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Access to healthcare is a fundamental determinant of public health sustainability. Current literature on healthcare access tends to focus largely on vulnerable groups and objective indicators where access is defined through service utilization. When the literature on "perceived access to healthcare" is examined, it is observed that perceived access is generally treated as a determining factor explaining health outcomes or behaviors. However, the investigation of the socioeconomic, self-rated health, health literacy and spatial features that shape this perception itself within a holistic framework remains a less focused area in the literature. Methodologically, perceived access to healthcare is often defined with a limited number of variables or specifically within particular disease groups. Especially in regions such as Trabzon, where rugged topography and geographical barriers are intertwined with socio-cultural dynamics, analyzing the factors shaping the individual's perception of access within a comprehensive framework will offer a significant contribution to the literature. This study aims to integrate multidimensional factors -including socioeconomic status (SES), self-rated health, health literacy, health-seeking behavior, and travel time-into a comprehensive structural framework for the first time in the literature; to validate their effects through Structural Equation Modeling (SEM), and to uncover the spatial dependence patterns in access. This reearch was conducted with 1,491 adults. Data were analyzed using Structural Equation Modeling (SEM) to evaluate multidimensional pathways, and geospatial analysis was performed to determine spatial dependence patterns. The results of the research demonstrate that health literacy and professional health-seeking behavior are the primary elements strengthening the perception of access, whereas online health-seeking and increased travel time weaken this perception. One of the most original findings of the study is that the direct negative effect of SES on access is balanced through health literacy; this indicates that cognitive capacity can mitigate socioeconomic disadvantages. Spatial models confirm that while the general perceived access to healthcare is shaped by personal factors, the "accessibility" dimension exhibits a spatial dependence tied to local topography within a 1-km radius. Consequently, these findings scientifically support that health planning should shift from macro-scale strategies toward micro-spatial interventions aimed at minimizing physical barriers at the neighborhood and street levels. Integrating approaches that improve health literacy with interventions that minimize travel barriers will play a fundamental role in reducing health inequalities.
Diabetes prevalence is increasing in Thailand, creating growing demands on the health system. Understanding the spatial distribution of diabetes risk and its association with socioeconomic and healthcare system factors among the diabetes risk population is critical for designing targeted prevention and intervention strategies. We examined the distribution of diabetes risk groups across provinces in Thailand with reference to the spatial association between economic, social and public health service factors based on data from the Ministry of Public Health's Health Data Center (HDC) for the year 2021. The dataset included 22,491,934 individuals across the 76 provinces as well as social, economic and public health services. The methods included Local Indicators of Spatial Association (LISA), Ordinary Least Squares (OLS), Spatial Lag Model (SLM) and Spatial Error Model (SEM). Explanatory variables included average night-time light intensity, average monthly income, hospital-to-population ratio and proportion of the population with health insurance. Major clusters of High-High (HH) diabetes risk were identified by LISA mainly located in the North of Thailand. In all models, the direction and significance of the associations were consistent (p<0.001 for all variables investigated and p<0.01). R2=0.47. The SLM gave the best fit, capturing spatial spill-over effects. Higher night-time light intensity (coefficient = -85.70, p<0.05) and higher monthly income (coefficient = -0.079, p<0.001) were negatively associated with diabetes risk. These inverse relationships implied that greater urbanization and higher socio-economic standing may protect against diabetes risk, possibly through improved access to health infrastructure, improved health education and preventive services. Conversely, the higher hospital-to-population ratios (coefficient = 572.28, p<0.001) and the larger proportions of Civil Servant Medical Benefits Scheme (CSMBS) coverage (coefficient = 226.46, p<0.001) the higher diabetes risk. These counterintuitive findings likely reflect reverse causation, in which provinces with higher disease burden or poor health attract more resources of health care and have increased insurance coverage, a pattern consistent with healthcare service distribution responding to existing health needs rather than preventing occurrence of disease.
