BackgroundPulmonary embolism (PE) and cerebrovascular disease are major global causes of mortality and may share common risk factors. This study analyzed U.S. all-cause mortality trends where PE and cerebrovascular diseases were recorded on the death certificate from 1999 to 2023.MethodsUsing national all-cause mortality data for adults aged over 25 years whose death certificates recorded both PE (ICD-10 I26) and cerebrovascular diseases (ICD-10 I60–I69), we calculated age-adjusted mortality rates (AAMRs), standardized to the 2000 U.S. population. Joinpoint regression was applied to identify significant trends and compute annual and average annual percent changes (APC and AAPC). Subgroup analyses were performed by sex, age, race, region, and urbanization level.ResultsBetween 1999 and 2023, 59,075 U.S. deaths involved both pulmonary embolism and cerebrovascular disease, with 4,274 recorded in 2023. Age-adjusted mortality increased from 1.00 to 1.55 per 100,000 (AAPC: 1.93%), accelerating sharply during 2018–2021. Higher AAMR was observed in males, adults over 85 years, Non-Hispanic Black individuals, residents of the South, and non-metropolitan areas. Substantial geographic heterogeneity existed, with states such as Minnesota, Washington, Massachusetts, and Florida showing significant long-term upward trends.ConclusionThe accelerating mortality and pronounced disparities across demographic and geographic groups highlight the need for more precise public health strategies. Mitigating this burden requires targeted interventions for high-risk populations, equity-focused policies, improved healthcare access, geriatric-sensitive care, and strengthened infrastructure in vulnerable regions.
BackgroundInfective endocarditis (IE) remains a life-threatening condition associated with substantial mortality. Over recent decades, evolving risk factors and treatment practices, yet contemporary population-level mortality patterns and the impact of the COVID-19 pandemic remain incompletely understood.MethodsWe analyzed national mortality data for IE in the United States from 1999 to 2023 using the National Vital Statistics System. Age-adjusted mortality rates (AAMRs) were calculated per 100,000 population standardized to the 2000 U.S. population. Analyses were stratified by sex, age, race/ethnicity, region, and urban–rural classification. Age–period–cohort models were used to explore temporal patterns, and excess mortality during 2019–2023 was estimated by extrapolating pre-pandemic (1999–2018) log-linear trends.ResultsFrom 1999 to 2023, IE deaths increased from 5,580 to 6,901, while the AAMR declined from 3.16 to 2.58 per 100,000 (AAPC −0.78%, 95% CI −1.11 to −0.44). Declines were greater among women (AAPC −1.09%) than men (−0.55%), and in metropolitan areas compared with rural counties. Hispanic and Asian/Pacific Islander populations experienced the largest declines, whereas non-Hispanic Black adults showed slower improvements. During 2019–2023, 34,601 deaths were observed vs. 35,926 expected, corresponding to a difference of −1,325 deaths (−3.7%). Age–period–cohort analysis revealed a pandemic-related period effect with short-term increases in mortality during 2020–2021, and a cohort effect indicating attenuated long-term declines among younger adults (25–44 years).ConclusionsMortality from IE in the United States has declined overall since 1999, but disparities persist across sex, geography, urban–rural status, and race/ethnicity. Pandemic-related disruptions produced a discernible period effect, while younger cohorts demonstrated slower long-term improvements.
Diseases of the circulatory (Cardiovascular) system
This thesis reconceptualizes American metropolitan areas as dissipative thermodynamic structures governed by non-equilibrium dynamics. Drawing on process philosophy, non-equilibrium thermodynamics, and information geometry, I analyze 386 MSAs using publicly US Census data from 2006–2024 (2020 excluded due to data disruption).I found that among 102 major US MSAs, 9 (8.5%) meet all criteria for confirmed dissipative structures, with 46.2% operating in the dissipative regime; 340 MSAs (88%) exhibit predominantly geodesic demographic trajectories with a mean geodesic efficiency η of 72.6%. Furthermore, only one manifold tearing event was found to have occurred (2008 Financial Crisis), creating societal transformative changes; But 95.6% of MSAs showed adiabatic (resilient) responses to the 2008 crisis and 91.3% to COVID-19, with zero non-adiabatic classifications. Validation confirms non-equilibrium dynamics (p=0.023).The findings challenge equilibrium-based urban planning, suggesting policy should focus on managing flows and enabling adaptive capacity rather than optimizing fixed forms. A surprising result was the universal adiabatic response of all major MSAs surveyed, suggest great resilience in medium to large American cities while refuting the “urban doom” thesis following the COVID-19 pandemic.All source codes are available at: http://github.com/rogerwzeng/dissipative-urbanismKeywords: dissipative structures, non-equilibrium thermodynamics, information geometry, urban complexity, process philosophy, metropolitan dynamics, demographic flows
This research examines how neuropedagogy and adaptive technologies can transform language education in Algeria. The investigation focuses on applying findings from cognitive neuroscience, particularly memory, attention, and motivational processes, to design differentiated teaching protocols. The integration of self-adaptive computational systems enables continuous optimization of learning trajectories, thereby enhancing accessibility and pedagogical performance. The research contextualizes these innovations within Algeria’s sociolinguistic configuration, characterized by the institutional coexistence of Arabic, Tamazight, French, and English, while accounting for infrastructural asymmetries between metropolitan and peripheral areas. It explores the potential of collaborative digital platforms and mobile applications as drivers for reducing educational inequalities. Drawing on international comparative analysis, this investigation offers recommendations for the systematic incorporation of these pedagogical innovations into Algeria’s educational ecosystem. It also addresses the ethical considerations inherent in managing personal data and mitigating systemic algorithmic biases, with a focus on fostering responsible and sustainable implementation.
