Google Trends Analysis of Seasonal Symptoms in India
Author Information
Author(s): Gahlot Urmila, Sharma Yogendra Kumar, Patel Jaichand, Ragumani Sugadev
Primary Institution: Bioinformatics Group, Defense Institute of Physiology and Allied Sciences, Defense Research and Development Organization, Lucknow Road, Timarpur, Delhi India
Hypothesis
The study aims to explore the major seasonal symptoms associated with seasonally sensitive comorbid lifestyle diseases (SCLDs) and evaluate their seasonal linkages via Google Trends.
Conclusion
The study identified 12 clinical symptoms strongly associated with seasonal changes in the Indian population, with 11 symptoms showing significant seasonal linkages.
Supporting Evidence
- The study identified 12 symptoms associated with seasonal changes.
- 11 out of the 12 symptoms showed significant seasonal linkages.
- The research utilized Google Trends data for analysis.
- The study highlights the importance of monitoring seasonal symptoms in the Indian population.
Takeaway
The researchers looked at how certain health symptoms change with the seasons in India, finding that many people search for these symptoms more during specific times of the year.
Methodology
The study used Google Trends data from January 2015 to December 2019 to analyze the search volume of symptoms associated with SCLDs.
Limitations
The study acknowledges the limitations of Google Trends data and the lack of clinical records for a larger population to validate the findings.
Participant Demographics
The study focused on the Indian population.
Digital Object Identifier (DOI)
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