Few populations face more disadvantage than those with lifelong intellectual and developmental disabilities (IDD) and those with serious mental illness (SMI). People with IDD may face unique challenges in the manifestation and treatment of SMI; little is known about these challenges during the widespread expansion of telehealth mental health services during the COVID-19 pandemic which disrupted service availability. Using Medicaid claims from Kansas, Massachusetts, New York and South Carolina, mental health service utilization patterns for three cohorts of people ages 1-45 years were studied: those with IDD, those with SMI, and those with SMI and IDD. Utilization was examined before (2018-2019) and during (2020-2021) the emergence of telehealth services for each cohort. Meta-analysis was used to compare odds of mental health service utilization by demographic subgroups. The prevalence of mental health service utilization was approximately 75% for the IDD/SMI cohort, 60% for the SMI cohort, and 30% of the IDD cohort in 2018. Teens 13-17 years and young adults tended to have the highest levels of service utilization. Service utilization was driven by different diagnoses for the groups. The SMI cohort utilized services significantly more for mood and anxiety disorders, and the IDD cohort utilized services significantly more for comorbid neurodevelopmental conditions, anxiety, and trauma-related disorders. The IDD/SMI cohort utilized services more bipolar and related disorders and had a younger median age of service utilizers for trauma- and stress-related disorders than the SMI cohort. The IDD/SMI cohort had the highest mental health service utilization rates compared to the other two cohorts, with minimal urban-rural differences, suggesting mental health services may be reaching those at the highest levels of risk for adverse outcomes. People with IDD demonstrated substantially lower rates of telehealth utilization for mental health needs; however, people in the cohort with IDD and SMI demonstrated similar or higher rates (in adults) of telehealth utilization compared to people with SMI only. Even with expanded telehealth services, the COVID-19 pandemic appeared to partially disrupt utilization across all cohorts and age groups. Findings suggest that people with IDD and SMI experience trauma- and stressor-related disorders that require treatment at younger ages than people with SMI only.
This study aimed to estimate the spatial accessibility of inpatient mental health services in Kerala, India. We also aimed to calculate bed-to-population ratios for these services for each district in the state. We used a Geospatial Information System (GIS)-based travel time isochrone analysis to estimate potential spatial accessibility. Kerala, India. A list of all mental health facilities licensed to admit patients was obtained from data published by the Kerala State Mental Health Authority in 2025. The facilities were geocoded and mapped. Population data were also obtained using satellite-based estimates from 2020 at a resolution of 100 m. Information on Road Networks was obtained using OpenStreetMap through the OpenRouteService plugin in 2025. We calculated the proportion of people who could access facilities within 15 min, 30 min and 45 min. We also calculated beds per population for each of the 14 districts. Kerala has an average of 21 mental health beds per 100 000 people, ranging from 0.75 in Kasargod to 68 in Idukki. In terms of bed-to-population ratios, one district was ideal, three met the basic requirements, two experienced slight shortages, four faced moderate shortages and four encountered severe shortages. Across the state, 67.95% of the population could access psychiatric services within 15 min, increasing to 96.85% within 45 min. GIS-based isochrone analysis indicated that 96.85% of the population could reach a facility by car within 45 min. Bed-to-population ratios varied substantially between districts.
Malaria remains a major public health concern in flood-prone districts where environmental vulnerability and weak health infrastructure exacerbate transmission risks. This study develops an integrated geospatial framework for malaria risk zonation by combining multi-criteria decision-making and machine learning. A geospatial modeling study integrating environmental, meteorological, and socio-demographic datasets with decision analysis and machine learning. Eleven predictor variables, including elevation, land surface temperature (LST), rainfall, slope, drainage density, humidity, flood inundation, population, proximity to roads and health facilities, and land use/land cover (LULC), were processed to generate hazard, vulnerability, and elements-at-risk (EAR) layers. Two approaches were employed: (i) the Analytical Hierarchy Process (AHP) integrating hazard, vulnerability, and EAR through weighted overlays; and (ii) a Random Forest (RF) model trained with 250 union council-level malaria Test Positivity Rate (TPR) records from 2014 to 2024. The RF model achieved 93.3% accuracy, 0.95 precision, 0.93 recall, and a Kappa coefficient of 0.86, confirming strong predictive performance. AHP identified 69.2% of the area as moderate risk and 13.8% as high risk, while RF produced localized hotspots with higher spatial resolution. Flood proximity, LST, rainfall, and LULC were dominant predictors. Validation against 2022 malaria outbreak data showed strong spatial agreement. The dual-model framework, integrating hazard, vulnerability, and EAR layers with data-driven validation, demonstrates practical utility for climate-resilient malaria control. The methodology is transferable to other disaster-prone regions for targeted interventions and resource allocation.
