A global metagenomic map of urban microbiomes and antimicrobial resistance.

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.

Elevated rates of horizontal gene transfer in the industrialized human microbiome.

Industrialization has impacted the human gut ecosystem, resulting in altered microbiome composition and diversity. Whether bacterial genomes may also adapt to the industrialization of their host populations remains largely unexplored. Here, we investigate the extent to which the rates and targets of horizontal gene transfer (HGT) vary across thousands of bacterial strains from 15 human populations spanning a range of industrialization. We show that HGTs have accumulated in the microbiome over recent host generations and that HGT occurs at high frequency within individuals. Comparison across human populations reveals that industrialized lifestyles are associated with higher HGT rates and that the functions of HGTs are related to the level of host industrialization. Our results suggest that gut bacteria continuously acquire new functionality based on host lifestyle and that high rates of HGT may be a recent development in human history linked to industrialization.

Diminishing benefits of urban living for children and adolescents' growth and development.

Optimal growth and development in childhood and adolescence is crucial for lifelong health and well-being1-6. Here we used data from 2,325 population-based studies, with measurements of height and weight from 71 million participants, to report the height and body-mass index (BMI) of children and adolescents aged 5-19 years on the basis of rural and urban place of residence in 200 countries and territories from 1990 to 2020. In 1990, children and adolescents residing in cities were taller than their rural counterparts in all but a few high-income countries. By 2020, the urban height advantage became smaller in most countries, and in many high-income western countries it reversed into a small urban-based disadvantage. The exception was for boys in most countries in sub-Saharan Africa and in some countries in Oceania, south Asia and the region of central Asia, Middle East and north Africa. In these countries, successive cohorts of boys from rural places either did not gain height or possibly became shorter, and hence fell further behind their urban peers. The difference between the age-standardized mean BMI of children in urban and rural areas was <1.1 kg m-2 in the vast majority of countries. Within this small range, BMI increased slightly more in cities than in rural areas, except in south Asia, sub-Saharan Africa and some countries in central and eastern Europe. Our results show that in much of the world, the growth and developmental advantages of living in cities have diminished in the twenty-first century, whereas in much of sub-Saharan Africa they have amplified.

Human mobility networks reveal increased segregation in large cities.

A long-standing expectation is that large, dense and cosmopolitan areas support socioeconomic mixing and exposure among diverse individuals1-6. Assessing this hypothesis has been difficult because previous measures of socioeconomic mixing have relied on static residential housing data rather than real-life exposures among people at work, in places of leisure and in home neighbourhoods7,8. Here we develop a measure of exposure segregation that captures the socioeconomic diversity of these everyday encounters. Using mobile phone mobility data to represent 1.6 billion real-world exposures among 9.6 million people in the United States, we measure exposure segregation across 382 metropolitan statistical areas (MSAs) and 2,829 counties. We find that exposure segregation is 67% higher in the ten largest MSAs than in small MSAs with fewer than 100,000 residents. This means that, contrary to expectations, residents of large cosmopolitan areas have less exposure to a socioeconomically diverse range of individuals. Second, we find that the increased socioeconomic segregation in large cities arises because they offer a greater choice of differentiated spaces targeted to specific socioeconomic groups. Third, we find that this segregation-increasing effect is countered when a city's hubs (such as shopping centres) are positioned to bridge diverse neighbourhoods and therefore attract people of all socioeconomic statuses. Our findings challenge a long-standing conjecture in human geography and highlight how urban design can both prevent and facilitate encounters among diverse individuals.

Increased heat risk in wet climate induced by urban humid heat.

