Trial reportScientific reports2016
Heterogeneous shedding of influenza by human subjects and its implications for epidemiology and control.
Trial report in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Should public health policy exempt cases with low viral load from isolation during an epidemic?: a modelling study.Infectious Disease Modelling · 2025Article
- Multivariate Host-Pathogen Interactions Driving Heterogeneous Viral Shedding and CD8medRxiv : the preprint server for health sciences · 2025Article
- Modeling natural coinfection in a bat reservoir shows modulation of Marburg virus shedding and spillover potential.PLoS pathogens · 2025Article
- Increasing child vaccination coverage can reduce influenza cases across age groups: An agent-based modeling study.The Journal of infection · 2025Article
- Accelerating antiviral drug discovery: lessons from COVID-19.Nature reviews. Drug discovery · 2023Review
- Border Control for Infectious Respiratory Disease Pandemics: A Modelling Study for H1N1 and Four Strains of SARS-CoV-2.Viruses · 2023Article
- Spread of viruses, which measures are the most apt to control COVID-19?Infectious diseases now · 2023Review
- Heterogeneity of Rift Valley fever virus transmission potential across livestock hosts, quantified through a model-based analysis of host viral load and vector infection.PLoS computational biology · 2022Article
- Impact of Oseltamivir Treatment on Influenza A and B Virus Dynamics in Human Volunteers.Frontiers in microbiology · 2021Article
- The Radiation-Transmission-Reception (RTR) model of propagation: Implications for the effectiveness of network interventions.PloS one · 2018Article
- Transmission of rhinovirus in the Utah BIG-LoVE families: Consequences of age and household structure.PloS one · 2018Article
- The Mechanisms for Within-Host Influenza Virus Control Affect Model-Based Assessment and Prediction of Antiviral Treatment.Viruses · 2017Article
- Quantifying Transmission.Microbiology spectrum · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Heterogeneity of infectiousness is an important feature of the spread of many infections, with implications for disease dynamics and control, but its relevance to human influenza virus is still unclear. For a transmission event to occur, an infected individual needs to release infectious particles via respiratory symptoms. Key factors to take into account are virus dynamics, particle release in relation to respiratory symptoms, the amount of virus shed and, importantly, how these vary between infected individuals. A quantitative understanding of the process of influenza transmission is relevant to designing effective mitigation measures. Here we develop an influenza infection dynamics model fitted to virological, systemic and respiratory symptoms to investigate how within-host dynamics relates to infectiousness. We show that influenza virus shedding is highly heterogeneous between subjects. From analysis of data on experimental infections, we find that a small proportion (<20%) of influenza infected individuals are responsible for the production of 95% of infectious particles. Our work supports targeting mitigation measures at most infectious subjects to efficiently reduce transmission. The effectiveness of public health interventions targeted at highly infectious individuals would depend on accurate identification of these subjects and on how quickly control measures can be applied.
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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.