Abstract
Objectives
Dengue fever is a major public health problem in countries like India, where traditional surveillance systems often suffer from delays. The study aims to examine the relationship between Google Trends data and the official record of dengue outbreaks in India as a supplementary tool to regular surveillance methods.
Methods
We used the Google Trends website to obtain the Google Trends data for the search terms “dengue fever,” “dengue symptoms,” and “dengue treatment” for the year 2023, along with the official record of the number of dengue outbreaks in the year 2023 from the Integrated Disease Surveillance Program (IDSP) website. Pearson’s correlation analysis, smoothed moving average, and the Toda-Yamamoto causality test were used to explore the strength, direction, and causality between the Google Trends data and official reports of the number of dengue outbreaks in India.
Results
The Toda-Yamamoto causality test revealed significant Granger causality between the search terms “dengue fever (p < 0.001),” “dengue symptoms (p < 0.001),” and “dengue treatment (p < 0.001)” with official records of the number of dengue outbreaks in India.
Conclusion
Google Trends data for the searched terms can supplement traditional surveillance methods for dengue outbreaks in India. Strong correlation coupled with significant Granger causality indicates its potential use as an early warning signal for dengue outbreaks in the country.
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Details
1 All India Institute of Medical Sciences, Raipur, India (GRID:grid.413618.9) (ISNI:0000 0004 1767 6103)
2 Balaji Institute of Medical Sciences, Raipur, India (GRID:grid.498559.c) (ISNI:0000 0004 4669 8846)