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http://dx.doi.org/10.4258/hir.2018.24.4.300

Google Search Trends Predicting Disease Outbreaks: An Analysis from India  

Verma, Madhur (Department of Community Medicine, Kalpana Chawla Government Medical College and Hospital)
Kishore, Kamal (Department of Biostatistics, Post Graduate Institute of Medical Education and Research (PGIMER))
Kumar, Mukesh (Department of Community Medicine, Vardhman Mahavir Medical College and Safdarjung Hospital)
Sondh, Aparajita Ravi (State Integrated Disease Surveillance Project (IDSP) Cell, Department of Health)
Aggarwal, Gaurav (Integrated Disease Surveillance Project (IDSP), Chandigarh Administration)
Kathirvel, Soundappan (Department of Community Medicine, School of Public Health, Post Graduate Institute of Medical Education and Research (PGIMER))
Publication Information
Healthcare Informatics Research / v.24, no.4, 2018 , pp. 300-308 More about this Journal
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.
Keywords
Disease Outbreaks; Communicable Diseases; Information Technology; Public Health Surveillance; Epidemiological Monitoring;
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