Interpreting Google flu trends data for pandemic H1N1 influenza: the New Zealand experience.

For the period of the spread of pandemic H1N1 influenza in New Zealand during 2009, we compared results from Google Flu Trends with data from existing surveillance systems. The patterns from Google Flu Trends were closely aligned with (peaking a week before and a week after) two independent national surveillance systems for influenza-like illness (ILI) cases. It was much less congruent with (delayed by three weeks) data from ILI-related calls to a national free-phone Healthline and with media coverage of pandemic influenza. Some patterns were unique to Google Flu Trends and may not have reflected the actual ILI burden in the community. Overall, Google Flu Trends appears to provide a useful free surveillance system but it should probably be seen as supplementary rather than as an alternative.

• Publication year

  2009

• Venue

  Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin

• Publication date

  2009-11-05

• Fields of study

  Medicine, Environmental Science

• Identifiers
  DOI 10.2807/ESE.14.44.19386-ENPMID 19941777
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• No references are available for this paper.

• Use of unconventional data to monitor behaviors associated with influenza and dengue infections: a systematic review

  2026cites this paper
• Developing predictive models for COVID-19 positive tests based on the XGBoost and random forest algorithms with internet search data

  2025cites this paper
• A Framework for Evaluating the Use of Surveillance Systems for Short‐Term Influenza Forecasting

  2025cites this paper
• Epidemic surveillance systems and containment strategies in complex networks

  2025cites this paper
• The Internet search engines as an additional tool in public health research in the context of disease outbreaks

  2022cites this paper
• Assessing the Predictive Power of Online Social Media to Analyze COVID-19 Outbreaks in the 50 U.S. States

  2021cites this paper
• Big Data in Academic Research: Challenges, Pitfalls, and Opportunities

  2021cites this paper
• Wang. Relationship between Google Trend and Daily Trend of New COVID-19 cases in the United States

  2021influential citation
• Can technological advancements help to alleviate COVID-19 pandemic? a review

  2021cites this paper
• Trends and Prediction in Daily New Cases and Deaths of COVID-19 in the United States: An Internet Search-Interest Based Model

  2020cites this paper
• CovidSens: A Vision on Reliable Social Sensing based Risk Alerting Systems for COVID-19 Spread

  2020cites this paper
• Retrospective analysis of the possibility of predicting the COVID-19 outbreak from Internet searches and social media data, China, 2020

  2020cites this paper
• Measuring objective and subjective well-being: dimensions and data sources

  2020cites this paper
• More Active Internet-Search on Google and Twitter Posting for COVID-19 Corresponds with Lower Infection Rate in the 50 U.S. States

  2020cites this paper
• CovidSens: a vision on reliable social sensing for COVID-19

  2020cites this paper
• Correlations of Online Search Engine Trends With Coronavirus Disease (COVID-19) Incidence: Infodemiology Study

  2020cites this paper
• Trends and prediction in daily incidence and deaths of COVID-19 in the United States: a search-interest based model

  2020cites this paper
• Social Media- and Internet-Based Disease Surveillance for Public Health.

  2020cites this paper
• Hey Google! will New Zealand vote to legalise cannabis? Using Google Trends data to predict the outcome of the 2020 New Zealand cannabis referendum.

  2020cites this paper
• Retrospective analysis of the accuracy of predicting the alert level of COVID-19 in 202 countries using Google Trends and machine learning

  2020cites this paper
• Prediction of COVID-19 Outbreaks Using Google Trends in India: A Retrospective Analysis

  2020cites this paper
• Measuring objective and subjective well-being: dimensions and data sources

  2020cites this paper
• Using Google Trends Data to Study Public Interest in Breast Cancer Screening in Malaysia

  2019cites this paper
• Machine-learned epidemiology: real-time detection of foodborne illness at scale

  2018cites this paper
• Accurate quantification of uncertainty in epidemic parameter estimates and predictions using stochastic compartmental models

  2018cites this paper
• Epidemiological and statistical basis for detection and prediction of influenza epidemics

  2017cites this paper
• Big data : a compressed sensing approach

  2017cites this paper
• Utility and potential of rapid epidemic intelligence from internet-based sources.

  2017cites this paper
• Disease Surveillance on Complex Social Networks

  2016cites this paper
• A look back: investigating Google Flu Trends during the influenza A(H1N1)pdm09 pandemic in Canada, 2009–2010

  2016cites this paper
• Tracking Outbreaks of Febrile Infectious Diseases in India Using Google Trends

  2016cites this paper
• Google Flu Trends in Canada: a comparison of digital disease surveillance data with physician consultations and respiratory virus surveillance data, 2010–2014

  2015cites this paper
• Research of the Correlation between the H1N1 Morbidity Data and Google Trends in Egypt

  2015cites this paper
• Assessing Google Correlate Queries for Influenza H1N1 Surveillance in Asian Developing Countries

  2015cites this paper
• Google Trends (GT) related to influenza.

  2015cites this paper
• Quantifying the determinants of outbreak detection performance through simulation and machine learning

  2015cites this paper
• Google Trends: Ready for real-time suicide prevention or just a Zeta-Jones effect? An exploratory study.

  2015cites this paper
• Spatial and temporal epidemiological analysis in the Big Data era

  2015cites this paper
• [Using Google Trends to estimate the incidence of influenza-like illness in Argentina].

