Background: A number of new technologies are under development for the control of mosquito transmitted viruses, such as dengue, chikungunya and Zika that all require the release of modified mosquitoes into the environment. None of these technologies has been able to demonstrate evidence that they can be implemented at a scale beyond small pilots. Here we report the first successful citywide scaled deployment of Wolbachia in the northern Australian city of Townsville. Methods: The wMel strain of Wolbachia was backcrossed into a local Aedes aegypti genotype and mass reared mosquitoes were deployed as eggs using mosquito release containers (MRCs). In initial stages these releases were undertaken by program staff but in later stages this was replaced by direct community release including the development of a school program that saw children undertake releases. Mosquito monitoring was undertaken with Biogents Sentinel (BGS) traps and individual mosquitoes were screened for the presence of Wolbachia with a Taqman qPCR or LAMP diagnostic assay. Dengue case notifications from Queensland Health Communicable Disease Branch were used to track dengue cases in the city before and after release. Results: Wolbachia was successfully established into local Ae. aegypti mosquitoes across 66 km 2 in four stages over 28 months with full community support. A feature of the program was the development of a scaled approach to community engagement. Wolbachia frequencies have remained stable since deployment and to date no local dengue transmission has been confirmed in any area of Townsville after Wolbachia has established, despite local transmission events every year for the prior 13 years and an epidemiological context of increasing imported cases. Conclusion: Deployment of Wolbachia into Ae. aegypti populations can be readily scaled to areas of ~60km 2 quickly and cost effectively and appears in this context to be effective at stopping local dengue transmission
Increasing the labour market participation of mothers is often seen as a solution to address skill shortages in countries with long child-related career interruptions. However, little is known about the leave-taking behaviour of parents with higher and lower skill levels. This study addresses that gap by examining how employment trajectories after the transition to parenthood vary by gender and skill level in Austria, which has one of the longest parental leave entitlements globally. We focus on understanding whether skill differences shape leave-taking and labour market re-entry, and to what extent they explain the large and persistent gender gaps in parental employment.
We use a new dataset that, for the first time, links Austrian administrative data on births and daily labour market activities (2009-2022) with tested skill scores from the OECD’s Programme for the International Assessment of Adult Competencies (PIAAC). Our main sample includes 5,130 Austrians born between 1942 and 1997. We focus on tested numeracy skills, which are strongly associated with employment and wages, offer a more precise measure of work-relevant skills than formal education, and account for important parts of the gender pay gap. Adopting a life-course perspective, we observe labour market patterns between the ages 20 and 70, and examine the three years before and after the birth of a first child to capture short- and medium-term dynamics.
We find clear differences by skill level. Higher-skilled women tend to return to employment more quickly and are more likely to use educational leave to extend their parental leave. Lower-skilled mothers, by contrast, experience longer periods out of the labour force. Among fathers, skill gradients are present as well: higher-skilled men are more likely to take parental leave than their lower-skilled counterparts, though leave uptake remains very low in absolute terms.
However, gender trumps skills. On average, mothers take 416 days of paid parental leave following the birth of their first child, while fathers take just nine days. Most mothers remain at home well beyond the period of paid leave, and part-time work is common upon return – regardless of skill level.
Our findings suggest that policies aimed at increasing female labour market participation − particularly among the skilled − face structural constraints. In a context of demographic ageing and rising skill shortages, improving access to early childcare and encouraging more balanced leave-taking may be necessary to reduce gender gaps and make better use of existing skills across the workforce.
Urban groups. The city. Urban sociology, City population. Including children in cities, immigration
Abstract Since 2002, Brazil has been granting refugee status on the grounds of sexual orientation and gender identity (SOGI). This topic has become more visible in the last few years due to the large flow of Venezuelans crossing the border, many of whom are not heterosexual and/or cisgender. However, there is an older, although less visible, flow of African people, mainly from Nigeria, Ghana, and Cameroon, who travel to Brazil in order to claim asylum because of their SOGI. Despite the fact that more research has been conducted recently on the intersection between migration and sexuality, most of this scholarship focuses on South-North movements, not South-South migrations with destinations such as Brazil. The aim of this article is to analyse the central role played by political and social (in)visibility of SOGI forced migrants in Brazil and the (dis)advantages provided by their (in)visibility. In order to do so, I draw on twelve months of ethnographic fieldwork in the city of São Paulo, which included participant observation and semi-structured interviews with SOGI forced migrants from African countries. I also draw on secondary data from ethnographies carried out with SOGI forced migrants from Venezuela in the cities of Boa Vista and Rio de Janeiro, as well as on official data published by the Brazilian government. My argument is that SOGI forced migrants play with their own (in)visibility, making strategic decisions before migrating to Brazil, during their journeys, and after their arrival in the country.
