Temporal Patterns of PTSD-Related Online Information-Seeking After Major Earthquakes: A Comparative Google Trends Study of Türkiye, Japan, and Indonesia

This repository contains the data and analysis materials supporting the study "Temporal Patterns of PTSD-Related Online Information-Seeking After Major Earthquakes: A Comparative Google Trends Study of Türkiye, Japan, and Indonesia." The data consist of Google Trends relative search volume (RSV) for the "Post-traumatic stress disorder" topic category, retrieved on 1 May 2026 for Türkiye, Japan, and Indonesia, with each country selected individually under the "Region" option. Two resolutions are provided: a monthly series spanning three years before to three years after each index earthquake (a 73-month window, with the earthquake month indexed as month 37), and a weekly series covering a short window of approximately six months before and after each earthquake. The index events are the 2023 Kahramanmaraş earthquake (Türkiye), the 2011 Tohoku earthquake (Japan), and the 2018 Sulawesi/Palu earthquake (Indonesia). Two analyses are included. The R scripts reproduce the Bayesian structural time-series (CausalImpact) interrupted time-series analysis, which estimates model-based deviations of observed post-earthquake RSV from a counterfactual projected from the pre-earthquake period. This analysis is univariate (no concurrent control series), and the counterfactual is therefore derived from the pre-earthquake period of the response series itself; this is reported as a limitation in the manuscript. The Joinpoint trend analysis was performed with the Joinpoint Regression Program (National Cancer Institute), and its original export files (model selection, model estimates, and final selected model) are included under the joinpoint folder. The README documents the extraction settings, file structure, and column definitions, and lists the expected CausalImpact and Joinpoint results. RSV values are normalized to 0 to 100 within each query window and are therefore relative within a series and not directly comparable in absolute terms across countries. Source code is released under the MIT License; data and documentation are released under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.