Innovative BIM technology application in the construction management of highway.

Within the global architecture, engineering, and construction industry, the use of Building Information Modeling (BIM) technology has significantly expanded. However, given the unique characteristics of road infrastructure, the application of BIM technology is still being explored. This article focuses on the Yuanchen Expressway, exploring innovative applications of BIM technology in comprehensive construction management. The project employs advanced technologies, including BIM, Geographic Information Systems (GIS), and the Internet of Things (IoT), to precisely identify critical nodes and breakthroughs. Supported by a detailed BIM model and a multi-level, diversified digital management platform, the project effectively addresses construction challenges in multiple tunnels, bridges, and complex interchanges, achieving intelligent construction innovation throughout the Yuanchen Expressway with BIM technology. By guiding construction through BIM models, utilizing a BIM+GIS-based management cloud platform system, and employing VR safety briefings, the project effectively reduces the difficulty of communication and coordination in project management, shortens the project measurement cycle, improves on-site work efficiency, and ensures comprehensive control and safety management. This article provides an exemplary case for the application of full-line construction management using BIM technology in the highway sector both in China and globally, offering new perspectives and strategies for highway construction management.

Geographic disparities and temporal changes of diabetes-related mortality risks in Florida: a retrospective study.

Background: Over the last few decades, diabetes-related mortality risks (DRMR) have increased in Florida. Although there is evidence of geographic disparities in pre-diabetes and diabetes prevalence, little is known about disparities of DRMR in Florida. Understanding these disparities is important for guiding control programs and allocating health resources to communities most at need. Therefore, the objective of this study was to investigate geographic disparities and temporal changes of DRMR in Florida. Methods: Retrospective mortality data for deaths that occurred from 2010 to 2019 were obtained from the Florida Department of Health. Tenth International Classification of Disease codes E10-E14 were used to identify diabetes-related deaths. County-level mortality risks were computed and presented as number of deaths per 100,000 persons. Spatial Empirical Bayesian (SEB) smoothing was performed to adjust for spatial autocorrelation and the small number problem. High-risk spatial clusters of DRMR were identified using Tango's flexible spatial scan statistics. Geographic distribution and high-risk mortality clusters were displayed using ArcGIS, whereas seasonal patterns were visually represented in Excel. Results: A total of 54,684 deaths were reported during the study period. There was an increasing temporal trend as well as seasonal patterns in diabetes mortality risks with high risks occurring during the winter. The highest mortality risk (8.1 per 100,000 persons) was recorded during the winter of 2018, while the lowest (6.1 per 100,000 persons) was in the fall of 2010. County-level SEB smoothed mortality risks varied by geographic location, ranging from 12.6 to 81.1 deaths per 100,000 persons. Counties in the northern and central parts of the state tended to have high mortality risks, whereas southern counties consistently showed low mortality risks. Similar to the geographic distribution of DRMR, significant high-risk spatial clusters were also identified in the central and northern parts of Florida. Conclusion: Geographic disparities of DRMR exist in Florida, with high-risk spatial clusters being observed in rural central and northern areas of the state. There is also evidence of both increasing temporal trends and Winter peaks of DRMR. These findings are helpful for guiding allocation of resources to control the disease, reduce disparities, and improve population health.

Census tract geospatial analysis comparing social determinants of health with tooth loss in California seniors: An ecologic study.