Cities are generally warmer than their adjacent rural land, a phenomenon known as the urban heat island (UHI). Often accompanying the UHI effect is another phenomenon called the urban dry island (UDI), whereby the humidity of urban land is lower than that of the surrounding rural land1-3. The UHI exacerbates heat stress on urban residents4,5, whereas the UDI may instead provide relief because the human body can cope with hot conditions better at lower humidity through perspiration6,7. The relative balance between the UHI and the UDI-as measured by changes in the wet-bulb temperature (Tw)-is a key yet largely unknown determinant of human heat stress in urban climates. Here we show that Tw is reduced in cities in dry and moderately wet climates, where the UDI more than offsets the UHI, but increased in wet climates (summer precipitation of more than 570 millimetres). Our results arise from analysis of urban and rural weather station data across the world and calculations with an urban climate model. In wet climates, the urban daytime Tw is 0.17 ± 0.14 degrees Celsius (mean ± 1 standard deviation) higher than rural Tw in the summer, primarily because of a weaker dynamic mixing in urban air. This Tw increment is small, but because of the high background Tw in wet climates, it is enough to cause two to six extra dangerous heat-stress days per summer for urban residents under current climate conditions. The risk of extreme humid heat is projected to increase in the future, and these urban effects may further amplify the risk.

Repeated cross-sectional sero-monitoring of SARS-CoV-2 in New York City.

In late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first detected in China and has since caused a pandemic of coronavirus disease 2019 (COVID-19). The first case of COVID-19 in New York City was officially confirmed on 1 March 2020 followed by a severe local epidemic1. Here, to understand seroprevalence dynamics, we conduct a retrospective, repeated cross-sectional analysis of anti-SARS-CoV-2 spike antibodies in weekly intervals from the beginning of February to July 2020 using more than 10,000 plasma samples from patients at Mount Sinai Hospital in New York City. We describe the dynamics of seroprevalence in an 'urgent care' group, which is enriched in cases of COVID-19 during the epidemic, and a 'routine care' group, which more closely represents the general population. Seroprevalence increased at different rates in both groups; seropositive samples were found as early as mid-February, and levelled out at slightly above 20% in both groups after the epidemic wave subsided by the end of May. From May to July, seroprevalence remained stable, suggesting lasting antibody levels in the population. Our data suggest that SARS-CoV-2 was introduced in New York City earlier than previously documented and describe the dynamics of seroconversion over the full course of the first wave of the pandemic in a major metropolitan area.

Burden of Typhoid and Paratyphoid Fever in India.

BACKGROUND: In 2017, more than half the cases of typhoid fever worldwide were projected to have occurred in India. In the absence of contemporary population-based data, it is unclear whether declining trends of hospitalization for typhoid in India reflect increased antibiotic treatment or a true reduction in infection. METHODS: From 2017 through 2020, we conducted weekly surveillance for acute febrile illness and measured the incidence of typhoid fever (as confirmed on blood culture) in a prospective cohort of children between the ages of 6 months and 14 years at three urban sites and one rural site in India. At an additional urban site and five rural sites, we combined blood-culture testing of hospitalized patients who had a fever with survey data regarding health care use to estimate incidence in the community. RESULTS: A total of 24,062 children who were enrolled in four cohorts contributed 46,959 child-years of observation. Among these children, 299 culture-confirmed typhoid cases were recorded, with an incidence per 100,000 child-years of 576 to 1173 cases in urban sites and 35 in rural Pune. The estimated incidence of typhoid fever from hospital surveillance ranged from 12 to 1622 cases per 100,000 child-years among children between the ages of 6 months and 14 years and from 108 to 970 cases per 100,000 person-years among those who were 15 years of age or older. Salmonella enterica serovar Paratyphi was isolated from 33 children, for an overall incidence of 68 cases per 100,000 child-years after adjustment for age. CONCLUSIONS: The incidence of typhoid fever in urban India remains high, with generally lower estimates of incidence in most rural areas. (Funded by the Bill and Melinda Gates Foundation; NSSEFI Clinical Trials Registry of India number, CTRI/2017/09/009719; ISRCTN registry number, ISRCTN72938224.).

Cancer Screening after the Adoption of Paid-Sick-Leave Mandates.

