Spatial and Spatio-Temporal Epidemiology最新文献

Relationship between time spent in outdoor recreational areas and stress among parents during the COVID-19 lockdown — A spatial temporal analysis of GPS traces from geographical EMA 在2019冠状病毒病封锁期间，在户外娱乐场所度过的时间与父母压力之间的关系——来自地理EMA的GPS痕迹的时空分析

IF 1.7 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Spatial and Spatio-Temporal Epidemiology

Pub Date : 2026-02-01 DOI: 10.1016/j.sste.2026.100782

Balaji Ramesh , Bridget Freisthler , Yun Ye , Katie Kieninger , Gia Barboza-Salerno , Holly Thurston

Background

The early COVID-19 period, with stay-at-home orders, was particularly stressful for parents. Outdoor recreation areas (ORAs), such as green spaces, may have helped alleviate stress.

Aim

To estimate the association between ORA visits and self-reported stress using geographical ecological momentary assessment (gEMA) with refined multi-sourced ORA boundaries.

Methods

Self-reported stress was collected from a cohort of 286 participants via EMA three times daily over 14 days, alongside continuous GPS tracking. ORA visit durations were derived by spatio-temporal clustering of GPS tracks. Generalized ordinal logistic regression model supporting partial proportional odds was used to estimate the association between ORA visit duration stress, adjusting for baseline covariates and weather.

Results

A minute-wise increase in ORA visit duration was not significantly associated with stress (Odds Ratio=0.99; 95% CI: 0.99 to 1.00). However, when the duration was categorized, ORA visits lasting between 15 and 35 min were associated with a 40% reduction in the odds of reporting higher stress (95% CI: 10% to 60%). A similar association was observed for shorter ORA visits (≤ 5 min), though the effect varied across stress levels. The odds of reporting higher stress were also associated with whether the parent was with their focal child, parental sex, marital status, work status, the time of day, and weekday/weekend.

Conclusion

Spending 15–35 min in ORAs may be optimal for parents to manage stress during challenging periods, such as the stay-at-home phase of the COVID-19 pandemic. Even brief ORA visits (< 5 min) may help parents experiencing high stress.

在COVID-19的早期，父母们的压力特别大，因为他们有呆在家里的命令。户外休闲区（ORAs），如绿地，可能有助于缓解压力。目的利用地理生态瞬时评价（gEMA）和改进的多源ORA边界估计ORA访问与自我报告的压力之间的关系。方法从286名参与者中收集自我报告的压力，每天三次，持续14天，同时持续进行GPS跟踪。通过GPS轨迹的时空聚类，推导出ORA访问持续时间。采用支持部分比例优势的广义有序逻辑回归模型，在调整基线协变量和天气后，估计ORA访问持续时间压力之间的关联。结果ORA就诊时间每分钟增加与应激无显著相关（优势比=0.99;95% CI: 0.99 ~ 1.00）。然而，当对持续时间进行分类时，持续15至35分钟的ORA访问与报告较高压力的几率降低40%相关（95% CI: 10%至60%）。在较短的ORA访问（≤5分钟）中观察到类似的关联，尽管影响因压力水平而异。报告更高压力的几率还与父母是否和他们的焦点孩子在一起、父母的性别、婚姻状况、工作状态、一天中的时间、工作日/周末有关。结论在具有挑战性的时期（如COVID-19大流行期间的居家阶段），父母在ora中花费15-35分钟可能是管理压力的最佳选择。即使是短暂的ORA访问（5分钟）也可以帮助父母体验高压力。

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引用次数: 0

Domestic violence, socio-spatial vulnerability and maxillofacial trauma: an ecological study to identify high-risk areas 家庭暴力、社会空间脆弱性和颌面创伤：一项确定高风险地区的生态学研究

IF 1.7 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Spatial and Spatio-Temporal Epidemiology

Pub Date : 2025-12-31 DOI: 10.1016/j.sste.2025.100781

Ítalo de Macedo Bernardino , Lorena Marques da Nóbrega , Larissa Trajano de Souza , Tayná Ribeiro Monteiro de Figueiredo , Andreza Cristina de Lima Targino Massoni , Sérgio d’Ávila