OBJECTIVES: Individual-level social determinant of health (SDOH) measures alone may insufficiently explain disparities in edentulism among seniors. Therefore, the authors examined the correlation of census tract-level SDOH and residential racial segregation measures with edentulism in Californian adults aged ≥65 years old. METHODS: Explanatory variables were obtained from Healthy Places Index (HPI), the National Cancer Institute and diversitydatakids.org. The edentulism outcome variable was obtained from CDC's PLACES small area estimates from the 2018 Behavioral Risk Factor Surveillance System data. Pearson and Spearman rank correlations were estimated. Multiple linear regression and multi-collinearity evaluations were performed. The Global Moran's I statistic assessed partial autocorrelation within census tracts. RESULTS: Pearson and Spearman correlations were similar, supporting robustness. HPI, an area measure of advantage, strongly negatively correlated with edentulism prevalence [correlation coefficient: -0.87; 95% confidence interval (CI): -0.87, -0.86]. A change of 1.0 in HPI corresponded to an estimated decrease in edentulism prevalence of 5.9% (linear model adjusted R2 = 0.78). Racially segregated census tracts with Hispanics or Blacks alone were positively correlated with edentulism prevalence [0.60, 95% CI: 0.58, 0.62; and 0.33, 95% CI: 0.31, 0.35, respectively]. The converse was seen in census tracts with non-Hispanic Whites alone [-0.57, 95% CI: -0.58, -0.55]. Global Moran's I statistic for edentulism (0.13) and HPI scores (0.19) were significant (both p < .001) indicating geospatial autocorrelation. CONCLUSIONS: Higher disadvantage and minority racial segregation within census tracts were positively correlated with edentulism prevalence. Future research and policy should consider possible interventions improving SDOH to reduce oral health inequities.

GIS-based spatiotemporal mapping of malaria prevalence and exploration of environmental inequalities.

Malaria poses a significant threat to global health, with particular severity in Nigeria. Understanding key factors influencing health outcomes is crucial for addressing health disparities. Disease mapping plays a vital role in assessing the geographical distribution of diseases and has been instrumental in epidemiological research. By delving into the spatiotemporal dynamics of malaria trends, valuable insights can be gained into population dynamics, leading to more informed spatial management decisions. This study focused on examining the evolution of malaria in Nigeria over twenty years (2000-2020) and exploring the impact of environmental factors on this variation. A 5-year-period raster map was developed using malaria indicator survey data for Nigeria's six geopolitical zones. Various spatial analysis techniques, such as point density, spatial autocorrelation, and hotspot analysis, were employed to analyze spatial patterns. Additionally, statistical methods, including Principal Component Analysis, Spearman correlation, and Ordinary Least Squares (OLS) regression, were used to investigate relationships between indicators and develop a predictive model. The study revealed regional variations in malaria prevalence over time, with the highest number of cases concentrated in northern Nigeria. The raster map illustrated a shift in the distribution of malaria cases over the five years. Environmental factors such as the Enhanced Vegetation Index, annual land surface temperature, and precipitation exhibited a strong positive association with malaria cases in the OLS model. Conversely, insecticide-treated bed net coverage and mean temperature negatively correlated with malaria cases in the same model. The findings from this research provide valuable insights into the spatiotemporal patterns of malaria in Nigeria and highlight the significant role of environmental drivers in influencing disease transmission. This scientific knowledge can inform policymakers and aid in developing targeted interventions to combat malaria effectively.

Spatio-temporal characterization of PM10 concentration across Abu Dhabi Emirate (UAE).

The abundance and recurrence of particulate matter in Abu Dhabi Emirate (ADE), are often derived from different emission sources such as the combustion of hydrocarbon, producing much of the PM2.5 found in outdoor air, as well as a significant proportion of PM10. Wind-blown dust from open desert areas and construction sites, landfills and agriculture, brush/waste burning, and industrial sources, has contributed markedly to the problem of the spread of haze and the long-range movement of pollutants in the country. In this study, the spatio-temporal characterization of PM10 concentration across the Emirate was analyzed utilizing geospatial interpolation, spanning the period between 2013 and 2017. The results suggest that the fluctuations of the PM10 concentration can be decomposed into three dominant types, each characterizing different spatial and temporal variations. First, the western region with PM10 showing a peak concentration during the summer season i.e., when the winds are predominantly northerlies or northwesterly, and a minimal concentration during the winter season. Second, the central region with the PM10 exhibiting a concentration surge in July-August, as a result of a mix of strong winds and high temperatures. Third, the eastern region with a low concentration of PM10. Seasonally, this component exhibits two concentration maxima during quarters 2 and 3 (summer), and two minima during quarters 1 and 4 (winter). Indeed, the seasonal variability of PM10 concentration in desertic countries like the UAE is closely linked to the seasonal variation of heat waves and dust storms, which are characteristic of the dryland climate. During the summer months, the UAE experiences high temperatures and arid conditions, creating favorable conditions for the formation of heat waves. Furthermore, it was noticed that the PM10 concentration also fluctuated markedly throughout the study period with anomalies detected in open desert areas and regions characterized by extensive industrial operations.

