ArticleScientific reports2019
Accurate regional influenza epidemics tracking using Internet search data.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- The era of "Infectious Diseases+" has arrived: multi-disciplinary integration in pediatric infectious disease prevention and control.Frontiers in pediatrics · 2026Review
- FaXNet: a frequency-adaptive, explainable, and uncertainty-aware network for influenza forecasting.Frontiers in public health · 2026Article
- Incorporating connectivity among Internet search data for enhanced influenza-like illness tracking.PloS one · 2024Article
- Neural network models for influenza forecasting with associated uncertainty using Web search activity trends.PLoS computational biology · 2023Article
- Forecasting virus outbreaks with social media data via neural ordinary differential equations.Scientific reports · 2023Article
- Joint COVID-19 and influenza-like illness forecasts in the United States using internet search information.Communications medicine · 2023Article
- Detecting Elevated Air Pollution Levels by Monitoring Web Search Queries: Algorithm Development and Validation.JMIR formative research · 2022Article
- Chimeric forecasting: combining probabilistic predictions from computational models and human judgment.BMC infectious diseases · 2022Article
- COVID-19 forecasts using Internet search information in the United States.Scientific reports · 2022Article
- COVID-19 hospitalizations forecasts using internet search data.Scientific reports · 2022Article
- The peopleParasitology · 2021Article
- Use Internet search data to accurately track state level influenza epidemics.Scientific reports · 2021Article
- Predicting regional influenza epidemics with uncertainty estimation using commuting data in Japan.PloS one · 2021Article
- Tracking and predicting U.S. influenza activity with a real-time surveillance network.PLoS computational biology · 2020Article
- Surveillance of early stage COVID-19 clusters using search query logs and mobile device-based location information.Scientific reports · 2020Article
- Sepsis information-seeking behaviors via Wikipedia between 2015 and 2018: A mixed methods retrospective observational study.PloS one · 2019Observational
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate, high-resolution tracking of influenza epidemics at the regional level helps public health agencies make informed and proactive decisions, especially in the face of outbreaks. Internet users' online searches offer great potential for the regional tracking of influenza. However, due to the complex data structure and reduced quality of Internet data at the regional level, few established methods provide satisfactory performance. In this article, we propose a novel method named ARGO2 (2-step Augmented Regression with GOogle data) that efficiently combines publicly available Google search data at different resolutions (national and regional) with traditional influenza surveillance data from the Centers for Disease Control and Prevention (CDC) for accurate, real-time regional tracking of influenza. ARGO2 gives very competitive performance across all US regions compared with available Internet-data-based regional influenza tracking methods, and it has achieved 30% error reduction over the best alternative method that we numerically tested for the period of March 2009 to March 2018. ARGO2 is reliable and robust, with the flexibility to incorporate additional information from other sources and resolutions, making it a powerful tool for regional influenza tracking, and potentially for tracking other social, economic, or public health events at the regional or local level.
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