, F Lejbkowicz22, O Barnett-Griness22, I L Andrulis23,24, H Ozcelik24, N Weerasooriya23, OCGN23, A-M Gerdes25, M Thomassen25, D G Cruger26, M A Caligo27, E Friedman28,29, B Kaufman28,29, Y Laitman28, S Cohen28, T Kontorovich28, R Gershoni-Baruch30, E Dagan31,32, H Jernström33, M S Askmalm34, B Arver35, B Malmer36, SWE-BRCA37, S M Domchek38, K L Nathanson38, J Brunet39, T RamĂłn y Cajal40, D Yannoukakos41, U Hamann42, HEBON37, F B L Hogervorst43, S Verhoef43, EB GĂłmez GarcĂa44,45, J T Wijnen46,47, A van den Ouweland48, EMBRACE37, D F Easton49, S Peock49, M Cook49, C T Oliver49, D Frost49, C Luccarini50, D G Evans51, F Lalloo51, R Eeles52, G Pichert53, J Cook54, S Hodgson55, P J Morrison56, F Douglas57, A K Godwin58, GEMO59,60,61, O M Sinilnikova59,60, L Barjhoux59,60, D Stoppa-Lyonnet61, V Moncoutier61, S Giraud59, C Cassini62,63, L Olivier-Faivre62,63, F RĂ©villion64, J-P Peyrat64, D Muller65, J-P Fricker65, H T Lynch66, E M John67, S Buys68, M Daly69, J L Hopper70, M B Terry71, A Miron72, Y Yassin72, D Goldgar73, Breast Cancer Family Registry37, C F Singer74, D Gschwantler-Kaulich74, G Pfeiler74, A-C Spiess74, Thomas v O Hansen75, O T Johannsson76, T Kirchhoff77, K Offit77, K Kosarin77, M Piedmonte78, G C Rodriguez79, K Wakeley80, J F Boggess81, J Basil82, P E Schwartz83, S V Blank84, A E Toland85, M Montagna86, C Casella87, E N Imyanitov88, A Allavena89, R K Schmutzler90, B Versmold90, C Engel91, A Meindl92, N Ditsch93, N Arnold94, D Niederacher95, H DeiĂźler96, B Fiebig97, R Varon-Mateeva98, D Schaefer99, U G Froster100, T Caldes101, M de la Hoya101, L McGuffog49, A C Antoniou49, H Nevanlinna6, P Radice4,5 and J BenĂtez1,3 on behalf of CIMB
Immigrant community integration in world cities
As a consequence of the accelerated globalization process, today major cities
all over the world are characterized by an increasing multiculturalism. The
integration of immigrant communities may be affected by social polarization and
spatial segregation. How are these dynamics evolving over time? To what extent
the different policies launched to tackle these problems are working? These are
critical questions traditionally addressed by studies based on surveys and
census data. Such sources are safe to avoid spurious biases, but the data
collection becomes an intensive and rather expensive work. Here, we conduct a
comprehensive study on immigrant integration in 53 world cities by introducing
an innovative approach: an analysis of the spatio-temporal communication
patterns of immigrant and local communities based on language detection in
Twitter and on novel metrics of spatial integration. We quantify the "Power of
Integration" of cities --their capacity to spatially integrate diverse
cultures-- and characterize the relations between different cultures when
acting as hosts or immigrants.Comment: 13 pages, 5 figures + Appendi
Early social distancing policies in Europe, changes in mobility & COVID-19 case trajectories: insights from Spring 2020
Background Social distancing have been widely used to mitigate community spread of SARS-CoV-2. We sought to quantify the impact of COVID-19 social distancing policies across 27 European counties in spring 2020 on population mobility and the subsequent trajectory of disease. Methods We obtained data on national social distancing policies from the Oxford COVID-19 Government Response Tracker and aggregated and anonymized mobility data from Google. We used a pre-post comparison and two linear mixed-effects models to first assess the relationship between implementation of national policies and observed changes in mobility, and then to assess the relationship between changes in mobility and rates of COVID-19 infections in subsequent weeks. Results Compared to a pre-COVID baseline, Spain saw the largest decrease in aggregate population mobility (~70%), as measured by the time spent away from residence, while Sweden saw the smallest decrease (~20%). The largest declines in mobility were associated with mandatory stay-at-home orders, followed by mandatory workplace closures, school closures, and non-mandatory workplace closures. While mandatory shelter-in-place