Geographic disparities and predictors of suicide mortality risk in Florida: spatial scan statistics and negative binomial modeling

This study identified geographic disparities and key predictors of suicide mortality risk across Florida counties. These findings can inform policymakers, healthcare providers, and community organizations in designing and implementing targeted suicide prevention programs tailored to the specific needs of high-risk communities.

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Publication Details

Journal
PeerJ
Published
2025-11-04
DOI
https://doi.org/10.7717/peerj.20075
Citations
1
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
1.35

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article

Geographic disparities and predictors of suicide mortality risk in Florida: spatial scan statistics and negative binomial modeling

Nirmalendu Deb Nath, Howard Onyuth, Agricola Odoi, Corey A. Day
1 citations
PeerJ
Data-Driven Disease Surveillance
1.35
article

Geographic disparities and predictors of suicide mortality risk in Florida: spatial scan statistics and negative binomial modeling

Nirmalendu Deb Nath, Howard Onyuth, Agricola Odoi, Corey A. Day
article en
1 citations

Abstract

This study identified geographic disparities and key predictors of suicide mortality risk across Florida counties. These findings can inform policymakers, healthcare providers, and community organizations in designing and implementing targeted suicide prevention programs tailored to the specific needs of high-risk communities.

PeerJVol. 13
Knoxville College (US), University of Tennessee at Knoxville (US)
Florida Department of Health
Openalex Percentile: Top 14%
Data-Driven Disease Surveillance
1.35
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Geographic disparities and predictors of suicide mortality risk in Florida: spatial scan statistics and negative binomial modeling — Nirmalendu Deb Nath, Howard Onyuth, et al. · PeerJ (2025) | TGRS Research Map | TGRS