Abstract The rapid economic growth and urbanization have significantly increased geographic mobility among individuals and families. While international migration has long been a topic of debate, internal migrations are gaining increasing attention. Using data from China Migration Dynamic Survey, this paper pays special attention to the role of internal migration in educational attainment of the next generation. Specifically, by examining the migration-induced (non-)disruption in schooling, this study aims to control certain confounding factors and explore the role of migration timing as a potential missing link. The findings reveal that non-disruptive migration (before children aged 5) results in increased children’s schooling years for both left-behind children (LBC) and migrant children (MC). Conversely, disruptive migration tends to have no significant effects on children’s education in most cases. To bolster the robustness of these findings, an alternative sample of younger children aged 6–20 is constructed to assess potential dropout rates. Additionally, to address concerns regarding endogenous issues, we instrument the (non)disruption with the average (non-)disruption rate and the employment rate of the migration year in the hometown and destination respectively for MC and LBC. Meanwhile, propensity score matching (PSM) technique is employed to gauge the average treatment effect by comparing the disrupted and non-disrupted. The results consistently reaffirm the main findings, highlighting the importance of interventions to mitigate disadvantages associated with migration timing. In particular, policies should focus on children who experience migration during their schooling years and ensure supportive educational environments to minimize potential disruptions.
Abstract This paper explores the phenomenon of ‘high’ birth rates among Syrian refugees in Lebanon, framed as, in their own words, “a human instinctive response to a profound fear of extinction.” Drawing from the concept of existential anxiety, theories of trauma and cultural identity theory, as well as on qualitative data from interviews with 278 Syrian refugees, the study delves into the psychological and sociocultural factors that underpin this demographic trend. It highlights how, against the backdrop of protracted displacement and uncertainty, many Syrian refugees perceive high fertility as a strategy for cultural and familial survival. The paper examines the intersection of trauma, displacement, and reproductive behaviour, revealing a complex narrative where fears of loss, erasure, and the desire to preserve identity manifest through increased birth rates. This research contributes to a nuanced understanding of refugee experiences, shedding light on how existential fears shape reproductive decisions and challenging conventional perspectives on population growth within refugee communities.
A smart city is essential for sustainable urban development. In addition to citizen engagement, a smart city enables connected infrastructure, data-driven decision making and smart mobility. For most of these features, network data plays a critical role, particularly from public Wi-Fi infrastructures, where cities can benefit from optimized services such as public transport management and the safety and efficiency of large events. One of the biggest concerns in developing a smart city is using secure and private data. This is particularly relevant in the case of Wi-Fi network data, where sensitive information can be collected. This paper specifically addresses the problem of sharing secure data to enhance the quality of the Wi-Fi network in a city. Despite the high importance of this type of data, related work focuses on improving the safety of mobility patterns, targeting only the protection of MAC addresses. On the opposite side, we provide a practical methodology for safeguarding all attributes in real Wi-Fi network data. This study was developed in collaboration with a multidisciplinary team of legal experts, data custodians and technical privacy specialists, resulting in high-quality data. On top of that, we show how to integrate the legal considerations for secure data sharing. Our approach promotes data-driven innovation and privacy awareness in the context of smart city initiatives, which have been tested in a real scenario.
This study investigates blood lead level (BLL) rates and testing among children under six years of age across the 42 neighborhoods in New York City from 2005 to 2021. Despite a citywide general decline in BLL rates, disparities at the neighborhood level persist and are not addressed in the official reports, highlighting the need for this comprehensive analysis. In this paper, we analyze the current BLL testing distribution and cluster the neighborhoods using a k-medoids clustering algorithm. We propose an optimized approach that improves resource allocation efficiency by accounting for case incidences and neighborhood risk profiles using a grid search algorithm. Our findings demonstrate statistically significant improvements in case detection and enhanced fairness by focusing on under-served and high-risk groups. Additionally, we propose actionable recommendations to raise awareness among parents, including outreach at local daycare centers and kindergartens, among other venues.
Helge Ritter, Otthein Herzog, Kurt Rothermel
et al.