A Geographically Weighted Cost-effectiveness Analysis of Newborn Cytomegalovirus Screening.

Background: Early identification of newborns with congenital cytomegalovirus (CMV) is necessary to provide antiviral therapy and other interventions that can improve outcomes. Prior research demonstrates that universal newborn CMV screening would be the most cost-effective approach to identifying newborns who are infected. CMV is not uniformly prevalent, and it is uncertain whether universal screening would remain cost-effective in lower-prevalence neighborhoods. Our aim was to identify geographic heterogeneity in the cost-effectiveness of universal newborn CMV screening by combining a geospatial analysis with a preexisting cost-effectiveness analysis. Methods: This study used the CMV testing results and zip code location data of 96 785 newborns in 7 metropolitan areas who had been tested for CMV as part of the CMV and Hearing Multicenter Screening study. A hierarchical bayesian generalized additive model was constructed to evaluate geographic variability in the odds of CMV. The zip code-level odds of CMV were then used to weight the results of a previously published model evaluating universal CMV screening vs symptom-targeted screening. Results: The odds of CMV were heterogeneous over large geographic scales, with the highest odds in the southeastern United States. Universal screening was more cost-effective and afforded more averted cases of severe hearing loss than targeted testing. Universal screening remained the most cost-effective option even in areas with the lowest CMV prevalence. Conclusions: Universal newborn CMV screening is cost-effective regardless of underlying CMV prevalence and is the preferred strategy to reduce morbidity from congenital CMV.

Neighborhood Access to the Built Environment and Allostatic Load: A Systematic Review of the Use of Geographic Information Systems.

Objectives: This paper systematically reviews how spatial analysis has been used to measure relationships between access to the built environment and Allostatic Load (AL) or biomarkers relevant to the stress pathway. Geographic Information Systems (GIS) facilitate objective measurement of built environment access that may explain unequal health outcomes linked to living in stressful environments. Methods: Systematic review, search date 13 July 2022 with methods published a priori. Included studies that quantitatively assessed associations between GIS measures of neighborhood attributes and biomarkers of stress. Results: 23 studies from 14 countries were included having used GIS measures to assess relationships between access to the built environment and biomarkers relevant to AL, with 17 being cross-sectional and 6 longitudinal. Just 2 studies explicitly assessed associations between GIS measures and AL, but 21 explored biomarkers relevant to the stress pathway. GIS was used to calculate density (how much of x within y) and proximity (how far from a to b) measures. Conclusion: GIS measures of greenspace, the food environment, area-level demographics, and land-use measures were found to influence biomarkers relevant to the stress pathway, highlighting the utility of this approach. GIS use is extremely limited when measuring the built environment and its influence on AL but has been widely used to consider effects on individual biomarkers of stress. Systematic Review Registration: [https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=348355], identifier [CRD42022348355].

Development of a Consolidated Health Facility Masterlist Using Data From Polio Electronic Surveillance in the World Health Organization African Region.

Geospatial data reporting from surveillance and immunization efforts is a key aspect of the World Health Organization (WHO) Global Polio Eradication Initiative in Africa. These activities are coordinated through the WHO Regional Office for Africa Geographic Information Systems Centre. To ensure the accuracy of field-collected data, the WHO Regional Office for Africa Geographic Information Systems Centre has developed mobile phone apps such as electronic surveillance (eSURV) and integrated supportive supervision (ISS) geospatial data collection programs. While eSURV and ISS have played a vital role in efforts to eradicate polio and control other communicable diseases in Africa, disease surveillance efforts have been hampered by incomplete and inaccurate listings of health care sites throughout the continent. To address this shortcoming, data compiled from eSURV and ISS are being used to develop, update, and validate a Health Facility master list for the WHO African region that contains comprehensive listings of the names, locations, and types of health facilities in each member state. The WHO and Ministry of Health field officers are responsible for documenting and transmitting the relevant geospatial location information regarding health facilities and traditional medicine sites using the eSURV and ISS form; this information is then used to update the Health Facility master list and is also made available to national ministries of health to update their respective health facility lists. This consolidation of health facility information into a single registry is expected to improve disease surveillance and facilitate epidemiologic research for the Global Polio Eradication Initiative, as well as aid public health efforts directed at other diseases across the African continent. This review examines active surveillance using eSURV at the district, country, and regional levels, highlighting its role in supporting polio surveillance and immunization efforts, as well as its potential to serve as a fundamental basis for broader public health initiatives and research throughout Africa.