orders were associated with 16.7% less mobility (95% CI: -23.7% to -9.7%), non-mandatory orders were only associated with an 8.4% decrease (95% CI: -14.9% to -1.8%). Large-gathering bans were associated with the smallest change in mobility compared with other policy types. Changes in mobility were in turn associated with changes in COVID-19 case growth. For example, a 10% decrease in time spent away from places of residence was associated with 11.8% (95% CI: 3.8%, 19.1%) fewer new COVID-19 cases. Discussion This comprehensive evaluation across Europe suggests that mandatory stay-at-home orders and workplace closures had the largest impacts on population mobility and subsequent COVID-19 cases at the onset of the pandemic. With a better understanding of policies’ relative performance, countries can more effectively invest in, and target, early nonpharmacological interventions
Resilience management during large-scale epidemic outbreaks
Assessing and managing the impact of large-scale epidemics considering only the individual risk and severity of the disease is exceedingly difficult and could be extremely expensive. Economic consequences, infrastructure and service disruption, as well as the recovery speed, are just a few of the many dimensions along which to quantify the effect of an epidemic on society's fabric. Here, we extend the concept of resilience to characterize epidemics in structured populations, by defining the system-wide critical functionality that combines an individual’s risk of getting the disease (disease attack rate) and the disruption to the system’s functionality (human mobility deterioration). By studying both conceptual and data-driven models, we show that the integrated consideration of individual risks and societal disruptions under resilience assessment framework provides an insightful picture of how an epidemic might impact society. In particular, containment interventions intended for a straightforward reduction of the risk may have net negative impact on the system by slowing down the recovery of basic societal functions. The presented study operationalizes the resilience framework, providing a more nuanced and comprehensive approach for optimizing containment schemes and mitigation policies in the case of epidemic outbreaks
Limited role of spatial selfstructuring in emergent trade-offs during pathogen evolution
Pathogen transmission and virulence are main evolutionary variables broadly assumed to be linked
through trade-offs. In well-mixed populations, these trade-offs are often ascribed to physiological
restrictions, while populations with spatial self-structuring might evolve emergent trade-offs. Here,
we reexamine a spatially-explicit, SIR model of the latter kind proposed by Ballegooijen and Boerlijst
with the aim of characterising the mechanisms causing the emergence of the trade-off and its structural
robustness. Using invadability criteria, we establish the conditions under which an evolutionary
feedback between transmission and virulence mediated by pattern formation can poise the system to
a critical boundary separating a disordered state (without emergent trade-off) from a self-structured
phase (where the trade-off emerges), and analytically calculate the functional shape of the boundary
in a certain approximation. Beyond evolutionary parameters, the success of an invasion depends
on the size and spatial structure of the invading and invaded populations. Spatial self-structuring is
often destroyed when hosts are mobile, changing the evolutionary dynamics to those of a well-mixed
population. In a metapopulation scenario, the systematic extinction of the pathogen in the disordered
phase may counteract the disruptive effect of host mobility, favour pattern formation and therefore
recover the emergent trade-off.This work has been supported by the Spanish Ministerio de EconomĂa, Industria y Competitividad and FEDER
funds of the EU through grants ViralESS (FIS2014-57686-P and FIS2017-84256-P). The internship of VB was
financed by the Severo Ochoa Centers of Excellence Program (SEV-2013-0347)
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