Spatial and temporal disparities in general practitioner provision: a 21-year longitudinal analysis from Lower Saxony, Germany
Equitable access to general practitioner services remains a persistent challenge for health systems and is critical for reducing health inequalities, particularly between urban and rural regions. Understanding the spatial and temporal dynamics of primary care provision is vital for informed healthcare planning and policy.
Enhancing elderly care services in high-density aging communities: a dual-dimensional GIS-SPO framework for spatial and temporal optimization
Is the neighbourhood environment associated with indicators of health in children and adolescents? Developing and testing a new proof-of-concept Healthy Environments Index for Children in Taranaki, New Zealand
We describe the development of a comprehensive proof-of-concept index of environmental exposures for children based on evidence-informed connections to health behaviours- the Healthy Environments Index for Children (HEIC) - with two sub-indices relating to the food environment (HEIC-FE) and physical activity environment (HEIC-PA) in Taranaki, New Zealand. Associations between this theory-informed index and health outcomes in a cohort of children and adolescents identified with overweight or obesity and enrolled in a community-based healthy lifestyle programme and randomised controlled trial were examined.
Spatial spillover effects of area-level socioeconomic factors on life expectancy in Japan: an ecological study
Area-level socioeconomic status is a well-established determinant of geographical disparities in life expectancy. However, limited attention has been paid to spatial spillover effects, whereby socioeconomic conditions in neighbouring regions influence health outcomes. This study aimed to estimate the direct and spatial spillover effects of socioeconomic factors on life expectancy in Japan and to explore possible mechanisms underlying the observed spillover patterns.
Spatial modeling of the population dynamics of Anopheles mosquitoes in Madagascar
Malaria, whose parasites are transmitted by Anopheles mosquitoes, remains a major public health burden in Madagascar despite the control measures led by the National Malaria Control Program. Understanding the population dynamics of Anopheles mosquitoes is therefore essential to optimize malaria surveillance and control. This study aimed to develop a model incorporating environmental, climatic and agricultural determinants of Anopheles abundance to predict their spatiotemporal distribution.
A participatory virtual audit of the built environment for age-friendliness
Geospatial studies that consider the relationships between the built environment and health typically rely on researcher-led 'objective' measurement of geospatial attributes of the built environment. Some studies can fail to find expected associations between environments and health outcomes where the geospatial measures do not reflect the experiences or perceptions of people themselves. We took a participatory approach to work with older adults with a concern for falling to assess the built environment in order that we could understand how their assessments relate to researcher assessments. We also wanted to assess whether specific demographic characteristics explained differences in assessments of the built environment between participants. Age-friendly environments can contribute to healthy active ageing. Falling and a fear of falling can lead to restricted outdoor activity. Therefore, understanding how the built environment contributes to fear of falling is important for age-friendly environments.
H3-MOSAIC: multimodal generative AI for semantic place detection from high-frequency GPS on H3 grids in mental health geomatics
Mental-health geomatics require reliable ways to convert high-frequency GPS trajectories into meaningful place types that support indicators such as homestay, location entropy, and spatial extent of daily activities. Raw coordinates are typically noisy and carry little semantic information. We introduce H3-MOSAIC(H3-based Multimodal OSM-and-Satellite AI for Classification), a multimodal generative framework that fuses OpenStreetMap (OSM) building text and satellite imagery on H3 grids to infer place semantics from high-frequency GPS.
Assessment of a gridded population sample frame for a household survey of refugee populations in Uganda, 2021
To date, few HIV-related population-based data are available for refugee populations. Household surveys typically require reliable population counts and well-defined geographic areas, which are often not available for refugee settlements. We describe the gridded population sampling approach as an option for conducting such a survey in Uganda and describe its application for a household survey in Uganda and assess its utility among refugee populations.