BACKGROUND: By the end of 2022, nearly 20 million workers in the United States have gained paid-sick-leave coverage from mandates that require employers to provide benefits to qualified workers, including paid time off for the use of preventive services. Although the lack of paid-sick-leave coverage may hinder access to preventive care, current evidence is insufficient to draw meaningful conclusions about its relationship to cancer screening. METHODS: We examined the association between paid-sick-leave mandates and screening for breast and colorectal cancers by comparing changes in 12- and 24-month rates of colorectal-cancer screening and mammography between workers residing in metropolitan statistical areas (MSAs) that have been affected by paid-sick-leave mandates (exposed MSAs) and workers residing in unexposed MSAs. The comparisons were conducted with the use of administrative medical-claims data for approximately 2 million private-sector employees from 2012 through 2019. RESULTS: Paid-sick-leave mandates were present in 61 MSAs in our sample. Screening rates were similar in the exposed and unexposed MSAs before mandate adoption. In the adjusted analysis, cancer-screening rates were higher among workers residing in exposed MSAs than among those in unexposed MSAs by 1.31 percentage points (95% confidence interval [CI], 0.28 to 2.34) for 12-month colorectal cancer screening, 1.56 percentage points (95% CI, 0.33 to 2.79) for 24-month colorectal cancer screening, 1.22 percentage points (95% CI, -0.20 to 2.64) for 12-month mammography, and 2.07 percentage points (95% CI, 0.15 to 3.99) for 24-month mammography. CONCLUSIONS: In a sample of private-sector workers in the United States, cancer-screening rates were higher among those residing in MSAs exposed to paid-sick-leave mandates than among those residing in unexposed MSAs. Our results suggest that a lack of paid-sick-leave coverage presents a barrier to cancer screening. (Funded by the National Cancer Institute.).

The growth equation of cities.

The science of cities seeks to understand and explain regularities observed in the world's major urban systems. Modelling the population evolution of cities is at the core of this science and of all urban studies. Quantitatively, the most fundamental problem is to understand the hierarchical organization of city population and the statistical occurrence of megacities. This was first thought to be described by a universal principle known as Zipf's law1,2; however, the validity of this model has been challenged by recent empirical studies3,4. A theoretical model must also be able to explain the relatively frequent rises and falls of cities and civilizations5, but despite many attempts6-10 these fundamental questions have not yet been satisfactorily answered. Here we introduce a stochastic equation for modelling population growth in cities, constructed from an empirical analysis of recent datasets (for Canada, France, the UK and the USA). This model reveals how rare, but large, interurban migratory shocks dominate city growth. This equation predicts a complex shape for the distribution of city populations and shows that, owing to finite-time effects, Zipf's law does not hold in general, implying a more complex organization of cities. It also predicts the existence of multiple temporal variations in the city hierarchy, in agreement with observations5. Our result underlines the importance of rare events in the evolution of complex systems11 and, at a more practical level, in urban planning.

Sources of particulate-matter air pollution and its oxidative potential in Europe.

Particulate matter is a component of ambient air pollution that has been linked to millions of annual premature deaths globally1-3. Assessments of the chronic and acute effects of particulate matter on human health tend to be based on mass concentration, with particle size and composition also thought to play a part4. Oxidative potential has been suggested to be one of the many possible drivers of the acute health effects of particulate matter, but the link remains uncertain5-8. Studies investigating the particulate-matter components that manifest an oxidative activity have yielded conflicting results7. In consequence, there is still much to be learned about the sources of particulate matter that may control the oxidative potential concentration7. Here we use field observations and air-quality modelling to quantify the major primary and secondary sources of particulate matter and of oxidative potential in Europe. We find that secondary inorganic components, crustal material and secondary biogenic organic aerosols control the mass concentration of particulate matter. By contrast, oxidative potential concentration is associated mostly with anthropogenic sources, in particular with fine-mode secondary organic aerosols largely from residential biomass burning and coarse-mode metals from vehicular non-exhaust emissions. Our results suggest that mitigation strategies aimed at reducing the mass concentrations of particulate matter alone may not reduce the oxidative potential concentration. If the oxidative potential can be linked to major health impacts, it may be more effective to control specific sources of particulate matter rather than overall particulate mass.

Universal abundance fluctuations across microbial communities, tropical forests, and urban populations.

