ArticlePLoS computational biology2023
Repeatability and timing of tropical influenza epidemics.
Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 12 citations in OpenAlex.
- Physics-guided framework for climate dependent disease prediction: coupling compartment model with deep learning.BMC public health · 2026Article
- Investigating a deterministic canonical model for tropical influenza.Scientific reports · 2026Article
- Noisy periodicity in tropical respiratory disease dynamics.medRxiv : the preprint server for health sciences · 2026Article
- Shifts in seasonal timing of respiratory diseases and causes of death following a natural pandemic event.PLOS global public health · 2026Article
- Eco-evolutionary dynamics of pathogen immune-escape: deriving a population-level phylodynamic curve.Journal of the Royal Society, Interface · 2025Article
- Evolutionary dynamics and molecular epidemiology of H1N1 pandemic 2009 influenza A viruses across swine farms in Denmark.Virus evolution · 2025Article
- Improving influenza forecast in the tropics and subtropics: a case study of Hong Kong.Journal of the Royal Society, Interface · 2025Article
- Article
- Influenza vaccination allocation in tropical settings under constrained resources.medRxiv : the preprint server for health sciences · 2024Article
- A combination of annual and nonannual forces drive respiratory disease in the tropics.BMJ global health · 2023Article
- A combination of annual and nonannual forces drive respiratory disease in the tropics.medRxiv : the preprint server for health sciences · 2023Article
- Benefits of near-universal vaccination and treatment access to manage COVID-19 burden in the United States.medRxiv : the preprint server for health sciences · 2023Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
Abstract
Much of the world experiences influenza in yearly recurring seasons, particularly in temperate areas. These patterns can be considered repeatable if they occur predictably and consistently at the same time of year. In tropical areas, including southeast Asia, timing of influenza epidemics is less consistent, leading to a lack of consensus regarding whether influenza is repeatable. This study aimed to assess repeatability of influenza in Vietnam, with repeatability defined as seasonality that occurs at a consistent time of year with low variation. We developed a mathematical model incorporating parameters to represent periods of increased transmission and then fitted the model to data collected from sentinel hospitals throughout Vietnam as well as four temperate locations. We fitted the model for individual (sub)types of influenza as well as all combined influenza throughout northern, central, and southern Vietnam. Repeatability was evaluated through the variance of the timings of peak transmission. Model fits from Vietnam show high variance (sd = 64-179 days) in peak transmission timing, with peaks occurring at irregular intervals and throughout different times of year. Fits from temperate locations showed regular, annual epidemics in winter months, with low variance in peak timings (sd = 32-57 days). This suggests that influenza patterns are not repeatable or seasonal in Vietnam. Influenza prevention in Vietnam therefore cannot rely on anticipation of regularly occurring outbreaks.
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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.