Geospatial Health最新文献

{"title":"Integrating agent-based disease, mobility and wastewater models for the study of the spread of communicable diseases.","authors":"Néstor DelaPaz-Ruíz, Ellen-Wien Augustijn, Mahdi Farnaghi, Sheheen A Abdulkareem, Raul Zurita Milla","doi":"10.4081/gh.2025.1326","DOIUrl":"https://doi.org/10.4081/gh.2025.1326","url":null,"abstract":"<p><p>Wastewater-based epidemiology was utilized during the COVID-19 outbreak to monitor the circulation of SARS-CoV-2, the virus causing this disease. However, this approach is limited by the need for additional methods to accurately translate virus concentrations in wastewater to disease-positive human counts. Combined modelling of COVID-19 disease cases and the concentration of its causative virus, SARS-CoV-2, in wastewater will necessarily deepen our understanding. However, this requires addressing the technical differences between disease, population mobility and wastewater models. To that end, we developed an integrated Agent-Based Model (ABM) that facilitates analysis in space and time at various temporal resolutions, including disease spread, population mobility and wastewater production, while also being sufficiently generic for different types of infectious diseases or pathogens. The integrated model replicates the epidemic curve for COVID-19 and can estimate the daily infections at the household level, enabling the monitoring of the spatial patterns of infection intensity. Additionally, the model allows monitoring the estimated production of infected wastewater over time and spatially across the sewage and treatment plant. The model addresses differences between resolutions and can potentially support Early Warning Systems (EWS) for future pandemics.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143400935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping livestock systems, bovine and caprine diseases in Mayo-Kebbi Ouest Province, Chad.","authors":"Kella Douzouné, Joseph Oloukoi, Ismaila Toko Imorou, Toure Gorgui Ba, Derrick Chefor Ymele Demeveng","doi":"10.4081/gh.2025.1365","DOIUrl":"10.4081/gh.2025.1365","url":null,"abstract":"<p><p>This study aimed to compile an inventory of the main diseases affecting these species in Mayo-Kebbi Ouest Province in Chad. A survey was conducted between 6 May and 7 August 2024 using a cascade data collection method identifying 310 farmers and 19 veterinarians with an average of 10 to 12 years of experience in advising and supporting livestock practices The data collected included socio-professional characteristics of participants, livestock practices, and geospatial information. These data were managed in Excel and analysed with R. The analysis involved descriptive and inferential statistical techniques including binary logistic regression resulting in maps illustrating disease hotspots and livestock systems. Thematic maps, tables and charts with a 5% significance threshold visualised risk areas and associated livestock practices. The results show a predominance of male farmers (91.9%) from 20 different ethnic groups. The livestock systems identified include data on farming divided into extensive (14.8%), mixed (0.3%) and semi-intensive farming (84.8%). On average, farms have 41 cattle and 25 goats. Animal diseases were found to cause 29.5% reduction in herd productivity. Transhumance (p=0.000356) and animal disease incidence (p=0.03) were observed as significant risk factors associated with the abandonment of livestock farming. The main diseases recorded in cattle include contagious bovine pleuropneumonia (11.3%), bovine tuberculosis (2.5%), foot-and-mouth disease (45.0%), bluetongue (1.7%) and disease with symptoms reminiscent of rinderpest (2.5%). For goats, notable diseases include brucellosis (3.8%), lumpy skin disease (19.2%), goat plague (7.9%) and Rift Valley fever (6.3%). These findings confirm the importance of a geospatial epidemiological surveillance tool for monitoring animal diseases in this region.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143124265","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial association of socioeconomic and health service factors with antibiotic self-medication in Thailand.","authors":"Worrayot Darasawang, Wongsa Laohasiriwong, Kittipong Sornlorm, Warangkana Sungsitthisawad, Roshan Kumar Mahato","doi":"10.4081/gh.2025.1329","DOIUrl":"https://doi.org/10.4081/gh.2025.1329","url":null,"abstract":"<p><p>Antibiotic Self-Medication (ASM) is a major contributing factor to Antimicrobial Resistance (AMR) that can lead to both mortality and long-term hospitalizations. High provincial ASM proportions associated with mortality due to AMR have been observed in Thailand but there is a lack of studies on geographic factors contributing to ASM. The present study aimed to quantify the distribution of ASM in Thailand and its correlated factors. Socioeconomic and health services factors were included in the spatial analysis. Moran's I was performed to identify global autocorrelation with the significance level set at p=0.05 and spatial regression were applied to identify the factors associated with ASM, the proportion of which is predominant in the north-eastern, central and eastern regions with Phitsanulok Province reporting the highest proportion of Thailand's 77 provinces. Autocorrelation between Night-Time Light (NTL) and the proportion of ASM was observed to be statistically significant at p=0.030. The Spatial Lag Model (SLM) and the Spatial Error Model (SEM) were used with the latter providing both the lowest R2 and Akaike Information Criterion (AIC). It was demonstrated that the proportion of alcohol consumption significantly increased the proportion of ASM. The annual number of outpatient department visits and the average NTL decreased the proportion of ASM by 1.5% and 0.4%, respectively. Average monthly household expenditures also decreased the ASM proportion. Policies to control alcohol consumption while promoting healthcare visits are essential strategies to mitigate the burden of AMR in Thailand.