scholarly journals Leveraging insurance customer data to characterize socioeconomic indicators of Swiss municipalities

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0246785
Author(s):  
Lorenzo Donadio ◽  
Rossano Schifanella ◽  
Claudia R. Binder ◽  
Emanuele Massaro
Keyword(s):  
Public Transportation ◽  
Wide Spectrum ◽  
Spatial Regression ◽  
User Profile ◽  
Location Based Services ◽  
Socioeconomic Indicators ◽  
Customer Data ◽  
Spatial And Temporal Scales ◽  
Socioeconomic Data ◽  
Global And Local

The availability of reliable socioeconomic data is critical for the design of urban policies and the implementation of location-based services; however, often, their temporal and geographical coverage remain scarce. We explore the potential for insurance customers data to predict socioeconomic indicators of Swiss municipalities. First, we define a features space by aggregating at city-level individual customer data along several behavioral and user profile dimensions. Second, we collect official statistics shared by the Swiss authorities on a wide spectrum of categories: Population, Transportation, Work, Space and Territory, Housing, and Economy. Third, we adopt two spatial regression models exploring both global and local geographical dependencies to investigate their predictability. Results show consistently a correlation between insurance customer characteristics and official socioeconomic indexes. Performance fluctuates depending on the category, with values of R2 > 0.6 for several target variables using a 5-fold cross validation. As a case study, we focus on predicting the percentage of the population using public transportation and we discuss the implications on a regional scope. We believe that this methodology can support official statistical offices and it could open up new opportunities for the characterization of socioeconomic traits at highly-granular spatial and temporal scales.

scholarly journals Measuring Equity through Spatial Variability of Infrastructure Systems across the Urban-Rural Gradient

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1202
Author(s):  
Shrobona Karkun Sen ◽  
Hamil Pearsall ◽  
Victor Hugo Gutierrez-Velez ◽  
Melissa R. Gilbert
Keyword(s):  
Predictive Power ◽  
Spatial Regression ◽  
Spatial Relationship ◽  
Socioeconomic Indicators ◽  
Infrastructure Systems ◽  
Regression Methods ◽  
Complex Interactions ◽  
Spatial Inequalities ◽  
Access To Health ◽  
Urban Rural

Recent regional research has taken an ‘infrastructure turn’ where scholars have called for examining the transformative ability of different infrastructures in causing systemic inequities beyond the spatial conception of ‘urban and the other’. This research examines the interconnected impact of infrastructure systems on existing spatial inequities through a study in metropolitan Philadelphia, Pennsylvania. This study investigates whether the urban-rural (U-R) gradient concept can enhance understanding of the spatial relationship between socioeconomic indicators and infrastructure systems. Indicators of spatial inequalities were regressed against infrastructure variables and imperviousness, as a proxy for the U-R gradient, using multivariate and spatial regression methods. The models show that imperviousness has a positive correlation with the concentration of racialized minorities and a negative correlation with access to health insurance. The study also shows that the predictive power of multiple infrastructures varies across space and does not adhere to urban boundaries or the U-R gradient. The complex interactions among different infrastructures shape inequities and require further inquiry in urban regions around the world.

scholarly journals Electric Bicycle-Sharing: A New Competitor in the Urban Transportation Market? An Empirical Analysis of Transaction Data

2019 ◽  
Vol 2673 (4) ◽  
pp. 15-26 ◽  
Author(s):  
Sergio Guidon ◽  
Henrik Becker ◽  
Horace Dediu ◽  
Kay W. Axhausen
Keyword(s):  
Public Transportation ◽  
Spatial Regression ◽  
Social Activity ◽  
Transaction Data ◽  
Fifth Generation ◽  
Transportation Service ◽  
Bike Sharing ◽  
Bicycle Infrastructure ◽  
Electric Bicycle ◽  
Key Drivers

