Stunting remains a significant public health concern in Indonesia, characterized by wide regional disparities and persistent prevalence in rural and underserved communities. This study applies the Bayesian Spatial Durbin Model (BSDM) to analyze the spatial distribution and interregional dynamics of childhood stunting across 31 provinces in Indonesia. District level data on stunting prevalence were obtained from the community-based health survey RISKESDAS survey of 2023, focusing on three programmatically salient covariates: the proportion of households with adequate housing, the proportion of children under five who received complete basic immunization and the proportion of infants aged 0-5 months who were exclusively breastfed. The BSDM quantifies direct and spatial spill-over effects while accounting for spatial autocorrelation and parameter uncertainty. Results indicate that adequate housing and complete immunization are associated with lower stunting prevalence and that exclusive breastfeeding are directionally protective. The study finds that spatially coordinated investments in housing quality, immunization outreach and infant feeding support accelerated stunting reduction.

This study assessed spatial accessibility to fixed mammography centres across Oklahoma State, USA using the Two-Step Floating Catchment Area (2SFCA) and the Enhanced Two-Step Floating Catchment Area (E2SFCA) methods to identify areas with limited or no access. For this analysis, we used data from the mammography facilities database of the US Food and Drug Administration verified by direct contact with the facility and the U.S. Census block group population and demographics for women aged 40 years and older. Analyses were stratified by urban areas; large rural areas; and small rural areas. Accessibility scores were calculated using the 2SFCA method with 30-minute drive times and the E2SFCA method with drive times of 10, 20 and 30 minutes weighted by distance decay. Block groups were categorized into quartiles based on accessibility scores. Among 940,994 eligible women, 10% lived in areas with no access. Small rural regions faced the greatest barriers. Spatial disparities were linked to racial and socioeconomic differences: non-Hispanic American Indian/Alaska Native and non-Hispanic White populations were more likely to reside in noaccess zones, while Black and Hispanic populations clustered in high-access urban areas. Spatial analysis reveals significant rural disparities in mammography access. Mobile machines should prioritize underserved rural regions to improve equity.

This study investigates spatial disparities in cancer and lung-cancer mortality across Europe through an integrative geospatial epidemiological framework. Using age-standardised Eurostat mortality data for 2022 at the NUTS-2 level, we combine Getis-Ord Gi* and Anselin Local Moran's I to detect statistically significant hot/cold spots, while multivariate regressions incorporate environmental and topographic predictors. Results reveal pronounced east-west and urban-rural gradients: persistent high-mortality clusters span Central and Eastern Europe, where historical industrialisation, elevated smoking prevalence, and structural healthcare gaps converge. By contrast, Southern European regions - Portugal, western Spain, and southern Greece - are associated with lower observed mortality levels, plausibly reflecting favourable behavioural profiles, environmental conditions, and healthcare accessibility. Spatial outliers identify territories where localised factors, such as air-pollution peaks or differential diagnostic capacity, modify broader regional patterns. Overall, the findings highlight geography as a structuring context for exposure, vulnerability, and access to care, rather than as a direct causal driver of cancer risk, and demonstrate the value of spatial epidemiology for territorial health governance, environmental monitoring, and urban planning. Policy relevance is twofold. First, the evidence supports region-specific interventions aligned with the Sustainable Development Goals (SDG) - especially SDG 3 (health), SDG 10 (reduced inequalities), and SDG 11 (sustainable cities). Second, the spatial outputs provide a robust empirical basis for informing the health-equity ambitions of Europe's Beating Cancer Plan and the environmental-justice agenda of the European Green Deal. By bridging granular geospatial evidence with EU-wide priorities, the study underscores the need for place-based, equity-oriented frameworks in cancer prevention and control across heterogeneous European landscapes.

In the State of Mexico, several venomous snakes have low median lethal doses, which therefore pose serious health risks. We anal- ysed the epidemiology of snakebites from 2003 to 2024 and examined their relationship with demographic, socioeconomic, and bio- logical factors. Incidence rates and demographic characteristics were calculated, and Getis-Ord Gi* statistics were used to identify snakebite hotspots. We also applied Non-Metric Multi-Dimensional Scaling (NMDS) to explore associations between hotspot cate- gories and socioeconomic conditions. The potential distribution of 14 venomous snake species was modelled to estimate venomous snake diversity across municipalities. A total of 3,972 cases were reported, with an increasing trend over time. Most bites occurred in summer, affecting mainly males aged 25-44. Hotspot analysis identified 27 municipalities as hotspots, 50 as not significant and 48 as coldspots. Southern municipalities showed higher snakebite incidence. Coldspot areas had higher educational attainment and greater employment in services and tertiary sectors, despite similar snake diversity to hotspots. These findings can guide public health strategies, particularly regarding the allocation of antivenoms in regional hospitals.

