Abstract
Annual suicide figures are critical in identifying trends and guiding research, yet challenges arising from significant lags in reporting can delay and complicate real-time interventions. In this paper, we utilized Google Trends search volumes for behavioral forecasting of national suicide rates in Ireland between 2004 and 2015. Official suicide rates are recorded by the Central Statistics Office in Ireland. While similar investigations using Google trends data have been carried out in other jurisdictions (e.g., United Kingdom, United Stated of America), such research had not yet been completed in Ireland. We compiled a collection of suicide- and depression-related search terms suggested by Google Trends and manually sourced from the literature. Monthly search rate terms at different lags were compared with suicide occurrences to determine the degree of correlation. Following two approaches based on vector autoregression and neural network autoregression, we achieved mean absolute error values between 4.14 and 9.61 when incorporating search query data, with the highest performance for the neural network approach. The application of this process to United Kingdom suicide and search query data showed similar results, supporting the benefit of Google Trends, neural network approach, and the applied search terms to forecast suicide risk increase. Overall, the combination of societal data and online behavior provide a good indication of societal risks; building on past research, our improvements led to robust models integrating search query and unemployment data for suicide risk forecasting in Ireland.
Highlights
Suicide is a leading cause of death and a global disease burden, accounting for nearly one million annual deaths across the world [1]
“depression” and “feeling down” queries we achieve the highest performance in the vector autoregressive models (VAR) approach, suggesting that the search volumes corresponding to these queries are able to improve the prediction of suicide occurrences in Ireland
Our work extends previous research by improving the methodology, focusing on country-specific search queries, applying neural network autoregression, and applying it to the forecasting of suicide rates in Ireland, where such analysis has not been completed previously
Summary
Suicide is a leading cause of death and a global disease burden, accounting for nearly one million annual deaths across the world [1]. Annual suicide figures are critical to understanding risk and guiding research, including the study of biological, social, psychological, and economic factors that may vary with data monitoring [2]. A significant lag between monitoring and public reporting of suicides often delays and challenges real-time interventions [3]. Res. Public Health 2019, 16, 3201; doi:10.3390/ijerph16173201 www.mdpi.com/journal/ijerph
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