Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Dec 30, 2019
Date Accepted: May 20, 2020
Causality Analysis of Google Trends and Dengue Incidences in Bandung, Indonesia: Linkages of Digital Data Modeling
ABSTRACT
Background:
In the last few decades, dengue has been identified as a fast-spreading disease by the World Health Organization (WHO) and has become a major health problem for people in all tropical and sub-tropical countries, including Indonesia. With no medicine and vaccine available for encountering the diseases, the focus of the health authorities is directed to control and to prevent the transmission. Surveillance of dengue cases is essential in early detection of dengue fever to execute the proper preventive actions which are necessary to avoid a possible outbreak.
Objective:
This paper will investigate the possibility that Google Trends (GT) can be used in the early detection of dengue outbreak.
Methods:
With Google as one of the most used online search engines in Indonesia, the popularity of certain keywords in Google might have a direct correlation with the related phenomena in the real world. Google Trends also contains real-time data, whereas data on dengue incidence cases may take time to process. If GT data can be used to detect future dengue cases, then it will be useful in giving valuable information for taking further preventive action before the occurrence of the outbreak. In this paper, a co-integration method is used to obtain a long-run equilibrium relationship.
Results:
By examining the stationarity of the popularity of keywords related to dengue fever in Google and the number of weekly dengue cases in Bandung as well as the linear combination of the two variables, it is shown that the two are co-integrated. Hence, an error-correction model (ECM) can be constructed to predict deviance from the equilibrium condition. It is also shown that the popularity of dengue fever in Google, Granger-causes the number of dengue cases, but the vice versa does not apply. This is further shown by examining the impulse response function and variance decomposition.
Conclusions:
Therefore, real-time data on the popularity of dengue in Google Trends can be used as an initial indicator of vigilance regarding dengue cases in the coming period.
Citation
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