The growth of complex populations, such as microbial communities, forests, and cities, occurs over vastly different spatial and temporal scales. Although research in different fields has developed detailed, system-specific models to understand each individual system, a unified analysis of different complex populations is lacking; such an analysis could deepen our understanding of each system and facilitate cross-pollination of tools and insights across fields. Here, we use a shared framework to analyze time-series data of the human gut microbiome, tropical forest, and urban employment. We demonstrate that a single, three-parameter model of stochastic population dynamics can reproduce the empirical distributions of population abundances and fluctuations in all three datasets. The three parameters characterizing a species measure its mean abundance, deterministic stability, and stochasticity. Our analysis reveals that, despite the vast differences in scale, all three systems occupy a similar region of parameter space when time is measured in generations. In other words, although the fluctuations observed in these systems may appear different, this difference is primarily due to the different physical timescales associated with each system. Further, we show that the distribution of temporal abundance fluctuations is described by just two parameters and derive a two-parameter functional form for abundance fluctuations to improve risk estimation and forecasting.

Transposable element variants and their potential adaptive impact in urban populations of the malaria vector Anopheles coluzzii.

Anopheles coluzzii is one of the primary vectors of human malaria in sub-Saharan Africa. Recently, it has spread into the main cities of Central Africa threatening vector control programs. The adaptation of An. coluzzii to urban environments partly results from an increased tolerance to organic pollution and insecticides. Some of the molecular mechanisms for ecological adaptation are known, but the role of transposable elements (TEs) in the adaptive processes of this species has not been studied yet. As a first step toward assessing the role of TEs in rapid urban adaptation, we sequenced using long reads six An. coluzzii genomes from natural breeding sites in two major Central Africa cities. We de novo annotated TEs in these genomes and in an additional high-quality An. coluzzii genome, and we identified 64 new TE families. TEs were nonrandomly distributed throughout the genome with significant differences in the number of insertions of several superfamilies across the studied genomes. We identified seven putatively active families with insertions near genes with functions related to vectorial capacity, and several TEs that may provide promoter and transcription factor binding sites to insecticide resistance and immune-related genes. Overall, the analysis of multiple high-quality genomes allowed us to generate the most comprehensive TE annotation in this species to date and identify several TE insertions that could potentially impact both genome architecture and the regulation of functionally relevant genes. These results provide a basis for future studies of the impact of TEs on the biology of An. coluzzii.

People's desire to be in nature and how they experience it are partially heritable.

Nature experiences have been linked to mental and physical health. Despite the importance of understanding what determines individual variation in nature experience, the role of genes has been overlooked. Here, using a twin design (TwinsUK, number of individuals = 2,306), we investigate the genetic and environmental contributions to a person's nature orientation, opportunity (living in less urbanized areas), and different dimensions of nature experience (frequency and duration of public nature space visits and frequency and duration of garden visits). We estimate moderate heritability of nature orientation (46%) and nature experiences (48% for frequency of public nature space visits, 34% for frequency of garden visits, and 38% for duration of garden visits) and show their genetic components partially overlap. We also find that the environmental influences on nature experiences are moderated by the level of urbanization of the home district. Our study demonstrates genetic contributions to individuals' nature experiences, opening a new dimension for the study of human-nature interactions.

Magnitude of urban heat islands largely explained by climate and population.

Urban heat islands (UHIs) exacerbate the risk of heat-related mortality associated with global climate change. The intensity of UHIs varies with population size and mean annual precipitation, but a unifying explanation for this variation is lacking, and there are no geographically targeted guidelines for heat mitigation. Here we analyse summertime differences between urban and rural surface temperatures (ΔTs) worldwide and find a nonlinear increase in ΔTs with precipitation that is controlled by water or energy limitations on evapotranspiration and that modulates the scaling of ΔTs with city size. We introduce a coarse-grained model that links population, background climate, and UHI intensity, and show that urban-rural differences in evapotranspiration and convection efficiency are the main determinants of warming. The direct implication of these nonlinearities is that mitigation strategies aimed at increasing green cover and albedo are more efficient in dry regions, whereas the challenge of cooling tropical cities will require innovative solutions.

Rising rural body-mass index is the main driver of the global obesity epidemic in adults.

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities1,2. This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity3-6. Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.

Environmental inequality in the neighborhood networks of urban mobility in US cities.

