Spatial and Spatio-Temporal Epidemiology最新文献

Disease mapping with individual level information; a case study of acute myocardial infarction mortality 基于个体水平信息的疾病制图；急性心肌梗死死亡率个案研究

IF 2.1

Spatial and Spatio-Temporal Epidemiology Pub Date : 2025-04-28 DOI: 10.1016/j.sste.2025.100721

Xavier Puig, Josep Ginebra

引用次数: 0

Integrating data at multiple spatial scales to estimate the local burden of the opioid syndemic 整合多个空间尺度的数据，以估计阿片类药物综合征的当地负担

IF 2.1

Spatial and Spatio-Temporal Epidemiology Pub Date : 2025-04-22 DOI: 10.1016/j.sste.2025.100720

Eva Murphy , David Kline , Erin McKnight , Andrea Bonny , William C. Miller , Lance Waller , Staci A. Hepler

{"title":"Integrating data at multiple spatial scales to estimate the local burden of the opioid syndemic","authors":"Eva Murphy , David Kline , Erin McKnight , Andrea Bonny , William C. Miller , Lance Waller , Staci A. Hepler","doi":"10.1016/j.sste.2025.100720","DOIUrl":"10.1016/j.sste.2025.100720","url":null,"abstract":"<div><div>The opioid epidemic has been particularly severe in Ohio, prompting significant efforts to understand its spatial patterns, mainly using available data at the county level. However, relying solely on county-level analysis can overlook crucial information relevant to localized effects. To address this, we integrate spatially misaligned data observed at the county and ZIP code levels to explore the complex interaction of five opioid-related outcomes, providing a more detailed local understanding of the opioid epidemic. We demonstrate how to map ZIP-code level data to ZIP-code Tabulation Areas (ZCTAs) and relate the county-level and ZCTA-level outcomes to a spatially correlated latent factor. The latent factor is defined on the intersection of the misaligned areal units, which provides a more granular understanding of the opioid epidemic. Furthermore, this approach allows us to identify areas with varying levels of opioid burden and reveals local regions with relatively high burden that county-level analyses might miss. Finally, we highlight the need for careful consideration when relying solely on ZIP code level data for naloxone, as it may lead to misinterpretations, particularly in rural regions.</div></div>","PeriodicalId":46645,"journal":{"name":"Spatial and Spatio-Temporal Epidemiology","volume":"53 ","pages":"Article 100720"},"PeriodicalIF":2.1,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143863591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Physician and healthcare partner engagement in the creation of healthfulness indices for West Michigan 医生和医疗保健合作伙伴参与创建健康指数为西密歇根州

IF 2.1

Spatial and Spatio-Temporal Epidemiology Pub Date : 2025-04-19 DOI: 10.1016/j.sste.2025.100722

Richard Casey Sadler , Samantha Gailey , Erin R. McNeely

{"title":"Physician and healthcare partner engagement in the creation of healthfulness indices for West Michigan","authors":"Richard Casey Sadler , Samantha Gailey , Erin R. McNeely","doi":"10.1016/j.sste.2025.100722","DOIUrl":"10.1016/j.sste.2025.100722","url":null,"abstract":"<div><div>Community participatory mapping can direct health research, offering opportunity to build spatial awareness and generate future research. Here we establish healthfulness indices by consulting healthcare system partners for their expert opinions on characteristics they felt influenced health. Partners started from 36 variables and narrowed to 16 in 4 simplified categories. The analytic hierarchy process was used to identify variable and category weights. Opinions were consolidated for each partner sub-group and overall. Map layers were assigned calculated weights and indices were created from weighted layers. Areas with more amenities scored higher, including in and around downtown areas and smaller towns. Lower scores were found in suburban and lower-income urban areas. Variation in maps among subgroups reflect differing priorities in tackling health equity issues. This work increases healthcare partner engagement in built environment work and generates future research pathways. Partners now have a tool for interrogating and communicating the environment’s cumulative impact.</div></div>","PeriodicalId":46645,"journal":{"name":"Spatial and Spatio-Temporal Epidemiology","volume":"53 ","pages":"Article 100722"},"PeriodicalIF":2.1,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143860326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A multivariate generalized logistic approach with spatially varying nonlinear components for modeling epidemic data 一种具有空间变化非线性分量的流行病数据建模的多元广义逻辑方法

IF 2.1

Spatial and Spatio-Temporal Epidemiology Pub Date : 2025-04-04 DOI: 10.1016/j.sste.2025.100718

Marcos O. Prates , Dani Gamerman , Samuel F. Candido , Luis M. Castro

引用次数: 0

A Bayesian spatial measurement error approach to incorporate heterogeneous population-at-risk uncertainty in estimating small-area opioid mortality rates 估算小区域阿片类药物死亡率时纳入异质性高危人群不确定性的贝叶斯空间测量误差方法

