多元正态空间扫描统计量模型在探测地方病最强聚集性中的应用

doi:10.3969/j.issn.1007-2861.2014.02.012

上海大学学报(自然科学版) ›› 2014, Vol. 20 ›› Issue (3): 274-280.doi: 10.3969/j.issn.1007-2861.2014.02.012

多元正态空间扫描统计量模型在探测地方病最强聚集性中的应用

蒋炜1, 沈晓蓓2, 宗福季3

1. 上海交通大学安泰经济与管理学院, 上海200052; 2. 上海大学管理学院, 上海200444; 3. 香港科技大学工业工程与物流管理学系, 香港999077

收稿日期:2014-05-02 出版日期:2014-06-26 发布日期:2014-06-26
通讯作者: 宗福季(1967—), 男, 国际质量研究院院士, 教授, 博士生导师, 博士, 研究方向为质量管理和统计过程控制等. E-mail:ftsung@gmail.com
作者简介:宗福季(1967—), 男, 国际质量研究院院士, 教授, 博士生导师, 博士, 研究方向为质量管理和统计过程控制等. E-mail: ftsung@gmail.com
基金资助:
RGC Competitive Earmarked Research (2012–2014)

Application of Multivariate Normal Scan Statistic to Most Severe Cluster of Local Diseases

JIANG Wei1, SHEN Xiao-bei2, TSUNG Fugee3

1. Antai College of Economics & Management, Shanghai Jiao Tong University, Shanghai 200052, China;
2. School of Management, Shanghai University, Shanghai 200444, China;
3. Department of Industrial Engineering and Logistic Management, The Hong Kong University of Science and Technology, Hong Kong 999077, China

Received:2014-05-02 Online:2014-06-26 Published:2014-06-26
Contact: 宗福季(1967—), 男, 国际质量研究院院士, 教授, 博士生导师, 博士, 研究方向为质量管理和统计过程控制等. E-mail: ftsung@gmail.com E-mail:ftsung@gmail.com
About author:宗福季(1967—), 男, 国际质量研究院院士, 教授, 博士生导师, 博士, 研究方向为质量管理和统计过程控制等. E-mail: ftsung@gmail.com
Supported by:
RGC Competitive Earmarked Research (2012–2014)

摘要/Abstract

摘要： 研究了在医疗资源有限的条件下, 如何在多组人群中探测某疾病最强地理聚集性的问题. 为了有效地探测疾病爆发, 只需特别监测和评估某些特定人群即可, 这类人群称为具有最强聚集性的人群(most severe cluster, MSC). 由于各组人群会相互影响, 因而提出了一种多元正态空间扫描统计量(multivariate normal scan statistic, MNSS)模型, 并以美国纽约州肺癌患者为例验证了该模型的适用性.

关键词: 多组人群, 连续数据, 人口相关性, 最强聚集性

Abstract: This paper focuses on the problem of detecting ageographical cluster with the most severe status in multiple groups of populations with the consideration of limited medical resources. In an early stage of a disease, an outbreak may only be present in some specific population group. Therefore, to efficiently detect the outbreak, specific groups need to be particularly monitored and evaluated. The objective of detection as the most severe cluster (MSC) is defined. Considering interaction among population groups, a multivariate normal scan statistic is proposed. The method is applied to an example of lung cancer in New York State to detect the MSC with a high mortality rate at the aggregate level.

Key words: correlation between population groups, geographical cluster with the most severe status, multiple groups of population, continuous data

中图分类号:

C 811

蒋炜1, 沈晓蓓2, 宗福季3. 多元正态空间扫描统计量模型在探测地方病最强聚集性中的应用[J]. 上海大学学报(自然科学版), 2014, 20(3): 274-280.

JIANG Wei1, SHEN Xiao-bei2, TSUNG Fugee3. Application of Multivariate Normal Scan Statistic to Most Severe Cluster of Local Diseases[J]. Journal of Shanghai University（Natural Science Edition）, 2014, 20(3): 274-280.

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多元正态空间扫描统计量模型在探测地方病最强聚集性中的应用

Application of Multivariate Normal Scan Statistic to Most Severe Cluster of Local Diseases

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