An ecotourism suitability index for a world heritage city using GIS-multi criteria decision analysis techniques.

The concept of ecotourism has experienced a significant surge in popularity over the past two decades, primarily driven by the multitude of adverse impacts associated with mass tourism. The objective of the study was to develop a comprehensive ecotourism suitability index to guide policymakers in implementing tourism development policies. Given the considerable appeal of the study area to both local and international tourists, it is essential to conduct a systematic evaluation to pinpoint suitable areas for ecotourism development. This necessity arises from the study area's placement within a fragile ecosystem and its proximity to a UNESCO World Heritage site. We employed a Geographic Information Systems (GIS) integrated environment coupled with a fuzzy Multi-Criteria Decision Analysis (MCDA) methodology. The GIS-MCDA integrated framework leverages the Analytic Hierarchy Process (AHP) and a weighted linear combination that seeks to amalgamate many features and criteria to assess ecotourism potential by integrating 20 criteria into six separate categories: landscape, topography, accessibility, climate, forest and wildlife, and negative factors. Weights were allocated to each criterion and factor based on the expert's opinions of their impact on the development of ecotourism. The final ecotourism suitability index comprised five unique classes: very high, high, moderate, less, and not suitable. Results reveal that out of the total areas, 45.4 % (259 km2) are within the high and very high suitable classes. The sensitivity analysis suggested that ecotourism potentials are more favorable to forest and accessibility variables. The generated index can be utilized as a road map since validation verified a 64 % accuracy. Given the dearth of earlier research, this study provides vital support for the development of sustainable ecotourism projects in the study area.

Intake of Snacks and Sweets in a National Study of Built and Social Environments: the REasons for Geographic And Racial Differences in Stroke Study.

BACKGROUND: Few national studies across the United States' rural-urban continuum examine neighborhood effects on snacks and sweets intake among adults. OBJECTIVES: This study examines associations of urbanicity/rurality-tailored measures of food store availability and neighborhood socioeconomic status (NSES) with the intake of snacks and sweets in a national sample of middle and older age adults. METHODS: This cross-sectional study used food frequency questionnaire data collected in the REasons for Geographic And Racial Differences in Stroke study (N = 21,204). What We Eat in America food group categorizations guided outcome classification into 1 main category (total snacks and sweets) and 4 subcategories (savory snacks and crackers; sweet bakery products; candy and desserts; nutrition bars and low-fat snacks and sweets). NSES and food store availability were determined using geographic information systems. Food store availability was characterized as geographic access to primary food stores (e.g., supermarkets, supercenters, and select food retailers) in urbanicity/rurality-tailored neighborhood-based buffers. Multiple linear regression was used to predict each outcome. RESULTS: Living in neighborhoods with a high density of primary food stores was associated with 8.6%, 9.5%, and 5.8% lower intake of total snacks and sweets, sweet bakery products, and candy and desserts, respectively. Living in the highest NSES quartile was associated with 11.3%, 5.8%, and 18.9% lower intake of total snacks and sweets, savory snacks and crackers, and sweet bakery products, respectively. Depending on primary food store availability, higher household income was associated with significantly greater intake of nutrition bars and low-fat snacks and sweets. Living in a United States Department of Agriculture-defined food desert was not associated with intake. CONCLUSIONS: In a geographically diverse sample of middle and older age United States adults, living in neighborhoods with no primary food stores or neighborhoods of low-SES was associated with higher intake of total snacks and sweets and subgroups of snacks and sweets.

Future Blood Debt: Projecting Blood Supply and Demand of Korea Based on Subnational Population Projections (2021-2050).