We attempt to take a comprehensive look at the challenges of representing the spatio-temporal structures and dynamic processes defining a city's overall characteristics. For the task of urban planning and urban operation, we take the stance that even if the necessary representations of these structures and processes can be achieved, the most important representation of the relevant mindsets of the citizens are, unfortunately, mostly neglected. After a review of major "traditional" urban models of structures behind urban scale, form, and dynamics, we turn to major recent modeling approaches triggered by recent advances in AI that enable multi-modal generative models. Some of these models can create representations of geometries, networks and images, and reason flexibly at a human-compatible semantic level. They provide huge amounts of knowledge extracted from Terabytes of text and image documents and cover the required rich representation spectrum including geographic knowledge by different knowledge sources, degrees of granularity and scales. We then discuss what these new opportunities mean for the modeling challenges posed by cities, in particular with regard to the role and impact of citizens and their interactions within the city infrastructure. We propose to integrate these possibilities with existing approaches, such as agent-based models, which opens up new modeling spaces including rich citizen models which are able to also represent social interactions. Finally, we put forward some thoughts about a vision of a "social AI in a city ecosystem" that adds relevant citizen models to state-of-the-art structural and process models. This extended city representation will enable urban planners to establish citizen-oriented planning of city infrastructures for human culture, city resilience and sustainability.
Are there multiple equilibria in the spatial economy? This paper develops a unified framework that integrates systems of cities and regional models to address this question within a general geographic space. A key feature is the endogenous formation of commuting areas linking a continuum of residential locations to a finite set of potential business districts. Using tools from computational geometry and shape optimization, we derive sufficient conditions for the existence and uniqueness of spatial equilibria. For plausible parameter values, urban location is indeterminate, but, conditional on an urban system, city sizes are uniquely determined. The framework reconciles seemingly conflicting empirical findings on the role of geography and scale economies in shaping the spatial economy.
<p dir="ltr">Fertility rates, especially in developed countries, are declining rapidly, and there is broad consensus that population size will also decline and age concurrently. This demographic shift is expected to produce a support crisis as the growing proportion of elderly individuals will place increasing demands on social and medical services. A solution often proposed is increased immigration, which can bolster the working-age population. A fundamental question that arises is “will there be enough immigrants, and from where? This paper, building on and expanding a 2000 study by the Guttmacher Institute, presents evidence that by 2050, higher-income and upper-middle income nations will be facing significant shortfalls of support cohort populations and will also be facing immigration deficits as well. This paper estimates population support ratios (PSR) available in 2050 for U.N. national and regional geographies. The PSR uses support cohort populations 15 to 64 year old and net migration forecasts made by the U.N. to estimate support population shortfalls by 2050. The PSR are the number of support (or working) population 15 to 64 years of age to the number of 65+ year old populations in U.N. geographic regions, subregions, and nations.</p>
Katherine O'Sullivan, J. Lumsden, Caroline Anderson
et al.
Linking data across local authorities and health boards has the potential to reduce inequalities and improve outcomes. However, cross-agency data sharing leads to complexities around data ownership, legal conditions for processing, organisational controls and risk assessments to ensure privacy and confidentiality of subjects whilst facilitating research and service improvements. We share a governance framework for cross-agency data sharing between a local authority and regional health board in Scotland. A cross-sector Child Neglect working group was established with representation from public sector agencies, the NHS, University researchers and a Trusted Research Environment to support research on children’s mental health prescribing and secondary specialist services provision and linking to the Aberdeen City Council Child Protection Register. Lessons learned were captured throughout the governance, data transfer and data linkage phases. Communication is the most important driver, with key individuals, deputies and routes of escalation agreed and involved throughout for clarity of roles and expectation setting. Key lessons learned include requiring input from all parties at the project initiation stage, particularly IG teams, including agreements on necessary templates. Knowledge exchange is required between the research team, data owners and data processors to ensure research protocol requirements are correctly understood and data transfer is supported. If possible, internal and/or external validation of data should also be performed before data is linked. Cross-agency data sharing is a vital means to understanding and improving outcomes for individuals and populations. Critical to this is establishing an action plan and formalised project process to achieve outcomes.
Abstract Climate change impacts are gendered. This is also true for climate-induced migration, which affects men and women differently. On account of this difference, legal instruments and policies seeking to address and support climate-induced migration need to be gender-focused to address differentiated needs and outcomes. This paper looks at existing policies and legal instruments for the inclusion of gender aspects of climate-related migration. We focus on Ethiopia, India, and Peru, all of them with developed instruments to address the human mobility-climate change nexus. We investigate the scope of provisions concerning gender in relevant instruments in the three country contexts, their likely impact to tackle gender-specific vulnerabilities arising with climate-induced migration and suggest strategies and priorities for enhancing gender-inclusion in policy development and application broadly.