Cesarean section is a lifesaving obstetric intervention when medically indicated; however, its utilization remains unequal across sub-Saharan Africa (SSA). Although the World Health Organization recommends cesarean section rates of 10-15%, access remains insufficient in many low-resource settings and excessive in others. Understanding geographic patterns and drivers is essential for maternal health planning. To examine the spatial variation and determinants of cesarean section delivery across SSA. We conducted a cross-sectional analysis using Demographic and Health Survey data (2015-2024) from 201,481 weighted samples across 28 SSA countries. Spatial autocorrelation and hotspot patterns were assessed using Global Moran's I and Getis-Ord Gi* statistics. Spatial regression models, including ordinary least squares, spatial lag, spatial error, geographically weighted regression, and multiscale geographically weighted regression, were fitted. Model performance was compared using corrected Akaike Information Criterion and adjusted R2. Cesarean section delivery showed significant spatial clustering (Moran's I = 0.18, z = 43.3, p < 0.01). Hotspot areas were identified in Uganda, Rwanda, Burundi, Kenya, Tanzania, Malawi, South Africa, Lesotho, Gabon, Ghana, and Senegal, while cold spots were observed in Ethiopia, Madagascar, Angola, Nigeria, Guinea, Cote d'Ivoire, Sierra Leone, Liberia, and Mauritania. Previous cesarean delivery, maternal age ≥35 years, pregnancy spacing behavior, and health insurance coverage were significant spatial predictors. Cesarean section utilization in SSA exhibits substantial geographic inequality driven by context-specific determinants. Spatially targeted maternal health policies, improved referral systems, and equitable financing mechanisms are needed to optimize access to medically indicated cesarean delivery while minimizing unnecessary procedures. Main findings: Caesarean section utilization in SSA demonstrated substantial geographic inequalities, with significant spatial clustering and regional variation influenced by previous caesarean sections, maternal age, insurance coverage, and reproductive health behaviors.Added knowledge: This study provides multicounty geospatial evidence using multiscale geographically weighted regression to identify location-specific predictors and geographic inequalities in caesarean section utilization across SSA.Global health impact for policy and action: Geographically targeted maternal health strategies are needed to improve equitable access to medically necessary caesarean section services while preventing unnecessary procedures across underserved regions of SSA.
Rising costs of groceries have prompted some United States (US) households to change their grocery shopping habits opting for dollar stores to lower household expenses. In previous work dollar stores have not been classified as a grocery store, limiting our understanding of how the dollar store associates with public health. Importantly, healthy food offerings such as fresh produce, whole grains, and lean proteins largely differ between traditional grocery stores and dollar stores. This public health study seeks to understand how the contrast in healthy food offerings associate with health outcomes across communities. We used 2016-2020 data where traditional grocery store and dollar store locations across the contiguous US were geocoded and assigned as standard quality (SQ) and low-quality (LQ) respectively. Access to SQ and LQ was gleaned using ArcGIS network analysis of these geocoded points with census tracts of metro areas represented by the 2019 release of the Centers for Disease Control (CDC) 500 Cities Project (2016-2017 estimates). ArcGIS generalized linear regression models analyzed links between health outcomes from the CDC 500 Cities Project and key variables: proximity to SQ stores, proximity to LQ stores, and an aggregate of socioeconomic factors indexed by the 2016 CDC Social Vulnerability Index (SVI). Results across and within most regions of the US demonstrated significant negative associations between proximity to SQ stores and adverse health outcomes such as obesity, diabetes, and high blood pressure. Conversely, proximity to LQ stores (i.e., dollar stores) demonstrated significant positive associations with all health outcomes across the US, even after accounting for SVI. This study demonstrates the importance of dollar stores with food environment, an important component of food policy. Beyond recognizing dollar stores as grocery sources, these results emphasize the need to incorporate grocery quality into food environment research and policymaking.
