Healthc Inform Res.  2018 Oct;24(4):300-308. 10.4258/hir.2018.24.4.300.

Google Search Trends Predicting Disease Outbreaks: An Analysis from India

• Verma M
• Kishore K
• Kumar M
• Sondh AR
• Aggarwal G
• Kathirvel

• KMID: 2434545
• DOI: http://doi.org/10.4258/hir.2018.24.4.300

Abstract

OBJECTIVES
Prompt detection is a cornerstone in the control and prevention of infectious diseases. The Integrated Disease Surveillance Project of India identifies outbreaks, but it does not exactly predict outbreaks. This study was conducted to assess temporal correlation between Google Trends and Integrated Disease Surveillance Programme (IDSP) data and to determine the feasibility of using Google Trends for the prediction of outbreaks or epidemics.
METHODS
The Google search queries related to malaria, dengue fever, chikungunya, and enteric fever for Chandigarh union territory and Haryana state of India in 2016 were extracted and compared with presumptive form data of the IDSP. Spearman correlation and scatter plots were used to depict the statistical relationship between the two datasets. Time trend plots were constructed to assess the correlation between Google search trends and disease notification under the IDSP
RESULTS
Temporal correlation was observed between the IDSP reporting and Google search trends. Time series analysis of the Google Trends showed strong correlation with the IDSP data with a lag of −2 to −3 weeks for chikungunya and dengue fever in Chandigarh (r > 0.80) and Haryana (r > 0.70). Malaria and enteric fever showed a lag period of −2 to −3 weeks with moderate correlation.
CONCLUSIONS
Similar results were obtained when applying the results of previous studies to specific diseases, and it is considered that many other diseases should be studied at the national and sub-national levels.

Keyword

Disease Outbreaks; Communicable Diseases; Information Technology; Public Health Surveillance; Epidemiological Monitoring

MeSH Terms

Communicable Diseases
Dataset
Dengue
Disease Notification
Disease Outbreaks*
Epidemiological Monitoring
India*
Malaria
Public Health Surveillance
Typhoid Fever

Figure

• 

  Figure 1 Screen shot of Google Trends website depicting the search strategy used for observing the pattern generated for the searches related to dengue in Chandigarh, 2016 (Map shows the geographical pattern of the searches made).

• 

  Figure 2 Correlational plots between Google Trends and IDSP (Integrated Disease Surveillance Programme) data for Haryana (A) and Chandigarh (B) in 2016.

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  Figure 3 Line diagram depicting Google Trends and IDSP data for major febrile illnesses for Haryana (left) and Chandigarh (right) in 2016.

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