ArticleInfectious Disease Modelling2025
Predicting influenza in China from October 1, 2023, to February 5, 2024: A transmission dynamics model based on population migration.
Article in Infectious Disease Modelling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evolutionary trajectory and co-infection dynamics of human influenza A(H1N1) virus (2000-2025): an integrated framework informed by expert-informed bibliometrics.Frontiers in microbiology · 2026Pooled it
- A Human Mobility-Based Modeling Study of Influenza Vaccination Strategies Across Socioeconomically Disparate Regions in China.Vaccines · 2026Article
- A hybrid ensemble approach: fusing ANFIS, LSTM, and LSSVM with PSO for enhanced influenza a forecasting.BMC infectious diseases · 2026Article
- Epidemiological characteristics of imported influenza viruses at Shanghai entry-exit ports from 2017 to 2024.Frontiers in public health · 2026Article
- Prediction of influenza-like illness incidence using meteorological factors in Kunming : deep learning model study.BMC public health · 2025Article
- Epidemiological trends of influenza A and B in one hospital in Chengdu and national surveillance data (2019-2024).Frontiers in cellular and infection microbiology · 2025Article
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Authors and funding
10 authors.
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Abstract
Introduction: Since November 2023, influenza has ranked first in reported cases of infectious diseases in China, with the outbreak in both northern and southern provinces exceeding the levels observed during the same period in 2022. This poses a serious health risk to the population. Therefore, short to medium-term influenza predictions are beneficial for epidemic assessment and can reduce the disease burden. Methods: A transmission dynamics model considering population migration, encompassing susceptible-exposed-infectious-asymptomatic-recovered (SEIAR) was used to predict the dynamics of influenza before the Spring Festival travel rush. Results: The overall epidemic shows a declining trend, with the peak expected to occur from week 47 in 2023 to week 1 in 2024. The number of cases of A (H3N2) is greater than that of influenza B, and the influenza situation is more severe in the southern provinces compared to the northern ones. Conclusion: Our method is applicable for short-term and medium-term influenza predictions. As the spring festival travel rush approaches. Therefore, it is advisable to advocate for nonpharmaceutical interventions (NPIs), influenza vaccination, and other measures to reduce healthcare and public health burden.
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