The development of an urban green space (UGS) quality assessment protocol addressing the health-related activities of older adults and children represents a sustainable approach to promoting health and well-being. Although most protocols have been developed for physical activity, few have considered other categories of health-related activities that encompass multiple age groups. This study develops a mixed-method green space for multiage health-related activities (GMHA) protocol to assess UGS quality for older adults, children, and the general population across different health-related activities, including physical activity and social interaction. Five conventional domains of facility, amenity, aesthetics, maintenance, safety, and incivilities audited by systematic observation are integrated with the geospatial domains of natural environments and spatial configuration, supported by unmanned aerial vehicle and space syntax techniques. Seventy UGS samples were tested for interrater reliability via intraclass correlation coefficients. The relative importance of each UGS domain in the protocol was further examined using a spatial autoregressive (SAR) model. Content validity is substantiated by scholarship. Preliminary tests verified quantitative reliability and concurrent validity. SAR results revealed varying associations between UGS domains and multiage health-related activities, highlighting the significance of the environment-individual-activity interaction. GMHA can facilitate targeting UGS quality enhancement across broader contexts and populations to benefit health and well-being.
Soil contamination by potentially harmful elements (PHEs) has become a pressing environmental concern in arid and semi-arid regions, where natural processes and human activities intensify the accumulation of these elements. Understanding the spatial variability, contamination and eco-toxicological implications of PHEs is vital for safeguarding ecosystem integrity, biodiversity and public health. This study highlights the need for a comprehensive analysis of the contamination levels, spatial distribution, potential sources and eco-toxicological status of PHEs in soils across various land-use types in the Sistan Basin, eastern Iran. Soil samples were analyzed for PHEs to assess the contamination factor (Cf), pollution load index (PLI), and ecological risk, supported by spatial mapping and health risk assessment. Results revealed that aluminum (Al) and iron (Fe) were major elements sourced from geogenic origin, whereas cadmium (Cd), arsenic (As), and lead (Pb) exhibited considerable enrichment in agricultural lands and dusty roads due to the use of agrochemicals, fertilizers, vehicle emissions and combustion activities. Cf values indicated low contamination in most sites, while PLI generally revealed low soil pollution levels. Based on Håkanson's classification, Cd was identified as the principal contributor to ecological risk. Health risk assessment revealed ingestion as the primary exposure route, with children being more vulnerable than adults, while non-carcinogenic and cancer risks remained within acceptable ranges, although the health risks in agricultural and dusty road zones suggest potential long-term effects. The integration of contamination indices, geospatial mapping, ecological and health risk underscores the importance of sustainable agricultural practices, regular monitoring and strategic management in conserving soil quality and wetland ecosystems in Sistan.
Despite global gains in vaccination coverage, Pakistan continues to lag in achieving universal immunization, with vaccine-preventable diseases (VPDs) contributing to approximately 15% of all deaths annually. We explored missed opportunities for vaccination (MOV) when eligible children failed to receive vaccines when their mothers visited healthcare facilities for unrelated medical needs. Secondary data analysis was conducted using the Pakistan Social and Living Standards Measurement Survey (PSLM) 2019-20, comprising 195,000 households and 103,464 eligible children. MOV was defined as the failure to administer an age-appropriate dose of either pentavalent (Penta-1, 2, 3) or measles (Measles-1, 2) vaccines during a maternal health visit. Weighted multivariate binomial logistic regression was used to explore the association between maternal visits to private healthcare facilities and MOV, adjusting for sociodemographic variables. Geospatial analysis was used to visualize district-level disparities using ArcGIS. Approximately 25% of children aged 1-5 years missed at least one dose of pentavalent or measles vaccination with regional variations. The rates of missed doses were similar for the first, second, and third antigen doses. Rural areas, male children, and households with uneducated mothers had more missed vaccinations, while missed opportunities were more common when mothers visited private healthcare facilities, particularly in urban settings (adjusted Odds Ratio (OR): 1.563 for Penta-1, Confidence Interval (CI): 1.519-1.608) where the private sector predominates and because the public sector accounts for nearly all vaccinations. However, since nearly all vaccinations are in the public sector and the bulk of healthcare seeking is in the private sector, opportunities to vaccinate missed children are lost. Policy and technological solutions that can identify and refer to these children for vaccination can close the national gap in universal vaccination.
