The Non-linear Health Consequences of Living in Larger Cities

The 15-minute city concept: The case study within a neighbourhood of Thessaloniki

Cities, crucial cultural hubs, mould individual and group identities. The global urban expansion, with over half the population in urban areas, presents interconnected challenges such as pollution, poverty, inequality, ageing infrastructure, resource overconsumption, land use changes, biodiversity impact and climate change. Addressing these demands ambitious actions targeting political, social and economic systems for transformative change. The theoretical framework guiding city transformation centres on an interdisciplinary approach influenced by the Smart and Green Transition. The '15-minute city' concept, emphasizing human scale and urban experience, proposes that cities enable residents to meet daily needs within a short walk or bike ride. The aim of this study was the exploration of its implementation in Greek cities, particularly Thessaloniki, which reveals inherent characteristics supporting the 15-minute concept. Through an interdisciplinary approach rooted in the Smart and Green Transition framework, the research provides concrete guidance for policymakers in tailoring urban planning strategies, allocating resources effectively and crafting policies conducive to successful and sustainable urban transformations. Moreover, prioritizing public engagement highlights the significance of community involvement in shaping urban development plans, ensuring that proposed initiatives align with residents' needs and desires. In essence, this research contributes tangible insights and actionable recommendations for Greek cities, paving the way for more liveable, resilient and sustainable urban environments.

First year of COVID-19 in Brazil: Factors associated with the spread of COVID-19 in small and large cities

AIM

To test the association between sociodemographic and social characteristics with COVID-19 cases and deaths in small and large Brazilian cities.

METHODS

This ecological study included COVID-19 data available in State Health Secretaries (managed by brasil.io API) and three national databases (IBGE, DATASUS and Embrapa). Temporal spread of COVID-19 in Brazil during the first year considered as outcome: a) days until 1st case in each city since 1st in the country; b) days until 1,000 cases/100,000 inhabitants since 1st case in each city; c) days until 1st death until 50 deaths/100,000 inhabitants. Covariates included geographic region, city social and environmental characteristics, housing conditions, job characteristics, socioeconomic and inequalities characteristics, and health services and coverage. The analysis were stratified by city size into small (<100,000 inhabitants) and large cities (≥100,00 inhabitants). Multiple linear regressions were performed to test associations of all covariates to adjust to potential confounders.

RESULTS

In small cities, the first cases were reported after 82.2 days and 1,000 cases/100,000 were reported after 117.8 days, whereas in large cities these milestones were reported after 32.1 and 127.7 days, respectively. For first death, small and large cities took 121.6 and 36.0 days, respectively. However, small cities were associated with more vulnerability factors to first case arrival in 1,000 cases/100,000 inhabitants, first death and 50 deaths/100,000 inhabitants. North and Northeast regions positively associated with faster COVID-19 incidence, whereas South and Southeast were least.

CONCLUSION

Social and built environment characteristics and inequalities were associated with COVID-19 cases spread and mortality incidence in Brazilian cities.

Associations between environmental perception and self-rated health in the city hierarchy of China: Findings from a national cross-sectional survey

Identifying environmental determinants of health and clarifying their variations is crucial for health promotion in different cities by providing tailored intervention strategies. Although the association between perceived urban environment and health (e.g., self-rated health) has been repeatedly explored, most studies have focused on cities of a specific size, and it is still unknown whether either significant environment variables or the magnitude of the association would vary across different-sized cities. This study investigated how perceived urban environment variables significantly associated with individuals' self-rated health varied from small cities to mega cities in China, based on a national survey including 5963 valid respondents. The results showed that the relationship between self-rated health and city size was U-shaped, with respondents in medium and large cities reporting a low-level self-rated health. Perceived greenness, public facilities, housing supply, and medical services were positively and significantly associated with self-rated health, with the odds ratio (OR) of 1.37 (95%CI: 1.29-1.46), 1.27 (95%CI: 1.19-1.35), 1.14 (95%CI: 1.09-1.20), and 1.17 (95%CI: 1.10-1.24), respectively. Furthermore, the magnitude of the association was significantly larger in mega cities. These findings provide useful evidence for promoting public health in cities of different sizes for achieving health equity and indicate that smaller cities and their health-supportive environment need further attention.

HIV and AIDS in the state of Paraná, Brazil, 2007-2022: trends and spatiotemporal distribution

OBJECTIVE

The aim of this study was to analyze the spatiotemporal evolution of the incidence rates of human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) in the state of Paraná, Brazil.

METHODS

An ecological study with an analytical component of time series analysis was conducted in the state of Paraná from 2007 to 2022. The data source was the Notifiable Diseases Information System. To study the trend, the Prais-Winsten generalized linear regression model was used by decomposing the time series, and for spatial analysis, the Moran's index was applied.

RESULTS

The total sample consisted of 50,676 HIV/AIDS records. The incidence rate showed an increasing trend, with an average growth of 2.14% [95% confidence interval - 95%CI 1.16-3.13] per month. From 2007 to 2014 and from 2015 to 2022, the average number of cases in the state was 105.64 and 159.20 per 100,000 inhabitants, respectively, with significant variation among municipalities. Spatial clusters of high risk persisted in the metropolitan region, the capital, and coastal areas, and a new cluster was observed in the northern region of the state.