In recent years, many European countries have experienced growing disparities
between urban and rural areas. These disparities are associated not only with differences in
infrastructure, public goods and cultural provision, but also with heterogeneous demographic
developments. In this paper, we intersect the perspectives of spatial demography, urban geography and social stratification by examining whether spatial inequalities between educational
groups have increased in six European countries since the turn of the millennium. Analytically,
we focus on (a) the educational composition of metropolitan and rural populations and (b) the
residential patterns of educational groups. The empirical analyses using European Social Survey (ESS) data suggest that while there are no systematic changes over the two-decade study
period, patterns of residential disparities differ considerably across the analysed countries. In
particular, France and Sweden emerge as countries with significant differences in residential
location between educational groups. At the same time, there is no evidence that the educational
gradient of place of residence is stronger among the younger than the older age groups.
Abstract Background Enhancing the retention of medical professionals in regional, rural and remote (RRR) areas requires a multi-faceted strategy that acknowledges and addresses the contextual barriers doctors face when deciding whether to continue practising in RRR hospitals. Gaining a deeper understanding of these factors can inform evidence-based workforce planning and policy development to mitigate the rural physician shortage across Australia. This study aimed to explore motivators and perceived barriers among junior medical doctors when choosing their training location- whether in RRR hospitals or metropolitan settings- during the early years of postgraduate training. Methods A qualitative study was conducted using virtual one-on-one interviews. The setting included four Hospital and Health Services (HHSs) in Northern Queensland, Australia (Townsville, Cairns, Mackay and North West). Participants were doctors in training from intern level to postgraduate year 5 (including prevocational and early vocational doctors). Twenty-five interviews were transcribed verbatim. Data were thematically analysed, through an inductive approach. Results Most participants were female (n = 19) and aged under 29 years (n = 21). The motivations for choosing RRR hospitals among most Australian-trained doctors included proximity to family, a desire for adventure, rural upbringing, peer recommendations, and the availability of benefits through incentivisation schemes. For many recently graduated doctors, regional hospitals were considered the “right size”, offering a broad range of specialties without feeling lost in the crowd often associated with larger metropolitan hospitals. Barriers included limited job opportunities in rural settings, challenges in securing preferred rotations, social isolation, lack of camaraderie in the workplace, and the cost of living. Conclusion This study provides valuable insights into the key pull and push factors influencing doctors’ decisions to train/ work in RRR areas. At both the HHS and national levels, these findings can help guide decision-makers and employers on where to invest to positively influence doctors’ choices regarding training and practice locations. A multifaceted approach is needed, with interventions tailored to doctors’ specific needs, particularly those that support family life, increase rural exposure, and offer competitive remuneration.
Shravani Banerjee, Diksha Diksha, Alisha Prasad
et al.
