ArticleHealthcare informatics research2020
Prediction of COVID-19 Outbreaks Using Google Trends in India: A Retrospective Analysis.
Article in Healthcare informatics research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Evaluating the Mainstream Influence of Cardiothoracic Surgical Research: An Analysis of Google Trends Data from 2004 to 2024.Brazilian journal of cardiovascular surgery · 2026Article
- Comparison of Artificial Intelligence Tools With Human Coding for Sentiment, Topic, and Thematic Analysis Tasks of Public Health Datasets During the COVID-19 Pandemic in Australia: Case Study.Online journal of public health informatics · 2026Article
- A novel model for accurate and fast prediction of cancer incidence.BMC public health · 2025Article
- Search traffic for inflatable penile prosthesis increased following the COVID-19 pandemic in the United States: a Google Trends analysis.International journal of impotence research · 2025Article
- Article
- Deep recurrent models for forecasting infectious diseases.Frontiers in public health · 2025Article
- Use of Digital Tools in Arbovirus Surveillance: Scoping Review.Journal of medical Internet research · 2024Article
- Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review.JMIR public health and surveillance · 2024Article
- The evolution of the COVID-19 pandemic through the lens of google searches.Scientific reports · 2023Article
- The lead time and geographical variations of Baidu Search Index in the early warning of COVID-19.Scientific reports · 2023Article
- A Psychometric Analysis of Fear of COVID-19 Scale in India.International journal of mental health and addiction · 2023Article
- Web-based surveillance of respiratory infection outbreaks: retrospective analysis of Italian COVID-19 epidemic waves using Google Trends.Frontiers in public health · 2023Article
- Detecting early signals of COVID-19 outbreaks in 2020 in small areas by monitoring healthcare utilisation databases: first lessons learned from the Italian Alert_CoV project.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2023Article
- The Relationship between Searches for COVID-19 Vaccines and Dynamics of Vaccinated People in Poland: An Infodemiological Study.International journal of environmental research and public health · 2022Article
- Forecasting and Surveillance of COVID-19 Spread Using Google Trends: Literature Review.International journal of environmental research and public health · 2022Review
- COVID-19 Infodemiology: Association Between Google Search and Vaccination in Malaysian Population.Cureus · 2022Article
- Geographic social inequalities in information-seeking response to the COVID-19 pandemic in China: longitudinal analysis of Baidu Index.Scientific reports · 2022Article
- COVID-19 forecasts using Internet search information in the United States.Scientific reports · 2022Article
- Enhancing COVID-19 Epidemic Forecasting Accuracy by Combining Real-time and Historical Data From Multiple Internet-Based Sources: Analysis of Social Media Data, Online News Articles, and Search Queries.JMIR public health and surveillance · 2022Article
- Utilizing Big Data From Google Trends to Map Population Depression in the United States: Exploratory Infodemiology Study.JMIR mental health · 2022Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveConsidering the rising menace of coronavirus disease 2019 (COVID-19), it is essential to explore the methods and resources that might predict the case numbers expected and identify the locations of outbreaks. Hence, we have done the following study to explore the potential use of Google Trends (GT) in predicting the COVID-19 outbreak in India.
methodsThe Google search terms used for the analysis were "coronavirus", "COVID", "COVID 19", "corona", and "virus". GTs for these terms in Google Web, News, and YouTube, and the data on COVID-19 case numbers were obtained. Spearman correlation and lag correlation were used to determine the correlation between COVID-19 cases and the Google search terms.
results"Coronavirus" and "corona" were the terms most commonly used by Internet surfers in India. Correlation for the GTs of the search terms "coronavirus" and "corona" was high (r > 0.7) with the daily cumulative and new COVID-19 cases for a lag period ranging from 9 to 21 days. The maximum lag period for predicting COVID-19 cases was found to be with the News search for the term "coronavirus", with 21 days, i.e., the search volume for "coronavirus" peaked 21 days before the peak number of cases reported by the disease surveillance system.
conclusionOur study revealed that GTs may predict outbreaks of COVID-19, 2 to 3 weeks earlier than the routine disease surveillance, in India. Google search data may be considered as a supplementary tool in COVID-19 monitoring and planning in India.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.