CONCLUSION

The incidence rates of HIV/AIDS showed an upward trend over time. The number of cases varied considerably in some municipalities, especially in the coastal region. Spatial analysis revealed geospatial patterns of high risk in the main metropolitan areas of Paraná: Curitiba (including the coastal area), Londrina, and Maringá, which share characteristics such as a high degree of urbanization and ongoing economic development.

Does the population size of a city matter to its older adults' self-rated health? Results of China data analysis

Clarifying the association between city population size and older adults' health is vital in understanding the health disparity across different cities in China. Using a nationally representative dataset, this study employed Multilevel Mixed-effects Probit regression models and Sorting Analysis to elucidate this association, taking into account the sorting decisions made by older adults. The main results of the study include: (1) The association between city population size and the self-rated health of older adults shifts from a positive linear to an inverted U-shaped relationship once individual socioeconomic status is controlled for; the socioeconomic development of cities, intertwined with the growth of their populations, plays a pivotal role in yielding health benefits. (2) There is a sorting effect in older adults' residential decisions; compared to cities with over 5 million residents, unobserved factors result in smaller cities hosting more less-healthy older adults, which may cause overestimation of health benefits in cities with greater population size. (3) The evolving socioeconomic and human-made environment resulting from urban population growth introduces health risks for migratory older adults but yields benefits for those with local resident status who are male, aged over 70, and have lower living standards and socioeconomic status. And (4) The sorting effects are more pronounced among older adults with greater resources supporting their mobility or those without permanent local resident status. Thus, policymakers should adapt planning and development strategies to consider the intricate relationship between city population size and the health of older adults.

A scaling investigation of urban form features in Latin America cities

This paper examines scaling behaviors of urban landscape and street design metrics with respect to city population in Latin America. We used data from the SALURBAL project, which has compiled and harmonized data on health, social, and built environment for 371 Latin American cities above 100,000 inhabitants. These metrics included total urbanized area, effective mesh size, area in km2 and number of streets. We obtained scaling relations by regressing log(metric) on log (city population). The results show an overall sub-linear scaling behavior of most variables, indicating a relatively lower value of each variable in larger cities. We also explored the potential influence of colonization on the current built environment, by analyzing cities colonized by Portuguese (Brazilian cities) or Spaniards (Other cities in Latin America) separately. We found that the scaling behaviors are similar for both sets of cities.

Scaling law characteristics and spatiotemporal multicomponent analysis of syphilis from 2016 to 2022 in Zhejiang Province, China

Background

Syphilis has caused epidemics for hundreds of years, and the global syphilis situation remains serious. The reported incidence rate of syphilis in Zhejiang Province has ranked first in the province in terms of notifiable infectious diseases for many years and is the highest in China. This study attempts to use the scaling law theory to study the relationship between population size and different types of syphilis epidemics, while also exploring the main driving factors affecting the incidence of syphilis in different regions.

Methods

Data on syphilis cases and affected populations at the county level were obtained from the China Disease Control and Prevention Information System. The scaling relationship between different stages of syphilis and population size was explained by scaling law. The trend of the incidence from 2016 to 2022 was tested by the joinpoint regression. The index of distance between indices of simulation and observation (DISO) was applied to evaluate the overall performance of joinpoint regression model. Furthermore, a multivariate time series model was employed to identify the main driving components that affected the occurrence of syphilis at the county level. The p value less than 0.05 or confidence interval (CI) does not include 0 represented statistical significance for all the tests.

Results

From 2016 to 2022, a total of 204,719 cases of syphilis were reported in Zhejiang Province, including 2 deaths, all of which were congenital syphilis. Latent syphilis accounted for 79.47% of total syphilis cases. The annual percent change (APCs) of all types of syphilis, including primary syphilis, secondary syphilis, tertiary syphilis, congenital syphilis and latent syphilis, were - 21.70% (p < 0.001, 95% CI: -26.70 to -16.30), -16.80% (p < 0.001, 95% CI: -20.30 to -13.30), -8.70% (p < 0.001, 95% CI: -11.30 to -6.00), -39.00% (p = 0.001, 95% CI: -49.30 to -26.60) and - 7.10% (p = 0.008, 95% CI: -11.20 to -2.80), respectively. The combined scaling exponents of primary syphilis, secondary syphilis, tertiary syphilis, congenital syphilis and latent syphilis based on the random effects model were 0.95 (95% CI: 0.88 to 1.01), 1.14 (95% CI: 1.12 to 1.16), 0.43 (95% CI: 0.37 to 0.49), 0.0264 (95% CI: -0.0047 to 0.0575) and 0.88 (95% CI: 0.82 to 0.93), respectively. The overall average effect values of the endemic component, spatiotemporal component and autoregressive component for all counties were 0.24, 0.035 and 0.72, respectively. The values of the autoregressive component for most counties were greater than 0.7. The endemic component of the top 10 counties with the highest values was greater than 0.34. Two counties with value of the spatiotemporal component higher than 0.1 were Xihu landscape county and Shengsi county. From 2016 to 2022, the endemic and autoregressive components of each county showed obvious seasonal changes.

