ArticleScience translational medicine2017
Evolution-informed forecasting of seasonal influenza A (H3N2).
Article in Science translational medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed.
- Resurgence of large-scale influenza A (H1N1) outbreaks: Modeling the interplay of transmission, loss of immunity, and vaccination.Infectious Disease Modelling · 2027Article
- Unraveling the mechanism behind the probable extinction of the B/Yamagata lineage of influenza B viruses.Nature communications · 2025Article
- Article
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- Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States.eLife · 2024Article
- Electrically polarized nanoscale surfaces generate reactive oxygenated and chlorinated species for deactivation of microorganisms.Science advances · 2024Article
- Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States.medRxiv : the preprint server for health sciences · 2024Article
- Affinity and Pseudo-Affinity Membrane Chromatography for Viral Vector and Vaccine Purifications: A Review.Membranes · 2023Review
- Resolving the enigma of Iquitos and Manaus: A modeling analysis of multiple COVID-19 epidemic waves in two Amazonian cities.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Biomimetic lung-on-a-chip to model virus infection and drug evaluation.European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences · 2023Review
- Avian H7N9 influenza viruses are evolutionarily constrained by stochastic processes during replication and transmission in mammals.Virus evolution · 2023Article
- Mechanisms for the circulation of influenza A(H3N2) in China: A spatiotemporal modelling study.PLoS pathogens · 2022Article
- Spatial Variation in Humidity and the Onset of Seasonal Influenza Across the Contiguous United States.GeoHealth · 2022Article
- Modelling the impact of universal influenza vaccines on seasonal influenza with different subtypes.Epidemiology and infection · 2021Article
- Between virus correlations in the outcome of infection across host species: Evidence of virus by host species interactions.Evolution letters · 2021Article
- Optimizing respiratory virus surveillance networks using uncertainty propagation.Nature communications · 2021Article
- Human Organs-on-Chips for Virology.Trends in microbiology · 2020Review
- A two-thresholds policy for a Filippov model in combating influenza.Journal of mathematical biology · 2020Article
- Integrating mathematical models with experimental data to investigate the within-host dynamics of bacterial infections.Pathogens and disease · 2019Review
- Seasonal influenza: Modelling approaches to capture immunity propagation.PLoS computational biology · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Interpandemic or seasonal influenza A, currently subtypes H3N2 and H1N1, exacts an enormous annual burden both in terms of human health and economic impact. Incidence prediction ahead of season remains a challenge largely because of the virus' antigenic evolution. We propose a forecasting approach that incorporates evolutionary change into a mechanistic epidemiological model. The proposed models are simple enough that their parameters can be estimated from retrospective surveillance data. These models link amino acid sequences of hemagglutinin epitopes with a transmission model for seasonal H3N2 influenza, also informed by H1N1 levels. With a monthly time series of H3N2 incidence in the United States for more than 10 years, we demonstrate the feasibility of skillful prediction for total cases ahead of season, with a tendency to underpredict monthly peak epidemic size, and an accurate real-time forecast for the 2016/2017 influenza season.
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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.