ArticlePsychological medicine2021
Suicide and the agent-host-environment triad: leveraging surveillance sources to inform prevention.
Article in Psychological medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Psychological Health Risk Factors Among Healthcare Workers: A Structural Equation Modeling Approach.Healthcare (Basel, Switzerland) · 2026Article
- Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review.JMIR public health and surveillance · 2024Article
- County-level estimates of suicide mortality in the USA: a modelling study.The Lancet. Public health · 2023Article
- Hindcasts and forecasts of suicide mortality in US: A modeling study.PLoS computational biology · 2023Observational
- Associations between traumatic event experiences, psychiatric disorders, and suicidal behavior in the general population of Afghanistan: findings from Afghan National Mental Health Survey.Injury epidemiology · 2022Article
- Impact of Firearm Surveillance on Gun Control Policy: Regression Discontinuity Analysis.JMIR public health and surveillance · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Suicide in the US has increased in the last decade, across virtually every age and demographic group. Parallel increases have occurred in non-fatal self-harm as well. Research on suicide across the world has consistently demonstrated that suicide shares many properties with a communicable disease, including person-to-person transmission and point-source outbreaks. This essay illustrates the communicable nature of suicide through analogy to basic infectious disease principles, including evidence for transmission and vulnerability through the agent-host-environment triad. We describe how mathematical modeling, a suite of epidemiological methods, which the COVID-19 pandemic has brought into renewed focus, can and should be applied to suicide in order to understand the dynamics of transmission and to forecast emerging risk areas. We describe how new and innovative sources of data, including social media and search engine data, can be used to augment traditional suicide surveillance, as well as the opportunities and challenges for modeling suicide as a communicable disease process in an effort to guide clinical and public health suicide prevention efforts.
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Registered trials
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