Geospatial Health最新文献_第2页

Nonlinear analysis of factors influencing tuberculosis outpatient visits in China: an explainable machine learning approach. 中国肺结核门诊就诊影响因素的非线性分析：一种可解释的机器学习方法。

IF 1.5 4区医学

Geospatial Health Pub Date : 2026-07-23 Epub Date: 2026-10-08 DOI: 10.4081/gh.2026.1535

Hui Wang, Dehong Sun, Shanjie Sui, Yanhong Xu

{"title":"Nonlinear analysis of factors influencing tuberculosis outpatient visits in China: an explainable machine learning approach.","authors":"Hui Wang, Dehong Sun, Shanjie Sui, Yanhong Xu","doi":"10.4081/gh.2026.1535","DOIUrl":"https://doi.org/10.4081/gh.2026.1535","url":null,"abstract":"This study aims to analyze the temporal trends, interprovincial differences, and key predictors of Tuberculosis Outpatient Visits (TOV) in China. It provides empirical evidence for understanding regional differences in tuberculosis-related outpatient service uti- lization. Panel data from 30 Chinese provinces from 2012 to 2024 were used. The study included variables related to economic development, health resources, education resources, environmental governance, pollutant emissions, and technological innovation. Correlation analysis, model comparison, and XGBoost-SHAP analysis were applied. From 2012 to 2024, TOV showed a gradual upward trend and clear interprovincial differences. Shanghai, Fujian, Guangdong, and Zhejiang had relatively higher total recorded outpatient volumes. XGBoost showed the best predictive performance among all candidate models (R2 = 0.8154). SHAP results identified Disposable Income Per Capita (DIPC), University Staff (USTF), Domestic Patent Applications (DPA), Hospital Beds (HBED), and Technology Market Turnover (TMT) as the main predictors. Environmental governance and pollutant emission vari- ables had lower overall contributions, but they still showed nonlinear predictive contributions in some value ranges. The findings suggest that interprovincial differences in TOV are jointly associated with economic development, health resources, education resources, environmental governance, and technological innovation. TOV mainly reflects outpatient service utilization and case detection capacity. It should not be interpreted as a direct measure of tuberculosis incidence risk.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 2","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149139425","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}

引用次数: 0

Spatial pattern of tuberculosis cases in Jos Metropolis, Nigeria in the period 2019-2022. 2019-2022年尼日利亚乔斯大都会结核病病例空间格局

IF 1.5 4区医学

Geospatial Health Pub Date : 2026-02-02 Epub Date: 2026-03-16 DOI: 10.4081/gh.2026.1456

Augustine Odo Ebonyi, Mary-Jane Ebire Ebonyi, Femi Rufus Tinuola, Isaiah Gwitira

{"title":"Spatial pattern of tuberculosis cases in Jos Metropolis, Nigeria in the period 2019-2022.","authors":"Augustine Odo Ebonyi, Mary-Jane Ebire Ebonyi, Femi Rufus Tinuola, Isaiah Gwitira","doi":"10.4081/gh.2026.1456","DOIUrl":"10.4081/gh.2026.1456","url":null,"abstract":"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.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147476258","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}

引用次数: 0

Unravelling the dual burden in regional context: how child malnutrition and socioeconomic gradients shape early childhood development. 解读区域背景下的双重负担：儿童营养不良和社会经济梯度如何影响儿童早期发展。

IF 1.5 4区医学

Geospatial Health Pub Date : 2026-02-02 Epub Date: 2026-02-05 DOI: 10.4081/gh.2026.1455

Muhammad Usman

{"title":"Unravelling the dual burden in regional context: how child malnutrition and socioeconomic gradients shape early childhood development.","authors":"Muhammad Usman","doi":"10.4081/gh.2026.1455","DOIUrl":"10.4081/gh.2026.1455","url":null,"abstract":"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.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146127605","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}

引用次数: 0

Comparing conditional autoregressive models for Bayesian spatial mapping of dengue cases in Indonesia. 比较印度尼西亚登革热病例贝叶斯空间映射的条件自回归模型。

IF 1.5 4区医学

Geospatial Health Pub Date : 2026-02-02 Epub Date: 2026-06-18 DOI: 10.4081/gh.2026.1443

