ArticleJournal of the Royal Society, Interface2013
Time and dose-dependent risk of pneumococcal pneumonia following influenza: a model for within-host interaction between influenza and Streptococcus pneumoniae.
Article in Journal of the Royal Society, Interface, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 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.
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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
26 citing papers in PubMed, 35 citations in OpenAlex.
- A mechanism-based model of immune status effects on antibiotic PK/PD targets in bacteremia.Journal of pharmacokinetics and pharmacodynamics · 2026Article
- Stochastic modeling of pneumonia transmission dynamics and implications for public health control.Frontiers in public health · 2026Article
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- Mathematical Modeling of the Lethal Synergism of Coinfecting Pathogens in Respiratory Viral Infections: A Review.Microorganisms · 2023Review
- Interactions among 17 respiratory pathogens: a cross-sectional study using clinical and community surveillance data.medRxiv : the preprint server for health sciences · 2022Article
- Immunopathological similarities between COVID-19 and influenza: Investigating the consequences of Co-infection.Microbial pathogenesis · 2021Review
- Simulation modelling for immunologists.Nature reviews. Immunology · 2020Review
- Treatment timing shifts the benefits of short and long antibiotic treatment over infection.Evolution, medicine, and public health · 2020Article
- Application of Optimal Control to Influenza Pneumonia Coinfection with Antiviral Resistance.Computational and mathematical methods in medicine · 2020Article
- Brazilian consensus on non-cystic fibrosis bronchiectasis.Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia · 2019Article
- Metabolic Modeling Elucidates the Transactions in the Rumen Microbiome and the Shifts Upon Virome Interactions.Frontiers in microbiology · 2019Article
- Mortality, morbidity, and hospitalisations due to influenza lower respiratory tract infections, 2017: an analysis for the Global Burden of Disease Study 2017.The Lancet. Respiratory medicine · 2019Article
- Article
- Host-pathogen kinetics during influenza infection and coinfection: insights from predictive modeling.Immunological reviews · 2018Review
- Influenza interaction with cocirculating pathogens and its impact on surveillance, pathogenesis, and epidemic profile: A key role for mathematical modelling.PLoS pathogens · 2018Review
- Article
- An agent-based model simulation of influenza interactions at the host level: insight into the influenza-related burden of pneumococcal infections.BMC infectious diseases · 2017Article
- Mathematical Modeling ofFrontiers in physiology · 2017Article
- Mathematical modeling of postcoinfection with influenza A virus andInternational journal of chronic obstructive pulmonary disease · 2017Article
- A Biomathematical Model of Pneumococcal Lung Infection and Antibiotic Treatment in Mice.PloS one · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
A significant fraction of seasonal and in particular pandemic influenza deaths are attributed to secondary bacterial infections. In animal models, influenza virus predisposes hosts to severe infection with both Streptococcus pneumoniae and Staphylococcus aureus. Despite its importance, the mechanistic nature of the interaction between influenza and pneumococci, its dependence on the timing and sequence of infections as well as the clinical and epidemiological consequences remain unclear. We explore an immune-mediated model of the viral-bacterial interaction that quantifies the timing and the intensity of the interaction. Taking advantage of the wealth of knowledge gained from animal models, and the quantitative understanding of the kinetics of pathogen-specific immunological dynamics, we formulate a mathematical model for immune-mediated interaction between influenza virus and S. pneumoniae in the lungs. We use the model to examine the pathogenic effect of inoculum size and timing of pneumococcal invasion relative to influenza infection, as well as the efficacy of antivirals in preventing severe pneumococcal disease. We find that our model is able to capture the key features of the interaction observed in animal experiments. The model predicts that introduction of pneumococcal bacteria during a 4-6 day window following influenza infection results in invasive pneumonia at significantly lower inoculum size than in hosts not infected with influenza. Furthermore, we find that antiviral treatment administered later than 4 days after influenza infection was not able to prevent invasive pneumococcal disease. This work provides a quantitative framework to study interactions between influenza and pneumococci and has the potential to accurately quantify the interactions. Such quantitative understanding can form a basis for effective clinical care, public health policies and pandemic preparedness.
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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.