ArticleEpidemics2018
Results from the second year of a collaborative effort to forecast influenza seasons in the United States.
Article in Epidemics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
66 citing papers in PubMed.
- 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
- Assessing human judgment forecasts in the rapid spread of the mpox outbreak: insights and challenges for pandemic preparedness.BMC infectious diseases · 2026Article
- Local Influenza Forecasts Outperform State-Level Forecasts in the United States.medRxiv : the preprint server for health sciences · 2026Article
- Influenza forecasting method based on dual-chan nel feature fusion of VMD decomposition.Scientific reports · 2026Article
- Ensemble forecasts of COVID-19 activity to support Australia's pandemic response: 2020-22.PLoS computational biology · 2026Article
- Improving outbreak forecasts through model augmentation.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Competition between transmission lineages mediated by human mobility shapes seasonal influenza epidemics in the US.Nature communications · 2025Article
- A prospective real-time transfer learning approach to estimate influenza hospitalizations with limited data.Epidemics · 2025Article
- What can we learn from 100,000 freshwater forecasts? A synthesis from the NEON Ecological Forecasting Challenge.Ecological applications : a publication of the Ecological Society of America · 2025Article
- Internet-based surveillance to track trends in seasonal allergies across the United States.PNAS nexus · 2024Article
- Integrating information from historical data into mechanistic models for influenza forecasting.PLoS computational biology · 2024Article
- Commuting-driven competition between transmission chains shapes seasonal influenza virus epidemics in the United States.medRxiv : the preprint server for health sciences · 2024Article
- Challenges of COVID-19 Case Forecasting in the US, 2020-2021.PLoS computational biology · 2024Article
- Multi-Model Prediction of West Nile Virus Neuroinvasive Disease With Machine Learning for Identification of Important Regional Climatic Drivers.GeoHealth · 2023Article
- Neural network models for influenza forecasting with associated uncertainty using Web search activity trends.PLoS computational biology · 2023Article
- Challenges in Forecasting Antimicrobial Resistance.Emerging infectious diseases · 2023Review
- Real-time forecasting the trajectory of monkeypox outbreaks at the national and global levels, July-October 2022.BMC medicine · 2023Article
- Retrospective evaluation of real-time estimates of global COVID-19 transmission trends and mortality forecasts.PloS one · 2023Article
- Fast and accurate influenza forecasting in the United States with Inferno.PLoS computational biology · 2022Article
- Adaptively stacking ensembles for influenza forecasting.Statistics in medicine · 2021Article
6 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
Accurate forecasts could enable more informed public health decisions. Since 2013, CDC has worked with external researchers to improve influenza forecasts by coordinating seasonal challenges for the United States and the 10 Health and Human Service Regions. Forecasted targets for the 2014-15 challenge were the onset week, peak week, and peak intensity of the season and the weekly percent of outpatient visits due to influenza-like illness (ILI) 1-4 weeks in advance. We used a logarithmic scoring rule to score the weekly forecasts, averaged the scores over an evaluation period, and then exponentiated the resulting logarithmic score. Poor forecasts had a score near 0, and perfect forecasts a score of 1. Five teams submitted forecasts from seven different models. At the national level, the team scores for onset week ranged from <0.01 to 0.41, peak week ranged from 0.08 to 0.49, and peak intensity ranged from <0.01 to 0.17. The scores for predictions of ILI 1-4 weeks in advance ranged from 0.02-0.38 and was highest 1 week ahead. Forecast skill varied by HHS region. Forecasts can predict epidemic characteristics that inform public health actions. CDC, state and local health officials, and researchers are working together to improve forecasts.
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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.