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Socio-spatial vulnerability index of type 2 diabetes mellitus in Mexico in 2020.","authors":"Enríque Ibarra-Zapata, Darío Gaytán-Hernández, Yolanda Terán-Figueroa, Verónica Gallegos-García, Carmen Del Pilar Suárez-Rodríguez, Sergio Zarazúa Guzmán, Omar Parra Rodríguez","doi":"10.4081/gh.2025.1348","DOIUrl":"10.4081/gh.2025.1348","url":null,"abstract":"<p><p>This study aimed to estimate a socio-spatial vulnerability index for type 2 diabetes mellitus (T2DM) at the municipal level in Mexico for 2020. It incorporated factors such as poverty, social backwardness, marginalization index, and human development index. This retrospective ecological study analyzed 317,011 incident cases of T2DM in 2020. Utilizing multi-criteria decision analysis, weighted values were assigned to each vulnerability criterion. A multiple linear regression model was developed, complemented by cluster and outlier analyses using Moran I's and the high-low clustering method. A clustered spatial autocorrelation of high values was found across 17.65% of Mexico, which was statistically significant (p < 0.001). Conversely, 37.78% of the territory showed a pattern of low values without significant evidence of groupings. The analysis revealed 117 nodes of very high vulnerability forming six focal areas, 172 nodes with high vulnerability across five areas, 168 nodes with medium vulnerability in two areas, 112 nodes with low vulnerability across 16 areas, and 152 nodes with very low vulnerability in 24 focal areas. This method proves to be robust and offers a technical-scientific basis for guiding T2DM prevention strategies and actions using a spatial/epidemiological approach. It is recommended that future strategies take into account factors such as poverty, social backwardness, marginalization index, and human development index to be effective.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of climate change on dengue fever: a bibliometric analysis.","authors":"Mai Liu, Yin Zhang","doi":"10.4081/gh.2025.1301","DOIUrl":"https://doi.org/10.4081/gh.2025.1301","url":null,"abstract":"<p><p>Dengue is the most widespread and fastest-growing vectorborne disease worldwide. We employed bibliometric analysis to provide an overview of research on the impact of climate change on dengue fever focusing on both global and Southeast Asian regions. Using the Web of Science Core Collection (WoSCC) database, we reviewed studies on the impact of climate change on dengue fever between 1974 and 2022 taking into account study locations and international collaboration. The VOS viewer software (https://www.vosviewer.com/) and the Bibliometrix R package (https://www.bibliometrix.org/) were used to visualise country networks and keywords. We collected 2,055 relevant articles published globally between 1974 and 2022 on the impact of climate change on dengue fever, 449 of which published in Southeast Asia. Peaking in 2021, the overall number of publications showed a strong increase in the period 2000-2022. The United States had the highest number of publications (n=558) followed by China (261) and Brazil (228). Among the Southeast Asian countries, Thailand had most publications (n=123). Global and Southeast Asian concerns about the impact of climate change on dengue fever are essentially the same. They all emphasise the relationship between temperature and other climatic conditions on the one hand and the transmission of Aedes aegypti on the other. A significant positive correlation exists between the number of national publications and socioeconomic index and between international collaboration and scientific productivity in the field. Our study demonstrates the current state of research on the impact of climate change on dengue and provides a comparative analysis of the Southeast Asian region. Publication output in Southeast Asia lags behind that of major countries worldwide, and various strategies should be implemented to improve international collaboration, such as increasing the number of international collaborative projects and providing academic resources and research platforms for researchers.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143460941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Land surface temperature predicts mortality due to chronic obstructive pulmonary disease: a study based on climate variables and impact machine learning.","authors":"Alireza Mohammadi, Bardia Mashhoodi, Ali Shamsoddini, Elahe Pishgar, Robert Bergquist","doi":"10.4081/gh.2025.1319","DOIUrl":"https://doi.org/10.4081/gh.2025.1319","url":null,"abstract":"<p><strong>Introduction: </strong>Chronic Obstructive Pulmonary Disease (COPD) mortality rates and global warming have been in the focus of scientists and policymakers in the past decade. The long-term shifts in temperature and weather patterns, commonly referred to as climate change, is an important public health issue, especially with regard to COPD.