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Article: Application of Scan Statistics to Detect Suicide Clusters in Australia

TitleApplication of Scan Statistics to Detect Suicide Clusters in Australia
Authors
Issue Date2013
PublisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.action
Citation
PLoS ONE, 2013, v. 8 n. 1, p. e54168 How to Cite?
AbstractBackground: Suicide clustering occurs when multiple suicide incidents take place in a small area or/and within a short period of time. In spite of the multi-national research attention and particular efforts in preparing guidelines for tackling suicide clusters, the broader picture of epidemiology of suicide clustering remains unclear. This study aimed to develop techniques in using scan statistics to detect clusters, with the detection of suicide clusters in Australia as example. Methods and Findings: Scan statistics was applied to detect clusters among suicides occurring between 2004 and 2008. Manipulation of parameter settings and change of area for scan statistics were performed to remedy shortcomings in existing methods. In total, 243 suicides out of 10,176 (2.4%) were identified as belonging to 15 suicide clusters. These clusters were mainly located in the Northern Territory, the northern part of Western Australia, and the northern part of Queensland. Among the 15 clusters, 4 (26.7%) were detected by both national and state cluster detections, 8 (53.3%) were only detected by the state cluster detection, and 3 (20%) were only detected by the national cluster detection. Conclusions: These findings illustrate that the majority of spatial-temporal clusters of suicide were located in the inland northern areas, with socio-economic deprivation and higher proportions of indigenous people. Discrepancies between national and state/territory cluster detection by scan statistics were due to the contrast of the underlying suicide rates across states/territories. Performing both small-area and large-area analyses, and applying multiple parameter settings may yield the maximum benefits for exploring clusters. © 2013 Cheung et al.
Persistent Identifierhttp://hdl.handle.net/10722/189551
ISSN
2015 Impact Factor: 3.057
2015 SCImago Journal Rankings: 1.395
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorCheung, YTDen_US
dc.contributor.authorSpittal, MJen_US
dc.contributor.authorWilliamson, MKen_US
dc.contributor.authorTung, SJen_US
dc.contributor.authorPirkis, Jen_US
dc.date.accessioned2013-09-17T14:46:13Z-
dc.date.available2013-09-17T14:46:13Z-
dc.date.issued2013en_US
dc.identifier.citationPLoS ONE, 2013, v. 8 n. 1, p. e54168en_US
dc.identifier.issn1932-6203-
dc.identifier.urihttp://hdl.handle.net/10722/189551-
dc.description.abstractBackground: Suicide clustering occurs when multiple suicide incidents take place in a small area or/and within a short period of time. In spite of the multi-national research attention and particular efforts in preparing guidelines for tackling suicide clusters, the broader picture of epidemiology of suicide clustering remains unclear. This study aimed to develop techniques in using scan statistics to detect clusters, with the detection of suicide clusters in Australia as example. Methods and Findings: Scan statistics was applied to detect clusters among suicides occurring between 2004 and 2008. Manipulation of parameter settings and change of area for scan statistics were performed to remedy shortcomings in existing methods. In total, 243 suicides out of 10,176 (2.4%) were identified as belonging to 15 suicide clusters. These clusters were mainly located in the Northern Territory, the northern part of Western Australia, and the northern part of Queensland. Among the 15 clusters, 4 (26.7%) were detected by both national and state cluster detections, 8 (53.3%) were only detected by the state cluster detection, and 3 (20%) were only detected by the national cluster detection. Conclusions: These findings illustrate that the majority of spatial-temporal clusters of suicide were located in the inland northern areas, with socio-economic deprivation and higher proportions of indigenous people. Discrepancies between national and state/territory cluster detection by scan statistics were due to the contrast of the underlying suicide rates across states/territories. Performing both small-area and large-area analyses, and applying multiple parameter settings may yield the maximum benefits for exploring clusters. © 2013 Cheung et al.-
dc.languageengen_US
dc.publisherPublic Library of Science. The Journal's web site is located at http://www.plosone.org/home.actionen_US
dc.relation.ispartofPLoS ONEen_US
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.titleApplication of Scan Statistics to Detect Suicide Clusters in Australiaen_US
dc.typeArticleen_US
dc.identifier.emailCheung, YTD: takderek@hku.hken_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1371/journal.pone.0054168-
dc.identifier.pmid23342098-
dc.identifier.scopuseid_2-s2.0-84872323678-
dc.identifier.hkuros225124en_US
dc.identifier.volume8en_US
dc.identifier.issue1en_US
dc.identifier.spagee54168en_US
dc.identifier.epagee54168en_US
dc.identifier.isiWOS:000314759400129-

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