Citation

Anjali, B RK. Asian J. Psychiatry 2023; 92: e103871.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.ajp.2023.103871

PMID

38160524

Abstract

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.

Language: en

Keywords

Public health; Multivariate analysis; Forecasting model; Preventive measures; Suicide rates; Time-series analysis