Cervical cancer remains a leading cause of cancer mortality among women in sub-Saharan Africa, with HIV infection amplifying risk through immunosuppression. This geospatial analysis examines the alignment between HIV prevalence and cervical cancer screening (CCS) coverage in 4 high-burden countries (South Africa, Kenya, Mozambique, and Lesotho) using recent Demographic and Health Survey data (2016-2023/24). Using nationally representative Demographic and Health Survey data sets from South Africa (2016), Kenya (2022), Mozambique (2022/23), and Lesotho (2023/24), this study used geospatial hotspot analysis to identify areas with high and low CCS coverage and their overlap with high HIV prevalence hotspots. RStudio was used to map and analyze spatial clusters. Substantial geographic heterogeneity was observed within and across countries. In South Africa, HIV hotspots were concentrated in Gauteng and KwaZulu-Natal, with strong alignment between HIV and CCS in metropolitan centers; however, high screening intensity in the Western Cape contrasted with relatively lower HIV burden. In Kenya, the most pronounced convergence occurred in the Lake Victoria basin (Kisumu, Homa Bay, Siaya, and Migori), whereas central counties demonstrated high CCS activity despite lower HIV prevalence. Mozambique showed the clearest spatial concordance, with near-complete overlap of HIV and CCS hotspots in Maputo City, Maputo Province, and Gaza, alongside limited screening presence in central and northern high-burden areas. In Lesotho, HIV and CCS hotspots were largely colocated in Maseru and border districts, with additional moderate overlap in Mokhotlong and southern districts. The analysis highlights where service integration might be working (overlap of HIV prevalence and CCS hotspots) and where urgent alignment is needed (HIV hotspots without CCS). Policymakers should invest in region-specific strategies, with greatest integration potential in Mozambique south, South African metros, and Kenya's Lake Victoria basin, while urgently addressing CCS gaps. Geographically tailored interventions are critical to accelerate progress toward World Health Organization's 90-70-90 cervical cancer elimination targets in high-prevalence settings.
The diphtheria-tetanus-pertussis (DTP) vaccine is one of the core vaccines provided through the Expanded Program on Immunization (EPI), which is administered to children in a series of three doses to protect against three bacterial diseases. Previous studies have assessed the factors associated with non-uptake of DTP3 vaccination among children. However, studies incorporating geospatial analysis remain limited, particularly in East Africa. Therefore, this study aimed to assess the spatial distribution and associated factors of non-uptake of DTP3 vaccination among children aged 12-23 months in East Africa. A total weighted sample of 14,200 children were included from demographic and health survey data of seven East African countries conducted from 2018 to 2023. ArcGIS Pro was used to explore the spatial distribution of non-uptake of DTP3 vaccination. Furthermore, spatial clusters were identified using Kulldorff's spatial scan statistics. Multiscale geographically weighted regression analysis was done to assess significant associated factors. The spatial distribution of non-uptake of DTP3 vaccination in East Africa was clustered. SaTScan identified 291 primary spatial clusters, with a relative risk of 3.97 at a p-value of < 0.001, in the central and most of the northern regions of Mozambique. Multiscale geographically weighted regression revealed that no maternal educational background and fewer than four antenatal care visits were positively associated with non-uptake of DTP3 vaccination, whereas health facility delivery was negatively associated with non-uptake of DTP3 vaccination in East Africa. In East African countries, the high rate of non-uptake of DTP3 vaccination was observed in eastern and northeastern parts of Kenya; central and northern parts of Mozambique; northern and southern parts of Madagascar; and southern and eastern parts of Ethiopia. Therefore, it is recommended to launch community-based educational campaigns and strengthen maternal and child health services in these hotspot areas.