Conclusion

The scaling exponent had both temporal trend characteristics and significant heterogeneity in the association between each type of syphilis and population size. Primary syphilis and latent syphilis exhibited a linear pattern, secondary syphilis presented a superlinear pattern, and tertiary syphilis exhibited a sublinear pattern. This suggested that further prevention of infection and transmission among high-risk populations and improvement of diagnostic accuracy in underdeveloped areas is needed. The autoregressive components and the endemic components were the main driving factors that affected the occurrence of syphilis. Targeted prevention and control strategies must be developed based on the main driving modes of the epidemic in each county.

Crime, inequality and public health: a survey of emerging trends in urban data science

Urban agglomerations are constantly and rapidly evolving ecosystems, with globalization and increasing urbanization posing new challenges in sustainable urban development well summarized in the United Nations' Sustainable Development Goals (SDGs). The advent of the digital age generated by modern alternative data sources provides new tools to tackle these challenges with spatio-temporal scales that were previously unavailable with census statistics. In this review, we present how new digital data sources are employed to provide data-driven insights to study and track (i) urban crime and public safety; (ii) socioeconomic inequalities and segregation; and (iii) public health, with a particular focus on the city scale.

COVID-19 and the city: Did urbanized countries suffer more fatalities?

In this paper we derive a theoretical model of the spread of a viral infection which we use as basis for an estimation strategy to test four interrelated hypotheses on the relationship between country-level COVID-19 mortality rates and the extent of urban development. Using data covering 81 countries we find evidence that countries with a higher population density, a higher share of the urban population living in the largest city, and countries with a higher urbanization rate had on average the same or fewer COVID-19 fatalities compared to less urbanized countries in 2020. Even though COVID-19 spreads faster in cities, fatalities may be lower, conditional on economic development, trust in government, and a well-functioning health care system. Generally, urbanization and city development are associated with economic development: with the resources urbanized countries have, it is easier for them to manage and maintain stricter lockdowns, and to roll out effective pharmaceutical interventions.

Equity in Coverage of Local Cannabis Control Policies in California, 2020‒2021

Objectives. To assess whether cannabis control policies that may protect public health were adopted evenly across California localities with differing sociodemographic compositions. Methods. From November 2020 to January 2021, we measured cannabis control policies for 241 localities across California and linked them to data on the characteristics of the communities affected by these policies. We evaluated whether disadvantaged communities were more likely to allow cannabis businesses and less likely to be covered by policies designed to protect public health. Results. Localities with all-out bans on cannabis businesses (65% of localities) were disproportionately high-education (55.8% vs 50.5% with any college) and low-poverty (24.3% vs 34.2%), with fewer Black (4.4% vs 6.9%) and Latinx (45.6% vs 50.3%) residents. Among localities that allowed retail cannabis businesses (28%), there were more cannabis control policies in localities with more high-income and Black residents, although the specific policies varied. Conclusions. Cannabis control policies are unequally distributed across California localities. If these policies protect health, inequities may be exacerbated. Public Health Implications. Uniform adoption of recommended cannabis control policies may help limit any inequitable health impacts of cannabis legalization. (Am J Public Health. 2022;112(11):1640-1650. https://doi.org/10.2105/AJPH.2022.307041).

Heterogeneity in Disparities in Life Expectancy Across US Metropolitan Areas

BACKGROUND

Life expectancy in the United States has declined since 2014 but characterization of disparities within and across metropolitan areas of the country is lacking.

METHODS

Using census tract-level life expectancy from the 2010 to 2015 US Small-area Life Expectancy Estimates Project, we calculate 10 measures of total and income-based disparities in life expectancy at birth, age 25, and age 65 within and across 377 metropolitan statistical areas (MSAs) of the United States.

RESULTS

We found wide heterogeneity in disparities in life expectancy at birth across MSAs and regions: MSAs in the West show the narrowest disparities (absolute disparity: 8.7 years, relative disparity: 1.1), while MSAs in the South (absolute disparity: 9.1 years, relative disparity: 1.1) and Midwest (absolute disparity: 9.8 years, relative disparity: 1.1) have the widest life expectancy disparities. We also observed greater variability in life expectancy across MSAs for lower income census tracts (coefficient of variation [CoV] 3.7 for first vs. tenth decile of income) than for higher income census tracts (CoV 2.3). Finally, we found that a series of MSA-level variables, including larger MSAs and greater proportion college graduates, predicted wider life expectancy disparities for all age groups.

CONCLUSIONS

Sociodemographic and policy factors likely help explain variation in life expectancy disparities within and across metro areas.

