Suicide contagion in France: an epidemiologic study

Queinec, Raphaëlle; Benjamin, Courteney L.; Beitz, Christophe; Lagarde, Emmanuel; Encrenaz, Gaëlle

doi:10.1136/ip.2010.029215.858

Cited by 2 publications

(2 citation statements)

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“…The primary aim of all the identified studies was the statistical verification of increased suicides within a population (i.e., the detection of mass clusters). The most employed statistical analyses include a time-series model such as the Seasonal Autoregressive Integrated Moving Average (SARIMA) model (n = 11) [74][75][76][77][78][79][80][81][82][83], a regression model (n = 8) [82][83][84][85][86][87][88][89], a Poisson model (n = 4) [84,[87][88][89], and non-parametric tests (n = 3) [87,90,91]. When comparing statistical models to detect mass clusters, a time-series regression model will capture the parameters of mass clustering as accurately as possible, based on temporal data.…”

Section: Resultsmentioning

confidence: 99%

Quantitative Methods to Detect Suicide and Self-Harm Clusters: A Systematic Review

Benson

Rigby

Brunsdon

et al. 2022

IJERPH

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Suicide and self-harm clusters exist in various forms, including point, mass, and echo clusters. The early identification of clusters is important to mitigate contagion and allocate timely interventions. A systematic review was conducted to synthesize existing evidence of quantitative analyses of suicide and self-harm clusters. Electronic databases including Medline, Embase, Web of Science, and Scopus were searched from date of inception to December 2020 for studies that statistically analyzed the presence of suicide or self-harm clusters. Extracted data were narratively synthesized due to heterogeneity among the statistical methods applied. Of 7268 identified studies, 79 were eligible for narrative synthesis. Most studies quantitatively verified the presence of suicide and self-harm clusters based on the scale of the data and type of cluster. A Poisson-based scan statistical model was found to be effective in accurately detecting point and echo clusters. Mass clusters are typically detected by a time-series regression model, although limitations exist. Recently, the statistical analysis of suicide and self-harm clusters has progressed due to advances in quantitative methods and geospatial analytical techniques, most notably spatial scanning software. The application of such techniques to real-time surveillance data could effectively detect emerging clusters and provide timely intervention.

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Section: Resultsmentioning

confidence: 99%

Quantitative Methods to Detect Suicide and Self-Harm Clusters: A Systematic Review

Benson

Rigby

Brunsdon

et al. 2022

IJERPH

View full text Add to dashboard Cite

show abstract

“…For example, extensive and prominent news coverage of suicides has been reported to play a role in the emergence of point clusters among youth (33). Several reports have documented increases in suicide rates following media reports of high-profile celebrities, who might be considered models for imitation (38)(39)(40)(41). In addition, there might be unintended negative consequences of entertainment media portrayals of suicide that do not adhere to best practices for safe reporting (42,43).…”

Section: Overview and Types Of Suicide Clustersmentioning

confidence: 99%

Background and Rationale — CDC Guidance for Communities Assessing, Investigating, and Responding to Suicide Clusters, United States, 2024

Ballesteros,

Ivey-Stephenson,

Trinh

et al. 2024

MMWR Suppl.

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Summary To assist community leaders in public health, mental health, education, and other fields with developing a community response plan for suicide clusters or for situations that might develop into suicide clusters, in 1988, CDC published Recommendations for a Community Plan for the Prevention and Containment of Suicide Clusters (MMWR Suppl 1988;37[No. Suppl 6]:1–12). Since that time, the reporting and investigation of suicide cluster events has increased, and more is known about cluster risk factors, assessment, and identification. This supplement updates and expands CDC guidance for assessing, investigating, and responding to suicide clusters based on current science and public health practice. This report is the first of three in the MMWR supplement that describes an overview of suicide clusters, information about the other reports in this supplement, methods used to develop the supplement guidance, and the intended use of the supplement reports. The second report, CDC Guidance for Community Assessment and Investigation of Suspected Suicide Clusters — United States 2024 , describes the potential methods, data sources and analysis that communities can use to identify and confirm suspected suicide clusters, and better understand the relevant issues. The final report, CDC Guidance for Community Response to Suicide Clusters — United States, 2024 , describes how local public health and community leaders can develop a response plan for suicide clusters. The guidance in this supplement is intended as a conceptual framework that can be used by public health practitioners and state and local health departments to develop response plans for assessing and investigating suspected clusters that are tailored to the needs, resources, and cultural characteristics of their communities.

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Suicide contagion in France: an epidemiologic study

Cited by 2 publications

References 0 publications

Quantitative Methods to Detect Suicide and Self-Harm Clusters: A Systematic Review

Quantitative Methods to Detect Suicide and Self-Harm Clusters: A Systematic Review

Background and Rationale — CDC Guidance for Communities Assessing, Investigating, and Responding to Suicide Clusters, United States, 2024

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