BACKGROUND: South Korea faces a critical challenge with its rapidly declining fertility rates and an increasingly aging population, which significantly impacts the country's blood supply and demand. Despite these nationwide trends, regional disparities in blood supply and demand have not been thoroughly studied. METHODS: This research utilized blood donation data from the Korean Red Cross and blood transfusion data from the Health Insurance Review and Assessment Service. We analyzed these datasets in conjunction with regional population projections to simulate blood supply and demand from 2021 to 2050 across South Korea. Sensitivity analyses were conducted to assess the impact of various factors, including the number of donors, age eligibility criteria for donations, frequency of donations, and blood discard rates. RESULTS: Our projections indicate a decreasing trend in blood supply, from 2.6 million units in 2021 to 1.4 million units by 2050, while demand is expected to peak at 5.1 million units by 2045 before declining. Metropolitan areas, particularly Gyeonggi Province, are projected to experience the most severe shortages. Sensitivity analyses suggest that increasing the donation frequency of existing donors and relaxing age eligibility criteria are more effective strategies in addressing these imbalances than merely increasing the number of new donors. Blood discard rates showed minimal impact on the overall blood shortage. CONCLUSION: The findings emphasize the urgent need for targeted strategies to mitigate national and regional blood supply shortages in South Korea. Encouraging frequent donations from experienced donors and broadening eligibility criteria are critical steps toward stabilizing the blood supply amidst demographic shifts. These strategies must be prioritized to address the impending regional disparities in blood availability.

The role of Geographic Information Systems in mitigating plastics pollution in the Global South-A spatial analysis of recycling facilities in Costa Rica.

Costa Rica is at the forefront of environmental conservation in Central America, with its focus on sustainability and green practices. Building on this foundation, the country joins a cohort of middle-income developing countries that have set forth ambitious goals to eliminate plastic pollution and become plastics-free. Recycling remains one of the most effective ways of removing plastic waste from the environment. Although GIS has been utilized in environmental research, its use is still expanding in developing countries of the Global South. These countries are experiencing unprecedented adverse climate and ecological impacts while also pursuing fundamental socioeconomic growth. The application of more cost-effective and strategic technological solutions, as well as data-driven decision-making, could fast-track the achievement of their urgent environmental goals. Using Geographic Information Systems (GIS) analysis, this study applies hot spot, location-allocation, and time-distance measures to examine Costa Rica's capacity to recycle plastic waste. Focusing specifically on availability and the public's access to recycling facilities, this article offers insights into the resource constraints and evolution of plastics governance in developing countries with environmentally-focused priorities. The findings of this study suggest that while Costa Rica is implementing progressive plastics regulatory policies, the ability to achieve plastics-free status is hampered by shortfalls in the number and distribution of recycling facilities and the public's access to recycling services. Expanding recycling infrastructure, including transportation, and adopting a less canton-centric waste administration system could contribute to resolving these challenges. This study contributes to discourses on global plastics governance and environmental change management in the Global South.

Mapping the Ecological Terrain of Stroke Prehospital Delay: A Nationwide Registry Study.

BACKGROUND: Delays in hospital presentation limit access to acute stroke treatments. While prior research has focused on patient-level factors, broader ecological and social determinants have not been well studied. We aimed to create a geospatial map of prehospital delay and examine the role of community-level social vulnerability. METHODS: We studied patients with ischemic stroke who arrived by emergency medical services in 2015 to 2017 from the American Heart Association Get With The Guidelines-Stroke registry. The primary outcome was time to hospital arrival after stroke (in minutes), beginning at last known well in most cases. Using Geographic Information System mapping, we displayed the geography of delay. We then used Cox proportional hazard models to study the relationship between community-level factors and arrival time (adjusted hazard ratios [aHR] <1.0 indicate delay). The primary exposure was the social vulnerability index (SVI), a metric of social vulnerability for every ZIP Code Tabulation Area ranging from 0.0 to 1.0. RESULTS: Of 750 336 patients, 149 145 met inclusion criteria. The mean age was 73 years, and 51% were female. The median time to hospital arrival was 140 minutes (Q1: 60 minutes, Q3: 458 minutes). The geospatial map revealed that many zones of delay overlapped with socially vulnerable areas (https://harvard-cga.maps.arcgis.com/apps/webappviewer/index.html?id=08f6e885c71b457f83cefc71013bcaa7). Cox models (aHR, 95% CI) confirmed that higher SVI, including quartiles 3 (aHR, 0.96 [95% CI, 0.93-0.98]) and 4 (aHR, 0.93 [95% CI, 0.91-0.95]), was associated with delay. Patients from SVI quartile 4 neighborhoods arrived 15.6 minutes [15-16.2] slower than patients from SVI quartile 1. Specific SVI themes associated with delay were a community's socioeconomic status (aHR, 0.80 [95% CI, 0.74-0.85]) and housing type and transportation (aHR, 0.89 [95% CI, 0.84-0.94]). CONCLUSIONS: This map of acute stroke presentation times shows areas with a high incidence of delay. Increased social vulnerability characterizes these areas. Such places should be systematically targeted to improve population-level stroke presentation times.