The aim of this study was to determine the incidence and spatial-temporal distribution of maxillofacial trauma caused by domestic violence using an innovative approach, through geostatistical techniques. For this purpose, an ecological study was carried out, involving the analysis of cases of maxillofacial trauma caused by domestic violence, using aggregated data from Brazilian victims attended at a Center of Forensic Medicine and Forensic Dentistry during a period of four years. Three types of spatial-temporal analysis techniques were performed: (i) analysis of the incidence of cases using finite mixture modeling; (ii) spatial autocorrelation analysis; and (iii) spatial regression analysis (p < 0.05). During the investigation period, 858 new cases of maxillofacial trauma caused by domestic violence were recorded. The results showed that the incidence was high and with tendency to increase in the last year of observation in about 30.0% of neighborhoods under study. The Getis-Ord indicator (Gi*) pointed to predominance of high-risk neighborhoods in the Eastern zone (p < 0.05) and in the Western zone (p < 0.05). Based on the final regression model, it was found that indicator 2 (proxy of socioeconomic status) remained significantly associated with the incidence of events (β = 8.403; SE = 2.738; p < 0.001). The association between socioeconomic status, domestic violence and maxillofacial trauma reinforces the role of social inequalities. The findings suggest an association between a higher number of cases and high socio-spatial vulnerability, highlighting the need for the development of public policies to prevent domestic violence and maxillofacial injuries.

本研究的目的是利用一种创新的方法，通过地质统计学技术，确定家庭暴力引起的颌面创伤的发生率和时空分布。为此目的，开展了一项生态研究，分析了家庭暴力造成的颌面创伤病例，使用了在法医和法医牙科中心接受治疗的巴西受害者的汇总数据，为期四年。采用三种时空分析技术：(i)使用有限混合模型分析病例发生率；（ii）空间自相关分析；(3)空间回归分析（p < 0.05）。调查期间共新增家庭暴力致颌面部外伤病例858例。结果表明，30.0%的社区在观察的最后一年发病率较高且有上升趋势。Getis-Ord指数（Gi*）显示东部地区（p < 0.05）和西部地区（p < 0.05）高危社区占主导地位。根据最终的回归模型，我们发现指标2（社会经济地位的代表）仍然与事件发生率显著相关（β = 8.403; SE = 2.738; p < 0.001）。社会经济地位、家庭暴力和颌面创伤之间的关联强化了社会不平等的作用。研究结果表明，较高的案件数量与较高的社会空间脆弱性之间存在关联，强调需要制定公共政策来预防家庭暴力和颌面伤害。

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引用次数: 0

Individual level modeling of infectious disease transmission with reinfection dynamics: Application to Tuberculosis in Manitoba, Canada 具有再感染动力学的传染病传播的个体水平建模：在加拿大马尼托巴省肺结核中的应用

IF 1.7 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Spatial and Spatio-Temporal Epidemiology

Pub Date : 2025-12-20 DOI: 10.1016/j.sste.2025.100780

Amin Abed , Mahmoud Torabi , Zeinab Mashreghi

Recent advancements in stochastic modeling of infectious disease transmission have increasingly incorporated spatial factors, enhancing the accuracy of disease spread predictions and public health interventions. For many infectious diseases, reinfection is a key factor that impacts disease dynamics, epidemic progression, prevalence, and control efforts, complicating management strategies. Accurately incorporating reinfection into disease modeling is essential for developing effective interventions. This study expands upon previously proposed Geographically Dependent Individual Level Models (GD-ILMs) of infectious diseases by integrating them within a Susceptible–Exposed–Infectious–Recovered–Susceptible (SEIRS) compartmental framework, termed GD-ILM SEIRS, to consider reinfection. A Monte Carlo Expectation Conditional Maximization algorithm was employed to estimate the parameters of the model. The GD-ILM SEIRS was applied to Tuberculosis data from Manitoba, Canada, covering the period from 2011 to 2018. It considers spatial dependencies, along with individual and regional risk factors influencing susceptibility to initial infection, reinfection, and infectivity. An analysis of Manitoba’s health authority districts highlights specific risk factors related to susceptibility to initial infection, reinfection, and infectivity. Additionally, the fitted model enables calculation of infection probabilities at high-resolution geographic scales. The results allow for targeted interventions and optimized resource allocation by detecting high-risk areas and vulnerable populations to reduce transmission rates, prevent reinfection, and enhance health outcomes in Manitoba. Moreover, a simulation study across various grid configurations demonstrates the model’s effectiveness in estimating parameters. This study highlights the need to integrate reinfection dynamics into infectious disease models to strengthen the impact of public health interventions and disease control strategies.