The study investigates the physical, social, and economic environment of the Kolkata Metropolitan Area (KMA) to elucidate the living conditions of informal settlements and its influence on the local environment using geoinformatics and multi-criteria decision making-analytical hierarchical process (MCDM-AHP). The informal settlements were delineated using high-resolution Google Earth imagery and generic ontology informal settlements. knowledge considering building characteristics, building density, locations of the dwelling units, and their characteristics. The study exhibits that most informal settlements were concentrated in the wards located in the eastern and central parts of the city. The neighborhood land-use functions of the major informal settlements indicated that the informal settlements were highly influenced by green space (R2=0.97), followed by water bodies (R2=0.74), unplanned settlement (R2=0.68) and planned settlement (R2=0.67) in KMA. In addition, the informal settlements were closely associated with very low relief zones (3m to 13m) followed by moderate relief zones (13-23m). The municipal ward-level analysis of the physical-socio-economic health conditions exhibited that most of the areas located in the low vulnerable zones (53.71 km2; primarily in southern, and eastern periphery), followed by very highly vulnerable zones (43.09 km2; primarily in central and northern parts). The study provides an insight into urban areas with special reference to informal settlements and necessitates the implication of effective policy for poverty alleviation. This study encourages the availability of real-time data that can improve mitigation activities in the event of a health disaster, such as SARS COVID-19 through methods for qualitative investigation of disadvantaged locations in Kolkata.
ABSTRACTWe investigate the impact of NO2 emissions reduction on O3 and CH4 levels in 14 metropolitan areas of Japan in 2020. To account for meteorological variations, we employ business-as-usual air quality time series generated by machine learning models. Additionally, we use satellite observations and biogeochemical model simulations to analyse air quality changes. During the lockdown period from April 7 to May 25 in 2020, we observed a NO2 reduction that equated to a decrease equivalent to 3.4 and 5 years of the corresponding trends in roadside and ambient air quality recorded from 2010 to 2019. After meteorological normalization, NO2 decreased by 14.5% at ambient air stations and 19.1% at roadside stations. Surprisingly, the NO2 reduction did not immediately lead to increased O3. Instead, O3 levels rose after the lockdown, specifically in August due to favorable sunny conditions. This finding is important for Japan and has not been reported in previous studies. We found that changes in NO2 and CO marginally contributed to variations in CH4 levels across the study areas. It is recommended to simultaneously reduce NOx as well as non-methane volatile organic compounds to mitigate their adverse effects on future policies.
Maria Angelica Carrillo, Rocio Cardenas, Johanna Yañez
et al.
Abstract Background Arbovirus diseases such as dengue, Zika, and chikungunya are a public health threat in tropical and subtropical areas. In the absence of a vaccine or specific treatment, vector management (in this case the control of the primary vector Aedes aegypti) is the best practice to prevent the three diseases. A good understanding of vector behaviour, ecology, human mobility and water use can help design effective vector control programmes. This study collected baseline information on these factors for identifying the arbovirus transmission risk and assessed the requirements for a large intervention trial in Colombia. Methods Baseline surveys were conducted in 5,997 households, randomly selected from 24 clusters (neighbourhoods with on average 2000 houses and 250 households inspected) in the metropolitan area of Cucuta, Colombia. The study established population characteristics including water management and mobility as well as larval-pupal indices which were estimated and compared in all clusters. Additionally, the study estimated disease incidence from two sources: self-reported dengue cases in the household survey and cases notified by the national surveillance system. Results In all 24 study clusters similar social and demographic characteristics were found but the entomological indicators and estimated disease incidence rates varied. The entomological indicators showed a high vector infestation: House Index = 25.1%, Container Index = 12.3% and Breteau Index = 29.6. Pupae per person Index (PPI) as an indicator of the transmission risk showed a large range from 0.22 to 2.04 indicating a high transmission risk in most clusters. The concrete ground tanks for laundry –mostly outdoors and uncovered- were the containers with the highest production of Ae. aegypti as 86.3% of all 17,613 pupae were identified in these containers. Also, the annual incidence of dengue was high: 841.6 self-reported cases per 100,000 inhabitants and the dengue incidence notified by the National surveillance system was 1,013.4 cases per 100,000 in 2019. Only 2.2% of the households used container water for drinking. 40.3% of the study population travelled during the day (when Aedes mosquitoes bite) outside their clusters. Conclusions The production of Ae. aegypti mosquitoes occurred almost exclusively in concrete ground tanks for laundry (lavadero), the primary intervention target. The baseline study provides necessary evidence for the design and implementation of a cluster randomized intervention trial in Colombia.
