Temporal trends of suicidality among hospitalised adolescents during COVID-19 pandemic: A Bayesian framework

Objective: Literature on temporal patterns of suicidality among youths during the COVID-19 pandemic is growing. The present work proposes a Bayesian approach to assess temporal patterns of suicide-related behaviours among inpatient adolescents during the COVID-19 pandemic. Methodology: Data referred to the first hospital discharge record with ICD9-CM codes related to suicide-related behaviour and/or suicidal ideation among adolescents aged 13-19 between 1 January 2017 and 31 March 2021 were collected in the Piedmont region, Italy (n = 334; median age: 15 years, IQR: 14-16; 80% girls). A Poisson Bayesian regression model performed on pre-COVID-19 data (2017-2020), adjusted by seasonality and stratified by sex, was adopted to provide the probability that the predicted counts exceed the observed ones in each pandemic year quarter. Results: A declining trend of suicidality was observed in April-June 2020 among both sex groups. Among females, an increasing pattern of suicidality was registered in early 2021 (January-March) compared to the pre-pandemic period. Conclusion: The present findings contributed to a growing literature on the COVID-19 pandemic's impact on adolescents' suicide-related behaviours from a gender perspective and encouraged wider adoption of Bayesian approaches as valuable tools to explore rare events and deeply enlighten open public health issues.