Childhood asthma disproportionately affects Hispanic children in the United States. Nevertheless, few longitudinal cohorts exist in Gulf Coast communities where environmental exposures may compound sociodemographic vulnerabilities. Corpus Christi, a majority-Hispanic city with high levels of petrochemical industrial operations, reports higher asthma prevalence than state and national averages. BREATHE-CC (Bridging Respiratory Exposures, Asthma, and Environmental Health in Corpus Christi) is a prospective cohort designed to investigate the role of air pollutants, household conditions, and social determinants of health in asthma exacerbations and wheezing phenotypes. Approximately 200 children less than 10 years of age with asthma will be enrolled from Driscoll Children's Hospital. Enrolled participants complete baseline assessments and are followed monthly for up to 18 months using a parent-reported modified ISAAC (International Study of Asthma and Allergies in Childhood) questionnaire that captures household exposures, asthma exacerbations, and wheezing episodes. Questionnaire responses will be validated and supplemented with electronic health record (EHR) reviews. Daily air pollutant concentrations (PM2.5, PM10, O3, SO2) from the Texas Commission on Environmental Quality (TCEQ) and U.S. Environmental Protection Agency (EPA) monitoring stations will be linked to participants' addresses. Generalized Additive Models (GAMs) and Poisson regressions will assess the associations between air pollutant exposures, household risk factors, asthma exacerbations, and wheezing phenotypes, adjusting for age, sex, body mass index (BMI), and other sociodemographic indicators. Group-Based Trajectory Modeling (GBTM) will identify latent phenotypes of wheezing. This is a longitudinal cohort examining Hispanic children residing in the Gulf Coast petrochemical corridor. In particular, the study integrates granular geospatial environmental monitoring to link daily air pollutant exposure levels with asthma exacerbation risk. GBTM will also be used to identify latent wheezing phenotypes, especially focusing on differences between infectious and non-infectious wheezing. Recruitment will occur at a single hospital in the Coastal Bend region with a modest sample size, which may limit generalizability. Clinical trial number: not applicable. Open Science Framework [https://osf.io/tbg6y/overview?view_only=87309518c35b4d78a7bbe79d5fa70ceb].
Pregnancy loss is the terminated pregnancy before the completed pregnancy time. Spatial location can significantly influence pregnancy outcomes, yet geographic disparities in the risk of pregnancy loss remain poorly studied in East Africa. This study is aimed at examining the spatial variation and determinants of time to pregnancy loss among women of reproductive age in the region. A Bayesian spatial survival model with an intrinsic conditional autoregressive approach was utilized to identify factors related to time to pregnancy loss across 169 regions in 9 East African countries using secondary data from recent demographic and health surveys (2015-2023). A spike-and-slab prior was used for variable selection. Model comparison utilized deviance information criteria, Watanabe-Akaike information criterion, and log pseudo marginal likelihood, with diagnostics from Cox and Snell residuals. Pregnancy loss showed significant spatial clustering. Earlier occurrence was observed among women aged 25-34 years (ϕ = 0.712; 95% CrI: 0.680-0.744) and ≥ 35 years (ϕ = 0.326; 95% CrI: 0.307-0.344), those living with their husbands (ϕ = 0.893; 95% CrI: 0.856-0.932), with primary education (ϕ = 0.939; 95% CrI: 0.892-0.987), regular media exposure (ϕ = 0.854; 95% CrI: 0.819-0.889), employed (ϕ = 0.818; 95% CrI: 0.788-0.850), and attending antenatal care (ϕ = 0.964; 95% CrI: 0.933-0.996). In contrast, college-educated women (ϕ = 1.109; 95% CrI: 1.024-1.203), rural residents (ϕ = 1.144; 95% CrI: 1.102-1.190), low parity (ϕ = 14.93; 95% CrI: 13.853-16.132), and grand multiparity (ϕ = 22.088; 95% CrI: 20.131-24.247) were associated with longer time to pregnancy loss. After adjusting for individual-level factors, residual variation in the hazard of pregnancy loss remained. Pregnancy loss remains a significant public health challenge in East Africa, with significant geographic variation. Spatial analysis can guide region-specific healthcare strategies and targeted interventions.