Mapping Bovine Tuberculosis in Colombia, 2001-2019.

INTRODUCTION: Bovine tuberculosis is a zoonotic disease of significant impact, particularly in countries where a pastoral economy is predominant. Despite its importance, few studies have analysed the disease's behaviour in Colombia, and none have developed maps using geographic information systems (GIS) to characterise it; as such, we developed this study to describe the temporal-spatial distribution of bovine tuberculosis in Colombia over a period of 19 years. METHODS: A retrospective cross-sectional descriptive study, based on reports by the Colombian Agricultural Institute (ICA), surveillance of tuberculosis on cattle farms in Colombia from 2001 to 2019 was carried out. The data were converted into databases using Microsoft Access 365®, and multiple epidemiological maps were generated with the QGIS® version 3.36 software coupled to shape files of all the country's departments. RESULTS: During the study period, 5273 bovine tuberculosis cases were identified in multiple different departments of Colombia (with a mean of 278 cases/year). Regarding its temporal distribution, the number of cases varied from a maximum of 903 cases (17.12% of the total) in 2015 to a minimum of 0 between 2001 and 2004 and between 2017 and 2019 (between 2005 and 2016, the minimum was 46 cases, 0.87%). CONCLUSIONS: GIS are essential for understanding the temporospatial behaviour of zoonotic diseases in Colombia, as is the case for bovine tuberculosis, with its potential implications for the Human and One Health approaches.

Utilizing social determinants of health to identify most vulnerable neighborhoods-Latent class analysis and GIS map.

OBJECTIVES: Public Health officials are often challenged to effectively allocate limited resources. Social determinants of health (SDOH) may cluster in areas to cause unique profiles related to various adverse life events. The authors use the framework of unintended teen pregnancies to illustrate how to identify the most vulnerable neighborhoods. METHODS: This study used data from the U.S. American Community Survey, Princeton Eviction Lab, and Connecticut Office of Vital Records. Census tracts are small statistical subdivisions of a county. Latent class analysis (LCA) was employed to separate the 832 Connecticut census tracts into four distinct latent classes based on SDOH, and GIS mapping was utilized to visualize the distribution of the most vulnerable neighborhoods. GEE Poisson regression model was used to assess whether latent classes were related to the outcome. Data were analyzed in May 2021. RESULTS: LCA's results showed that class 1 (non-minority non-disadvantaged tracts) had the least diversity and lowest poverty of the four classes. Compared to class 1, class 2 (minority non-disadvantaged tracts) had more households with no health insurance and with single parents; and class 3 (non-minority disadvantaged tracts) had more households with no vehicle available, that had moved from another place in the past year, were low income, and living in renter-occupied housing. Class 4 (minority disadvantaged tracts) had the lowest socioeconomic characteristics. CONCLUSIONS: LCA can identify unique profiles for neighborhoods vulnerable to adverse events, setting up the potential for differential intervention strategies for communities with varying risk profiles. Our approach may be generalizable to other areas or other programs. KEY MESSAGES: What is already known on this topic Public health practitioners struggle to develop interventions that are universally effective. The teen birth rates vary tremendously by race and ethnicity. Unplanned teen pregnancy rates are related to multiple social determinants and behaviors. Latent class analysis has been applied successfully to address public health problems. What this study adds While it is the pregnancy that is not planned rather than the birth, access to pregnancy intention data is not available resulting in a dependency on teen birth data for developing public health strategies. Using teen birth rates to identify at-risk neighborhoods will not directly represent the teens at risk for pregnancy but rather those who delivered a live birth. Since teen birth rates often fluctuate due to small numbers, especially for small neighborhoods, LCA may avoid some of the limitations associated with direct rate comparisons. The authors illustrate how practitioners can use publicly available SDOH from the Census Bureau to identify distinct SDOH profiles for teen births at the census tract level. How this study might affect research, practice or policy These profiles of classes that are at heightened risk potentially can be used to tailor intervention plans for reducing unintended teen pregnancy. The approach may be adapted to other programs and other states to prioritize the allocation of limited resources.