Electric bicycles (e-bikes) are a new addition to bicycle-sharing and may improve its competitiveness. E-bikes allow for higher speeds at a higher level of comfort than conventional bicycles and, compared with traditional bicycle-sharing, e-bike-sharing is better positioned to complement or compete with existing public transportation, or to even challenge established taxi services. In this paper, eight months of transaction data from a free-floating e-bike-sharing system in Zürich, Switzerland, were used to study the market position of e-bike sharing and drivers of demand. The results of the analysis indicate that a large proportion of the trips are commuting, and that the distance range of e-bike-sharing trips overlaps with the distance ranges of traditional public transportation and taxi services. Intensity of use is sensitive to precipitation. Spatial regression modeling indicates that economic and social activity, public transportation service quality, and the availability of bicycle infrastructure are key drivers of demand for free-floating e-bike-sharing. Given the substantial differences in the service compared with traditional bicycle-sharing, a new fifth generation of bicycle-sharing schemes is proposed.

Modeling Crop Yield in West‐African Rainfed Agriculture Using Global and Local Spatial Regression

2013 ◽  
Vol 105 (4) ◽  
pp. 1177-1188 ◽  
Author(s):  
Muhammad Imran ◽  
Raul Zurita‐Milla ◽  
Alfred Stein
Keyword(s):  
Crop Yield ◽  
Spatial Regression ◽  
West African ◽  
Rainfed Agriculture ◽  
Global And Local

Public Engagement in Public Transportation Projects

2015 ◽  
Vol 2537 (1) ◽  
pp. 88-95 ◽  
Author(s):  
Jeffrey M. Casello ◽  
Will Towns ◽  
Julie Bélanger ◽  
Sanathan Kassiedass
Keyword(s):  
Public Engagement ◽  
Public Transportation ◽  
Wide Spectrum ◽  
Public Support ◽  
Daily Basis ◽  
Light Rail ◽  
Transit Planning ◽  
Public Investments ◽  
Direct Benefits ◽  
In Transit

Public participation for transit projects faces a number of unique challenges compared with many other similar public investments. For example, a smaller subset of the community uses transit on a daily basis as compared with highways; moreover, public transit is seen to be limited—both spatially and demographically—in its appeal. Combined, these factors can limit the widespread engagement of the public in the development and evaluation of transit projects. Further, given the lack of direct benefits from transit, it is often more difficult to garner public support for public transport projects. Specific considerations and techniques are demonstrated that can be undertaken by planners and policy makers to actively engage the community beyond those strongly in favor of or opposed to a transit project. Strategies employed in the Region of Waterloo, Ontario, Canada, in the context of public engagement before the introduction of light-rail transit are explored. In light of these strategies and the experiences of planners in Waterloo and in conjunction with evidence from the literature, a number of conclusions are drawn regarding an effective framework for engaging a wide spectrum of community members in transit planning.

scholarly journals Spatial and temporal analysis of the Human Immunodeficiency Virus (HIV) in an area of social vulnerability in Northeast Brazil

2020 ◽  
Vol 15 (2) ◽  
Author(s):  
Géssyca Cavalcante de Melo ◽  
Emilia Carolle Azevedo de Oliveira ◽  
Iane Brito Leal ◽  
Carolina Piedade Morais de Freitas Soares Silva ◽  
Roberta Andrade Beltrão ◽  
...  
Keyword(s):  
Human Immunodeficiency Virus ◽  
Hiv Infection ◽  
Incidence Rate ◽  
Spatial Regression ◽  
Public Health Problem ◽  
Infection Prevention And Control ◽  
Northeast Brazil ◽  
Hiv Incidence ◽  
Socioeconomic Indicators ◽  
Immunodeficiency Virus