A novel approach for mapping exposure to land cover at the small statistical geography level
Many studies linking spatial environmental exposures to health outcomes rely on small statistical geography units, such as Lower-layer Super Output Areas (LSOAs), to estimate exposure. However, these units commonly vary in size, particularly between urban and rural areas, leading to potential exposure misclassification. This study proposes a new method for better capturing environmental exposure at the small statistical geography unit level. Using the Living England Habitat Map as an example, we combined LSOA and postcode-level data to account for varying area sizes and mitigate edge effects. We compared our method with the typical approach, which calculates an average at the small geography unit level. Overall, our proposed method resulted in lower exposure to non-built-up areas compared to averaging across entire LSOAs, whereas exposure to built-up areas was higher by 8-10%. However, these patterns varied based on region, urban/rural classification, land cover type, and LSOA size class. We suggest that this proposed method offers a more consistent approach to estimating neighbourhood exposure to nature.
Impact of spatial accessibility to primary care physicians on health care outcomes and costs
This study is the first in Taiwan to apply the enhanced two-step floating catchment area (E2SFCA) method to evaluate the spatial accessibility of primary care. Traditional physician-to-population ratios by administrative region overlook cross-boundary healthcare-seeking and travel distance barriers. This study accounts for these limitations and further examines the impact of accessibility on healthcare utilization and outcomes.
Pneumonia incidence and determinants in South Punjab, Pakistan (2016-2020): a spatial epidemiological study at Tehsil-level
Pneumonia remains a major cause of morbidity and mortality, particularly in low- and middle-income countries, such as Pakistan. In this study, we aimed to examine the spatial and temporal patterns of pneumonia incidence in South Punjab, Pakistan, and to analyze their association with socio-ecological factors.
Self-reported mental distress in the United States: a Bayesian analysis of the spatial structure over the COVID-19 pandemic across age groups
The COVID-19 had an outstanding impact on well-being and mental health, which might have elicited geographical variations over time. This study examines the eventual impact of COVID-19 on self-reported mental distress in the mainland USA.
Assessing spatial variability in observed infectious disease spread in a prospective time-space series
Most of the growing prospective analytic methods in space-time disease surveillance and intended functions of disease surveillance systems focus on earlier detection of disease outbreaks, disease clusters, or increased incidence. The spread of the virus such as SARS-CoV-2 has not been spatially and temporally uniform in an outbreak. With the identification of an infectious disease outbreak, recognizing and evaluating anomalies (excess and decline) of disease incidence spread at the time of occurrence during the course of an outbreak is a logical next step. We propose and formulate a hypergeometric probability model that investigates anomalies of infectious disease incidence spread at the time of occurrence in the timeline for many geographically described populations (e.g., hospitals, towns, counties) in an ongoing daily monitoring process. It is structured to determine whether the incidence grows or declines more rapidly in a region on the single current day or the most recent few days compared to the occurrence of the incidence during the previous few days relative to elsewhere in the surveillance period. The new method uses a time-varying baseline risk model, accounting for regularly (e.g., daily) updated information on disease incidence at the time of occurrence, and evaluates the probability of the deviation of particular frequencies to be attributed to sampling fluctuations, accounting for the unequal variances of the rates due to different population bases in geographical units. We attempt to present and illustrate a new model to advance the investigation of anomalies of infectious disease incidence spread by analyzing subsamples of spatiotemporal disease surveillance data from Taiwan on dengue and COVID-19 incidence which are mosquito-borne and contagious infectious diseases, respectively. Efficient R packages for computation are available to implement the two approximate formulae of the hypergeometric probability model for large numbers of events.
Validity and reliability of the virtual audit tool for estimating built-environment characteristics in Taiwan
Environmental factors significantly influence health behaviors and outcomes. While Google Street View (GSV) has emerged as a cost-effective tool for environmental auditing in various countries, its feasibility in Taiwan remains unexplored. This study aimed to examine the validity and reliability of GSV-based environmental audits in Taiwan.
Socio-spatial inequalities in accessibility of Indigenous community-controlled mental health services in South East Queensland, Australia
Mental disorders significantly burden Indigenous communities, worsened by limited culturally appropriate services. Spatial inequalities in access further disadvantage Indigenous peoples, especially in socio-economically challenged areas. This paper measures the spatial accessibility of Indigenous community-controlled mental health services in South East Queensland, Australia and examines its social inequalities across the region.
