ArticlePLoS computational biology2021
Modeling influenza seasonality in the tropics and subtropics.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed, 60 citations in OpenAlex.
- Resurgence of large-scale influenza A (H1N1) outbreaks: Modeling the interplay of transmission, loss of immunity, and vaccination.Infectious Disease Modelling · 2027Article
- The limitations of non-mechanistic methods for characterizing pathogen-pathogen interactions: A simulation study.PLoS computational biology · 2026Article
- Multi-source machine learning for short-term influenza forecasting in Hunan Province, China: a spatiotemporal analysis using surveillance, search, meteorological and air-quality data.BMC infectious diseases · 2026Article
- Physics-guided framework for climate dependent disease prediction: coupling compartment model with deep learning.BMC public health · 2026Article
- Strain-specific differences in the response to egg-derived versus recombinant protein influenza vaccines.Journal of virology · 2026Article
- Unified climate factors predict influenza outbreak seasonality across tropical and temperate regions.PNAS nexus · 2026Article
- Investigating a deterministic canonical model for tropical influenza.Scientific reports · 2026Article
- Spatiotemporal instability of influenza seasonality during viral co-circulation.NPJ systems biology and applications · 2026Article
- Noisy periodicity in tropical respiratory disease dynamics.medRxiv : the preprint server for health sciences · 2026Article
- Strain-specific differences in the response to egg-derived versus recombinant protein influenza vaccines.bioRxiv : the preprint server for biology · 2026Article
- Optimizing spatiotemporal nonpharmaceutical interventions for influenza: An adaptive reinforcement learning approach for regional heterogeneity.Infectious Disease Modelling · 2026Article
- How Has the COVID-19 Pandemic Affected the Influenza Seasonality Patterns in Different Climate Regions?-A Time-Series Analysis.Health science reports · 2026Article
- Article
- Temperature-based spatiotemporal heterogeneity of hand, foot, and mouth disease transmission in China.BMC infectious diseases · 2025Article
- Association between Short-Term Exposure to Humidex and Influenza Incidence in Japan: A Nationwide Time-Stratified Case-Crossover Study.Journal of epidemiology and global health · 2025Article
- Epidemiological characteristics and spatio-temporal analysis of influenza in Sichuan Province from 2015 to 2024.BMC infectious diseases · 2025Article
- Modeling the influences of climate conditions on measles transmission in China.Epidemiology and infection · 2025Article
- Spatiotemporal Risk Assessment of H5 Avian Influenza in China: An Interpretable Machine Learning Approach to Uncover Multi-Scale Drivers.Animals : an open access journal from MDPI · 2025Article
- Mathematical Modeling of Influenza Dynamics: Integrating Seasonality and Gradual Waning Immunity.Bulletin of mathematical biology · 2025Article
- Synergistic Inactivation of Airborne Viruses by Low-Concentration Ozone With High Humidity and Temperature.Microbiology and immunology · 2025Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
Climate drivers such as humidity and temperature may play a key role in influenza seasonal transmission dynamics. Such a relationship has been well defined for temperate regions. However, to date no models capable of capturing the diverse seasonal pattern in tropical and subtropical climates exist. In addition, multiple influenza viruses could cocirculate and shape epidemic dynamics. Here we construct seven mechanistic epidemic models to test the effect of two major climate drivers (humidity and temperature) and multi-strain co-circulation on influenza transmission in Hong Kong, an influenza epidemic center located in the subtropics. Based on model fit to long-term influenza surveillance data from 1998 to 2018, we found that a simple model incorporating the effect of both humidity and temperature best recreated the influenza epidemic patterns observed in Hong Kong. The model quantifies a bimodal effect of absolute humidity on influenza transmission where both low and very high humidity levels facilitate transmission quadratically; the model also quantifies the monotonic but nonlinear relationship with temperature. In addition, model results suggest that, at the population level, a shorter immunity period can approximate the co-circulation of influenza virus (sub)types. The basic reproductive number R0 estimated by the best-fit model is also consistent with laboratory influenza survival and transmission studies under various combinations of humidity and temperature levels. Overall, our study has developed a simple mechanistic model capable of quantifying the impact of climate drivers on influenza transmission in (sub)tropical regions. This model can be applied to improve influenza forecasting in the (sub)tropics in the future.
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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.