Suicide Risk Factors During the COVID-19 Pandemic

The COVID-19 pandemic introduced a complex array of stressors—physical infection, social isolation, economic hardship and disruption to healthcare—that collectively exacerbated known risk factors for suicide. Emerging evidence has identified multiple intersecting domains of vulnerability. First, direct and perceived exposure to the virus and associated health anxieties have been linked to increased psychological distress and suicidal ideation. Second, prolonged lockdowns and social distancing measures intensified feelings of isolation, particularly among older adults, lone households and marginalised groups. Third, economic downturns, job loss and precarious employment have had a disproportionate impact on those with low socioeconomic status, with financial insecurity serving as a potent predictor of self-harm and suicide attempts. Fourth, disruption to routine mental health services and reluctance to seek primary care during lockdowns led to under-detection of depression and anxiety in the community, delaying interventions for high-risk individuals. Lastly, existing mental health conditions, substance misuse and limited social support networks have been consistently recognised as amplifiers of suicide risk during the pandemic. The interaction of these factors has prompted calls for integrated public health responses, combining economic support, accessible mental health care and community outreach to mitigate long-term harms.

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Suicide Risk Factors During the COVID-19 Pandemic publication trend

The graph below shows the total number of articles in suicide risk factors during the covid-19 pandemic across all publications each year (not limited to Nature Index journals).

Technical terms

Suicidal ideation: Thoughts or preoccupations with ending one’s life.
Self-harm: Deliberate injury to oneself, often as a coping mechanism for distress.
Propensity score weighting: A statistical method to balance groups on observed characteristics for fair comparison.
Auto-regressive integrated moving average (ARIMA) model: A time-series technique for forecasting trends while accounting for past values and seasonal effects.
Interrupted time series analysis: A method to assess the impact of an intervention or event by comparing observed trends before and after its onset.

References

1. Suicidal ideation following self-reported COVID-19-like symptoms or serology-confirmed SARS-CoV-2 infection in France: A propensity score weighted analysis from a cohort study. PLOS Medicine (2023).
2. Impact of the COVID-19 pandemic on self-harm and self-harm/suicide ideation: population-wide data linkage study and time series analysis. The British Journal of Psychiatry (2023).
3. Suicide numbers during the first 9-15 months of the COVID-19 pandemic compared with pre-existing trends: An interrupted time series analysis in 33 countries. EClinicalMedicine (2022).