ArticleDisaster medicine and public health preparedness2021
Suitability of Google Trends™ for Digital Surveillance During Ongoing COVID-19 Epidemic: A Case Study from India.
Article in Disaster medicine and public health preparedness, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Using Google Trends to Predict Dengue Outbreaks in Pakistan: A Time-Series and Causality Analysis.EJIFCC · 2026Article
- A COVID-19 prediction Model based on symptomatology google trends and its optimization.BMC infectious diseases · 2026Article
- Between resistance and adaptation in COVID-19 times: The outbreak daily prevalence moderates the association between conspiracy thinking and adherence to government protocols.British journal of health psychology · 2026Article
- Deep recurrent models for forecasting infectious diseases.Frontiers in public health · 2025Article
- Artificial intelligence-based prediction of pathogen emergence and evolution in the world of synthetic biology.Microbial biotechnology · 2024Review
- The Interest in Betting, Smoking, Alcohol, and Drugs in Malawi: Changing Trends between 2012-2022.Malawi medical journal : the journal of Medical Association of Malawi · 2024Article
- The evolution of the COVID-19 pandemic through the lens of google searches.Scientific reports · 2023Article
- Pandemic and precocious puberty - a Google trends study.World journal of methodology · 2023Article
- Mining Google Trends data for nowcasting and forecasting colorectal cancer (CRC) prevalence.PeerJ. Computer science · 2023Article
- Googling Insomnia, Light, Metabolism, and Circadian: A Population Interest Simple Report.Brain sciences · 2022Article
- Forecasting and Surveillance of COVID-19 Spread Using Google Trends: Literature Review.International journal of environmental research and public health · 2022Review
- COVID-19 and thyroid disease: An infodemiological pilot study.World journal of methodology · 2022Article
- Modeling COVID-19 incidence with Google Trends.Frontiers in research metrics and analytics · 2022Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
objectiveDigital surveillance has shown mixed results as a supplement to traditional surveillance. Google Trends™ (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.
methodsData 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.
resultsGT 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.
conclusionThe 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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