Previously submitted to: JMIR Public Health and Surveillance (no longer under consideration since Dec 31, 2020)
Date Submitted: Nov 23, 2020
Open Peer Review Period: Nov 23, 2020 - Dec 7, 2020
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Suitability of Google Trends™ for digital surveillance during ongoing COVID-19 epidemic: a case study from India
ABSTRACT
Background:
Digital surveillance has shown mixed results as supplement to the traditional surveillance. Google Trends™ (GT) is a digital platform explored for surveillance during pandemics of H1N1, Ebola and MERS. Similar efforts have been reported for the ongoing COVID-19 pandemic too.
Objective:
We used GT to correlate the information seeking on COVID-19 with number of tests and cases reported both at national and state levels.
Methods:
We obtained data on daily tests and cases from WHO, ECDC and covid19india.org websites. We retrieved GT data between 1st January 2020 to 31st May 2020 for India using a comprehensive search strategy in the form of relative search volume (RSV). We used time-lag correlation analysis to assess the temporal relationships between RSV and daily new COVID-19 cases and daily tests.
Results:
High time-lag correlation was observed between both the daily reported number of tests and cases and RSV for the terms “COVID 19”, “COVID”, “social distancing”, “soap” and “lockdown” at national level. Similar high time-lag correlation was observed for the terms “COVID 19”, “COVID”, “Corona”, “social distancing”, “soap”, “lockdown” in five high-burden states. Peaks in RSV both at national level and high-burden states corresponded with media coverage or government declarations on the ongoing pandemic.
Conclusions:
The results of this study show that Google Trends™ data are highly correlated with COVID-19 tests and cases in India. This correlation may be because of search behaviour induced either by media-coverage of the pandemic or health-seeking for COVID-19 illness. We argue that GT can supplement the traditional surveillance system, more easily and at a lower cost.
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