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Related Experiment Video

Updated: Sep 23, 2025

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

Ruth Benson1,2, Jan Rigby3, Christopher Brunsdon3

  • 1School of Public Health, College of Medicine and Health, University College Cork, Western Gateway Building, T12 XF62 Cork, Ireland.

International Journal of Environmental Research and Public Health
|May 14, 2022
PubMed
Summary

Early identification of suicide and self-harm clusters is crucial. Quantitative analyses and advanced statistical methods, like spatial scanning, effectively detect these clusters for timely intervention.

Keywords:
cluster detectioncontagiongeospatial analysisself-harmsuicidesystematic review

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Area of Science:

  • Epidemiology
  • Public Health
  • Statistical Analysis

Background:

  • Suicide and self-harm clusters, including point, mass, and echo types, pose significant public health challenges.
  • Early detection is vital for mitigating contagion and implementing timely interventions.

Purpose of the Study:

  • To systematically review and synthesize existing evidence on quantitative analyses of suicide and self-harm clusters.
  • To identify effective statistical methods for cluster detection.

Main Methods:

  • A systematic review of electronic databases (Medline, Embase, Web of Science, Scopus) was performed.
  • Studies published from inception to December 2020, using statistical analyses for suicide/self-harm clusters, were included.
  • Data from 79 eligible studies were narratively synthesized due to methodological heterogeneity.

Main Results:

  • Most studies quantitatively confirmed the presence of suicide and self-harm clusters.
  • Poisson-based scan statistics effectively detected point and echo clusters.
  • Time-series regression models were commonly used for mass clusters, with noted limitations.

Conclusions:

  • Advances in quantitative and geospatial techniques, particularly spatial scanning software, have improved cluster analysis.
  • Real-time surveillance data combined with these techniques can enable early detection of emerging clusters.
  • This facilitates prompt and effective public health interventions for suicide and self-harm.