  2015cites this paper
• Sources of spatial animal and human health data: Casting the net wide to deal more effectively with increasingly complex disease problems

  2015cites this paper
• Online Information Search, Market Fundamentals and Apartment Real Estate

  2015cites this paper
• Big Data y salud. Potencial para salvar vidas y cuidar personas

  2015cites this paper
• Uso de la herramienta Google Trends para estimar la incidencia de enfermedades tipo influenza en Argentina

  2015cites this paper
• Google Trends (GT) related to influenza Google Trends relacionado à influenza Google Trends relacionado a la influenza

  2015cites this paper
• The Relationship between Indian Realty Stocks and Online Searches

  2015cites this paper
• Triggering Interventions for In fl uenza: The ALERT Algorithm

  2015cites this paper
• Web GIS-Based Public Health Surveillance Systems: A Systematic Review

  2014cites this paper
• Nowcasting Obesity in the U.S. Using Google Search Volume Data

  2014cites this paper
• HOME ABOUT LOG IN REGISTER SEARCH UPCOMING CURRENT ARCHIVES ANNOUNCEMENTS SUBSCRIBE SUBMIT OPEN REVIEW BECOME MEMBER TOP ARTICLES JMIR PROTOCOLS JMIR MHEALTH JMIR SERIOUS GAMES JMIR MEDINFORM I-JMR MED2 PROC JOBS

  2014cites this paper
• Performance of eHealth Data Sources in Local Influenza Surveillance: A 5-Year Open Cohort Study

  2014cites this paper
• Datafication, dataism and dataveillance: Big Data between scientific paradigm and ideology

  2014cites this paper
• Using Google Flu Trends data in forecasting influenza-like-illness related ED visits in Omaha, Nebraska.

  2014cites this paper
• Cumulative Query Method for Influenza Surveillance Using Search Engine Data

  2014cites this paper
• Medical Cost Estimation Using Hardware-Accelerated Neural Networks

  2014cites this paper
• Emergency department and ‘Google flu trends’ data as syndromic surveillance indicators for seasonal influenza

  2014cites this paper
• Surveillance for emerging respiratory viruses

  2014cites this paper
• Managing uncertainty in early estimation of epidemic behaviors using scenario trees

  2014cites this paper
• Use of large web-based data to identify public interest and trends related to endangered species

  2014cites this paper
• Triggering Interventions for Influenza: The ALERT Algorithm

  2014cites this paper
• Exploring the potentials of volunteered geographic Information as a source for spatial data acquisition

  2014cites this paper
• Machine Learning for Disease Outbreak Detection Using Probabilistic Models

  2014cites this paper
• Bariatric surgery interest around the world: what Google Trends can teach us.

  2014cites this paper
• Internet-based surveillance systems for monitoring emerging infectious diseases

  2013cites this paper
• Infodemiology to improve public health situational awareness: An investigation of 2010 pertussis outbreaks in California, Michigan and Ohio

  2013cites this paper
• Reassessing Google Flu Trends Data for Detection of Seasonal and Pandemic Influenza: A Comparative Epidemiological Study at Three Geographic Scales

  2013cites this paper
• Correlation between National Influenza Surveillance Data and Google Trends in South Korea

  2013cites this paper
• Comparison of five influenza surveillance systems during the 2009 pandemic and their association with media attention

  2013cites this paper
• Using Google Trends for Influenza Surveillance in South China

  2013cites this paper
• The 2009 influenza pandemic: a review of the strengths and weaknesses of the health sector response in New Zealand.

  2012cites this paper
• Early detection of influenza like illness through medication sales.

  2012cites this paper
• Optimizing Provider Recruitment for Influenza Surveillance Networks

  2012cites this paper
• GET WELL: an automated surveillance system for gaining new epidemiological knowledge

  2011cites this paper
• “Google Flu Trends” and Emergency Department Triage Data Predicted the 2009 Pandemic H1N1 Waves in Manitoba

  2011cites this paper
• Assessing Google Flu Trends Performance in the United States during the 2009 Influenza Virus A (H1N1) Pandemic

  2011cites this paper
• Schleudertrauma und Werther-Effekt – das Potenzial von Google Insights for Search für die medizinische Forschung und öffentliche Gesundheit

  2011cites this paper
• [Influenza A, pregnancy and neuraminidase inhibitors].

  2011cites this paper
• Correlation of ”Google Flu Trends“ with Sentinel Surveillance Data forInfluenza in 2009 in Japan

  2011cites this paper
• Monitoring Influenza Activity in the United States: A Comparison of Traditional Surveillance Systems with Google Flu Trends

  2011influential citation
• Social Media: A Systematic Review to Understand the Evidence and Application in Infodemiology

  2011cites this paper
• H1N1 2009 influenza vaccine prevention: a comparison between the Italian press and the scientific recommendations

  2011cites this paper
• Online monitoring of flu in Belgium

  2011cites this paper
• Prediction and surveillance of influenza epidemics

  2011cites this paper
• Flu Trends ” and Emergency Department Triage Data Predicted the 2009 Pandemic H 1 N 1 Waves in Manitoba

  2011cites this paper
• Monitoring influenza activity in Europe with Google Flu Trends: comparison with the findings of sentinel physician networks - results for 2009-10.

  2010cites this paper
• Pandemics in the Age of Twitter: A Content Analysis of the 2009 H1N1 Outbreak

  2010cites this paper
• Update: follow-up study showing post-pandemic decline in hand sanitiser use, New Zealand, December 2009.

  2010cites this paper
• Eye-Opening Approach to Norovirus Surveillance

  2010cites this paper