Multidecadal mangrove forest change in Macajalar Bay, Northern Mindanao, Philippines (1950-2020) using remote sensing and geographic information systems.

The mangrove forest in Macajalar Bay is regarded as an important coastal ecosystem since it provides numerous ecosystem services. Despite their importance, the clearing of mangroves has been rampant and has reached critical rates. Addressing this problem and further advancing its conservation require accurate mangrove mapping. However, current spatial information related to mangroves is sparse and insufficient to understand the historical change dynamics. In this study, the synergy of 1950 vegetation maps and Landsat images was explored to provide multidecadal monitoring of mangrove forest change dynamics in Macajalar Bay, Philippines. Vegetation maps containing the 1950 mangrove extent and Landsat images were used as input data to monitor the rates of loss over 70 years. In 2020, the mangrove forest cover was estimated to be 201.73 ha, equivalent to only 61.99% of the 325.43 ha that was estimated in 1950. Between 1950 and 2020, net mangrove loss in Macajalar Bay totaled 324.29 ha. The highest clearing rates occurred between 1950 and 1990 when it recorded a total of 258.51 ha, averaging 6.46 ha/year. The original mangrove forest that existed in 1950 only represents 8.56% of the 2020 extent, suggesting that much of the old-growth mangrove had been cleared before 2000 and the existing mangrove forest is mainly composed of secondary mangrove forest stands. Across Macajalar Bay, intensified clearing that happened between 1950 and 1990 has been driven by large-scale aquaculture developments. Mangrove gains on the other hand were evident and have increased the total extent by 79.84 ha since 2000 as a result of several afforestation programs. However, approximately half of these gains that were observed since 2010 exhibited low canopy cover. As of writing, approximately 85% of the 2020 mangrove forest stands fall outside the 1950 original mangrove extent. Examining the viability of the original mangrove forest for mangrove reforestation together with promoting site-species matching, and biophysical assessment are necessary undertakings to advance current mangrove conservation initiatives in Macajalar Bay.

Measuring Spatial Access of Vulnerable Population to HIV Testing Facilities in the Baton Rouge Metropolitan Statistical Area, Louisiana.

Ensuring adequate and equitable access to affordable HIV testing is a crucial step toward ending the HIV epidemic (EHE). Using the high-burden Baton Rouge Metropolitan Statistical Area (MSA) as an example, we measure spatial access to HIV testing facilities for vulnerable populations and assess whether their access would improve if eliminating a considerable barrier-costs. Locations and status (free, low-cost, and full cost) of HIV testing facilities are searched on the Internet and confirmed through a field survey. Vulnerable populations include the uninsured and people living with HIV (PLWH), disaggregated from county-level HIV prevalence data. Spatial access is computed by a normalized urban-rural two-step floating catchment area (NUR2SFCA) method. Our survey confirms that only 11% and 37% of the 103 Internet-searched HIV testing facilities are indeed free and low-cost. Making more facilities cheaper or free increases the average access of PLWH, the uninsured, and the entire population but their geographic patterns vary. Free testing facilities, clustered in Baton Rouge city, are highly accessible to 82.6%, 69.4%, and 70.2% of three population groups living in East and West Baton Rouge Parish. In comparison, making all low-cost facilities free increases access in most outlying parishes but at the cost of reducing access in East Baton Rouge Parish, leaving west Livingston, north Iberville, and east Pointe Coupee Parish with the poorest access. Making all full-cost facilities cheaper or free exhibits a similar pattern. The study has important policy implications for where and how to improve access to HIV testing for vulnerable populations.

