Uncovering the Time-Frequency Relationship Between Google Trends and COVID-19 Vaccination Metrics: A Hybrid ARDL-Wavelet Coherence Model for Prediction
The results show that Google Trends has good long-term prediction ability in the vaccine promotion stage, but its short-term prediction effect shows volatility with time and frequency. The ARDL-wavelet coherence analysis framework proposed in this paper provides a new research paradigm for evaluating the public's influence on vaccination. The research results emphasize the potential and importance of Google Trends in the construction of real-time public health response and early warning systems.
Authors
- Zongjing Liang (ORCID: https://orcid.org/0000-0002-2121-1320)
- Yun Kuang (ORCID: https://orcid.org/0000-0002-2136-0350)
- Liang Ge (ORCID: https://orcid.org/0000-0002-7371-2039)
- Zhijie Li (ORCID: https://orcid.org/0000-0001-9283-6072)
Institutions
- Guangxi Normal University (CN)
Publication Details
- Journal
- Cureus
- Published
- 2025-09-25
- DOI
- https://doi.org/10.7759/cureus.93193
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 0.00