Non-linear relations between life expectancy, socio-economic, and air pollution factors: a global assessment with spatial disparities

Influential factors of socio-economic and air pollution on life expectancy (LE) show complexity. The investigations of non-linear functions of LE, socio-economic, and air pollution factors have not been largely conducted, and spatial and temporal differences of the linear or non-linear relations between LE and the influential factors have been obscured across countries in the world. In this study, the non-linear relations between LE and factors of per capita gross national income (GNI_pc), urban population rate (UPR), and fine-particulate (PM_2.5) were estimated from 2000 to 2015 by using a generalized additive model (GAM). The collected data included the 219 countries and regions with sufficient data and covers the period 2000-2015. The results demonstrate that at the global level, the GNI_pc plays a stable and significant non-linear role in LE, while the non-linear relationships between UPR, PM_2.5, and LE are not significant. The temporal variation was further investigated that the non-linear effect of PM_2.5 on LE is gradually strengthened, and the non-linear effect of UPR on LE shows a weakened trend. However, GNI_pc always plays a significantly non-linear role in the LE level. Furthermore, the spatial difference in the non-linear relations among different continents is detected. In sum, it cannot be ignored the non-linear effects of socio-economic and air pollution factors on LE at a global scale and across different continents.

Urban Scaling of Health Outcomes: a Scoping Review

Urban scaling is a framework that describes how city-level characteristics scale with variations in city size. This scoping review mapped the existing evidence on the urban scaling of health outcomes to identify gaps and inform future research. Using a structured search strategy, we identified and reviewed a total of 102 studies, a majority set in high-income countries using diverse city definitions. We found several historical studies that examined the dynamic relationships between city size and mortality occurring during the nineteenth and early twentieth centuries. In more recent years, we documented heterogeneity in the relation between city size and health. Measles and influenza are influenced by city size in conjunction with other factors like geographic proximity, while STIs, HIV, and dengue tend to occur more frequently in larger cities. NCDs showed a heterogeneous pattern that depends on the specific outcome and context. Homicides and other crimes are more common in larger cities, suicides are more common in smaller cities, and traffic-related injuries show a less clear pattern that differs by context and type of injury. Future research should aim to understand the consequences of urban growth on health outcomes in low- and middle-income countries, capitalize on longitudinal designs, systematically adjust for covariates, and examine the implications of using different city definitions.

Urban scaling of opioid overdose deaths in the USA: a cross-sectional study in three periods between 2005 and 2017

OBJECTIVES

To describe the association between population size, population growth and opioid overdose deaths-overall and by type of opioid-in US commuting zones (CZs) in three periods between 2005 and 2017.

SETTINGS

741 CZs covering the entirety of the US CZs are aggregations of counties based on commuting patterns that reflect local economies.

PARTICIPANTS

We used mortality data at the county level from 2005 to 2017 from the National Center for Health Statistics.

OUTCOME

Opioid overdose deaths were defined using underlying and contributory causes of death codes from the International Classification of Diseases, 10th revision (ICD-10). We used the underlying cause of death to identify all drug poisoning deaths. Contributory cause of death was used to classify opioid overdose deaths according to the three major types of opioid, that is, prescription opioids, heroin and synthetic opioids other than methadone.

RESULTS

Opioid overdose deaths were disproportionally higher in largely populated CZs. A CZ with 1.0% larger population had 1.10%, 1.10%, and 1.16% higher opioid death count in 2005-2009, 2010-2014, and 2015-2017, respectively. This pattern was largely driven by a high number of deaths involving heroin and synthetic opioids, particularly in 2015-2017. Population growth over time was associated with lower age-adjusted opioid overdose mortality rate: a 1.0% increase in population over time was associated with 1.4% (95% CI: -2.8% to 0.1%), 4.5% (95% CI: -5.8% to -3.2%), and 1.2% (95% CI: -4.2% to 1.8%) lower opioid overdose mortality in 2005-2009, 2010-2014, and 2015-2017, respectively. The association between positive population growth and lower opioid mortality rates was stronger in larger CZs.

CONCLUSIONS

Opioid overdose mortality in the USA was disproportionately higher in mid-sized and large CZs, particularly those affected by declines in population over time, regardless of the region where they are located.

Scaling of mortality in 742 metropolitan areas of the Americas

We explored how mortality scales with city population size using vital registration and population data from 742 cities in 10 Latin American countries and the United States. We found that more populated cities had lower mortality (sublinear scaling), driven by a sublinear pattern in U.S. cities, while Latin American cities had similar mortality across city sizes. Sexually transmitted infections and homicides showed higher rates in larger cities (superlinear scaling). Tuberculosis mortality behaved sublinearly in U.S. and Mexican cities and superlinearly in other Latin American cities. Other communicable, maternal, neonatal, and nutritional deaths, and deaths due to noncommunicable diseases were generally sublinear in the United States and linear or superlinear in Latin America. Our findings reveal distinct patterns across the Americas, suggesting no universal relation between city size and mortality, pointing to the importance of understanding the processes that explain heterogeneity in scaling behavior or mortality to further advance urban health policies.