Analyzing the stability of gun violence patterns during the COVID-19 pandemic in Syracuse, New York
Gun violence is a leading cause of death in the United States. Understanding the geospatial patterns of gun violence and how the COVID-19 pandemic may have affected them is essential for developing evidence-based prevention strategies. This study investigates whether COVID-19 altered the geospatial patterns of gun violence in Syracuse, New York. To assess spatial and temporal trends, we analyzed the annual total gunshots (ATG) from 2009-2023 aggregated in census block groups and applied geospatial techniques including mean center, standard distance, Moran's I, and Getis-Ord Gi*. The ATG number was higher before the pandemic than during the pandemic, something not observed in other studies. Its geographic centers before and during the pandemic clustered within or near one census block and the associated standard distance remained similar between the two periods. Both global patterns and local clusters of ATG in the two periods not only showed similar patterns and consistent local hotspots located in similar areas, but also logarithmically related to the ATG number with statistical significance, suggesting that gun violence rates intensified within established areas rather than spreading citywide and demonstrated a similar distance-decay effect in both periods. This effect suggests that the incidence of gunshots diminished with increasing distance from the core concentrated zone, challenging assumptions of spatial spillover or contagion models in crime studies. These findings suggest that entrenched structural conditions, such as neighborhood-level socioeconomic disparities, are the primary drivers of gun violence patterns, rather than temporary pandemic-related policies. Methodologically, the study highlights the importance of long-term, meso-scale geospatial analyses to uncover persistent violence dynamics and guide preventive interventions. We argue that future violence prevention strategies should focus on enduring geospatial patterns of gun violence and their underlying structural determinants, rather than reacting solely to short-term fluctuations in incident frequency.
Street view images help to reveal the impact of noisy environments on the survival duration of stroke patients
While road traffic noise is an emerging environmental risk for cardiovascular mortality, its age-group-specific effects on stroke mortality remain unclear. This study further explored socioeconomic disparities in this association.
Exploring spatial-temporal heterogeneity in new-type urbanization's impact on health expenditure: a GTWR analysis
To address challenges arising from rapid urban development, China has formulated and implemented the New-Type Urbanization strategy. However, empirical research on the specific impacts between New-Type Urbanization and health expenditures remains limited.
Current and future temperature suitability for autochthonous transmission of malaria in Canada
Malaria continues to be one of the most significant infectious diseases in terms of morbidity and mortality. In many parts of North America, including parts of southern Canada, competent malaria vectors Anopheles quadrimaculatus and Anopheles freeborni are present. With climate change, Canada may be increasingly suitable for transmission of the malaria parasite Plasmodium spp. The objective of this study was to identify the geographic locations in Canada where, and the frequency with which, temperature conditions may be suitable for autochthonous transmission of Plasmodium vivax and Plasmodium falciparum under current and projected climate.
An AI-based gravitrap surveillance for spatial interaction analysis in predicting aedes risk
Dengue fever is transmitted to humans through bites of Aedes mosquito vectors. Therefore, controlling the Aedes population can decrease the incidence and block transmission of dengue fever and other diseases transmitted by these mosquito species. In many countries, gravitraps are used to monitor mosquito vector densities, but this approach usually underestimates the population of Aedes mosquitoes. Moreover, literature on the spatio-temporal dynamics of Aedes populations in a single city is limited. For example, in Kaohsiung of Taiwan, population densities vary substantially between villages, and the city government has relatively limited resources to deploy gravitraps. Therefore, a well-defined index should be developed to reflect the spatial-temporal dynamics of adult Aedes mosquitoes in urban environments. This would allow reduction of sources and removal of vector habitats under various situations.
Optimizing ambulance location based on road accident data in Rwanda using machine learning algorithms
The optimal placement of ambulances is critical for ensuring timely emergency medical responses, especially in regions with high accident frequencies. In Rwanda, where road accidents are a leading cause of injury and death, the strategic positioning of ambulances can significantly reduce response times and improve survival rates. The national records of Rwanda reveal a rising trend in the number of road accidents and deaths. In 2020, there were 4203 road traffic crashes throughout Rwanda with 687 deaths, data from 2021 demonstrated 8639 road traffic crashes with 655 deaths. Then in 2022 national statistics indicated 10,334 crushes with 729 deaths. The study used emergency response and road accident data collected by Rwanda Biomedical Centre in two fiscal years 2021-2022 and 2022-2023 consolidated with the administrative boundary of Rwandan sectors (shapefiles).