Vaccination remains one of the most effective public health measures, yet many children in Nigeria continue to miss essential vaccines, leaving them exposed to preventable diseases. Understanding the geographic and temporal patterns of missed vaccinations is important for designing targeted and equitable immunization strategies. This study investigates the geospatial variations in the prevalence of children who missed diphtheria-pertussis-tetanus vaccination in Nigeria. Data were obtained from the Nigeria Demographic and Health Surveys conducted between 2003 and 2023/2024. Bayesian geostatistical models were fitted within the Integrated Nested Laplace Approximation (INLA) framework to estimate the prevalence of zero-dose and under-immunized children across states and survey periods. Exceedance probability maps were used to identify states with a high likelihood that the prevalence of zero-dose children exceeded ten percent. The results show clear geographic clustering, with persistently higher prevalence of missed vaccinations in the northern regions compared to the south. Dropout between consecutive DPT doses has decreased over time, indicating improved follow-through once children start vaccination; however, each successive dose still shows a higher prevalence of missed vaccinations than the preceding one. Exceedance probability maps further highlight states such as Kebbi, Sokoto, Zamfara, and parts of Niger, Kwara, Borno, Yobe, Taraba, and Kogi, where the likelihood of zero-dose prevalence surpassing 10% remains high. Despite improvements in childhood vaccination coverage, large geographic disparities persist, especially in northern states. The continued presence of states with a high probability of zero-dose prevalence suggests that national progress has not resulted in equitable gains. Strengthening local immunization systems, addressing regional barriers, and prioritizing targeted interventions are needed to ensure that all children benefit from routine vaccination services.
Highly processed food (HPF) intake contributes to negative health outcomes, yet gaps remain in understanding population-level consumption. This study characterized HPF consumption across 14 food categories among Geneva adults and identified related socioeconomic, spatial, and health patterns. This study analyzed data from 3600 adults in the Specchio cohort (March 2025). HPF consumption across 14 categories was assessed using the validated short screening-HPF questionnaire. Participants were classified as high/low HPF consumption. Multivariable logistic regression examined associations with socioeconomic, lifestyle, and health factors; spatial analysis assessed geographic clustering. Overall, 20% were high HPF consumers. Stratified per HPF categories, high consumption was most prevalent for fats (85%), full-fat dairy (71%), refined products (70%), sweet dairy (43%), and snacks (38%). Male sex was the strongest determinant of HPF consumption, with stronger associations for distilled beverages (adjusted odds ratio [aOR] = 4.8, 95% CI: 3.7-6.4) and fried foods (aOR = 2.3, 95% CI: 1.8-3.0). Younger age was associated with higher consumption of snacks, refined products, and ready-to-eat meals. Financial stress and family conflicts were associated with higher consumption of specific HPF categories. High HPF consumption was associated with worse cardiometabolic outcomes, particularly obesity and diabetes, which were most strongly associated to ready-to-eat meals and sweet drinks. Spatial analysis showed distinct patterns for specific HPF categories but no geographic clustering for overall HPF. One in five adults consume high levels of HPF, with distinct patterns across demographics and food categories, particularly ready-to-eat meals, sweet drinks, fried foods, and processed meat, with male sex, younger age, financial stress, and family conflicts as major risk factors. Findings support targeted prevention and primary care strategies focusing on specific HPF categories in high-risk populations, which may prove more impactful and efficient than broad, uniform approaches.