Urban scaling of opioid analgesic sales in the United States

Opioid misuse is a public health crisis in the United States. The origin of this crisis is associated with a sharp increase in opioid analgesic prescribing. We used the urban scaling framework to analyze opioid prescribing patterns in US commuting zones (CZs), i.e., groups of counties based on commuting patterns. The urban scaling framework postulates that a set of scaling relations can be used to predict health outcomes and behaviors in cities. We used data from the Drug Enforcement Administration’s Automated Reports and Consolidated Ordering System (ARCOS) to calculate counts of oxycodone/hydrocodone pills distributed to 607 CZs in the continental US from 2006 to 2014. We estimated the scaling coefficient of opioid pill counts by regressing log(pills) on log(population) using a piecewise linear spline with a single knot at 82,363. Our results show that CZs with populations below the knot scaled superlinearly (β = 1.36), i.e., larger CZs had disproportionally larger pill counts compared to smaller CZs. On the other hand, CZs with populations above the knot scaled sublinearly (β = 0.92), i.e., larger CZs had disproportionally smaller pill counts compared to smaller CZs. This dual scaling pattern was consistent across US census regions. For CZs with population below the knot, the superlinear scaling of pills is consistent with the explanation that an increased number of successful matches between prescribers and users will lead to higher prescribing rates. The non-linear scaling behavior observed could be the result of a combination of factors, including stronger health care systems and prescribing regulation in largely populated commuting zones, as well as high availability of other opioids such as heroin in these commuting zones. Future research should explore potential mechanisms for the non-linearity of prescription opioid pills.

Lockdown induced night-time light dynamics during the COVID-19 epidemic in global megacities

The lockdown of cities against the COVID-19 epidemic directly decreases urban socioeconomic activities. Remotely sensed night-time light (NTL) provides a macro perspective to capture these variations. Here, taking 20 global megacities as examples, we adopted the NASA's Black Marble NTL data with a daily resolution to investigate their spatio-temporal changes. We collected daily NTL products for four weeks (one month) before and after the date of lockdown in each city, which were then summarized as weekly and monthly averaged NTL images after pre-processing (cloud removing, outlier detection, etc.). Results show that NTL overall decreased after the lockdown of cities, but with regional disparities and varying spatial patterns. Asian cities experienced the most obvious reduction of NTL. Particularly, the monthly averaged NTL in Mumbai, India, decreased by nearly 20% compared to one month before. However, there was no significant decline in NTL in European cities. African cities also experienced stable changes of NTL. Spatially, city centers darkened more obviously than the urban periphery. Facing emergencies, NTL data has broad applications in monitoring socioeconomic dynamics and assessing public policies in a near real-time manner.

Estimating the drivers of urban economic complexity and their connection to economic performance

Estimating the capabilities, or inputs of production, that drive and constrain the economic development of urban areas has remained a challenging goal. We posit that capabilities are instantiated in the complexity and sophistication of urban activities, the know-how of individual workers, and the city-wide collective know-how. We derive a model that indicates how the value of these three quantities can be inferred from the probability that an individual in a city is employed in a given urban activity. We illustrate how to estimate empirically these variables using data on employment across industries and metropolitan statistical areas in the USA. We then show how the functional form of the probability function derived from our theory is statistically superior when compared with competing alternative models, and that it explains well-known results in the urban scaling and economic complexity literature. Finally, we show how the quantities are associated with metrics of economic performance, suggesting our theory can provide testable implications for why some cities are more prosperous than others.

Urban social determinants of non-communicable diseases risk factors in Argentina

We examined associations of individual-, neighborhood- and city-level education -as proxies of SES at different levels-, with diabetes, hypertension, obesity, smoking and binge drinking (non-communicable disease risk factors -NCD/RF) among Argentinian adults. We estimated mixed models based on 21,415 individuals from the 2013 National Survey of Risk Factors, living in 2,698 neighborhoods and 33 cities. Gradients by individual-level education differed by gender and NCD/RF, and some were modified by city education. In addition, we identified contextual effects of neighborhood and city education on some NCD/RF. Urban efforts to tackle NCD/RF in Argentina should be context- and gender-sensitive, and mainly focused on socially disadvantaged groups.

The scaling of social interactions across animal species

Social animals self-organise to create groups to increase protection against predators and productivity. One-to-one interactions are the building blocks of these emergent social structures and may correspond to friendship, grooming, communication, among other social relations. These structures should be robust to failures and provide efficient communication to compensate the costs of forming and maintaining the social contacts but the specific purpose of each social interaction regulates the evolution of the respective social networks. We collate 611 animal social networks and show that the number of social contacts E scales with group size N as a super-linear power-law [Formula: see text] for various species of animals, including humans, other mammals and non-mammals. We identify that the power-law exponent [Formula: see text] varies according to the social function of the interactions as [Formula: see text], with [Formula: see text]. By fitting a multi-layer model to our data, we observe that the cost to cross social groups also varies according to social function. Relatively low costs are observed for physical contact, grooming and group membership which lead to small groups with high and constant social clustering. Offline friendship has similar patterns while online friendship shows weak social structures. The intermediate case of spatial proximity (with [Formula: see text] and clustering dependency on network size quantitatively similar to friendship) suggests that proximity interactions may be as relevant for the spread of infectious diseases as for social processes like friendship.