</p><p><strong>Method: </strong>Using the most recent county-level age-adjusted COPD mortality rates among adults older than 25 years, this study aimed to investigate the spatial trajectory of COPD in the United States between 2001 and 2020. Global Moran's I was used to investigate spatial relationships utilising data from Terra satellite for night-time land surface temperatures (LSTnt), which served as an indicator of warming within the same time period across the United States. The forest-based classification and regression model (FCR) was applied to predict mortality rates.</p><p><strong>Results: </strong>It was found that COPD mortality over the 20-year period was spatially clustered in certain counties. Moran's I statistic (I=0.18) showed that the COPD mortality rates increased with LSTnt, with the strongest spatial association in the eastern and south-eastern counties. The FCR model was able to predict mortality rates based on LSTnt values in the study area with a R2 value of 0.68.</p><p><strong>Conclusion: </strong>Policymakers in the United States could use the findings of this study to develop long-term spatial and health-related strategies to reduce the vulnerability to global warming of patients with acute respiratory symptoms.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143722936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Local healthcare resources associated with unmet healthcare needs in South Korea: a spatial analysis.","authors":"Sang Min Lee, Dong Woo Huh, Young Gyu Kwon","doi":"10.4081/gh.2025.1295","DOIUrl":"https://doi.org/10.4081/gh.2025.1295","url":null,"abstract":"<p><p>Despite national initiatives to enhance healthcare accessibility, unmet healthcare needs in South Korea remain notably high, particularly in specific regions. This study investigated the factors contributing to geographical disparities in unmet healthcare needs by employing spatial regression models to examine the spatial interactions between healthcare resources and unmet needs. Utilizing data from the 2020 Community Health Survey and Statistics Korea for 216 local government entities, excluding remote areas to ensure data consistency, we identified significant spatial clusters of unmet healthcare needs. These clusters are primarily located in non-metropolitan regions facing transportation barriers and limited healthcare infrastructure. Spatial regression analysis revealed that general hospitals and clinics are significantly associated with reduced unmet healthcare needs underscoring their critical role in mitigating regional disparities. In contrast, hospitals (≥30 beds) and convalescent hospitals did not exhibit significant effects, likely owing to their focus on specialised inpatient and long-term care services, which do not directly address immediate outpatient needs. These findings advance the understanding of how healthcare resource distribution impacts unmet needs at a regional level in South Korea and highlight the necessity for allocating general hospitals and clinics strategically to promote health equity. Based on these results, we recommend evidence- based policy interventions that optimise existing healthcare resources and strategically deploy new facilities in underserved regions. These insights provide valuable guidance for policymakers to reduce geographical health disparities and enhance overall public health outcomes.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and implementation of a spatial database for analysis of wheelchair accessibility.","authors":"Peter Nezval, Takeshi Shirabe","doi":"10.4081/gh.2025.1324","DOIUrl":"https://doi.org/10.4081/gh.2025.1324","url":null,"abstract":"<p><p>Accessibility is an essential consideration in the design of public spaces, and commonly referred to as 'pedestrian accessibility' when walking is the primary mode of transportation. Computational methods, frequently coupled with Geographic Information systems (GIS), are increasingly available for assessing pedestrian accessibility using digital cartographic data such as road networks and digital terrain models. However, they often implicitly assume a level of mobility that may not be achievable by individuals with mobility impairments, e.g., wheelchair users. Therefore, it remains uncertain whether conventional pedestrian accessibility adequately approximates 'wheelchair accessibility,' and, if not, what computational resources would be required to evaluate it more accurately. We therefore designed a spatial database aimed at customizing mobility networks according to mobility limitations and compared the accessibility of a university campus for people with and without wheelchairs under various assumptions. The results showed there are clusters of locations either completely inaccessible or substantially less accessible for wheelchair users, indicating the presence of particular 'wheelchair coldspots', not only due to steep slopes and stairways but also arising from unforeseen consequences of aesthetic and safety enhancements, such as pebble pavements and raised sidewalks. It was found that a combination of simple spatial queries would help identifying potential locations for mobility aids such as ramps. These findings suggest that accessibility is not an invariant of a public space but experienced differently by different groups. Therefore, more comprehensive needs analysis and spatial database design are necessary to support inclusive design of healthier public spaces.