West Nile virus (WNV) is a globally distributed mosquito-borne flavivirus with significant implications for both veterinary and public health. While horses are incidental dead-end hosts, their epidemiological role extends beyond clinical disease, as they can serve as effective sentinel hosts for detecting local viral circulation. Their frequent exposure to mosquito vectors, ability to mount measurable antibody responses, geographic stability, accessibility for monitoring, and the possibility of observation within managed owner-veterinarian systems make them particularly suitable for surveillance within a One Health framework. Evidence from Europe and the Americas demonstrates that equine seroprevalence and field surveillance can identify transmission hotspots, reveal silent circulation, and contribute to the understanding of spatial and temporal risk patterns. The review also addresses key limitations, including vaccination effects, flavivirus cross-reactivity, methodological heterogeneity, and challenges in interpreting serological data across different ecological contexts. Strengthening equine sentinel surveillance through standardized methodologies and integration with predictive and geospatial approaches may improve early warning capacity and support more effective control of WNV and other emerging arboviral diseases.
Inspired by conceptual principles from quantum information theory, a novel classical approach to address temporal delays in spatial data analysis is presented. Current geospatial services face latency challenges due to complex processing chains, which motivate an investigation of whether the quantum-inspired paradigm could offer efficiency gains when implemented using classical hardware. A framework is proposed that incorporates three metaphors derived from quantum concepts: i) application of bit-like representation that mimics Qubit superposition to handle data uncertainty probabilistically; ii) use of probabilistic distributions for handling data uncertainty; and iii) creation of efficient data linkages by establishing pre-computed spatial correlations as an analogue to quantum entanglement. This model suggests potential temporal improvements while acknowledging current classical computing limitations. The proof-of-concept was tested on urban air quality monitoring, integrating data from fixed stations and mobile sensors. Simulation results indicated potential latency reduction while maintaining analytical accuracy (mean error <5.2% in controlled tests). Compared to the standard classical methods, the quantum-inspired metaphor showed efficiency improvements in theory when scaled to appropriate problem sizes, with simulated refresh rates of 250 milliseconds. Error analysis support the usefulness of the system for environmental health applications running on existing classical infrastructure. This research contributes: i) a framework for using quantum- inspired metaphors to address temporal challenges in geospatial analysis; ii) a simulation prototype for air quality monitoring; and iii) preliminary evidence of potential advantages from a bio-inspired approach in GIS processing. The technique may prove valuable for time-sensitive applications with today's technology and could inform future designs for potential quantum computing implementations.
Exposure to tobacco advertising at tobacco retail outlets (TROs) is associated with smoking initiation among youth. There is limited geospatial evidence on the density of TROs in Lao People's Democratic Republic (PDR), a country with high prevalence of tobacco smoking. This study examined the density and proximity of TROs around schools in two urban districts and one rural district of Vientiane Capital, Lao PDR, using geographic information systems. We audited 233 TROs around 27 schools between January 19 and February 18, 2024. TROs were mapped within 250 m and 500 m buffers in two urban districts (Chanthabuly and Sissatanak), and 500 m and 1,000 m buffers in one rural district (Naxaithong). Buffer analysis and network analysis estimated TRO density and median walking distances between TROs and schools. We used the Kruskal-Wallis test to determine if TRO density varied significantly in urban districts within two buffers and the chi-square test to examine differences in TRO characteristics based on proximity to schools. TRO density was defined as the number of TROs mapped within a 250 m radius of urban schools and those mapped within 1,000 m radius of rural schools. TRO density was higher within the buffer of 250-500 m in Chanthabuly (median = 12), followed by Sissatanak (median = 3) (p = 0.01). Comparing the two urban districts, the median distance between TROs and schools within the buffer of 250-500 m was significantly less in Sissatanak compared to Chanthabuly (p = 0.04). The shortest distance between an urban school and any TRO (i) without age verification signage was 21.58 m, (ii) with outside cigarette advertisements was 9.95 m, and (iii) selling "single" cigarettes was 311.36 m. In the rural district, the TRO density was higher within 500-1,000 m (median = 2) compared to within 500 m (median = 0.5). Within the context of the Lao PDR, our study provides the first geospatial evidence of tobacco retail outlet density in both urban and rural districts of Vientiane Capital, revealing a substantially higher concentration of outlets in urban districts.We also quantified walking distances between schools and outlets violating tobacco control measures, including lack of age verification signage and outdoor cigarette advertising. These findings suggest that stricter regulation of tobacco retail outlets could strengthen tobacco control policy implementation in Lao PDR.