传染病传播随机建模的最新进展越来越多地纳入了空间因素，提高了疾病传播预测和公共卫生干预的准确性。对于许多传染病，再感染是影响疾病动态、流行进展、流行和控制努力的关键因素，使管理策略复杂化。准确地将再感染纳入疾病模型对于制定有效的干预措施至关重要。本研究扩展了先前提出的传染病地理依赖个体水平模型（GD-ILMs），将其整合到易感-暴露-感染-恢复-易感（SEIRS）区隔框架中，称为GD-ILM SEIRS，以考虑再感染。采用蒙特卡罗期望条件最大化算法对模型参数进行估计。GD-ILM SEIRS应用于加拿大马尼托巴省2011年至2018年期间的结核病数据。它考虑了空间依赖性，以及影响初次感染、再感染和传染性易感性的个体和区域风险因素。对马尼托巴省卫生当局各区的分析强调了与初次感染、再感染和传染性易感性有关的具体风险因素。此外，该拟合模型能够在高分辨率地理尺度上计算感染概率。结果允许通过检测高风险地区和弱势群体进行有针对性的干预和优化资源分配，以降低传播率，防止再感染，并改善马尼托巴省的健康状况。此外，在不同网格配置下的仿真研究表明了该模型在估计参数方面的有效性。这项研究强调需要将再感染动力学纳入传染病模型，以加强公共卫生干预措施和疾病控制战略的影响。

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引用次数: 0

Spatial and spatio-temporal county-level trends in COVID-19 mortality and emergency department visits in U.S. with R-INLA 基于R-INLA的美国COVID-19死亡率和急诊就诊的时空变化趋势

IF 1.7 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Spatial and Spatio-Temporal Epidemiology

Pub Date : 2025-12-12 DOI: 10.1016/j.sste.2025.100779

Diba Khan , Mark J. Panaggio , Molly E. Gallagher , Philip Graff , Lance Broeker , Mark Weng , Farida Ahmad , Michael Sheppard

Background

Weekly county-level COVID-19 mortality and emergency department (ED) visits data are critical data sources for understanding COVID-19 trends, but subject to reporting delays, sampling variability, potential instability and concerns due to statistical reliability as well as data suppression due to small numbers and the need to protect personally identifiable information. Such suppression limits meaningful examination of county-level variation in COVID-19 mortality rates and ED visits.

Methods

In this study, we use Bayesian inference on latent Gaussian models in the software R-INLA (Integrated Nested Laplace Approximation) to generate reliable weekly estimates of COVID-19 ED visits and mortality rates at the county level in order to examine spatiotemporal variation.

Results

The results demonstrate that weekly county-level COVID-19 mortality rates and ED visits can be accurately modeled using the INLA method. Model-based estimates reflect marked geographic variability for the years 2020–2025.

Conclusions

Effective public health interventions rely on access to timely and detailed spatiotemporal data. Granular estimates that are subject to less reporting noise, such as those produced via INLA modeling, can be used to guide surveillance, improve response strategies, enhance preparedness, and inform public health policy.

每周县级COVID-19死亡率和急诊就诊数据是了解COVID-19趋势的关键数据来源，但由于统计可靠性以及由于数量少和保护个人可识别信息的需要而受到报告延迟、抽样可变性、潜在不稳定性和担忧的影响。这种抑制限制了对COVID-19死亡率和急诊科就诊的县级差异进行有意义的检查。方法在本研究中，我们在R-INLA（集成嵌套拉普拉斯近似）软件中使用隐高斯模型的贝叶斯推断，生成可靠的每周COVID-19急诊科就诊和县一级死亡率估计，以检验时空变化。结果使用INLA方法可以准确地建模县级每周COVID-19死亡率和急诊访问量。基于模式的估算反映了2020-2025年显著的地理变异性。结论有效的公共卫生干预依赖于获得及时、详细的时空数据。受到较少报告噪声影响的细粒度估计，例如通过INLA模型产生的估计，可用于指导监测、改进应对战略、加强准备并为公共卫生政策提供信息。

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引用次数: 0

Pathways of spread of COVID-19 in Québec from 2020 to 2022 2020 - 2022年青海地区新冠肺炎传播途径分析

IF 1.7 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Spatial and Spatio-Temporal Epidemiology

Pub Date : 2025-12-10 DOI: 10.1016/j.sste.2025.100778

Adrien Saucier , Élise Fortin , Katia Charland , Christine Lacroix , Kate Zinszer