Cost-Savings Associated with Reductions in Public Service Utilization with Provision of Permanent Supported Housing in Midsized City in the United States

Severe and persistent mental illnesses are frequently associated with homelessness and extensive use of public services. Cost savings after the provision of permanent supportive housing (PSH) have been examined in large metropolitan areas but not in medium-sized communities. Administrative and clinical data were collected to determine use of public services, such as use of emergency services, inpatient psychiatric and medical services, and correctional facilities, in the year preceding and the year subsequent to placement in PSH. Costs of the housing and the utilized services were also calculated. Ninety-one subjects were in housing first (HF) programs and 19 were in treatment first (TF) programs. Overall there was a net cost savings of over $1.2 million or $6134/consumer/year of PSH. Nearly all cost savings were in reduced service utilization which implies prevention of both medical and psychiatric morbidity. In HF the average per patient cost savings ($21,082.12) was not significantly greater than TF ($12,907.29; p = 0.33). Provision of PSH in a mid-sized city provides significant cost savings.

Associations of regional racial attitudes with chronic illness in the United States

RATIONALE

A growing body of literature has identified a robust relationship between the experience of racial discrimination and negative self-reported physical and mental health outcomes.

OBJECTIVE

The current study seeks to identify which factors -at the community level- predict racial disparities in actual disease manifestation. This study focuses on the extent to which regional demographics and racial attitudes, both implicit and explicit, are associated with prevalence rates of several diseases for Black and White patients in the United States.

METHODS

Implicit and explicit racial attitudes obtained from Project Implicit (Xu et al., 2017) were aggregated at the county level to predict variation in the prevalence rates of several chronic illnesses among Medicare recipients.

RESULTS

When controlling for economic indicators, Black and White patients who live in areas with high implicit and explicit racial bias tend to exhibit a higher incidence of chronic health problems, including cancer, stroke, asthma, diabetes, and heart failure. These relationships tended to be stronger for Black patients. Additionally, patients in racially diverse and racially segregated regions also tended to exhibit a higher incidence of chronic health problems.

CONCLUSION

Findings from the study highlight the reliable relationship between both racial biases and regional demographics and the incidence rates of several chronic diseases, particularly in Black patients.

An ecological study of the relationship between urban built environment and cardiovascular hospital admissions (2004-2016) in an Asian developing country

This study aims to evaluate the relationship between urban built environment and hospital admissions from cardiovascular diseases in Kuala Lumpur, Malaysia. Hospital admission data from 2004 to 2016 for cardiovascular diseases were used with patient residential postcodes as the unit of analysis. Data was split into 2004-2009 (12,551 cases) and 2010-2016 (17,154 cases) periods corresponding to land use data. We used generalized linear mixed model to analyse population density, property value, entropy index, and the kernel density (800 m) of specific land use, bus and rail stations, and road junctions, with time period and postcodes as the random effects to generate incidence rate ratios (IRRs). Results indicated that entropy index and recreational area density were associated with fewer hypertensive disease and ischemic heart disease hospital admissions (IRR range: 0.49-0.68, 95%CI: 0.27, 0.97). Population density and property value were associated with fewer cerebrovascular disease hospital admissions (IRR range: 0.29-0.34, 95%CI: 0.11, 0.75). Contrarily, density of road junctions was associated with 2.5-6.3 times more hospital admissions for cardiovascular disease hospital admissions (IRR range: 2.53-6.34, 95%CI: 1.07,17.91). There were no significant association between hospital admission and density of residential area, undeveloped land, rail and bus stations. The shapes of relationships for all attributes were non-linear, and changed markedly at the third quartile except for recreational area density. The findings suggest that land use attributes have some protective effects on the cardiovascular disease admission cases as compared to the transport attributes. These findings have important merits for integrating health into urban planning.

Understanding the role of urban design in disease spreading

Cities are complex systems whose characteristics impact the health of people who live in them. Nonetheless, urban determinants of health often vary within spatial scales smaller than the resolution of epidemiological datasets. Thus, as cities expand and their inequalities grow, the development of theoretical frameworks that explain health at the neighbourhood level is becoming increasingly critical. To this end, we developed a methodology that uses census data to introduce urban geography as a leading-order predictor in the spread of influenza-like pathogens. Here, we demonstrate our framework using neighbourhood-level census data for Guadalajara (GDL, Western Mexico). Our simulations show that daily mobility patterns can drive neighbourhood-level variations in the basic reproduction number R 0 , which in turn give rise to robust spatiotemporal patterns in the spread of disease. To generalize our results, we ran simulations in hypothetical cities with the same population, area, schools and businesses as GDL but different land use zoning. Experiments in these synthetic cities demonstrate that the agglomeration of daily activities can influence the growth rate, size and timing of urban epidemics. Overall, these findings support the view that cities can be redesigned to limit the geographical scope of influenza-like outbreaks.