Public health is a key component of the United Nations Sustainable Development Goals (SDGs) and is central to the all-round development of individuals. Based on panel data from 31 provinces in China between 2010 and 2023, this article adopts the Population Mortality Rate (PMR) as a measure of public health and employs the Generalized Additive Model (GAM) from machine learning to systematically investigate the nonlinear effects of multidimensional factors-including medical resources, environmental pollution, socioeconomic conditions, and technology-on public health. The results of the study show that China's PMR exhibits an overall upward trend, with a spatially uneven distribution and significant regional disparities, as mortality rates in the central and western regions are generally higher than those in the eastern coastal provinces. All influencing factors show significant associations with the PMR. The effects of all influencing factors on mortality exhibit complex nonlinear characteristics, with their impacts varying considerably across different value ranges. Specifically, the influence of medical resources exhibits critical thresholds, such as the Number of Urban Practicing (assistant) Physicians per 10,000 people (NUPP) reaching its maximum health benefit at approximately 40; while the relationship between environmental indicators and mortality reveals potential complex confounding mechanisms, as evidenced by the negative association observed between Sulphur Dioxide Emissions (SDE) and mortality rates within the observed range; whereas the health benefits of basic resources and developmental factors, such as Per Capita Water Resources (PCWR), stabilize after crossing a specific threshold (20,000 cubic meters per person). Finally, some practical policy recommendations are put forward.

Plateau State is one of Nigeria's 14 states with a high Tuberculosis (TB) burden. In this state and its capital city, Jos Metropolis, TB cases have been on the increase. There are no reported studies on the spatial mapping of TB cases from Jos Metropolis. Thus, it is not known how TB hotspots and clusters may contribute to the propagation of area-wide TB transmission in this area and the implications for prevention and control. The objective of this study was to determine the spatial pattern of TB cases in Jos Metropolis from 2019-2022 based on existing TB data in the treatment registers and their residential addresses. We geolocated the cases to the nearest Polling Unit (PU) in their Electoral Ward (EW) using the Global Positioning System (GPS) coordinates obtained from the Polling Unit Locator (PUL) on the website of the Independent National Electoral Commission (INEC). In ArcGIS Pro (version 3.5.3) environment, TB hotspots were determined. Using the SaTScan software (version 10.3.2), a retrospective purely spatial analysis was carried out to identify purely spatial TB clusters based on the discrete Poisson model. A total of 4,897 TB cases were mapped. Significant TB hotspots (Z-score >1.96 and p-value <0.05) and primary TB clusters were found for each of the study years. The hotspots and clusters were located in the northern part of the Jos Metropolis, particularly the more centrally located areas. We found both a potential for future increase in TB cases and a spread to other areas of the Jos Metropolis from these TB hotspots and clusters in the northern part of the metropolis. Hence, there is an urgent need for a targeted TB screening and treatment, resource allocation and health education campaigns in the identified EWs.

Rapid urban growth has increased concerns about spatial equity in access to Primary Healthcare Facilities (PHCs), particularly in contexts where proximity-based assessments may overestimate effective access by overlooking population demand and service capacity. This study evaluates district-level accessibility and equity of PHCs in Jeddah, Saudi Arabia using a capacity-sensitive Modified Two-Step Floating Catchment Area (M2SFCA) framework incorporating population weighting, distance decay and bed capacity. Network-based service area analysis was used to define catchment thresholds, while origin-destination cost matrices supported accessibility indexing. Spatial patterns were examined using Global Moran's I, and distributional equity was assessed through coefficient of variation, percentile ratio, accessibility shares, Gini coefficient and Lorenz curves. A planning-oriented location-allocation model evaluated a scenario-based PHC expansion. Results show that although approximately 69% of the urban area lies within nominal PHC catchments, baseline accessibility exhibits noticeable spatial inequities, with near-zero access in several peripheral districts and significant spatial clustering (Moran's I = 0.398). The proposed scenario introducing four PHCs with varied capacity produced systematic improvements in underserved areas. The percentage ratio declined sharply from 81.34 to 9.13, demonstrating substantial disparities between the highest and lowest-access districts. This increased the accessibility share of the bottom 40% of the population, and lowered overall inequality from 0.191 to 0.172 while slightly weakening spatial clustering. The findings demonstrate that capacity-aware accessibility modelling integrated with planning scenarios provides policy-relevant insights for improving spatial equity in PHC provision and is transferable to other rapidly urbanizing urban contexts.

