Suicide is a major global public health crisis, taking over 700,000 lives each year, according to the World Health Organization. Despite many initiatives, rates in numerous countries have not fallen substantially, indicating that current prevention strategies lack sufficient breadth and integration. Despite numerous initiatives, suicide rates in many countries have not declined significantly, suggesting that current prevention strategies are insufficiently comprehensive.

From a public health perspective, suicide requires population-level interventions that address social determinants of health—poverty, unemployment, social isolation, and access to care. An upstream approach enables community policies and awareness campaigns that reduce stigma and promote mental well-being. Priority should also go to early identification of at-risk groups—adolescents, Indigenous communities, migrants, and people with chronic illness—through school-based programs, workplace interventions, and culturally tailored outreach.

Identifying suicide risk patterns requires a coordinated system. Epidemiology offers the wide lens, linking hospital, ER, and death registry data and using machine learning to detect clusters and flag individual and community risk for timely intervention. Forensic medicine then ensures accurate case classification through multidisciplinary postmortems and analyses of notes, circumstances, and toxicology—feeding high-quality data back into surveillance. In addition, digital tools—AI crisis lines, monitoring apps, and social media signals—extend detection and support into daily life. As these handle sensitive personal and biometric data, these tools must be assessed for effectiveness, privacy, and public acceptability within clear, co-developed ethical frameworks. Together, accurate classification strengthens surveillance, surveillance informs prevention, and digital tools turn insight into timely action.

This Research Topic aims to establish a collaborative platform to co-design and evaluate suicide prevention across disciplines. By replacing siloed approaches with integrated, data-driven, and ethically grounded models, it reframes suicide as a complex social, biological, and legal phenomenon and enables holistic, cross-sector interventions for a more equitable and effective response. This collection welcomes the following themes, but not limited to:

• Upstream, population-level prevention targeting social determinants (poverty, unemployment, housing, social isolation);
• Community co-designed anti-stigma and mental health literacy campaigns;
• Equitable access to care via primary care integration, crisis services, and community supports;
• Early identification in universal settings (schools, workplaces, primary care) with stepped-care pathways;
• Culturally safe, community-led approaches for priority groups (Indigenous peoples, migrants, youth, people with chronic illness);
• Digital tools for early detection of suicide risk and for support into daily life.

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Suicide Prevention in a Globalized World: A Multidisciplinary Framework for Action