City size and the spreading of COVID-19 in Brazil

The current outbreak of the coronavirus disease 2019 (COVID-19) is an unprecedented example of how fast an infectious disease can spread around the globe (especially in urban areas) and the enormous impact it causes on public health and socio-economic activities. Despite the recent surge of investigations about different aspects of the COVID-19 pandemic, we still know little about the effects of city size on the propagation of this disease in urban areas. Here we investigate how the number of cases and deaths by COVID-19 scale with the population of Brazilian cities. Our results indicate small towns are proportionally more affected by COVID-19 during the initial spread of the disease, such that the cumulative numbers of cases and deaths per capita initially decrease with population size. However, during the long-term course of the pandemic, this urban advantage vanishes and large cities start to exhibit higher incidence of cases and deaths, such that every 1% rise in population is associated with a 0.14% increase in the number of fatalities per capita after about four months since the first two daily deaths. We argue that these patterns may be related to the existence of proportionally more health infrastructure in the largest cities and a lower proportion of older adults in large urban areas. We also find the initial growth rate of cases and deaths to be higher in large cities; however, these growth rates tend to decrease in large cities and to increase in small ones over time.

On the relation between transversal and longitudinal scaling in cities

Does the scaling relationship between population sizes of cities with urban metrics like economic output and infrastructure (transversal scaling) mirror the evolution of individual cities in time (longitudinal scaling)? The answer to this question has important policy implications, but the lack of suitable data has so far hindered rigorous empirical tests. In this paper, we advance the debate by looking at the evolution of two urban variables, GDP and water network length, for over 5500 cities in Brazil. We find that longitudinal scaling exponents are city-specific. However, they are distributed around an average value that approaches the transversal scaling exponent provided that the data is decomposed to eliminate external factors, and only for cities with a sufficiently high growth rate. We also introduce a mathematical framework that connects the microscopic level to global behaviour, finding good agreement between theoretical predictions and empirical evidence in all analyzed cases. Our results add complexity to the idea that the longitudinal dynamics is a micro-scaling version of the transversal dynamics of the entire urban system. The longitudinal analysis can reveal differences in scaling behavior related to population size and nature of urban variables. Our approach also makes room for the role of external factors such as public policies and development, and opens up new possibilities in the research of the effects of scaling and contextual factors.

Urban scaling of health outcomes: a protocol for a scoping review

INTRODUCTION

With most of the world's population living in urban areas, it is important to understand the health effects of city living. Precise descriptions of the relations of city size and growth with population health metrics have not been systematically described. Describing these relationships can provide clues regarding the factors driving differences in health across cities.

OBJECTIVE

The goal of this scoping review is to map the existing evidence regarding the scaling properties of health outcomes, with a special emphasis on city size and growth.

METHOD AND ANALYSIS

We will conduct this scoping review based on a structured search of a combination of keywords for the exposures that aim to capture the population growth and size of cities along with degree of urbanisation, for health-related outcomes regardless of their type (incidence or prevalence of diseases and injuries and mortality). We will search the MEDLINE and Latin American & Caribbean Health Sciences Literature databases from inception for studies in English, Spanish or Portuguese and perform manual searches of references and citations in the included studies. The search will be conducted from April 2019 to September 2019. We will report results using the PRISMA-ScR guidelines. This review aims to inform future research on the role of increasing levels of urbanisation on health outcomes, provide clues into what city level factors may drive patterns of urban health and lead to the design and implementation of policies that promote sustainable growth and improved health.

ETHICS AND DISSEMINATION

This review will not collect any primary data and will rely on published articles. The findings of this review will be published in a peer-reviewed scientific journal.

Modeling the origin of urban-output scaling laws

Urban outputs often scale superlinearly with city population. A difficulty in understanding the mechanism of this phenomenon is that different outputs differ considerably in their scaling behaviors. Here, we formulate a physics-based model for the origin of superlinear scaling in urban outputs by treating human interaction as a random process. Our model suggests that the increased likelihood of finding required collaborations in a larger population can explain this superlinear scaling, which our model predicts to be non-power-law. Moreover, the extent of superlinearity should be greater for activities that require more collaborators. We test this model using a novel dataset for seven crime types and find strong support.

Does urbanization make emergence of zoonosis more likely? Evidence, myths and gaps

Rapid urbanization in the global South is adding epidemiological and nutritional challenges and increasing disease and health burdens for citizens. Greater movement of people, animals, food and trade often provides favourable grounds for the emergence of infectious diseases, including zoonoses. We conduct a rapid evidence scan to explore what is known and hypothesized about the links between urbanization and zoonosis emergence. This points to rapid demographic growth, migration and density, increased movement of people and animals, and changes in land uses as the main processes linked to the prevalence of zoonosis in the urban global South. We argue that this emerging global health challenge is also deeply connected with the urbanization of poverty and inequalities within cities. Tackling the micro-level causal relationships between urbanization and zoonosis requires urgent attention to living conditions, as well as the wider socioenvironmental transitions and structural drivers that produce and reproduce risk accumulation in urban settings.

