A Bayesian space-time model for clustering areal units based on their disease trends.
A Bayesian space-time model for clustering areal units based on their disease trends.
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DOI：
10.1093/biostatistics/kxy024
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发表时间：
2019-10-01
期刊：
影响因子：
--
通讯作者：
Lawson A
中科院分区：
文献类型：
--
作者：
Napier G;Lee D;Robertson C;Lawson A
一组不重叠的地区单位的人口水平疾病风险在空间和时间上各不相同，大量研究文献已经制定了识别风险增加的地区单位集群的方法。然而，几乎没有研究扩展聚类范例来识别表现出相似的临时性疾病趋势的区域单位组。为了实现这一目标，我们提出了一种新的贝叶斯分层混合模型，并基于Metropolis耦合的马尔可夫链蒙特卡罗(MC)算法进行推理。与标准的马尔可夫链蒙特卡罗实现相比，MC算法的有效性在仿真研究中得到了验证，该方法受到英国两个重要案例研究的启发。第一个问题是，将麻疹、腮腺炎和风疹疫苗接种与自闭症风险增加联系起来的不可信的论文对麻疹易感性的影响，并调查苏格兰所有地区是否都同样受到影响。第二项与呼吸道住院有关，并对格拉斯哥部分地区的风险在10年内有所增加、减少和没有变化的情况进行了调查。
Population-level disease risk across a set of non-overlapping areal units varies in space and time, and a large research literature has developed methodology for identifying clusters of areal units exhibiting elevated risks. However, almost no research has extended the clustering paradigm to identify groups of areal units exhibiting similar temporal disease trends. We present a novel Bayesian hierarchical mixture model for achieving this goal, with inference based on a Metropolis-coupled Markov chain Monte Carlo ((MC)) algorithm. The effectiveness of the (MC) algorithm compared to a standard Markov chain Monte Carlo implementation is demonstrated in a simulation study, and the methodology is motivated by two important case studies in the United Kingdom. The first concerns the impact on measles susceptibility of the discredited paper linking the measles, mumps, and rubella vaccination to an increased risk of Autism and investigates whether all areas in the Scotland were equally affected. The second concerns respiratory hospitalizations and investigates over a 10 year period which parts of Glasgow have shown increased, decreased, and no change in risk.
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影响因子：
2.5
作者：
Jiang, Huijing;Serban, Nicoleta
通讯作者：
Serban, Nicoleta
DOI：
10.1214/16-aoas941
发表时间：
2016-09-28
期刊：
The annals of applied statistics
影响因子：
--
作者：
Lee D;Lawson A
通讯作者：
Lawson A
影响因子：
1.9
作者：
Knorr-Held, L;Rasser, G
通讯作者：
Rasser, G
DOI：
10.1198/016214505000000187
发表时间：
2006-03-01
影响因子：
3.7
作者：
Heard, NA;Holmes, CC;Stephens, DA
通讯作者：
Stephens, DA
影响因子：
1.9
作者：
MacNab, YC;Dean, CB
通讯作者：
Dean, CB