Spatial and sociodemographic disparities in COVID-19 cases have been well documented in the literature although the specific pathways through which the virus spread across territories have received comparatively less attention. Yet, understanding these pathways can offer valuable insights into the progression of the pandemic and the spatial dynamics shaping COVID-19 transmission. In this study, we used a trend-surface analysis to retrospectively examine how COVID-19 diffused across Québec, Canada, drawing on provincial-wide surveillance data from 2020 to 2022. Our work shows how COVID-19 tended to spread outwards from urban centers and that its speed of spread increased substantially over time, from 6.1 km per day during Wave 1 to 24.7 km per day by Wave 7. By characterizing the spatial pathways and velocity of spread of COVID-19 in Québec, this work provides information that could support public health authorities in preparing for future pandemics and strengthening geographically informed surveillance systems.

文献中已详细记录了COVID-19病例的空间和社会人口差异，尽管病毒跨地区传播的具体途径受到的关注相对较少。然而，了解这些途径可以为了解大流行的进展和形成COVID-19传播的空间动态提供有价值的见解。在本研究中，我们利用2020年至2022年全省监测数据，采用趋势面分析方法回顾性研究了COVID-19在加拿大魁省的传播情况。我们的研究表明，COVID-19倾向于从城市中心向外传播，其传播速度随着时间的推移大幅增加，从第一波的每天6.1公里增加到第七波的每天24.7公里。通过描述COVID-19在曲海的空间路径和传播速度，这项工作提供的信息可支持公共卫生当局为未来的大流行做好准备，并加强地理上知情的监测系统。

引用次数: 0

Spatial-temporal coupling of malaria vector habitat suitability and biting probability 疟疾媒介生境适宜性与叮咬概率的时空耦合

IF 1.7 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Spatial and Spatio-Temporal Epidemiology

Pub Date : 2025-12-03 DOI: 10.1016/j.sste.2025.100777

Grace R. Aduvukha , Elfatih M. Abdel-Rahman , Onisimo Mutanga , John Odindi , Henri E.Z. Tonnang

Effective control of malaria vectors is crucial for achieving successful malaria elimination. Modelling techniques play a key role in understanding the behaviour and distribution of Anopheles mosquito, the vector responsible for malaria transmission upon infection with the Plasmodium parasite. Despite advances in species distribution modelling (SDM), the behavioural dynamics of malaria vectors, particularly biting probability, have not been fully integrated into these models. This study aimed to model both the habitat suitability and biting probability of malaria vectors. Specifically, relevant remotely sensed data, climatic and topographic variables, and presence-only malaria vector data were integrated into MaxEnt (maximum entropy), an SDM to assess the distribution of malaria vectors. Subsequently, additional variables such as the modelled malaria vector presence, human availability, confirmed insecticide resistance and bed net usage were incorporated in fuzzy logic rule-based techniques to assess the spatial and temporal biting risk probability of these vectors from 2000 to 2018. Two different rule-based model scenarios with distinct rule combinations (Model 1: flexible optimal climatic and environmental conditions (i.e., ORs) and Model 2: strict optimal climatic and environmental conditions (i.e., ANDs)) were evaluated. An independent set of validation data with An. gambiae complex biting observations (n =25) for the years (2017-2021) was used. Validation of the models yielded a mean accuracy of 91% for both models. The models showed reduced biting probability with increased bed net usage amid optimal conditions for biting. This pattern was also comparable to the reduced Plasmodium falciparum prevalence rate from 2000 to 2018 due to an increase in intervention measures. The results highlight the significance of integrating modelled malaria vector presence, ecological conditions, human availability/presence and control methods in the assessment of malaria transmission risk as an early warning system in changes to climate and control methods usage. These findings are pivotal for optimizing targeted malaria vector management and malaria elimination strategies, providing essential insights for public health and disease control stakeholders.

