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Multivariate normal spatial scan statistic for detecting the most severe cluster of a disease
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作者 xiaobei shen Wei Jiang 《Journal of Management Analytics》 EI 2014年第2期130-145,共16页
This paper focuses on the problem of detecting the geographical cluster with the most severe status in multiple groups of population given limited medical resources.Populations are grouped based on characteristics suc... This paper focuses on the problem of detecting the geographical cluster with the most severe status in multiple groups of population given limited medical resources.Populations are grouped based on characteristics such as age,gender,and race.In the early stages of a disease,an outbreak may only present in specific population groups.Therefore,to efficiently detect the outbreak,we are particularly interested in monitoring and evaluating such groups.We define the objective of detection as the most severe cluster(MSC).Taking into account the interactions between population groups,a multivariate normal scan statistic is proposed to simultaneously determine the location and size of a significant MSC,as well as the specific population groups in which the MSC is located.The proposed method is applied to an example of lung cancer in New York State,where the MSC with the highest mortality rate at the aggregate level is detected.Further,the detection capacity of this method is evaluated using a simulation study based on the lung cancer example. 展开更多
关键词 continuous data multiple groups of population correlation between population groups geographical cluster with the most severe status
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