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A study on detecting multi-dimensional clusters of infectious diseases

A study on detecting multi-dimensional clusters of infectious diseases
A study on detecting multi-dimensional clusters of infectious diseases

To indentify early signs of unusual health events is critical to early warning of infectious diseases. A new method for detecting multi-dimensional clusters of infectious diseases is presented in this paper. Ant colony clustering algorithm is applied to classify the cases of specified infectious diseases according to their crowd characters; then the cases belonging to the same class in terms of the space adjacency is separated; finally, the prior information about previous diseases outbreaks in the study area is applied to test the hypothesis that there was no disease cluster at various sub-regions. The detection ability of the method shows that this method does not need to accumulate case data within a long time period to detect irregular-shaped hot spots. It is useful for introducing spatial analysis to detection of infectious disease outbreaks.

Ant colony clustering algorithm, Bayesian Gamma-Poisson model, Cluster, Infectious diseases, Spatial analysis
0375-5444
435-443
Liao, Yilan
7a1a861c-a091-417a-8c94-c1c6d5e6c875
Wang, Jinfeng
3b2e15d2-baff-451c-8a30-d05c3970059f
Yang, Weizhong
65d18fbc-d752-42a7-ac38-01534ceda15c
Li, Zhongjie
8c060065-5459-449e-a776-29d55614adb7
Jin, Lianmei
339ce7b9-541a-4ed4-ac63-e62cd3545000
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Zheng, Xiaoying
c549e9fe-1c5e-48fe-bd3c-60a818bdeb80
Liao, Yilan
7a1a861c-a091-417a-8c94-c1c6d5e6c875
Wang, Jinfeng
3b2e15d2-baff-451c-8a30-d05c3970059f
Yang, Weizhong
65d18fbc-d752-42a7-ac38-01534ceda15c
Li, Zhongjie
8c060065-5459-449e-a776-29d55614adb7
Jin, Lianmei
339ce7b9-541a-4ed4-ac63-e62cd3545000
Lai, Shengjie
b57a5fe8-cfb6-4fa7-b414-a98bb891b001
Zheng, Xiaoying
c549e9fe-1c5e-48fe-bd3c-60a818bdeb80

Liao, Yilan, Wang, Jinfeng, Yang, Weizhong, Li, Zhongjie, Jin, Lianmei, Lai, Shengjie and Zheng, Xiaoying (2012) A study on detecting multi-dimensional clusters of infectious diseases. Dili Xuebao, 67 (4), 435-443.

Record type: Article

Abstract

To indentify early signs of unusual health events is critical to early warning of infectious diseases. A new method for detecting multi-dimensional clusters of infectious diseases is presented in this paper. Ant colony clustering algorithm is applied to classify the cases of specified infectious diseases according to their crowd characters; then the cases belonging to the same class in terms of the space adjacency is separated; finally, the prior information about previous diseases outbreaks in the study area is applied to test the hypothesis that there was no disease cluster at various sub-regions. The detection ability of the method shows that this method does not need to accumulate case data within a long time period to detect irregular-shaped hot spots. It is useful for introducing spatial analysis to detection of infectious disease outbreaks.

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More information

Published date: 1 January 2012
Additional Information: Acta Geographica Sinica
Keywords: Ant colony clustering algorithm, Bayesian Gamma-Poisson model, Cluster, Infectious diseases, Spatial analysis

Identifiers

Local EPrints ID: 429996
URI: http://eprints.soton.ac.uk/id/eprint/429996
ISSN: 0375-5444
PURE UUID: a2648c54-c5dd-42a3-a99b-c3f708a6b460
ORCID for Shengjie Lai: ORCID iD orcid.org/0000-0001-9781-8148

Catalogue record

Date deposited: 09 Apr 2019 16:30
Last modified: 06 Jun 2024 02:03

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Contributors

Author: Yilan Liao
Author: Jinfeng Wang
Author: Weizhong Yang
Author: Zhongjie Li
Author: Lianmei Jin
Author: Shengjie Lai ORCID iD
Author: Xiaoying Zheng

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