Urban scaling in Europe

Bettencourt, Luís M. A.; Lobo, José

doi:10.1098/rsif.2016.0005

Cited by 167 publications

(193 citation statements)

References 31 publications

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“…MAs are integrated labor markets circumscribing areas of work and residence for most of their inhabitants. For other definitions of cities, whether political or resulting from density thresholds, agglomeration effects may vanish or seem inconsistent, possibly because not all heterogeneity is included (38,39).…”

Section: Resultsmentioning

confidence: 99%

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Heterogeneity and scale of sustainable development in cities

Brelsford

Lobo

Hand

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

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166

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Rapid worldwide urbanization is at once the main cause and, potentially, the main solution to global sustainable development challenges. The growth of cities is typically associated with increases in socioeconomic productivity, but it also creates strong inequalities. Despite a growing body of evidence characterizing these heterogeneities in developed urban areas, not much is known systematically about their most extreme forms in developing cities and their consequences for sustainability. Here, we characterize the general patterns of income and access to services in a large number of developing cities, with an emphasis on an extensive, high-resolution analysis of the urban areas of Brazil and South Africa. We use detailed census data to construct sustainable development indices in hundreds of thousands of neighborhoods and show that their statistics are scale-dependent and point to the critical role of large cities in creating higher average incomes and greater access to services within their national context. We then quantify the general statistical trajectory toward universal basic service provision at different scales to show that it is characterized by varying levels of inequality, with initial increases in access being typically accompanied by growing disparities over characteristic spatial scales. These results demonstrate how extensions of these methods to other goals and data can be used over time and space to produce a simple but general quantitative assessment of progress toward internationally agreed sustainable development goals.neighborhoods | slums | urban services | spatial correlations | inequality T he current worldwide growth of cities presents at once an unprecedented historical opportunity for universal socioeconomic development and an immense challenge to global sustainability (1, 2). The mechanisms that generate improved living conditions and economic growth in cities-and that typically also increase overall energy and resource consumption-are still only partially understood (1-5) and remain hard to disentangle.Many recent studies have emphasized the environmental and geophysical adverse consequences of an increasing proportion of the planet's population living in cities and of the acceleration of this transformation in recent decades (6-8). The type and scope of these impacts vary but include air and water pollution, land-cover change, loss of natural habitats, strain on water resources, higher demand for energy, and rising greenhouse gas emissions (1,8,9).Conversely, the positive correlation between urbanization and many important dimensions of human development has also become increasingly clear. At the national level, the association between higher levels of urbanization and per capita economic productivity has been clear for some time (2). More recently, as city-scale data have become available, evidence has emerged for broader relationships between urbanization and better health, education, longer lifespans, and greater access to basic services, such as water or electricity, at lower...

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Section: Resultsmentioning

confidence: 99%

“…2A shows centered data, obtained by subtracting the average logarithmically transformed population and income (see ref. 39). …”

Section: Methodsmentioning

confidence: 99%

Heterogeneity and scale of sustainable development in cities

Brelsford

Lobo

Hand

et al. 2017

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

166

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“…In the same vein, the hypothesis raised by Bettencourt & Lobo [8] proposes a new explanation based fundamentally on network effects: the mere fact that individuals are spatially close to each other increases the number of potential encounters between them. Theoretically, the probability of encounters and interaction grows as the individuals get closer and this process lowers the transaction and communication costs.…”

Section: Introductionmentioning

confidence: 99%

A model of urban scaling laws based on distance dependent interactions

et al. 2017

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Socio-economic related properties of a city grow faster than a linear relationship with the population, in a log–log plot, the so-called superlinear scaling. Conversely, the larger a city, the more efficient it is in the use of its infrastructure, leading to a sublinear scaling on these variables. In this work, we addressed a simple explanation for those scaling laws in cities based on the interaction range between the citizens and on the fractal properties of the cities. To this purpose, we introduced a measure of social potential which captured the influence of social interaction on the economic performance and the benefits of amenities in the case of infrastructure offered by the city. We assumed that the population density depends on the fractal dimension and on the distance-dependent interactions between individuals. The model suggests that when the city interacts as a whole, and not just as a set of isolated parts, there is improvement of the socio-economic indicators. Moreover, the bigger the interaction range between citizens and amenities, the bigger the improvement of the socio-economic indicators and the lower the infrastructure costs of the city. We addressed how public policies could take advantage of these properties to improve cities development, minimizing negative effects. Furthermore, the model predicts that the sum of the scaling exponents of social-economic and infrastructure variables are 2, as observed in the literature. Simulations with an agent-based model are confronted with the theoretical approach and they are compatible with the empirical evidences.

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“…It is also necessary to estimate their accessibility and degree of activity. This is what our work did through this particular pathway [36][37][38].…”

Section: Discussionmentioning

confidence: 70%

Management of rare diseases of the Head, Neck and Teeth: results of a French population-based prospective 8-year study

Friedlander

Choquet

Galliani

et al. 2017

Orphanet J Rare Dis

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Background: In the last ten years, national rare disease networks have been established in France, including national centres of expertise and regional ones, with storage of patient data in a bioinformatics tool. The aim was to contribute to the development and evaluation of health strategies to improve the management of patients with rare diseases. The objective of this study has been to provide the first national-level data concerning rare diseases of the head, neck and teeth and to assess the balance between demand and supply of care in France. Methods: Centres of expertise for rare diseases record a minimum data set on their clinical cases, using a list of rare Head, Neck and Teeth diseases established in 2006. The present analysis focuses on 2008 to 2015 data based on the Orphanet nomenclature. Each rare disease RD "case" was defined by status "affected" and by the degree of diagnostic certainty, encoded as: confirmed, probable or non-classifiable. Analysed parameters, presented with their 95% confidence intervals using a Poisson model, were the following: time and age at diagnosis, proportions of crude and standardized RD prevalence by age, gender and geographical site. The criteria studied were the proportions of patients in Paris Region and the "included cases geography", in which these proportions were projected onto the other French Regions, adjusting for local populations.Results: In Paris Region, estimated prevalence of these diseases was 5.58 per 10,000 inhabitants (95% CI 4.3-7.1). At December 31st 2015, 11,342 patients were referenced in total in France, of whom 7294 were in Paris Region. More than 580 individual clinical entities (ORPHA code) were identified with their respective frequencies. Most abnormalities were diagnosed antenatally. Nearly 80% of patients recorded come to Paris hospitals to obtain either diagnosis, care or follow up. We observed that the rarer the disease, the more patients were referred to Paris hospitals. Conclusions:A health network covering a range of aspects of the rare diseases problematic from diagnostics to research has been developed in France. Despite this, there is still a noticeable imbalance between health care supply and demand in this area.

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Urban scaling in Europe

Cited by 167 publications

References 31 publications

Heterogeneity and scale of sustainable development in cities

Heterogeneity and scale of sustainable development in cities

A model of urban scaling laws based on distance dependent interactions

Management of rare diseases of the Head, Neck and Teeth: results of a French population-based prospective 8-year study

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