Predicting the Number of Suicides in Japan: A Vector Autoregression Time Series Model Using Internet Search Queries (Preprint)

BACKGROUND The number of suicides in Japan increased during the COVID-19 pandemic. Predicting the number of suicides is critical to take timely preventive measures. OBJECTIVE In this study, we examine whether the number and characteristics of suicides can be predicted based on the Internet search behavior and the search queries. METHODS The monthly number of suicides by gender, collected and published by the National Police Agency, was used as an outcome variable. The number of searches by gender on the queries associated with "suicide" on "Yahoo Search" from January 2016 to December 2020 was used as a predictive variable. The following five phrases highly relevant to "suicide" were searched before searching for the keyword "suicide," and extracted and used for analyses: "abuse," "work, don’t want to go," "company, want to quit," "divorce," and "no money." The Augmented Dickey–Fuller and Johansen's tests were performed for the original series and to verify the existence of unit roots and cointegration for each variable, respectively. The vector autoregression model was applied to predict the number of suicides. The Breusch–Godfrey Lagrangian multiplier (BG-LM) test, autoregressive conditional heteroskedasticity Lagrangian multiplier (ARCH-LM) test, and Jarque–Bera (JB) test were employed to confirm model convergence. In addition, a Granger causality test was performed for each predictive variable. RESULTS In the original series, unit roots were found in the trend model, whereas in the first-order difference series, both men (minimum tau 3: −9.24, max tau 3: −5.38) and women (minimum tau 3: −9.24, max tau 3: −5.38) had no unit roots for all variables. In Johansen's test, a cointegration relationship was observed among several variables. The queries used in the converged models were "divorce" for men (BG-LM test: p= 0.55; ARCH-LM test: p= 0.63; JB test: p= 0.66) and "no money" for women (BG-LM test: p = 0.17; ARCH-LM test: p = 0.15; JB test: p= 0.10). In the Granger causality test for each variable, "divorce" was significant for both men (F= 3.29, p = 0.041) and women (F = 3.23, p = 0.044). ¬ CONCLUSIONS The number of suicides can be predicted by the search queries related to the keyword "suicide." Previous studies have reported that financial poverty and divorce are associated with suicide. The results of this study, in which search queries on "no money" and "divorce" predict suicide, support the findings of previous studies. Further research on the economic poverty of women and those with complex problems is necessary.