Ferra Yanuar, Yudiantri Asdi, Aidinil Zetra, Sofiana Wudlu, Fenni Kurnia Mutiya, Rahmawita Rahmawita

{"title":"Comparing conditional autoregressive models for Bayesian spatial mapping of dengue cases in Indonesia.","authors":"Ferra Yanuar, Yudiantri Asdi, Aidinil Zetra, Sofiana Wudlu, Fenni Kurnia Mutiya, Rahmawita Rahmawita","doi":"10.4081/gh.2026.1443","DOIUrl":"10.4081/gh.2026.1443","url":null,"abstract":"Dengue Haemorrhagic Fever (DHF) remains a public health burden in Indonesia with substantial provincial variation. We modelled province-level DHF counts in 2023 using Bayesian spatial conditional autoregressive Poisson models with population offsets. Predictors were average annual temperature (per 1°C) and the number of public health workers (province-level count). Spatial dependence was supported by Moran's I=0.4689 (p=0.021). We fitted models using Besag-York-Mollié (BYM) and Leroux priors via Markov chain Monte Carlo and compared fit using the Deviance Information Criterion (DIC) and the Watanabe-Akaike Information Criterion (WAIC). In the BYM model, temperature was associated with lower risk (RR=0.90; 95% CrI: 0.76 to 1.07), with uncertainty including unity, whereas workforce density was associated with higher reported risk (RR=1.05; 95% CrI: 1.03 to 1.07). Estimates were similar under the Leroux prior (temperature RR=0.89; 95% CrI: 0.74 to 1.07; workforce RR=1.04; 95% CrI: 1.02 to 1.07), and BYM showed marginally better fit. Risk mapping indicated elevated burden in parts of Kalimantan and eastern Indonesia. Findings may inform geographically targeted surveillance and vector control; the workforce association should be interpreted cautiously because it may reflect reporting capacity or reactive deployment.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148273985","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}

引用次数: 0

Strengthening disease control and trade through zoning and biosecurity. 通过分区和生物安全加强疾病控制和贸易。

IF 1.5 4区医学

Geospatial Health Pub Date : 2026-02-02 Epub Date: 2026-05-13 DOI: 10.4081/gh.2026.1391

Nicola Ferrè, Guido Di Martino, Benedetta Cappelletti, Carlotta Ferroni, Marija Korac, Paolo Tizzani, Federica Sbettega, Giovanni Cattoli

{"title":"Strengthening disease control and trade through zoning and biosecurity.","authors":"Nicola Ferrè, Guido Di Martino, Benedetta Cappelletti, Carlotta Ferroni, Marija Korac, Paolo Tizzani, Federica Sbettega, Giovanni Cattoli","doi":"10.4081/gh.2026.1391","DOIUrl":"10.4081/gh.2026.1391","url":null,"abstract":"Zoning and biosecurity are fundamental tools in veterinary public health and international trade. However, their implementation suffers from fragmented approaches to geospatial representation and uneven adoption across countries. This article discusses outcomes of the G7 Chief Veterinary Officers (CVOs) meeting (Padua, October 2024), where the integration of zoning and biosecurity was highlighted as a possible pathway to strengthen disease control and facilitate trade. Two initiatives, GeoZone and ClassyFarm are used to illustrate this approach. The former advances zoning clarity through a geospatial framework based on ISO TC211 standards, defining spatial data structures and exchange protocols to improve cross-country GIS interoperability, while the latter complements this approach by providing structured biosecurity data collection and risk classification at farm, regional and national levels. We critically discuss the potential and limitations of both systems, and their contribution to the advancement of geospatial epidemiology. By treating zoning and biosecurity as harmonized, data-driven frameworks, these initiatives mark progress towards more a transparent, standardised and globally applicable animal health management.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147935697","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}

引用次数: 0

Bayesian modelling of dengue incidence with climatic drivers: comparing fixed-effects, nonlinear and dynamic approaches. 登革热发病率与气候驱动因素的贝叶斯模型：比较固定效应、非线性和动态方法。