Urban spatial elements present agglomeration and dispersion geographic processes in the urban development. Identifying the characteristics of their distribution changes and accurately capturing the evolution of the urban spatial structure is of great significance to urban construction and management. This study takes Wuhan as a case study and focuses on the spatial agglomeration distribution of urban elements. Point of Interest (POI) data from 2017 to 2021 were collected, and the Block2Vec model was employed to extract the comprehensive geographic information from various elements within the traffic analysis zones (TAZs). Subsequently, identification and division were carried out to access the level of urban spatial element agglomeration. Finally, the spatial–temporal evolution characteristics of urban aggregated elements in the Wuhan metropolitan development area over five years were compared and analyzed. The results indicate the following: (1) urban elements present an obvious circle structure in their spatial agglomeration, with distinct differences observed among different element types; (2) from 2017 to 2021, the Wuhan urban development zone experienced obvious expansion in urban space; (3) increased agglomeration of spatial elements mainly occurred in the surrounding areas of the city, while some areas in the city center displayed weaker element agglomeration and a reduction in various service facilities. The results demonstrate that the method used in this study could effectively identify the spatial agglomeration distribution of urban elements, as well as accurately distinguishing regions with distinct development characteristics. This approach could provide robust support for optimizing land use and urban spatial planning.
Rural dog populations have long been recognized to be inadequately managed in terms of disease control and prevention. In this study we consider dog management in rural Shanghai and its implications for rabies control in the entire metropolitan area of Shanghai. The prerequisite to improve rabies vaccination coverage in rural Shanghai depends on a proper enumeration of the total rural dog population. In this study we selected one of the nine administrative districts in Shanghai (Jiading), within which there are 7 towns and 2 industrial zones (township-level division) that contain agricultural areas. A total of 9 villages (rabies model villages) were chosen from each township-level division in Jiading, and an additional 3 non-model villages were also included in the study. A household questionnaire survey was implemented in all 12 villages recruited. In 3 of the model villages and the 3 non-model villages chosen as a comparison, two methods of enumeration—a sight-resight survey and a household census survey—were implemented. Results from the household survey in these 6 villages showed that among the total 1,560 owned dogs, 80.4% were Chinese Garden Dogs, 69.1% were aged 1 to 3 years, 49.2% were homebred, and 88.3% were kept for the purpose of guarding the house. However, only 3.7% of the owned dogs were desexed. There was a higher proportion of chained or confined dogs in model compared to non-model villages. The model villages had an absolute rabies vaccination coverage of 100% among its owned dog population and a smaller number of stray dogs. It was also identified that the two enumeration methods yielded similar counts (P = 0.12), particularly within smaller villages. From the questionnaire survey implemented within all 12 villages and based on the average human-to-dog ratio, the total rural dog population of Jiading district was estimated to be 24,058. This study generated information on the general demographics of the rural dog population in Jiading, and demonstrates an approach to the study of rural dog populations within the context of a megacity. In such a context, rural dog populations need to be considered as a critical component of animal and public health.
Sigfrido Iglesias-Gonzalez, Maria E. Huertas-Bolanos, Ivan Y. Hernandez-Paniagua
et al.
Statistical time series forecasting is a useful tool for predicting air pollutant concentrations in urban areas, especially in emerging economies, where the capacity to implement comprehensive air quality models is limited. In this study, a general multiple regression with seasonal autoregressive moving average errors model was estimated and implemented to forecast maximum ozone concentrations with a short time resolution: overnight, morning, afternoon and evening. In contrast to a number of short-term air quality time series forecasting applications, the model was designed to explicitly include the effects of meteorological variables on the ozone level as exogenous variables. As the application location, the model was constructed with data from five monitoring stations in the Monterrey Metropolitan Area of Mexico. The results show that, together with structural stochastic components, meteorological parameters have a significant contribution for obtaining reliable forecasts. The resulting model is an interpretable, useful and easily implementable model for forecasting ozone maxima. Moreover, it proved to be consistent with the general dynamics of ozone formation and provides a suitable platform for forecasting, showing similar or better performance compared to models in other existing studies.
The Milano Metropolitan Area [named FUA (functional urban area)] has a history of heavy industrialization causing a large portion of area being affected by significant diffuse contaminations of soil and groundwater. Among the various contaminants, chlorinated solvents (e.g., tetrachloroethylene and trichloroethylene) are the most used in industrial processes and represent the major cause of groundwater pollution within the FUA. The background diffuse contamination generated by these pollutants is so persistent and widely spread that makes it extremely challenging to identify the sources responsible for their release. Such background contamination originates from the overlapping of both known sources (point sources), associated to specific high release of contamination, and unknown small sources (multiple point sources), clustered within a large area, whose release is low but persistent. The aim of this article is to present the methodology, developed within the framework of the AMIIGA Project (Interreg Central Europe Grant N° CE32), which combines multivariate statistical analysis and groundwater numerical modeling in order to separate the point sources contribution from the background diffuse contamination, and supporting public authorities in the management of groundwater remediation. A methodological workflow is proposed guiding local and regional institutions to use the methodology (i.e., exploratory analysis of big dataset, simulation of groundwater flow and transport, multivariate and geostatistical analysis) to assess diffuse pollution background levels in large urbanized areas.
