Universal patterns of long-distance commuting and social assortativity in cities

Bokányi, Eszter; Juhász, Sándor; Karsai, Márton; Lengyel, Balázs

doi:10.1038/s41598-021-00416-1

Cited by 18 publications

(20 citation statements)

References 55 publications

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“…The fraction of workers who have their homes in the same district is very close to the census data in the outer districts (15)(16)(17)(18)(19)(20)(21)(22)(23) but generally overestimated in the core districts (1, 5-9) and the inner districts (2)(3)(4)(10)(11)(12)(13)(14). The workers from other district groups show the best match to the census data (where the CDR should have the best quality), while the agglomeration is somewhat overestimated in many districts.…”

Section: Validation By Censussupporting

confidence: 57%

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Commuting Analysis of the Budapest Metropolitan Area using Mobile Network Data

Pintér¹,

Felde²

2022

Preprint

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The analysis of the human movement patterns based on the mobile network data makes it possible to examine a very large population cost-effectively, and led to several discoveries about human dynamics. However, the application of this data source is still not common practice. The goal of this study was to analyze the commuting tendencies of the Budapest Metropolitan Area using mobile network data and propose an automatized alternative to the current, questionnaire-based method. Commuting is predominantly analyzed by the census, but that is performed only once in a decade in Hungary. To analyze commuting, the home and the work locations of the subscribers are determined based on their appearances during and outside the working hours. The home locations were compared to census data at a settlement level. Then, the settlement and district level commuting tendencies were identified and compared to the findings of census-based sociological studies. It has been found that commuting analysis based on mobile network data strongly correlates with the census-based findings, even though home and work locations have been estimated by statistical methods. All the examined aspects, including commuting from sectors of the agglomeration to the districts of Budapest and demographic distribution of the commuters, show that mobile network data can be an automatized, fast, cost-effective, and relatively accurate way of commuting analysis, that could provide a powerful tool to the sociologists interested in commuting.

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Section: Validation By Censussupporting

confidence: 57%

“…Since these locations fundamentally determine the people's mobility customs, the commuting trends can be analyzed between these locations. The commuting is studied, using mobile network data, within a city [7,8], or between cities [9][10][11], and also examined by social network data, such as Twitter [12,13].…”

Section: Literature Reviewmentioning

confidence: 99%

Commuting Analysis of the Budapest Metropolitan Area using Mobile Network Data

Pintér¹,

Felde²

2022

Preprint

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“…As we have discussed, signatures of segregation can be associated to strong diagonal elements in these matrices, indicating that people of a given SES are the most likely to visit places associated with the same or similar SES, as compared to random visiting patterns. To quantify the strength of diagonal concentration of visiting probabilities, we measure the diagonality index of the normalised stratification matrices [46], which is similar to the assortativity coefficient used by others [5,47]. It is defined as the Pearson correlation coefficient of matrix entries as…”

Section: Mobility Mixing and Segregated Residencesmentioning

confidence: 99%

Socioeconomic biases in urban mixing patterns of US metropolitan areas

2022

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Urban areas serve as melting pots of people with diverse socioeconomic backgrounds, who may not only be segregated but have characteristic mobility patterns in the city. While mobility is driven by individual needs and preferences, the specific choice of venues to visit is usually constrained by the socioeconomic status of people. The complex interplay between people and places they visit, given their personal attributes and homophily leaning, is a key mechanism behind the emergence of socioeconomic stratification patterns ultimately leading to urban segregation at large. Here we investigate mixing patterns of mobility in the twenty largest cities of the United States by coupling individual check-in data from the social location platform Foursquare with census information from the American Community Survey. We find strong signs of stratification indicating that people mostly visit places in their own socioeconomic class, occasionally visiting locations from higher classes. The intensity of this ‘upwards bias’ increases with socioeconomic status and correlates with standard measures of racial residential segregation. Our results suggest an even stronger socioeconomic segregation in individual mobility than one would expect from system-level distributions, shedding further light on uneven mobility mixing patterns in cities.

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“…Literature on contact patterns across socioeconomic groups is limited. However, it is known that workplace and housing environments differ for low and high SES [74,75], SES groups tend to have more mobility within-group than outside of their group [9,76], and low SES groups have not been as able to reduce their mobility during the pandemic (e.g. [2,10]).…”

Section: Mechanistic Modelmentioning

confidence: 99%

Quantifying the impact of SARS-CoV-2 temporal vaccination trends and disparities on disease control

Larsen

Shin

Joseph

et al. 2023

Preprint

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SARS-CoV-2 vaccines were developed and distributed during a global crisis at unprecedented speed. Still, little is known about trends in vaccine uptake over time, their association with socioeconomic inequality, and the impact of these temporal trends on disease control. By analyzing data from dozens of countries, we examined vaccination rates across high and low socioeconomic (SES) groups, showing that socioeconomic disparities in the fraction of the population vaccinated exist at both national and sub-national levels. We also identified two distinct vaccination trends: one characterized by rapid initial roll-out, quickly reaching a plateau; and another trend that is sigmoidal and slow to begin. Informed by these patterns, we implemented an SES-stratified mechanistic model, finding profound differences across the two vaccination types in the burden of infections and deaths. The timing of initial roll-out has a more significant effect on transmission and deaths than the eventual level of coverage or the degree of SES disparity. Surprisingly, the speed of the roll-out is not associated with wealth inequality or GDP per capita of countries. While socioeconomic disparity should be addressed, accelerating the initial roll-out for all groups is a broadly accessible intervention and has the potential to minimize the burden of infections and deaths across socioeconomic groups.

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Universal patterns of long-distance commuting and social assortativity in cities

Cited by 18 publications

References 55 publications

Commuting Analysis of the Budapest Metropolitan Area using Mobile Network Data

Commuting Analysis of the Budapest Metropolitan Area using Mobile Network Data

Socioeconomic biases in urban mixing patterns of US metropolitan areas

Quantifying the impact of SARS-CoV-2 temporal vaccination trends and disparities on disease control

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