Human Immunodeficiency Virus (HIV) infection still represents an important public health problem, because it involves clinical, epidemiological, social, economic and political issues. We analyzed the temporal and spatial pattern of the HIV incidence in an area of social inequality in northeast Brazil and its association with socioeconomic indicators. An ecological study was carried out with a focus on all HIV cases reported in Alagoas State, Northeast Brazil from 2007 to 2016 using its 102 municipalities as the units of our analysis. Data from the Brazilian information systems were used. Georeferenced data were analyzed using TerraView 4.2.2 software, QGis 2.18.2 and GeoDa 1.14.0. Time trend analyses were performed by the Joinpoint Regression software and the spatial analyses included the empirical Bayesian model and Moran autocorrelation. Spatial regression was used to determine the influence of space on HIV incidence rate and socioeconomic inequalities. There was an increasing trend of HIV rates, especially in the municipalities of the interior. Significant spatial correlations were observed with the formation of clusters with emphasis on the coast of the state and in tourist regions. Spatial regression explained 46% of the dependent variable. The HIV incidence rate was positively influenced by rate of primary health care units (p=0.00), and negatively by Gini index (p = 0.00) and proportion of heads of household without or low education (p=0.02). We conclude that the relationship found between indicators of better socioeconomic conditions and HIV infection suggests unequal access to the diagnosis of infection. Prevention and control strategies can be established according to each epidemiological reality.

scholarly journals Rekayasa Model Perencanaan Transportasi dalam Menciptakan Mobilitas yang Aman pada Masa Pandemi Covid 19 (Studi Kasus : Mobilitas Mahasiswa di Jawa Timur)

2021 ◽  
Vol 1 ◽  
pp. 191-198
Author(s):  
Alfiatus Aisyah Nurhidayah ◽  
Amanda Ristriana Pattisinai
Keyword(s):  
Public Transportation ◽  
Travel Behavior ◽  
Transportation Planning ◽  
Student Mobility ◽  
Planning Stage ◽  
Restriction Policy ◽  
Research Findings ◽  
Global And Local ◽  
The Impact ◽  
The City

The mobility restriction policy imposed in response to the increasing transmission of Covid-19 brought changes in people's travel behavior, both at the global and local levels. The four traditional models at the transportation planning stage became biased because the need for travel was different during this pandemic. This study aimed to create a modification of transportation planning, where the mobility continues to use the existing four-stage transportation planning model but at the same time ensures safety from the dangers of Covid-19 transmission. The survey was conducted online on students (N=100) spread across cities in East Java Province, where the impact of the COVID-19 pandemic in the implementation of higher education, especially student mobility. The research findings indicated that students still travel actively to universities. The student's motive for traveling was only because of important and urgent matters dominated by work and receiving news of death from family. In contrast, the majority used private vehicles, especially on trips within the city. However, the tendency to use public transportation when traveling long distances was also still in demand by respondents. 

scholarly journals Identifying Spatial Driving Factors of Energy and Water Consumption in the Context of Urban Transformation

2021 ◽  
Vol 13 (19) ◽  
pp. 10503
Author(s):  
I-Chun Chen ◽  
Kuang-Ly Cheng ◽  
Hwong-Wen Ma ◽  
Cathy C.W. Hung
Keyword(s):  
Water Consumption ◽  
Spatial Regression ◽  
Resource Consumption ◽  
Urban Transformation ◽  
Strong Positive Correlation ◽  
Domestic Water ◽  
Spatial And Temporal Scales ◽  
Urban Energy ◽  
Socio Economic Variables ◽  
Domestic Resource

Urban energy and water consumption varies substantially across spatial and temporal scales, which can be attributed to changes of socio-economic variables, especially for a city undergoing urban transformation. Understanding these variations in variables related to resource consumptions would be beneficial to regional resource utilization planning and policy implementation. A geographically weighted regression method with modified procedures was used to explore and visualize the relationships between socio-economic factors and spatial non-stationarity of urban resource consumption to enhance the reliability of predicted results, taking Taichung city with 29 districts as an example. The results indicate that there is a strong positive correlation between socio-economic context and domestic resource consumption, but that there are relatively weak correlations for industrial and agricultural resource consumption. In 2015, domestic water and energy consumption was driven by the number of enterprises followed by population and average income level (depending on the target districts and sectors). Domestic resource consumption is projected to increase by approximately 84% between 2015 and 2050. Again, the number of enterprises outperforms other factors to be the dominant variable responsible for the increase in resource consumption. Spatial regression analysis of non-stationarity resource consumption and its associated variables offers useful information that is helpful for targeting hotspots of dominant resource consumers and intervention measures.