This paper analyzes the impact of local political fragmentation on population, employment, and per capita money income growth in 314 U.S. metropolitan areas. The results are mixed. Smaller central cities and more special district overlap are important for population growth. The find- ings do not generalize to employment or per capita money income growth. These findings mask important regional variation: political fragmentation is largely unrelated to economic growth in Midwestern and Western metropolitan areas. These results partially support the hypothesis that governmental fragmentation can enhance local economic growth; however, the overall impact appears muted relative to a metropolitan area’s economic characteristics
Abstract Background Rapid economic development in China has resulted in an increase in severe air pollution in city groups such as the Beijing–Tianjin–Hebei Metropolitan Region. PM2.5 (fine particles with an aerodynamic equivalent diameter of 2.5 μm or less) is one of the most important pollutants. The deposition process is an important way of removing particles from the air. To evaluate the effect of an urban forest on atmospheric particle removal, a concentration gradient method was used to measure the deposition velocities of water-soluble inorganics in PM2.5 in two national forest parks in Beijing, China. The following eight water-soluble inorganic ions in PM2.5 were investigated: sodium, ammonium, potassium, magnesium, calcium, chloride, nitrate, and sulfate. Methods Samples were taken from two sites in Beijing from the 7th to the 15th May, 2013. The concentrations of water-soluble inorganic ions were analyzed with ion chromatography. We used the concentration gradient technique to estimate the deposition flux and velocity. To determine the relationships between leaf traits and particle accumulation, typical leaf samples from each selected species were studied using scanning electron microscopy. Results The total deposition flux and total deposition velocity during the daytime were higher than those at night. Sulfate showed the biggest deposition flux and velocity at both study sites, whereas the other ions showed different trends at each site. Result from higher proportion of coniferous to broadleaved trees, the total deposition flux of the eight ions measured in Jiufeng National Forest Park was greater than that in Olympic Forest Park. Conclusions The deposition velocity was affected by meteorological conditions such as wind speed, temperature, and humidity. The deposition velocity was also influenced by tree species. The surface of plants is an important factor influencing particle deposition. The results of this study may help in assessing the effects of forestry systems on particle removal and provide evidence for urban air pollution control and afforestation of urban areas.
Background & objectives: Dengue is highly prevalent in tropical and subtropical regions. The prevalence of dengue is influenced by number of factors, i.e. host, vector, virus and environmental conditions including urbanization and population density. A cross sectional study was undertaken to determine the seroprevalence of dengue in two selected villages that differed in the level of their urbanization and population density.
Methods: Two villages with demographically well-defined populations close to Pune, a metropolitan city of western India, were selected for the study. Age stratified serosurvey was carried out during February to May 2011 in the two villages-a rural village A, located 6 km from the national highway with a population density of 159/km2 ; and an urbanized village B, located along the highway with a population density of 779/km2 . Assuming a low seroposi- tivity of 10%, 702 serum samples were collected from village A. Sample size for village B was calculated on the basis of seropositivity obtained in village A, and 153 samples were collected. Serum samples were tested for the presence of dengue virus (DENV)-specific IgG. Simple proportional analyses were used to calculate and compare the seroprevalence.
Results: Of the 702 samples collected from village A, 42.8% were found positive for anti-DENV IgG. A significantly higher seropositivity for DENV (58.8%) was found in village B. In village A, there was an age dependent increase in seroprevalence; whereas, in village B, there was a steep increase from 17% positivity in 0-10 yr age group to 72% in the 11-20 yr age group. The seroprevalence was almost similar in the older age groups.
Interpretation & conclusion: The observations suggested that prevalence of dengue is probably associated with urbanization and host population density. Areas that are in the process of urbanization needs to be monitored for prevalence of dengue and its vector, and appropriate vector control measures may be implemented.
This article presents the architecture, features, and operating mode of a DSS (Decision Support System) aiming to assist entrepreneurs and managers in the process of location decision making. The research assembled concepts derived from theory, findings of empirical studies, together with open GIS (Geographical Information System) software and data, and modelled them into a DSS software tool, according to an original methodology and design. The users are guided step-by-step to input information on their businesses into the DSS (industry, preferences for land-use areas and facility types, weights of key location factors), and are returned two sets of results: one based on own options, and another one aggregate for the industry they operate in. The results consist in the top five locations for the user's firm, as well as for the industry, depicted both in a graphical report (map) and a text report (explanation of results).