ArticleF1000Research2026
Public Search Behavior and Tuberculosis Cases in Indonesia 2019-2023: An Infodemiology Study Using Google Trends .
Article in F1000Research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
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Authors and funding
12 authors.
Funding
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Abstract
Background: Tuberculosis (TB) remains a major health challenge in Indonesia, which ranks second globally in 2024. As the 2030 elimination target approaches, gaps in early detection and public education persist. The public's tendency to seek health information online before consulting professionals presents an opportunity to leverage infodemiology for public health surveillance. Therefore, this study aimed to assess the relationship between multi-term Google search trends and annual TB report data in Indonesia to disseminate the potential use of digital search data as a complementary indicator for epidemiological surveillance. Methods: A repeated cross-sectional design was conducted using provincial data from all Indonesian provinces between 2019 and 2023. Official provincial TB case data were obtained from the Indonesian Health Profile, while Google Trends Relative Search Volume (RSV) data were extracted for 53 TB-related search terms. Provincial TB case counts were normalized to a 0-100 scale to match RSV values before analysis. Normality was assessed using the Shapiro-Wilk test. The associations between TB cases and RSV were examined using Spearman's rank correlation. Multiple testing was controlled using the Benjamini-Hochberg False Discovery Rate (BH-FDR) procedure, with statistical significance defined as an FDR-adjusted Results: After false discovery rate adjustment, 38-42 of the 53 tuberculosis-related Google Trends search terms remained significantly correlated with monthly TB cases across 2019-2023, indicating a stable association between online search behavior and disease incidence. Colloquial search terms (e.g., "Flek Paru"), clinical characteristic queries, and keywords related to symptoms, prevention, transmission, treatment, and pediatric TB consistently showed the strongest positive correlations, with correlation coefficients reaching Conclusion: Google Trends data, correlated strongly with TB case in Indonesia, can complement conventional TB surveillance by reflecting regional disease patterns and supporting timely monitoring, despite limitations related to internet access and search behavior.
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