ArticleProceedings of the National Academy of Sciences of the United States of America2019
A collaborative multiyear, multimodel assessment of seasonal influenza forecasting in the United States.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 155 papers, 1 of them a synthesis that pooled it.
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Who cites it
155 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Identification and evaluation of epidemic prediction and forecasting reporting guidelines: A systematic review and a call for action.Epidemics · 2020Pooled it
- Fine-tuned large language models enhance influenza forecasting.Cell reports methods · 2026Article
- A real-time forecasting framework for emerging infectious diseases affecting animal populations.PLoS computational biology · 2026Article
- Evaluation of respiratory disease hospitalisation forecasts using synthetic outbreak data.Communications medicine · 2026Article
- Learning shared forecast-error structure to improve ensemble forecasts of seasonal respiratory outbreaks.medRxiv : the preprint server for health sciences · 2026Article
- Multi-source machine learning for short-term influenza forecasting in Hunan Province, China: a spatiotemporal analysis using surveillance, search, meteorological and air-quality data.BMC infectious diseases · 2026Article
- Adaptive multi-model ensembles for improved epidemic projections and decision support.medRxiv : the preprint server for health sciences · 2026Article
- Predictive Modeling of Enterovirus Hospital Burden Using Machine Learning and Age-Specific Surveillance Data: Operational Forecasting in Taiwan During the Postpandemic Era.JMIR formative research · 2026Article
- In silico models in oncology, neurology, and epidemiology: systems-level and multiscale perspectives.NPJ systems biology and applications · 2026Review
- EpiGIS pro: an AI-powered geospatial intelligence platform for integrated disease surveillance and predictive analytics.International journal of health geographics · 2026Article
- A Software Platform for Collaborative Infectious Disease Modeling.Nature health · 2026Article
- Local Influenza Forecasts Outperform State-Level Forecasts in the United States.medRxiv : the preprint server for health sciences · 2026Article
- A real-time early warning system to anticipate respiratory disease outbreaks using transfer learning.Nature communications · 2026Article
- Ensemble forecasts of COVID-19 activity to support Australia's pandemic response: 2020-22.PLoS computational biology · 2026Article
- A disease-agnostic approach to ensemble learning for infectious disease forecasting.Nature communications · 2026Article
- Basic Baseline model design choices can substantially influence performance in collaborative forecast hubs.medRxiv : the preprint server for health sciences · 2026Article
- AI Agents and Epidemic Intelligence on Respiratory Infectious Diseases: Toward a Conceptual Framework Integrating Decision Support.Journal of medical Internet research · 2026Article
- An Open-Source Data Driven Hybrid Modeling System for Infectious Disease Surveillance and Early Warning.China CDC weekly · 2026Article
- Leveraging probabilistic forecasts for dengue preparedness and control: The 2024 Dengue Forecasting Sprint in Brazil.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Integrating Surveillance and Stakeholder Insights to Predict Influenza Epidemics: A Bayesian Network Study in Queensland, Australia.International journal of environmental research and public health · 2026Article
95 more citing papers are in PubMed but not listed here.
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Authors and funding
14 authors.
Funding
Abstract
Influenza infects an estimated 9-35 million individuals each year in the United States and is a contributing cause for between 12,000 and 56,000 deaths annually. Seasonal outbreaks of influenza are common in temperate regions of the world, with highest incidence typically occurring in colder and drier months of the year. Real-time forecasts of influenza transmission can inform public health response to outbreaks. We present the results of a multiinstitution collaborative effort to standardize the collection and evaluation of forecasting models for influenza in the United States for the 2010/2011 through 2016/2017 influenza seasons. For these seven seasons, we assembled weekly real-time forecasts of seven targets of public health interest from 22 different models. We compared forecast accuracy of each model relative to a historical baseline seasonal average. Across all regions of the United States, over half of the models showed consistently better performance than the historical baseline when forecasting incidence of influenza-like illness 1 wk, 2 wk, and 3 wk ahead of available data and when forecasting the timing and magnitude of the seasonal peak. In some regions, delays in data reporting were strongly and negatively associated with forecast accuracy. More timely reporting and an improved overall accessibility to novel and traditional data sources are needed to improve forecasting accuracy and its integration with real-time public health decision making.
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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.