A Bayesian hierarchical model of nontraumatic lower-extremity amputation rates [0.03%]
下肢非创伤性截肢率的贝叶斯分层模型
Xiaoyi Min,Dongchu Sun,Zhuoqiong He et al.
Xiaoyi Min et al.
A Bayesian hierarchical generalized linear model is used to estimate the risk of lower-extremity amputations (LEA) among diabetes patients from different counties in the state of Missouri. The model includes fixed age effects, fixed gender ...
Residential address errors in public health surveillance data: a description and analysis of the impact on geocoding [0.03%]
公共卫生监测数据中的住宅地址错误及其对地理编码影响的描述与分析
Kate Zinszer,Christian Jauvin,Aman Verma et al.
Kate Zinszer et al.
The residential addresses of persons with reportable communicable diseases are used increasingly for spatial monitoring and cluster detection, and public health may direct interventions based upon the results of routine spatial surveillance...
Linda Williams Pickle,Daniel B Carr
Linda Williams Pickle
Maps have long been used to display the geographic patterns of disease. Identification of cancer "hot spots", clusters of high rates, and subsequent speculation as to their cause led to important epidemiologic findings such as a link betwee...
Inference from ecological models: estimating the relative risk of stroke from air pollution exposure using small area data [0.03%]
基于生态学模型的推理：使用小区域数据估计空气污染暴露的中风相对风险
Robert Haining,Guangquan Li,Ravi Maheswaran et al.
Robert Haining et al.
Maheswaran et al. (2006) analysed the effect of outdoor modelled NO(x) levels, classified into quintiles, on stroke mortality using a Poisson Bayesian hierarchical model with spatial random effects. An association was observed between highe...
On the effect of diagnostic misclassification bias on the observed spatial pattern in regional count data--a case study using West Nile virus mortality data from Ontario, 2005 [0.03%]
诊断误分类偏差对观测到的空间格局的影响——基于2005年安大略省西尼罗河病毒死亡数据的案例研究
Olaf Berke,Lance Waller
Olaf Berke
Geographic epidemiology is concerned with the investigation of spatially referenced data to discover spatial patterns in the health status of populations. In this context it is generally assumed that a perfect diagnostic test is used to cla...
Colin Robertson,Trisalyn A Nelson,Ying C MacNab et al.
Colin Robertson et al.
A review of some methods for analysis of space-time disease surveillance data is presented. Increasingly, surveillance systems are capturing spatial and temporal data on disease and health outcomes in a variety of public health contexts. A ...
Andrew B Lawson
Andrew B Lawson
Modelling individual space-time exposure opportunities: a novel approach to unravelling the genetic or environment disease causation debate [0.03%]
建模个体空间和时间上的暴露机会：解开遗传或环境病因论争的新方法
Clive E Sabel,Paul Boyle,Gillian Raab et al.
Clive E Sabel et al.
The aetiology of Amyotrophic Lateral Sclerosis (ALS) is uncertain. While around 10% is assumed to be inherited, the relative influence of genetic versus physical or social environmental factors (or some combination of the two) has yet to be...
Linking health and environmental data in geographical analysis: it's so much more than centroids [0.03%]
地理分析中的健康与环境数据链接问题：不仅仅是中心点的问题
Linda J Young,Carol A Gotway,Jie Yang et al.
Linda J Young et al.
Programs and studies increasingly use existing data from multiple sources (e.g., surveillance systems, health registries, or governmental agencies) for analysis and inference. These data usually have been collected on different geographical...
The epidemic of lung cancer in Tuscany (Italy): a joint analysis of male and female mortality by birth cohort [0.03%]
意大利托斯卡纳肺癌流行病学研究——出生队列联合分析死亡率（男性和女性）
A Biggeri,D Catelan,E Dreassi
A Biggeri
Lung cancer epidemic among males and females was studied at small geographical level in Tuscany Region (Italy), about 3.5 million inhabitants over almost 30 years (1971-1999). The joint analysis of the space-time pattern of relative risk fo...