有效控制疟疾病媒对于成功消除疟疾至关重要。建模技术在理解疟蚊的行为和分布方面发挥关键作用，疟蚊是感染疟原虫后负责疟疾传播的媒介。尽管物种分布模型（SDM）取得了进展，但疟疾病媒的行为动态，特别是叮咬概率，尚未完全纳入这些模型。本研究旨在建立疟疾媒介的生境适宜性和叮咬概率模型。具体而言，将相关遥感数据、气候和地形变量以及仅存在的疟疾病媒数据整合到MaxEnt（最大熵）SDM中，以评估疟疾病媒的分布。随后，在基于模糊逻辑规则的技术中纳入了模型疟疾媒介存在、人类可用性、确认的杀虫剂抗性和蚊帐使用等附加变量，以评估2000 - 2018年这些媒介的时空叮咬风险概率。评估了两种不同规则组合的基于规则的模型情景（模型1：灵活的最优气候和环境条件（即ORs）和模型2：严格的最优气候和环境条件（即ANDs））。一个独立的验证数据集。使用了2017-2021年冈比亚复杂咬伤观测数据（n =25）。模型的验证结果表明，两种模型的平均准确率均为91%。模型显示，在最佳的叮咬条件下，随着蚊帐使用量的增加，叮咬概率降低。这一模式也与2000年至2018年由于干预措施的增加而导致的恶性疟原虫患病率下降相当。这些结果强调了将模拟的疟疾媒介存在、生态条件、人类可用性/存在和控制方法作为气候变化和控制方法使用的早期预警系统，在疟疾传播风险评估中具有重要意义。这些发现对于优化有针对性的疟疾病媒管理和消除疟疾战略至关重要，为公共卫生和疾病控制利益攸关方提供了重要见解。

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引用次数: 0

Intra-urban inequalities in the community food environment of a Brazilian metropolitan region: An analysis of food deserts, swamps, and oases 巴西都市地区社区食物环境的城市内部不平等：对食物沙漠、沼泽和绿洲的分析

IF 1.7 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Spatial and Spatio-Temporal Epidemiology

Pub Date : 2025-11-20 DOI: 10.1016/j.sste.2025.100768

Emília Chagas Costa , Vanessa Sá Leal , Juliana Souza Oliveira , Nathalia Paula de Souza , Emerson Iago Garcia e Silva , Marco Aurélio de Valois Correia Júnior , Risia Cristina Egito de Menezes , Pedro Israel Cabral de Lira , Paula Santana , Ricardo Almendra

The food environment in metropolitan areas is characterized by population concentration, the dynamism of food systems, and the intensity of social, cultural, and labor flows. In Brazil, these areas reflect profound intra-urban social and economic inequalities that condition access to food choices. This work aims to characterize the food environment, identifying areas of deserts, swamps, and oases according to health vulnerabilities in a context of social inequalities. A cross-sectional and ecological study was performed. A total of 231 food stores were audited, using buffer analysis(1600 m) and census data. Food deserts, swamps, and oases were classified according to the methodology of the CDC from the Modified Retail Food Environment Index(number of healthy food stores/total available). Information on social vulnerabilities involved sanitation, socioeconomic aspects, and the Health Vulnerability Index of the census tracts. The analyzed region was classified as highly vulnerable in terms of health and no food oases were found. There was scarce availability of healthy foods, with over 90 % of the territory classified as a food swamp. The populations living in the included areas reported a low average monthly income and there were high percentages of black, brown, and indigenous individuals. In a context of social inequality, the region studied presents high health vulnerability, with socioeconomic inequalities and a greater concentration of black, brown, and indigenous people in areas of food deserts and swamps. These findings reinforce the need for public policies that guarantee equity in the distribution of establishments that offer healthy foods, ensuring their accessibility to the population.

大都市地区的食物环境以人口集中、食物系统的活力以及社会、文化和劳动力流动的强度为特征。在巴西，这些地区反映了城市内部深刻的社会和经济不平等，这制约了人们获得食物的选择。这项工作旨在描述粮食环境的特征，根据社会不平等背景下的健康脆弱性确定沙漠、沼泽和绿洲地区。进行了横断面和生态学研究。使用缓冲分析（1600 m）和普查数据，共审计了231家食品店。食物沙漠、沼泽和绿洲是根据美国疾病控制与预防中心的方法从修正零售食品环境指数（健康食品商店数量/可用总数）中分类的。关于社会脆弱性的信息涉及人口普查区的卫生、社会经济方面和健康脆弱性指数。所分析的区域在健康方面被列为高度脆弱，没有发现食物绿洲。健康食品稀缺，90%以上的领土被列为食物沼泽。居住在被调查地区的人口平均月收入较低，黑人、棕色人种和土著人口的比例很高。在社会不平等的背景下，所研究的区域呈现出高度的健康脆弱性，存在社会经济不平等，黑人、棕色人种和土著人口更多地集中在食物沙漠和沼泽地区。这些发现进一步表明，有必要制定公共政策，保证提供健康食品的机构公平分配，确保人们能够获得这些食品。

