Forecast models for suicide: Time-series analysis with data from Italy

Exploring cause-specific strategies for suicide prevention in India: A multivariate VARMA approach

Efficiently predicting suicide rates aids resource allocation and response preparedness. This study investigates time-series data with multiple variables to model and forecast suicide events in India. Utilizing official suicide statistics (2001-2021), results highlight the superiority of the multivariate VARMA model over VAR and univariate ARIMA models. This approach uncovers overlooked patterns and a concerning upward trend in future Indian suicide incidents. The research provides insights that aid public health professionals in targeting high-need areas and enhancing readiness and suggests cause-specific preventive strategies to counter this trend.

Time Series Analysis of Monthly Suicide Rates in West of Iran, 2006-2013

INTRODUCTION

Iran's western provinces have higher suicide rate compared to the other provinces of the country. Although suicide rates fluctuate over time, suitable statistical models can describe their underlying stochastic dynamics.

METHODS

This study was conducted to explore the fluctuations of the monthly suicide rates in the most populated western province of Iran using exponential smoothing state space model to compute the forecasts. For this reason, the monthly frequencies of completed suicides were converted to rates per 100,000 and a state-space approach was identified and fitted to the monthly suicide rates. Diagnostic checks were performed to determine the adequacy of the fitted model.

RESULTS

A significant seasonal variation was detected in completed suicide with a peak in August. Diagnostic checks and the time series graph of the observed monthly suicide rates against predicted values from the fitted model showed that in the study period (from March 2006 to September 2013), the observed and predicted values were in agreement. Thus, the model was used to obtain the short-term forecasts of the monthly suicide rates.

CONCLUSIONS

In this study, we had no significant trend but seasonal variations in the suicide rates that were identified. However, additional data from other parts of the country with longer duration are needed to visualize the reliable trend of suicide and identify seasonality of suicide across the country.

Chris Cornell, the Black Hole Sun, and the Seasonality of Suicide

PURPOSE

Seattle-inspired rock and roll superstar Chris Cornell died by suicide in May 2017. In the northern hemisphere, May represents the peak of the widely replicated but still unexplained seasonal spring rhythm in suicide. Years earlier, Cornell had suffered openly from recurrent bouts of severe depression, and his early musical lyrics do indeed suggest an enduring sensitivity to the vicissitudes of depressed and suicidal states. Cornell's most famous song, Black Hole Sun, suggests a mixed mood state, the incidence of which also peaks in the spring. The present work explores Cornell's May suicide from a chronobiologic perspective.

METHODS

Review of Cornell's lyrics and literature on suicide.

RESULTS

Cornell's lyrics contain clear indicators of mixed depressive and seasonal imagery, highlighting 3 fundamental axioms of suicidology: (1) the yearly suicide rhythm peaks in May in the northern hemisphere, (2) mixed depressive states are particularly lethal, and (3) the suicide risk increases dramatically when recovering from depression and mood turns mixed.

CONCLUSIONS

Cornell, in his life and music, left us with a novel and important hypothesis about the spring seasonality of suicide, namely, that the yearly suicide risk becomes maximal when winter turns to spring and there emerges a deadly mixed mood state under a May photoperiod, i.e., the suicide risk is maximal when a Black Hole Sun occurs in May. It is hoped that Cornell's legacy and sensitive hypothesis inspire research into the etiology and treatment of the spring seasonality of suicide risk and mixed mood states.

LIMITATIONS

The Cornell hypothesis was formulated based in part on several speculative inferences regarding the course of his functioning just prior to his suicide.