Unveiling relationships between crime and property in England and Wales via density scale-adjusted metrics and network tools

Scale-adjusted metrics (SAMs) are a significant achievement of the urban scaling hypothesis. SAMs remove the inherent biases of per capita measures computed in the absence of isometric allometries. However, this approach is limited to urban areas, while a large portion of the world's population still lives outside cities and rural areas dominate land use worldwide. Here, we extend the concept of SAMs to population density scale-adjusted metrics (DSAMs) to reveal relationships among different types of crime and property metrics. Our approach allows all human environments to be considered, avoids problems in the definition of urban areas, and accounts for the heterogeneity of population distributions within urban regions. By combining DSAMs, cross-correlation, and complex network analysis, we find that crime and property types have intricate and hierarchically organized relationships leading to some striking conclusions. Drugs and burglary had uncorrelated DSAMs and, to the extent property transaction values are indicators of affluence, twelve out of fourteen crime metrics showed no evidence of specifically targeting affluence. Burglary and robbery were the most connected in our network analysis and the modular structures suggest an alternative to "zero-tolerance" policies by unveiling the crime and/or property types most likely to affect each other.

Spatial variations and determinants of infant and under-five mortality in Bangladesh

Reducing child mortality is a Sustainable Development Goal yet to be achieved by many low-income countries. We applied a subnational and spatial approach based on publicly available datasets and identified permanent insolvency, urbanicity, and malaria endemicity as factors associated with child mortality. We further detected spatial clusters in the east of Bangladesh and noted Sylhet and Jamalpur as those districts that need immediate attention to reduce child mortality. Our approach is transferable to other regions in comparable settings worldwide and may guide future studies to identify subnational regions in need for public health attention. Our study adds to our understanding where we may intervene to more effectively improve health, particularly among disadvantaged populations.

Spatial patterns of dengue cases in Brazil

Dengue infection plays a central role in our society, since it is the most prevalent vector-borne viral disease affecting humans. We statistically investigated patterns concerning the spatial spreading of dengue epidemics in Brazil, as well as their temporal evolution in all Brazilian municipalities for a period of 12 years. We showed that the distributions of cases in municipalities follow power laws persistent in time and that the infection scales linearly with the population of the municipalities. We also found that the average number of dengue cases does not have a clear dependence on the longitudinal position of municipalities. On the other hand, we found that the average distribution of cases varies with the latitudinal position of municipalities, displaying an almost constant growth from high latitudes until reaching the Tropic of Capricorn leveling to a plateau closer to the Equator. We also characterized the spatial correlation of the number of dengue cases between pairs of municipalities, where our results showed that the spatial correlation function decays with the increase of distance between municipalities, following a power-law with an exponential cut-off. This regime leads to a typical dengue traveling distance. Finally, we considered modeling this last behaviour within the framework of a Edwards-Wilkinson equation with a fractional derivative on space.

Geospatial analysis and distribution patterns of home nursing care in a metropolitan area - a large-scale analysis

AIMS

This study focuses on home nursing care distribution in an urban setting in Germany.

BACKGROUND

A shortage of nursing care workforce is present in Germany.

METHODS

A geospatial analysis was performed to examine distribution patterns at the district level in Frankfurt, Germany (n = 46 districts) and factors were analysed influencing the location choice of home nursing care providers (n = 151). Furthermore, within the analysis we focused on the population aged over 65 years to model the demand for nursing care.

RESULTS

The analysis revealed a tendency of home nursing care providers to be located near the city centre (centripetal distribution pattern). However, the demand for care showed more inconsistent patterns. Still, a centripetal distribution pattern of demand could be stated. Compared with the control groups (e.g. acute hospitals and pharmacies) similar geographical distribution patterns were present. However, the location of home nursing care providers was less influenced by demand compared with the control groups.

CONCLUSION

The supply of nursing care was unevenly distributed in this metropolitan setting, but still matched the demand for nursing care.

IMPLICATION FOR NURSING MANAGEMENT

Due to the rapidly changing health care environments policy, regulations must be (re-)evaluated critically to improve the management and delivery of nursing care provision.

Rural to Urban Population Density Scaling of Crime and Property Transactions in English and Welsh Parliamentary Constituencies

Urban population scaling of resource use, creativity metrics, and human behaviors has been widely studied. These studies have not looked in detail at the full range of human environments which represent a continuum from the most rural to heavily urban. We examined monthly police crime reports and property transaction values across all 573 Parliamentary Constituencies in England and Wales, finding that scaling models based on population density provided a far superior framework to traditional population scaling. We found four types of scaling: i) non-urban scaling in which a single power law explained the relationship between the metrics and population density from the most rural to heavily urban environments, ii) accelerated scaling in which high population density was associated with an increase in the power-law exponent, iii) inhibited scaling where the urban environment resulted in a reduction in the power-law exponent but remained positive, and iv) collapsed scaling where transition to the high density environment resulted in a negative scaling exponent. Urban scaling transitions, when observed, took place universally between 10 and 70 people per hectare. This study significantly refines our understanding of urban scaling, making clear that some of what has been previously ascribed to urban environments may simply be the high density portion of non-urban scaling. It also makes clear that some metrics undergo specific transitions in urban environments and these transitions can include negative scaling exponents indicative of collapse. This study gives promise of far more sophisticated scale adjusted metrics and indicates that studies of urban scaling represent a high density subsection of overall scaling relationships which continue into rural environments.