ArticleEpidemiology and infection2018
Prediction of Zika-confirmed cases in Brazil and Colombia using Google Trends.
Article in Epidemiology and infection, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
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Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 45 citations in OpenAlex.
- Temporal and Spatiotemporal Arboviruses Forecasting by Machine Learning: A Systematic Review.Frontiers in public health · 2022Pooled it
- The Application of Internet-Based Sources for Public Health Surveillance (Infoveillance): Systematic Review.Journal of medical Internet research · 2020Pooled it
- Challenges and Opportunities in One Health: Google Trends Search Data.Pathogens (Basel, Switzerland) · 2023Article
- What does Google Trends reveal about the proportion of waterpipe users in the Brazilian population?Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil · 2023Article
- Interest in dentistry in early months of the COVID-19 global pandemic: A Google Trends approach.Health information and libraries journal · 2022Article
- Article
- Scoping future outbreaks: a scoping review on the outbreak prediction of the WHO Blueprint list of priority diseases.BMJ global health · 2021Article
- The Causality Inference of Public Interest in Restaurants and Bars on Daily COVID-19 Cases in the United States: Google Trends Analysis.JMIR public health and surveillance · 2021Article
- Google Trends correlation and sensitivity for outbreaks of dengue and yellow fever in the state of São Paulo.Einstein (Sao Paulo, Brazil) · 2021Article
- Rapid Decline in Online Search Queries for Hip and Knee Arthroplasties Concurrent With the COVID-19 Pandemic.The Journal of arthroplasty · 2020Article
- Investigating the utility of Google trends for Zika and Chikungunya surveillance in Venezuela.BMC public health · 2020Article
- Analysis of the Filipinos' Interest in Searching Online for Oral Cancer.Asian Pacific journal of cancer prevention : APJCP · 2020Article
- The impact of monthly campaigns and other high-profile media coverage on public interest in 13 malignancies: a Google Trends analysis.Ecancermedicalscience · 2020Article
- Tracking U.S. Pertussis Incidence: Correlation of Public Health Surveillance and Google Search Data Varies by State.Scientific reports · 2019Article
- A dynamic neural network model for predicting risk of Zika in real time.BMC medicine · 2019Article
- Avian Influenza A (H7N9) and related Internet search query data in China.Scientific reports · 2019Article
- Google Trends Predicts Present and Future Plague Cases During the Plague Outbreak in Madagascar: Infodemiological Study.JMIR public health and surveillance · 2019Article
- The impact of cancer campaigns in Brazil: a Google Trends analysis.Ecancermedicalscience · 2019Article
Corrections and comments
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Authors and funding
8 authors at 6 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Zika virus infection in humans has been linked to severe neurological sequels and foetal malformations. The rapidly evolving epidemics and serious complications made the frequent updates of Zika virus mandatory. Web search query has emerged as a low-cost real-time surveillance system to anticipate infectious diseases' outbreaks. Hence, we developed a prediction model that could predict Zika-confirmed cases based on Zika search volume in Google Trends. We extracted weekly confirmed Zika cases of two epidemic countries, Brazil and Colombia. We got the weekly Zika search volume in the two countries from Google Trends. We used standard time-series regression (TSR) to predict the weekly confirmed Zika cases based on the Zika search volume (Zika query). The basis TSR model - using 1-week lag of Zika query and using 1-week lag of Zika cases as a control for autocorrelation - was the best for predicting Zika cases in Brazil and Colombia because it balanced the performance of the model and the advance time in the prediction. Our results showed that we could use Google search queries to predict Zika cases 1 week earlier before the outbreak. These findings are important to help healthcare authorities evaluate the outbreak and take necessary precautions.
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Registered trials
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.