ArticleBMC public health2019
Applying infectious disease forecasting to public health: a path forward using influenza forecasting examples.
Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers.
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Who cites it
80 citing papers in PubMed.
- "Sometimes I'm interested in seeing a fuller story to tell with numbers" Implementing a forecasting dashboard for harm reduction and overdose prevention: a qualitative assessment.BMC public health · 2025Trial
- Borrowing Data From Other Populations to Forecast Epidemic Size.Ecology and evolution · 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
- A Software Platform for Collaborative Infectious Disease Modeling.Nature health · 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
- Machine learning and probabilistic approaches for forecasting infectious disease transmission and cases.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2026Article
- Networked SIRS model with Kalman filter state estimation for epidemic monitoring in Europe.Communications medicine · 2026Article
- Forecastability of infectious disease time series: are some seasons and pathogens intrinsically more difficult to forecast?PLoS computational biology · 2026Article
- Basic Baseline model design choices can substantially influence performance in collaborative forecast hubs.medRxiv : the preprint server for health sciences · 2026Article
- Survey on mathematical modeling of infectious disease dynamics: insights and applications.BMC infectious diseases · 2026Review
- An Open-Source Data Driven Hybrid Modeling System for Infectious Disease Surveillance and Early Warning.China CDC weekly · 2026Article
- A hybrid model for influenza forecasting in Xinjiang: adapting to complex seasonality and post-COVID-19 structural breaks.BMC public health · 2026Article
- The evolution of public health statistical modeling approaches and how to advance their incorporation into modern arboviral surveillance.Journal of medical entomology · 2026Article
- Weighted ensemble learning outperforms statistical, machine-learning, and deep-learning models for varicella forecasting: a 12-model benchmarking study using 11-year surveillance data from Nanjing, China.Frontiers in public health · 2026Article
- PrepCare: a two-stage framework for infectious disease prioritization and alerts for nursing preparedness.Frontiers in public health · 2026Article
- Improving outbreak forecasts through model augmentation.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Coordinating collaborative infectious disease modeling projects with the hubverse.medRxiv : the preprint server for health sciences · 2025Article
- When data disappear: public health pays as US policy strays.The Lancet. Digital health · 2025Review
20 more citing papers are in PubMed but not listed here.
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18 authors.
Funding
Abstract
backgroundInfectious disease forecasting aims to predict characteristics of both seasonal epidemics and future pandemics. Accurate and timely infectious disease forecasts could aid public health responses by informing key preparation and mitigation efforts. MAIN BODY: For forecasts to be fully integrated into public health decision-making, federal, state, and local officials must understand how forecasts were made, how to interpret forecasts, and how well the forecasts have performed in the past. Since the 2013-14 influenza season, the Influenza Division at the Centers for Disease Control and Prevention (CDC) has hosted collaborative challenges to forecast the timing, intensity, and short-term trajectory of influenza-like illness in the United States. Additional efforts to advance forecasting science have included influenza initiatives focused on state-level and hospitalization forecasts, as well as other infectious diseases. Using CDC influenza forecasting challenges as an example, this paper provides an overview of infectious disease forecasting; applications of forecasting to public health; and current work to develop best practices for forecast methodology, applications, and communication.
conclusionsThese efforts, along with other infectious disease forecasting initiatives, can foster the continued advancement of forecasting science.
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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.