IF 2.1

Spatial and Spatio-Temporal Epidemiology Pub Date : 2025-03-31 DOI: 10.1016/j.sste.2025.100719

Emily N. Peterson , Rachel C. Nethery , Jarvis T. Chen , Loni P. Tabb , Brent A. Coull , Frederic B. Piel , Lance A. Waller

{"title":"A Bayesian spatial measurement error approach to incorporate heterogeneous population-at-risk uncertainty in estimating small-area opioid mortality rates","authors":"Emily N. Peterson , Rachel C. Nethery , Jarvis T. Chen , Loni P. Tabb , Brent A. Coull , Frederic B. Piel , Lance A. Waller","doi":"10.1016/j.sste.2025.100719","DOIUrl":"10.1016/j.sste.2025.100719","url":null,"abstract":"<div><div>Monitoring small-area geographical population trends in opioid mortality has significant implications for informing preventative resource allocation. A common approach to estimating small-area opioid mortality uses a standard disease mapping method where population-at-risk estimates (denominators) are treated as fixed. This assumption ignores the uncertainty in small-area population estimates, potentially biasing risk estimates and underestimating their uncertainties. We compare a Bayesian Spatial Berkson Error model and a Bayesian Spatial Classical Error model to a naive approach that treats denominators as fixed. Using simulations, we illustrate potential bias from ignored population-at-risk uncertainty. We apply these methods to obtain 2020 opioid mortality risk estimates for 159 counties in Georgia. Assessing differences in bias and uncertainty across approaches can improve the accuracy of small-area opioid risk estimates, guiding public health interventions, policies, and resource allocation.</div></div>","PeriodicalId":46645,"journal":{"name":"Spatial and Spatio-Temporal Epidemiology","volume":"53 ","pages":"Article 100719"},"PeriodicalIF":2.1,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spatial modeling and risk assessment of chagas disease vector distribution in Espírito Santo, Brazil: A comprehensive approach for targeted control 巴西Espírito圣托的恰加斯病媒介分布的空间建模和风险评估：目标控制的综合方法

IF 2.1

Spatial and Spatio-Temporal Epidemiology Pub Date : 2025-02-01 DOI: 10.1016/j.sste.2025.100710

Stefanie Barbosa Potkul Soares , Gustavo Rocha Leite , Guilherme Sanches Corrêa-do-Nascimento , Karina Bertazo del Carro , Blima Fux

{"title":"Spatial modeling and risk assessment of chagas disease vector distribution in Espírito Santo, Brazil: A comprehensive approach for targeted control","authors":"Stefanie Barbosa Potkul Soares , Gustavo Rocha Leite , Guilherme Sanches Corrêa-do-Nascimento , Karina Bertazo del Carro , Blima Fux","doi":"10.1016/j.sste.2025.100710","DOIUrl":"10.1016/j.sste.2025.100710","url":null,"abstract":"<div><div>Chagas disease, a persistent and life-threatening infection caused by the protozoan <em>Trypanosoma cruzi</em>, remains a significant public health concern in Latin America. Despite the Brazilian State of Espírito Santo (ES) not being classified as a high-risk area, the presence of epidemiologically significant triatomines like <em>Panstrongylus megistus</em> suggests a latent risk of <em>T. cruzi</em> transmission. This study, employing spatial modeling, assesses the distribution of key triatomine species in ES and predicts areas at risk for Chagas disease transmission. Our models, constructed with Maxent, KUENM, and QGIS, identified high suitability for most species in ES's southeast and south regions, with <em>P. diasi</em> showing high suitability in the central-west. Notably, 13 autochthonous cases of vector-borne Chagas disease were reported between 2001 and 2023. The risk assessment highlighted significant risk areas corresponding to the locations of these cases, indicating that most regions in ES are at higher risk of <em>P. megistus</em> presence. These findings provide crucial insights for enhancing regional epidemiological surveillance and inform targeted vector control strategies, effectively addressing latent risks.</div></div>","PeriodicalId":46645,"journal":{"name":"Spatial and Spatio-Temporal Epidemiology","volume":"52 ","pages":"Article 100710"},"PeriodicalIF":2.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A fast approach for analyzing spatio-temporal patterns in ischemic heart disease mortality across US counties (1999–2021) 一种快速分析美国各县缺血性心脏病死亡率时空模式的方法（1999-2021）

IF 2.1

Spatial and Spatio-Temporal Epidemiology Pub Date : 2025-02-01 DOI: 10.1016/j.sste.2024.100700

A. Urdangarin , T. Goicoa , P. Congdon , M.D. Ugarte

引用次数: 0

On the lagged non-linear association between air pollution and COVID-19 cases in Belgium 关于比利时空气污染与COVID-19病例之间的滞后非线性关联