Research has made clear that neighborhoods impact the health and well-being of their residents. A related strand of research shows that neighborhood disadvantage is geographically clustered. Because the neighborhoods of low-income and minority populations tend to be more disadvantaged, neighborhood conditions help explain racial and socioeconomic inequalities. These strands of research restrict processes of neighborhood influence to operate only within and between geographically contiguous neighbors. However, we are underestimating the role of neighborhood conditions in explaining inequality if disadvantage extends beyond the residential and extralocal environments into a network of neighborhoods spanning the urban landscape based on where residents move within a city. I use anonymized mobile phone data to measure exposure to air pollution among residents of poor and minority neighborhoods in 88 of the most populous US cities. I find that residents from minority and poor neighborhoods travel to neighborhoods that have greater air pollution levels than the neighborhoods that residents from White and nonpoor neighborhoods visit. Hispanic neighborhoods exhibit the greatest overall pollution burden, Black/White and Asian/White disparities are greatest at the network than residential scale, and the socioeconomic advantage of lower risk exposure is highest for residents from White neighborhoods. These inequalities are notable given recent declines in segregation and air pollution levels in American cities.

Systemic racism alters wildlife genetic diversity.

In the United States, systemic racism has had lasting effects on the structure of cities, specifically due to government-mandated redlining policies that produced racially segregated neighborhoods that persist today. However, it is not known whether varying habitat structures and natural resource availability associated with racial segregation affect the demographics and evolution of urban wildlife populations. To address this question, we repurposed and reanalyzed publicly archived nuclear genetic data from 7,698 individuals spanning 39 terrestrial vertebrate species sampled in 268 urban locations throughout the United States. We found generally consistent patterns of reduced genetic diversity and decreased connectivity in neighborhoods with fewer White residents, likely because of environmental differences across these neighborhoods. The strength of relationships between the racial composition of neighborhoods, genetic diversity, and differentiation tended to be weak relative to other factors affecting genetic diversity, possibly in part due to the recency of environmental pressures on urban wildlife populations. However, the consistency of the direction of effects across disparate taxa suggest that systemic racism alters the demography of urban wildlife populations in ways that generally limit population sizes and negatively affect their chances of persistence. Our results thus support the idea that limited capacity to support large, well-connected wildlife populations reduces access to nature and builds on existing environmental inequities shouldered by predominantly non-White neighborhoods.

Early-life nasal microbiota dynamics relate to longitudinal respiratory phenotypes in urban children.

BACKGROUND: Five distinct respiratory phenotypes based on latent classes of longitudinal patterns of wheezing, allergic sensitization. and pulmonary function measured in urban children from ages from 0 to 7 years have previously been described. OBJECTIVE: Our aim was to determine whether distinct respiratory phenotypes are associated with early-life upper respiratory microbiota development and environmental microbial exposures. METHODS: Microbiota profiling was performed using 16S ribosomal RNA-based sequencing of nasal samples collected at age 12 months (n = 120) or age 36 months (n = 142) and paired house dust samples collected at 3 months (12-month, n = 73; 36-month, n = 90) from all 4 centers in the Urban Environment and Childhood Asthma (URECA) cohort. RESULTS: In these high-risk urban children, nasal microbiota increased in diversity between ages 12 and 36 months (ß = 2.04; P = .006). Age-related changes in microbiota evenness differed significantly by respiratory phenotypes (interaction P = .0007), increasing most in the transient wheeze group. At age 12 months, respiratory illness (R2 = 0.055; P = .0001) and dominant bacterial genus (R2 = 0.59; P = .0001) explained variance in nasal microbiota composition, and enrichment of Moraxella and Haemophilus members was associated with both transient and high-wheeze respiratory phenotypes. By age 36 months, nasal microbiota was significantly associated with respiratory phenotypes (R2 = 0.019; P = .0376), and Moraxella-dominated microbiota was associated specifically with atopy-associated phenotypes. Analysis of paired house dust and nasal samples indicated that 12 month olds with low wheeze and atopy incidence exhibited the largest number of shared bacterial taxa with their environment. CONCLUSION: Nasal microbiota development over the course of early childhood and composition at age 3 years are associated with longitudinal respiratory phenotypes. These data provide evidence supporting an early-life window of airway microbiota development that is influenced by environmental microbial exposures in infancy and associates with wheeze- and atopy-associated respiratory phenotypes through age 7 years.