Suitability of Google Trends™ for Digital Surveillance During Ongoing COVID-19 Epidemic: A Case Study from India

被引:13
|
作者
Satpathy, Parmeshwar [1 ]
Kumar, Sanjeev [2 ]
Prasad, Pankaj [2 ]
机构
[1] Veer Surendra Sai Inst Med Sci & Res, Dept Community Med, Burla, Odisha, India
[2] All India Inst Med Sci AIIMS, Dept Community & Family Med, Bhopal, Madhya Pradesh, India
关键词
disease surveillance; infodemiology; ICT in healthcare; pandemic; time lag correlation; SEARCH TRENDS; POPULATION; TOOL;
D O I
10.1017/dmp.2021.249
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Objective: Digital surveillance has shown mixed results as a supplement to traditional surveillance. Google Trends (TM) (GT) (Google, Mountain View, CA, United States) has been used for digital surveillance of H1N1, Ebola and MERS. We used GT to correlate the information seeking on COVID-19 with number of tests and cases in India. Methods: Data was obtained on daily tests and cases from WHO, ECDC and covid19india.org. We used a comprehensive search strategy to retrieve GT data on COVID-19 related information-seeking behavior in India between January 1 and May 31, 2020 in the form of relative search volume (RSV). We also used time-lag correlation analysis to assess the temporal relationships between RSV and daily new COVID-19 cases and tests. Results: GT RSV showed high time-lag correlation with both daily reported tests and cases for the terms "COVID 19," "COVID," "social distancing," "soap," and "lockdown" at the national level. In 5 high-burden states, high correlation was observed for these 5 terms along with "Corona." Peaks in RSV, both at the national level and in high-burden states corresponded with media coverage or government declarations on the ongoing pandemic. Conclusion: The correlation observed between GT data and COVID-19 tests/cases in India may be either due to media-coverage-induced curiosity, or health-seeking curiosity.
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页数:10
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