Influenza epidemics tend to impact the poorest populations living in dense, unhealthy conditions more than the wealthier living in healthier, less dense surroundings. This study shows how the relationship between influenza mortality and the wealth of London's population during the Russian Flu pandemic of the early 1890's contradicts this conventional wisdom. This analysis examines London's 1890, 1891 and 1892 epidemic waves statistically and geographically, comparing wave flu mortality to population wealth, density and healthiness metrics. Correlation analysis shows that flu mortality directly correlates with wealth in all three waves; and inversely correlates with both population healthiness and density metrics. Some deficiencies exist in the 130-year-old data that pre- clude applying 21st-century rigor to the data analysis. For example, the causative agent of the flu was unknown at the time causing significant misidentification of causes of deaths. Nevertheless, analysis of the spatial association of flu mortality with population wealth using Lee's L statistic shows areas of both high mortality and high wealth in the wealthy areas east of the City of London, supporting the counterintuitive results of London's experience. This study does not seek to explain the reasons for these unexpected outcomes; however, the results suggest that today's metropolitan and regional planning authorities need to account for unexpected nuances in contingency plans for potential epidemics based upon best practice recommendations from appropriate national authori- ties. These plans need to consider previous local experience and must have a mechanism/process in place to detect and react to observed departures from the 'expected.'

To gain insight into the common pathogenic, bacterial zoonosis represented by Salmonella infections in poultry and humans, we acted to determine salmonellosis prevalence in poultry and humans in Nigeria mapping hotspots. Using multi-sourced data, we conducted a meta-analysis to determine national and sub-national prevalence of salmonellosis in poultry from 2000 until 2020. Bayesian spatial joint modelling was used to map Non-Typhoidal Salmonella (NTS) infections in humans and poultry using climatic and demographic predictor variables. With the overall prevalence in poultry at 31.6%, the highest state-level prevalence rates were seen in Ogun (70.2%), Lagos (61.8%), Zamfara (58.2%) and Bauchi (57.1%). The North-West, South-West and South-South regions of Nigeria have the highest regional-level prevalence in poultry amounting to 38.5%, 36.9% and 33.6%, respectively. Thirteen states have higher than the average national prevalence (31.6%). While we found a negative association between NTS in humans and in poultry, the prevalence of diarrhoea in humans positively predicted salmonellosis in poultry. Not surprisingly, poultry populations positively predicted salmonellosis in other poultry populations. Higher numbers of human cases were predicted in the North, with more poultry cases in the South and in some North-Eastern states. The observed human NTS-poultry salmonellosis correlation is counterfactual to logic and plausibility as high poultry density and contamination in poultry are expected to predict human infection. The outcome pointed to under-reporting linked to self-treatment, under-testing in the public health and veterinary laboratory and lack of uniform primary healthcare services, particularly in under-served areas of Nigeria. Salmonellosis continues to be a serious burden, and provision of better health data is needed.

While the relationship between socioeconomic status and Early Childhood Development (ECD) is well-documented, less is known about how developmental outcomes and child malnutrition cluster and interact across geographically proximate areas. This study applies spatial analysis to examine regional disparities in ECD in Pakistan and to assess the extent of spatial dependency in these outcomes. Using cross-sectional data from multiple indicator cluster survey (120,151 children across 144 districts) covering 2017- 2018, Moran's I statistics revealed significant positive spatial autocorrelation, consistent with Tobler's First Law of Geography. Districts with high (or low) ECD outcomes tended to be surrounded by similar districts. A distinct core periphery pattern emerged, with Punjab and Gilgit-Baltistan forming high-high clusters and Sindh, Khyber Pakhtunkhwa and Balochistan forming low-low clus- ters. Ordinary Least Squares (OLS) and Spatial Error Models (SEM) confirmed that stunting, underweight and overweight negative- ly affect ECD, while female literacy, access to mass media and child engagement in playing activities influence development posi- tively. Wasting showed no significant relationship. Results reveal that unobserved regional factors contribute to child development across districts, indicating that developmental deficits often cluster geographically. These findings extend spatial dependency theory to the ECD context in South Asia, underscoring the need for geographically coordinated interventions that address both local deter- minants and regionally shared underlying influences on child development.