ArticleProceedings of the National Academy of Sciences of the United States of America2018
Forecasting the spatial transmission of influenza in the United States.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 108 papers, 1 of them a synthesis that pooled it.
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Who cites it
108 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review of spatial epidemiological modeling approaches applied during the COVID-19 pandemic.BMC public health · 2026Pooled it
- Multisource Early Warning Framework Integrating Regional Pathogen Surveillance and Baidu Index Data for Respiratory Infectious Disease Prediction in Beijing: Retrospective Time-Series Modeling Study.JMIR formative research · 2026Article
- Improving Malaria Parasite Gene Flow Inference Under Sparse Spatial Sampling.Molecular ecology resources · 2026Article
- Learning shared forecast-error structure to improve ensemble forecasts of seasonal respiratory outbreaks.medRxiv : the preprint server for health sciences · 2026Article
- Absolute humidity drives seasonal influenza A transmission in Hong Kong through social contact modulation: Evidence from compartmental modeling.Infectious Disease Modelling · 2026Article
- Networked SIRS model with Kalman filter state estimation for epidemic monitoring in Europe.Communications medicine · 2026Article
- Rural-to-urban migrant worker mobility shaped measles epidemics in China.PLoS computational biology · 2026Article
- Reconstructing the early spatial spread of pandemic respiratory viruses in the United States.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- FaXNet: a frequency-adaptive, explainable, and uncertainty-aware network for influenza forecasting.Frontiers in public health · 2026Article
- Data assimilation for estimating time-varying reproduction numbers.Journal of the Royal Society, Interface · 2025Article
- Reconstructing the early spatial spread of pandemic respiratory viruses in the United States.medRxiv : the preprint server for health sciences · 2025Article
- The tale of two assumptions: incorporating healthcare-seeking behaviour in epidemic forecasting.BMC infectious diseases · 2025Article
- Inferring pathogen superspreading potential using early spatial spread patterns.medRxiv : the preprint server for health sciences · 2025Article
- Transmission components of hand, foot, and mouth disease in Guangdong Province and their association with meteorological factors: a modelling study.BMC infectious diseases · 2025Article
- A Systematic Review of Spatial Epidemiological Modeling Approaches Applied During the COVID-19 Pandemic.medRxiv : the preprint server for health sciences · 2025Article
- Competition between transmission lineages mediated by human mobility shapes seasonal influenza epidemics in the US.Nature communications · 2025Article
- Behavior-driven forecasts of neighborhood-level COVID-19 spread in New York City.PLoS computational biology · 2025Article
- Joint estimation of hand-foot-mouth disease model and prediction in korea using the ensemble kalman filter.PLoS computational biology · 2025Article
- Increased Risk of Influenza-Like Illness Clusters in Schools, Taiwan from 2011 to 2020: A Retrospective Study.Journal of epidemiology and global health · 2025Article
- Leveraging dynamics informed neural networks for predictive modeling of COVID-19 spread: a hybrid SEIRV-DNNs approach.Scientific reports · 2025Article
48 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Recurrent outbreaks of seasonal and pandemic influenza create a need for forecasts of the geographic spread of this pathogen. Although it is well established that the spatial progression of infection is largely attributable to human mobility, difficulty obtaining real-time information on human movement has limited its incorporation into existing infectious disease forecasting techniques. In this study, we develop and validate an ensemble forecast system for predicting the spatiotemporal spread of influenza that uses readily accessible human mobility data and a metapopulation model. In retrospective state-level forecasts for 35 US states, the system accurately predicts local influenza outbreak onset,-i.e., spatial spread, defined as the week that local incidence increases above a baseline threshold-up to 6 wk in advance of this event. In addition, the metapopulation prediction system forecasts influenza outbreak onset, peak timing, and peak intensity more accurately than isolated location-specific forecasts. The proposed framework could be applied to emergent respiratory viruses and, with appropriate modifications, other infectious diseases.
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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.