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prioritizing the location of vaccination centres during the COVID-19 pandemic by bike in the Netherlands.","authors":"Adel Al-Huraibi, Sherif Amer, Justine Blanford","doi":"10.4081/gh.2025.1293","DOIUrl":"https://doi.org/10.4081/gh.2025.1293","url":null,"abstract":"<p><p>Once a vaccine against COVID-19 had been developed, distribution strategies were needed to vaccinate large numbers of the population as efficiently as possible. In this study we explored the geographical accessibility of vaccination centres and examined their optimal location. To achieve this, we used open-source data. For the analysis we assessed the centre-to-population ratio served to assess inequalities and examined the optimal number and location of centres needed to serve 50%, 70% and 85% of the population, while ensuring physical accessibility using a common mode of transportation, the bicycle. The Location Set Covering Problem (LSCP) model was used to determine the lowest number of vaccination centres needed and assess where these should be located for each Municipal Health Service (GGD) region in The Netherlands. Our analysis identified an unequal distribution of health centres by GGD region, with a primary concentration of vaccination locations in the central region of the Netherlands. GGD Region Noord en Oost Gelderland (N=34), Utrecht (N=29) and Hollands-Midden (N=26) had the highest numbers, while the lowest were found in West-Brabant (N=1), Brabant-Zuidoost (N=2), with Kennemerland, Hollands-Noorden, Groningen and Flevoland (N=3) each. The centre-to-population ratio ranged from 1 centre serving 22,000 people (Noord en Oost Gelderland) to 1 centre serving 672,000 people (West Brabant region). The location-allocation analysis identified several regions that would benefit by adding more centres, most of which would serve densely populated regions previously neglected by the existing vaccination strategy. The number of centres needed ranged from 110 to 322 to achieve 50% and 85% population coverage respectively. In conclusion, location-allocation models coupled with Geographic Information Systems (GIS) can aid decision-making efforts during mass vaccination efforts. To increase effectiveness, a nuanced distribution approach considering accessibility and coverage would be useful. The methodology presented here is valuable for aiding decisionmakers in providing optimized locally adapted crucial health services accessible for the population, such as vaccination centres.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143544681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The future of general practitioner care in Lower Saxony, Germany: an analysis of actual <i>vs</i> target states using a GIS-based floating catchment area method.","authors":"Jonas Schoo, Frank Schüssler","doi":"10.4081/gh.2025.1339","DOIUrl":"https://doi.org/10.4081/gh.2025.1339","url":null,"abstract":"<p><p>Ensuring universal and equitable accessibility to healthcare services is crucial for fostering equal living conditions aligned with global and national objectives. This study examines disparities in accessing General Practitioner (GP) care within Lower Saxony and Bremen, Germany, using the two-step floating catchment area method for spatial analysis at street section level, incorporating various transportation modes. Findings are compared with needs-related planning guidelines to uncover spatial disparities and deviations between prescribed guidelines (target state) and empirical findings (actual state). The analysis reveals significant discrepancies, with over 50% of the population inadequately supplied due to accessibility or capacity issues, particularly in rural and some urban areas, challenging assumptions of sufficient urban healthcare provision. This is the first detailed analysis of primary care provision at this granular level in Lower Saxony, exposing substantial gaps between current GP care and planning targets. Fine-grained spatial analysis proves essential for revealing healthcare accessibility inequities and offers a roadmap for targeted policy interventions. Despite limitations, such as not fully capturing real-world dynamics or patient preferences, the study provides valuable insights into enhancing geographically equitable GP care. It contributes to the discourse on achieving equal living conditions through equitable healthcare accessibility, advocating a more refined, localised approach to healthcare planning, emphasizing the importance of detailed spatial analysis for informed decision-making and promoting health equity.</p>","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"20 1","pages":""},"PeriodicalIF":1.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143460942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}