IF 2.1

Spatial and Spatio-Temporal Epidemiology Pub Date : 2025-02-01 DOI: 10.1016/j.sste.2024.100709

Sara Rutten , Marina Espinasse , Elisa Duarte , Thomas Neyens , Christel Faes

{"title":"On the lagged non-linear association between air pollution and COVID-19 cases in Belgium","authors":"Sara Rutten , Marina Espinasse , Elisa Duarte , Thomas Neyens , Christel Faes","doi":"10.1016/j.sste.2024.100709","DOIUrl":"10.1016/j.sste.2024.100709","url":null,"abstract":"<div><div>Exposure to air pollution has been proposed as a determinant of COVID-19 dynamics. While the connection between air pollution and COVID-19 has been established for several countries worldwide, few such analyses exist in Belgium. Therefore, we examine this potential association in Belgium, using COVID-19 cases of all 581 municipalities between September 2020 and January 2022. We employ a Bayesian spatio-temporal negative binomial model, allowing for potential non-linear and lagged effects of pollution. Comparing different single-pollutant models, we find that the model providing the best fit to the data contains black carbon. At the median pollution level, a cumulative risk of <span><math><mrow><mn>1</mn><mo>.</mo><mn>66</mn><mspace></mspace><mrow><mo>(</mo><mn>1</mn><mo>.</mo><mn>57</mn><mo>,</mo><mn>1</mn><mo>.</mo><mn>74</mn><mo>)</mo></mrow></mrow></math></span> over 8 weeks is found for this pollutant, compared to the 5% pollution quantile. In addition, the study reveals a remarkable similarity in COVID-19 incidence between adjacent municipalities in Belgium.</div><div>Our findings suggest paying careful attention to highly air polluted areas when preparing for future pandemics of respiratory diseases.</div></div>","PeriodicalId":46645,"journal":{"name":"Spatial and Spatio-Temporal Epidemiology","volume":"52 ","pages":"Article 100709"},"PeriodicalIF":2.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Geospatial distribution of the adoption of dipeptidyl-peptidase-4 inhibitors for type 2 diabetes among Medicare beneficiaries 医疗保险受益人采用二肽基肽酶-4抑制剂治疗2型糖尿病的地理空间分布

IF 2.1

Spatial and Spatio-Temporal Epidemiology Pub Date : 2025-02-01 DOI: 10.1016/j.sste.2025.100711

Jack Cordes , Robert J. Glynn , Alexander M. Walker , Sebastian S. Schneeweiss

{"title":"Geospatial distribution of the adoption of dipeptidyl-peptidase-4 inhibitors for type 2 diabetes among Medicare beneficiaries","authors":"Jack Cordes , Robert J. Glynn , Alexander M. Walker , Sebastian S. Schneeweiss","doi":"10.1016/j.sste.2025.100711","DOIUrl":"10.1016/j.sste.2025.100711","url":null,"abstract":"<div><h3>Objective</h3><div>To characterize the geospatial distribution of the adoption of dipeptidyl-peptidase-4 inhibitor (DPP-4i) antidiabetics versus second generation sulfonylureas (SU).</div></div><div><h3>Methods</h3><div>Using Medicare claims data 2012–2017, two cohorts were built with new-users of either sitagliptin or saxagliptin each versus active comparator SU. For each ZIP Code tabulation area (ZCTA), the proportion DPP-4i prescribing was used in a local indicator of spatial association hotspot analysis. Multilevel logistic models were used to quantify the variation in medication use at the individual, ZCTA, state, and region levels.</div></div><div><h3>Results</h3><div>DPP-4i utilization proportion was low (sitagliptin median = 0.22; interquartile range 0.15 to 0.33; saxagliptin median = 0.025; 0.00 to 0.069). Clustering was observed for sitagliptin (Moran's <em>I</em> = 0.32) and saxagliptin (Moran's <em>I</em> = 0.20). States and ZCTAs accounted for 8.1 % and 13.3 % of variation in sitagliptin and saxagliptin prescribing, respectively.</div></div><div><h3>Conclusions</h3><div>Variation across ZCTAs suggests neighborhood factors may be important determinants of prescribing.</div></div>","PeriodicalId":46645,"journal":{"name":"Spatial and Spatio-Temporal Epidemiology","volume":"52 ","pages":"Article 100711"},"PeriodicalIF":2.1,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143136168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimating subnational under-five mortality rates using a spatio-temporal Age-Period-Cohort model 使用时空年龄-时期-队列模型估计国家以下五岁以下儿童死亡率

IF 2.1

Spatial and Spatio-Temporal Epidemiology Pub Date : 2025-02-01 DOI: 10.1016/j.sste.2024.100708

Connor Gascoigne , Theresa Smith , John Paige , Jon Wakefield

引用次数: 0