IF 1.5 4区医学

Geospatial Health Pub Date : 2026-02-02 DOI: 10.4081/gh.2026.1461

Farah Kristiani, I Gede Nyoman Mindra Jaya, Robyn Irawan, Inanta Maria Priscilia

{"title":"Bayesian modelling of dengue incidence with climatic drivers: comparing fixed-effects, nonlinear and dynamic approaches.","authors":"Farah Kristiani, I Gede Nyoman Mindra Jaya, Robyn Irawan, Inanta Maria Priscilia","doi":"10.4081/gh.2026.1461","DOIUrl":"10.4081/gh.2026.1461","url":null,"abstract":"Climatic variability plays a critical role in shaping dengue transmission dynamics, yet empirical findings remain inconsistent across studies. Divergent conclusions regarding the associations of temperature, relative humidity, wind speed, air pressure, precipitation, number of rainy days, and sunshine duration with dengue incidence often stem from unmodelled interactions and methodological limitations. To address these challenges, this study applies a Bayesian modelling framework to examine the associations between climatic drivers and dengue incidence in Bandung City, Indonesia, using monthly data from 2016 to 2024. We compared fixedeffects, nonlinear and dynamic modelling approaches to evaluate both the direction and magnitude of these associations while addressing overdispersion and potential multicollinearity among predictors. Our findings highlight temperature and relative humidity as the primary climatic variables associated with temporal variations in dengue incidence, with effects manifesting most strongly at a two-month lag. These results underscore the importance of adopting robust Bayesian modeling frameworks to support early warning systems and inform evidence-based public health interventions for dengue control.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146107891","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}

引用次数: 0

Prioritizing the tuberculosis burden by the analytic hierarchy process for effective targeted intervention. 通过层次分析法对结核病负担进行优先排序，以便进行有效的针对性干预。

IF 1.5 4区医学

Geospatial Health Pub Date : 2026-02-02 Epub Date: 2026-06-15 DOI: 10.4081/gh.2026.1454

Madhu Basavegowda, Manjunatha M Chikkapapanna, Sahana K Suresh, Bhuvanesh Giriya

{"title":"Prioritizing the tuberculosis burden by the analytic hierarchy process for effective targeted intervention.","authors":"Madhu Basavegowda, Manjunatha M Chikkapapanna, Sahana K Suresh, Bhuvanesh Giriya","doi":"10.4081/gh.2026.1454","DOIUrl":"10.4081/gh.2026.1454","url":null,"abstract":"Tuberculosis (TB) remains a major public health concern in India, with an estimated 2.69 million cases annually. This study aimed to identify priority TB burden groups in Mysuru District using the Analytic Hierarchy Process (AHP) to support targeted interventions. A retrospective cross-sectional analysis was conducted using 8,459 TB case records reported between 2017 and 2019. Urban areas accounted for most cases (64.8%), with Mysuru City alone contributing 36.5%. Integrating AHP with Geographic Information Systems (GIS), a secondary surveillance approach was used to prioritize high-risk populations and geographic zones. Type of resi- dence, gender, age group, and co-morbidities were selected as key risk criteria based on epidemiological evidence and expert judgement. Relative weights were derived through pair-wise comparisons, with consistency verified using Consistency Ratio (CR), a metric used in the AHP to measure how logically consistent a decision-maker's subjective judgments are when comparing pairs of items. Rankings were assigned based on the highest (4) and lowest (1) proportional burden. The analysis identified urban males aged 40- 59 and 20-39 years as the highest-risk groups, classified as \"very high\" priority, followed by urban females aged 20-39 years and elderly males as \"high\" priority. Younger and older age groups constituted moderate to low-risk categories. The findings highlight a disproportionately higher TB burden among urban, male, and working-age populations and demonstrate the utility of AHP in guiding targeted, evidence-based TB control strategies used.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148254689","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}

引用次数: 0

Optimizing mobile mammography deployment in Oklahoma 2024: a two-step floating catchment area approach. 优化俄克拉何马州2024年移动乳房x光检查部署：两步浮动集水区方法

IF 1.5 4区医学

Geospatial Health Pub Date : 2026-02-02 Epub Date: 2026-04-21 DOI: 10.4081/gh.2026.1426

Janis E Campbell, Amanda Janitz, Ayesha B Sambo, Nubwa St James, Stephanie F Pharr, Mark P Doescher