The health of individuals is frequently assessed based on self-reported information derived from surveys. However, self-reports are often inconsistent with their tested equivalents, indicating measurement issues. While discrepancies between self-reported and tested health indicators have been investigated for high-income countries in Europe, little comparative research has been conducted involving other low-income regions. This paper analyses discrepancies between self-reported and tested health limitations across 25 countries from six world regions with different income-levels, cultural backgrounds, institutional settings, and epidemiological trajectories. Using harmonised data from the Gateway to Global Aging, we match self-reported mobility and cognition with their tested equivalent to assess discrepancies at the individual level. Our results suggest that the consistency between these measures is strongly correlated with the Human Development Index, with lower scores of development showing higher discrepancies. Examining patterns by age reveals that self-reports do not accurately reflect the deterioration of health associated with aging – tested health exhibits a pronounced age gradient, whereas self-reported health varies little over the life course, particularly self-reported memory. We find no persistent gender differences in consistency. These discrepancies cast doubt on the reliability of mobility and cognitive self-reports, especially when comparing health across nations with differing development levels.
* This article belongs to a special issue on “Levels and Trends of Health Expectancy: Understanding its Measurement and Estimation Sensitivity”.
Urban groups. The city. Urban sociology, City population. Including children in cities, immigration
City scene generation has gained significant attention in autonomous driving, smart city development, and traffic simulation. It helps enhance infrastructure planning and monitoring solutions. Existing methods have employed a two-stage process involving city layout generation, typically using Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), or Transformers, followed by neural rendering. These techniques often exhibit limited diversity and noticeable artifacts in the rendered city scenes. The rendered scenes lack variety, resembling the training images, resulting in monotonous styles. Additionally, these methods lack planning capabilities, leading to less realistic generated scenes. In this paper, we introduce CityCraft, an innovative framework designed to enhance both the diversity and quality of urban scene generation. Our approach integrates three key stages: initially, a diffusion transformer (DiT) model is deployed to generate diverse and controllable 2D city layouts. Subsequently, a Large Language Model(LLM) is utilized to strategically make land-use plans within these layouts based on user prompts and language guidelines. Based on the generated layout and city plan, we utilize the asset retrieval module and Blender for precise asset placement and scene construction. Furthermore, we contribute two new datasets to the field: 1)CityCraft-OSM dataset including 2D semantic layouts of urban areas, corresponding satellite images, and detailed annotations. 2) CityCraft-Buildings dataset, featuring thousands of diverse, high-quality 3D building assets. CityCraft achieves state-of-the-art performance in generating realistic 3D cities.
Understanding and predicting Origin-Destination (OD) flows is crucial for urban planning and transportation management. Traditional OD prediction models, while effective within single cities, often face limitations when applied across different cities due to varied traffic conditions, urban layouts, and socio-economic factors. In this paper, by employing Large Language Models (LLMs), we introduce a new method for cross-city OD flow prediction. Our approach leverages the advanced semantic understanding and contextual learning capabilities of LLMs to bridge the gap between cities with different characteristics, providing a robust and adaptable solution for accurate OD flow prediction that can be transferred from one city to another. Our novel framework involves four major components: collecting OD training datasets from a source city, instruction-tuning the LLMs, predicting destination POIs in a target city, and identifying the locations that best match the predicted destination POIs. We introduce a new loss function that integrates POI semantics and trip distance during training. By extracting high-quality semantic features from human mobility and POI data, the model understands spatial and functional relationships within urban spaces and captures interactions between individuals and various POIs. Extensive experimental results demonstrate the superiority of our approach over the state-of-the-art learning-based methods in cross-city OD flow prediction.
Migration research often focuses on exclusionary laws and social processes and how they impact children and the families they are embedded within. While important, this focus on harmful social structures can obscure forms of creative agency that are also inherent to young people’s migration, even in the face of racialized immigration policies that erect barriers to integration. In this theoretical article, we contend that spaces of belonging, where connection, sustenance, and recognition are readily available, are equally essential to immigrant youth and families’ experiences of migration. We conceptualize how these spaces are constructed at the relational, community, and national level, demonstrating how place, including physical, legal, political, and cultural geographies, shape these multilayered opportunities for belonging. First, we demonstrate how place informs the relationships that young people form with each other, with their families, and with other adults, and how the care that can emerge from these relationships is a critical foundation for spaces of belonging. Second, we articulate the conditions that enable spaces of belonging at the community level by examining how the geographic features of neighborhoods and cities shape young people’s opportunities for agency and recognition beyond their immediate relationships. Finally, we address the national-level dynamics that foster spaces of belonging, while attending to the reality that migrant young people and their families often live transnational lives across nation-state borders. This paper offers new ways of understanding how place informs migrant youth and children’s sense of inclusion and agency, illuminating how spaces of belonging at the relational, community, and national level support their dignity and well-being.