scholarly journals Socioeconomic Status and Metabolic Syndrome in Southwest Iran: Results from Hoveyzeh Cohort Study(HCS)

2021 ◽  
Author(s):  
Nader Saki ◽  
Seyed Jalal Hashemi ◽  
Seyed Ahmad Hosseini ◽  
Zahra Rahimi ◽  
Fakher Rahim ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Cohort Study ◽  
Strong Predictor ◽  
Premature Mortality ◽  
Socioeconomic Indicators ◽  
Wealth Status ◽  
Face To Face ◽  
Townsend Score ◽  
Socioeconomic Data ◽  
Southwest Iran

Abstract BackgroundSocioeconomic status (SES) is a strong predictor of morbidity and premature mortality, especially non-communicable diseases (NCDs). However, the effect of these factors on Metabolic Syndrome (MetS) is not yet clear. This study is to assess the relationship between socioeconomic indicators and MetS.MethodsIn this prospective cohort study, 10009 people aged 35-70 years enrolled from May 2016 to August 2018. MetS was determined based on the standard national cholesterol education program (NCEP) - adult treatment panel III (ATP III) or NCEP-ATP III criteria. Demographics and socioeconomic data were gathered face to face by trained interviews. Also, lab, anthropometrics, and blood pressure measurements were assayed for participants. Logistic regression was used to estimate the association between SES and MetS, with adjustment of potential confounding variables. ResultsThe overall prevalence of MetS in participants was 39.1%. The crude odds ratios for all the assessed variables were statistically significant (p<0.05). After adjustment for age, sex, physical activity, smoking, and alcohol use as potential confounders, the results indicated significant direct independent associations between skill level (p=0.006) and Townsend index (p=0.002) with MetS, while no significant associations were seen between educational level and wealth status with MetS. ConclusionThe results of our study showed that SES is related to MetS. Among four assessed SES indicators, skilled levels and Townsend score had a stronger association with MetS. We recommend considering people’s SES when interventional programs are planning and conducting on MetS in each community.

scholarly journals Smart Privacy Protection for Location-Based Services using Queueing Modelling

2020 ◽  
Vol 184 ◽  
pp. 01066
Author(s):  
Chamana H Ram Sai Jeetesh ◽  
Yerubandi Sai Sriram ◽  
Kavitha Kayiram ◽  
V.N. Rama Devi
Keyword(s):  
Waiting Time ◽  
Privacy Protection ◽  
Smart Phone ◽  
User Profile ◽  
Location Based Services ◽  
Sensitive Information ◽  
Privacy Risk ◽  
Queuing Model ◽  
Digital Era ◽  
User Location

In the digital era, we are greatly dependent on the popular applications of the Location Based Services (LBS) in our day-to-day activities. The smart phone comes with a variety of applications which acquire the user location and build up user profile like the user activities, hobbies, places of visit, food orders etc. Such sensitive information in the LBS server can pose privacy risk for the user. To safe guard the user from such threat we propose a smart privacy protection technique in this paper that can conceal the user location when using the location based services. We adopt the generation of dummy locations to obfuscate the user original location from the LBS server. The server generates the result set for the dummy user locations. In this work we try to optimize the things at server as well as user ends with two objectives. The first goal is to work towards identifying the overlap in result sets and generate unique and reduced result set with which the communication load on the network can be reduced. The second goal is to prioritize the result set by Queuing model for the result set through which waiting time of the customer can be minimized. We have also illustrated that this model show good performance in terms of the reduced communication load through experimental results.

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