{"title":"Optimizing mobile mammography deployment in Oklahoma 2024: a two-step floating catchment area approach.","authors":"Janis E Campbell, Amanda Janitz, Ayesha B Sambo, Nubwa St James, Stephanie F Pharr, Mark P Doescher","doi":"10.4081/gh.2026.1426","DOIUrl":"10.4081/gh.2026.1426","url":null,"abstract":"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.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13255058/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147730795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Diabetes prevalence in the state of Alabama: identifying the risk factors. 阿拉巴马州糖尿病患病率：确定危险因素。

IF 1.5 4区医学

Geospatial Health Pub Date : 2026-02-02 Epub Date: 2026-03-31 DOI: 10.4081/gh.2026.1465

Kwaku Karikari Manu, Seth Appiah-Opoku

{"title":"Diabetes prevalence in the state of Alabama: identifying the risk factors.","authors":"Kwaku Karikari Manu, Seth Appiah-Opoku","doi":"10.4081/gh.2026.1465","DOIUrl":"10.4081/gh.2026.1465","url":null,"abstract":"Diabetes mellitus, a chronic metabolic disorder characterized by elevated blood glucose, remains a pressing public health challenge in the United States. This study aims to identify spatial clusters of diabetes and examine associated factors at a granular scale using the state of Alabama. Data on diabetes prevalence, socioeconomic, environmental and behavioural risk factors were extracted at the census tract level from the CDC PLACES Project. Moran's I and Getis-Ord Gi* were first used to assess the spatial autocorrelation and spatial clusters of diabetes, respectively. Due to the existence of spatial autocorrelation (Moran's I = 0.275, p<0.001) of diabetes prevalence, three additional spatial statistical techniques, including the Spatial Lag Model (SLM), the Spatial Error Model (SEM) and Geographically Weighted Regression (GWR), were used to examine its associated factors while detecting the local spatial variations. Several significant clusters of high diabetes prevalence were found in most counties in the middle, known as the Black Belt. The GWR model (R2 = 0.921 & AICc = 2414.0) outperformed SLM and SEM and was therefore used to explore the strong spatial heterogeneity in the associated risk factors. Statistically significant predictors identified were smoking, drinking, obesity, poverty, and age 65+. These localized findings enable governments to develop interventions targeting risk factors to address diabetes prevalence in the state of Alabama.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147583183","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}

引用次数: 0

Evaluation of household knowledge, attitudes and practices concerning malaria in the city of Djibouti. 吉布提市家庭对疟疾的知识、态度和做法的评估。

IF 1.5 4区医学

Geospatial Health Pub Date : 2026-02-02 Epub Date: 2026-06-16 DOI: 10.4081/gh.2026.1451

Osman Abdillahi Guedi, Yao Télesphore Brou, Eric Delmelle, Sébastien Briolant

{"title":"Evaluation of household knowledge, attitudes and practices concerning malaria in the city of Djibouti.","authors":"Osman Abdillahi Guedi, Yao Télesphore Brou, Eric Delmelle, Sébastien Briolant","doi":"10.4081/gh.2026.1451","DOIUrl":"10.4081/gh.2026.1451","url":null,"abstract":"This study presents the first Knowledge Attitudes, and Practices (KAP) survey on malaria in Djibouti City. It was conducted among 1,344 household heads across nine neighbourhoods in Djibouti City. Composite scores were calculated for each KAP dimension. Analysis of variance and multinomial logistic regression identified socio-demographic predictors and Local Indicators of Spatial Association (LISA) characterised the spatial clustering of the KAP scores. No significant association was found between sociodemographic or economic factors and malaria knowledge. Prevention practices varied notably across neighbourhoods, driven by place of residence, mother tongue, and education-underlining the primacy of spatial determinants. Attitudes were found to be linked to gender and income. Despite high disease awareness, 60% of respondents misidentified transmission routes, nearly two-thirds of respondents failed to adopt effective preventive behaviours, while Long-Lasting Insecticidal Net (LLIN) ownership far exceeded correct use. The gap between awareness and practice suggests that information-deficit approaches have reached their limits; future interventions should target motivational norm-based determinants of behaviour, spatially concentrated in the highest-risk neighbourhoods. Language and cultural barriers require tailored communication strategies beyond standard broadcast campaigns. Strengthened vector control and active surveillance remain essential complements to any behavioural intervention.","PeriodicalId":56260,"journal":{"name":"Geospatial Health","volume":"21 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148260848","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}

引用次数: 0