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引用次数: 0

Socio-spatial characterization of sub-sewersheds for wastewater-based epidemiology (WBE): Developing and evaluating two estimators for population-related variables 污水流行病学（WBE）下下水道的社会空间特征：开发和评估人口相关变量的两个估计器

IF 1.7 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Spatial and Spatio-Temporal Epidemiology

Pub Date : 2025-11-01 DOI: 10.1016/j.sste.2025.100759

Yassine Talleb , Ferry Heinzelmann , Timo Haselhoff , Tina Schmidt , Issa Nafo , Susanne Moebus , Katja Ickstadt , Dennis Schmiege

Wastewater-based epidemiology (WBE) offers valuable population-level health insights. Sampling within sewer systems enables small-scale differentiation, but requires accurate local population data. Allocating population data to sewersheds is complicated by mismatched administrative and sewershed boundaries, for which no established method exists. This study introduces and evaluates two methods for estimating sub-sewershed populations: Proportional Building-based Population Estimation (PBPE) and the Spatial Grid Population Estimation (SGPE). Both were compared with the reported population figures and the result of a simple overlay procedure. The methods were then applied to characterize populations in 195 sub-sewersheds in a large German metropolitan area.

PBPE reallocates population data by weighting intersecting city sub-units based on the number of residential buildings, while SGPE uses inverse-distance weighting to interpolate population density based on residential land use across a hexagonal lattice. Despite different data requirements and methodologies, both estimators produced highly concordant results with strong correlations between estimated and reported population numbers (Pearson r: 0.97 for both) and between estimates for all population-related parameters (Pearson r range: 0.89–0.95). Median deviations were -0.6% (PBPE) and +3.3% (SGPE) for total population, and under 5% across age and socio-economic strata.

The strong agreement confirms both estimators are reliable. PBPE shows lower deviations but requires detailed building data and is sensitive to missing structures and uniform-occupancy assumptions. SGPE works without exhaustive building footprints but depends on user-selected grid parameters. This study provides an empirical basis for improving small-scale WBE data use and interpretability in densely populated urban areas, facilitating an improved public health database.

基于废水的流行病学（WBE）提供了有价值的人口层面的健康见解。在下水道系统内取样可以实现小规模的区分，但需要准确的当地人口数据。由于行政区划与污水排放区边界不匹配，人口数据的分配十分复杂，目前尚无确定的方法。本文介绍并评价了基于建筑物比例的人口估计（PBPE）和空间网格人口估计（SGPE）两种估算地下下水道人口的方法。两者都与报告的人口数字和简单叠加程序的结果进行了比较。然后将这些方法应用于德国大城市地区195个地下下水道的人口特征。PBPE通过基于住宅建筑数量的交叉城市子单元加权来重新分配人口数据，而SGPE使用反距离加权来插值基于住宅用地的人口密度。尽管数据要求和方法不同，但两种估计方法都产生了高度一致的结果，估计和报告的人口数量之间存在很强的相关性（两者的Pearson r均为0.97），所有人口相关参数的估计之间存在很强的相关性（Pearson r范围为0.89-0.95）。总人口的中位数偏差为-0.6% （PBPE）和+3.3% (SGPE)，年龄和社会经济阶层的中位数偏差低于5%。强有力的一致性证实了两个估计都是可靠的。PBPE显示出较低的偏差，但需要详细的建筑数据，并且对缺失的结构和统一占用假设很敏感。SGPE的工作没有详尽的建筑足迹，但取决于用户选择的网格参数。本研究为提高人口密集城市地区小规模WBE数据的使用和可解释性提供了经验基础，促进了公共卫生数据库的改进。

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引用次数: 0

Identifying county-level effect modifiers of the association between heat waves and preterm birth using a Bayesian spatial meta regression approach 利用贝叶斯空间元回归方法识别热浪与早产关联的县域效应调节因子

IF 1.7 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Spatial and Spatio-Temporal Epidemiology

Pub Date : 2025-11-01 DOI: 10.1016/j.sste.2025.100762

Shuqi Lin , Howard H. Chang , Lyndsey A. Darrow , Matthew J. Strickland , Amy Fitch , Andrew Newman , Xiaping Zheng , Joshua L. Warren