To assess perceptions of risk and related factors concerning COVID-19 epidemic among residents in Chongqing city, China. With convenience sampling, a web questionnaire survey was conducted among 476 residents living in Chongqing on February 13rd to 14th in 2020, when citizens just started to get back to work. Residents’ estimated perceived risks were (4.63 ± 0.57), (4.19 ± 0.76), (3.23 ± 0.91) and (2.29 ± 0.96) for the infectivity, pathogenicity, lethality and self-rated infection possibility of COVID-19, respectively. Females (OR = 4.234), people with income ≥ 2000 yuan (2000–4999 yuan: OR = 5.052, 5000–9999 yuan: OR = 4.301, ≥ 10,000 yuan: OR = 23.459), the married status (OR = 1.811), the divorced status, widows or widowers (OR = 3.038), people living with families including children (OR = 5.085) or chronic patients (OR = 2.423) had a higher perceived risk level, as well as people who used free media websites (OR = 1.756), community workers (OR = 4.064) or community information platforms (OR = 2.235) as main media information sources. The perceived risk increased by 4.9% for every one-year increase of age. People who used WeChat contacts (OR = 0.196) as the main media information source, reported a lower perceived risk. Residents reported a high level of risk perception towards COVID-19 in Chongqing and it was impacted by the population demographic characteristics. Media information sources, including community information platforms and community workers may cause the increase of public risk perceptions.
The current article contributes to the discussion on the trajectories of the economic integration of immigrants in adverse, informal contexts. Specifically, it explores the processes of the generation and application of business resources among Central Asian migrant entrepreneurs in Russia. This study highlights the crucial and multifaceted importance of former employment for migrant entrepreneurs. With restricted access to resources in Russia, Central Asian migrants deliberately used their workplaces to access business knowledge, networks and financial capital. By applying these resources, they replicated the successful business models of their former employers. This integration path appears to be shaped by the ambivalent forces of informality in the Russian economy.
Colonies and colonization. Emigration and immigration. International migration, City population. Including children in cities, immigration
Procedurally generating cities in Minecraft provides players more diverse scenarios and could help understand and improve the design of cities in other digital worlds and the real world. This paper presents a city generator that was submitted as an entry to the 2023 Edition of Minecraft Settlement Generation Competition for Minecraft. The generation procedure is composed of six main steps, namely vegetation clearing, terrain reshaping, building layout generation, route planning, streetlight placement, and wall construction. Three algorithms, including a heuristic-based algorithm, an evolving layout algorithm, and a random one are applied to generate the building layout, thus determining where to place different redstone style buildings, and tested by generating cities on random maps in limited time. Experimental results show that the heuristic-based algorithm is capable of finding an acceptable building layout faster for flat maps, while the evolving layout algorithm performs better in evolving layout for rugged maps. A user study is conducted to compare our generator with outstanding entries of the competition's 2022 edition using the competition's evaluation criteria and shows that our generator performs well in the adaptation and functionality criteria
The focus of this article is on falling birthrates in developed nations, and it examines the underlying causes, consequences, and initiatives taken to address it. It covers a variety of topics, including political science, international relations, and other subjects in addition to economics and demographics. The effects of low fertility are discussed, along with how they affect household income, capital growth, and automation. Gender variations are also evaluated. The essay also discusses the U.S.-centered national policy and its effects on things like taxes and aging.Since the detriments outweigh the benefits, the policy needs to be implemented. The three policies (immigration, automation, and baby care) directly or implicitly increase fertility and thus social productivity, while generating a set of issues that need to be refined. In general, the aging situation and the population density of cities may be compromised by the implementation of the policies and produce multiplier effects. In general, rising fertility adds varied amounts of stress to each family. And somehow, by implementing childcare programs, strain on women will be substantially less and their productivity will rise to some level. In the long run, the government will also generate more fiscal revenue due to the increase in personal income tax, which boosts social welfare and raises government input. The effects are favorable for social productivity and employment rates. The senior population has improved security, and the pension shortfall is partially closed.