RESUMEN: Medimos el acceso espacial a las instalaciones de pruebas de VIH para poblaciones vulnerables y evaluamos si su acceso mejoraría si se eliminaran las barreras de costos, utilizando como ejemplo el área estadística metropolitana de Baton Rouge, que tiene una alta carga. Nuestra encuesta confirma que el 11% y el 37% de los 103 centros de pruebas de VIH buscados en Internet son efectivamente gratuitos y de bajo costo. Hacer que más instalaciones sean más baratas o gratuitas aumenta el acceso promedio de las PLWH, las personas sin seguro y toda la población, pero sus patrones geográficos varían. Las instalaciones de pruebas gratuitas, agrupadas en la ciudad de Baton Rouge, son muy accesibles para el 82,6%, el 69,4% y el 70,2% de los tres grupos de población del este y oeste de Baton Rouge. En comparación, hacer que las instalaciones de bajo costo sean gratuitas aumenta el acceso en las parroquias periféricas, pero a costa de reducir el acceso en East Baton Rouge. Hacer que las instalaciones de costo total sean más baratas o gratuitas muestra un patrón similar. El estudio tiene importantes implicaciones políticas para mejorar el acceso a las pruebas del VIH para las poblaciones vulnerables.

Needs and readiness to use tele-practice for identification and rehabilitation of children with hearing and speech-language disorders: perceptions of public sector care providers in South India.

The current study was a first step towards planning the implementation of tele-practice in a South Indian state's public-sector services for childhood hearing and speech, language disorders. The aim was to understand the perceptions of public-sector health care providers (HCPs) regarding their need and readiness to accept and implement tele-practice-based diagnostics and rehabilitation services. A cross-sectional study design was used, which included focus group discussions (FGDs), semi-structured interviews (SSIs) and geo-spatial analysis. Participants in the qualitative component included various cadres of health HCPs in public-sector services. Theoretical saturation and cross-case variance were used to assess the data's sufficiency. A hybrid deductive-inductive thematic analytical approach was used to analyse the data. Geo-tags and geo-locations of addresses of all children with disabilities and all the public-sector service providers were used to generate geospatial maps. The HCPs considered the currently available services for childhood hearing and speech-language disorders to be insufficient and reported shortage of professionals to meet current demands. There was inconsistent availability of suitable equipment and professionals in the existing district-level facilities. HCPs were comfortable using technology, and were willing to investigate tele-practice, but they required training in tele-practice [Q2].

Residential Density Is Associated With BMI Trajectories in Children and Adolescents: Findings From the Moving to Health Study.

Introduction: This study investigates the associations between built environment features and 3-year BMI trajectories in children and adolescents. Methods: This retrospective cohort study utilized electronic health records of individuals aged 5-18 years living in King County, Washington, from 2005 to 2017. Built environment features such as residential density; counts of supermarkets, fast-food restaurants, and parks; and park area were measured using SmartMaps at 1,600-meter buffers. Linear mixed-effects models performed in 2022 tested whether built environment variables at baseline were associated with BMI change within age cohorts (5, 9, and 13 years), adjusting for sex, age, race/ethnicity, Medicaid, BMI, and residential property values (SES measure). Results: At 3-year follow-up, higher residential density was associated with lower BMI increase for girls across all age cohorts and for boys in age cohorts of 5 and 13 years but not for the age cohort of 9 years. Presence of fast food was associated with higher BMI increase for boys in the age cohort of 5 years and for girls in the age cohort of 9 years. There were no significant associations between BMI change and counts of parks, and park area was only significantly associated with BMI change among boys in the age cohort of 5 years. Conclusions: Higher residential density was associated with lower BMI increase in children and adolescents. The effect was small but may accumulate over the life course. Built environment factors have limited independent impact on 3-year BMI trajectories in children and adolescents.