High temperature is associated with adverse health outcomes, particularly for vulnerable subpopulations including pregnant individuals and their unborn babies. Several recent studies have investigated the association between temperature and preterm birth at different geographic scales and across different spatial locations. However, there has been less focus on characterizing spatial heterogeneity in risks and identifying modifiable factors that contribute to the observed variation. In this work, we carry out a two-stage modeling approach to (i) estimate county-level short-term associations between heat waves and preterm birth across eight states in the United States and (ii) explore county-level factors that modify these associations using a newly developed hierarchical Bayesian spatial meta-regression approach. Specifically, we extend the traditional meta-regression framework to account for spatial correlation between counties within the same state by modeling the effect estimates using a variant of the conditional autoregressive model. We report several variables that modified the associations between heatwaves and preterm birth, including housing quality, energy affordability, and social vulnerability for minority status and language barriers. An R package, SpMeta, is developed for analyses that aims to synthesize area-level risk estimates while accounting for spatial dependence.

高温与不利的健康结果有关，特别是对包括孕妇及其未出生婴儿在内的脆弱亚人群。最近的几项研究在不同的地理尺度和不同的空间位置调查了温度与早产之间的关系。然而，对表征风险的空间异质性和确定导致观察到的变化的可改变因素的关注较少。在这项工作中，我们采用了一种两阶段的建模方法来(i)估计美国八个州的热浪和早产之间的县级短期关联；（ii）使用新开发的分层贝叶斯空间元回归方法探索改变这些关联的县级因素。具体而言，我们扩展了传统的元回归框架，通过使用条件自回归模型的变体对效果估计进行建模，来解释同一州内县之间的空间相关性。我们报告了几个改变热浪和早产之间关系的变量，包括住房质量、能源负担能力、少数民族身份和语言障碍的社会脆弱性。开发了一个R软件包SpMeta，用于综合区域级风险估计，同时考虑空间依赖性的分析。

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引用次数: 0

Urban sprawl and the spatial expansion of rabid bat encounters with humans in Los Angeles County, California, USA 美国加利福尼亚州洛杉矶县城市蔓延和狂犬病蝙蝠与人类接触的空间扩展

IF 1.7 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

Spatial and Spatio-Temporal Epidemiology

Pub Date : 2025-11-01 DOI: 10.1016/j.sste.2025.100763

Joni Downs, Jaryd Hinch, Hansamali Abeysinghe Mudiyanselage, Saurav Chakraborty

Background

Rabies, a lethal zoonotic disease primarily affecting mammals, is commonly transmitted to humans through bites or contact with saliva from infected animals, including bats. In Los Angeles County, California, human cases of rabies have been documented for over a century. This study leverages Maximum Entropy (Maxent) modeling to map the spatial distribution of human encounters with rabid bats over three distinct periods (2009–2013, 2014–2018, and 2019–2023).

Methods

Using land use/land cover (LULC) and hydrological data, the models predict encounter hotspots across the county, highlighting the relationship between bat encounters and various environmental factors such as proximity to water bodies, developed areas, and shrublands.

Results

The results show a shift in risk, with increases in human-bat interactions particularly noted at the urban fringes where new residential developments have emerged. These findings underscore the importance of targeted public health interventions, particularly in areas undergoing urban expansion.

Conclusion

The spatial risk maps generated provide a valuable tool for guiding rabies prevention strategies and public education efforts in Los Angeles County.

狂犬病是一种主要影响哺乳动物的致命人畜共患疾病，通常通过叮咬或接触受感染动物（包括蝙蝠）的唾液传播给人类。在加利福尼亚州的洛杉矶县，人类狂犬病病例已经记录了一个多世纪。本研究利用最大熵（Maxent）模型绘制了三个不同时期（2009-2013年、2014-2018年和2019-2023年）人类与狂犬病蝙蝠接触的空间分布。方法利用土地利用/土地覆盖（LULC）和水文数据，建立蝙蝠遭遇热点预测模型，突出蝙蝠遭遇与邻近水体、发达地区和灌丛地等环境因素的关系。结果显示风险发生了变化，特别是在新住宅开发出现的城市边缘，人与蝙蝠的互动增加。这些发现强调了有针对性的公共卫生干预的重要性，特别是在正在进行城市扩张的地区。结论生成的空间风险图为指导洛杉矶县狂犬病预防策略和公众教育工作提供了有价值的工具。

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