ReviewExperimental biology and medicine (Maywood, N.J.)2011
The use of mathematical models to inform influenza pandemic preparedness and response.
Review in Experimental biology and medicine (Maywood, N.J.), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
18 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Mathematical and Computational Models for Pain: A Systematic Review.Pain medicine (Malden, Mass.) · 2021Pooled it
- Population-level mathematical modeling of antimicrobial resistance: a systematic review.BMC medicine · 2019Pooled it
- Clinical and public health economic impact of rapid strain-matched vaccination in influenza pandemic mitigation: A UK-like population dynamic transmission model.Human vaccines & immunotherapeutics · 2026Article
- Mathematical modelling for pandemic preparedness in Canada: Learning from COVID-19.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2024Article
- Physical radiofrequency adjuvant enhances immune responses to influenza H5N1 vaccination.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2022Article
- Review of fractional epidemic models.Applied mathematical modelling · 2021Review
- Early Insights from Statistical and Mathematical Modeling of Key Epidemiologic Parameters of COVID-19.Emerging infectious diseases · 2020Article
- Article
- Are RNA Viruses Candidate Agents for the Next Global Pandemic? A Review.ILAR journal · 2017Review
- Recalibrating disease parameters for increasing realism in modeling epidemics in closed settings.BMC infectious diseases · 2016Article
- Infectious disease modeling methods as tools for informing response to novel influenza viruses of unknown pandemic potential.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2015Review
- Modeling infectious disease dynamics in the complex landscape of global health.Science (New York, N.Y.) · 2015Review
- The Effectiveness of Age-Specific Isolation Policies on Epidemics of Influenza A (H1N1) in a Large City in Central South China.PloS one · 2015Article
- Assessment of malaria incidence using the Richards model in Arunachal Pradesh, India.Epidemiology and infection · 2014Article
- Indemics: An Interactive High-Performance Computing Framework for Data Intensive Epidemic Modeling.ACM transactions on modeling and computer simulation : a publication of the Association for Computing Machinery · 2014Article
- Article
- Anticipating the prevalence of avian influenza subtypes H9 and H5 in live-bird markets.PloS one · 2013Article
- Deviations in influenza seasonality: odd coincidence or obscure consequence?Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2012Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Influenza pandemics have occurred throughout history and were associated with substantial excess mortality and morbidity. Mathematical models of infectious diseases permit quantitative description of epidemic processes based on the underlying biological mechanisms. Mathematical models have been widely used in the past decade to aid pandemic planning by allowing detailed predictions of the speed of spread of an influenza pandemic and the likely effectiveness of alternative control strategies. During the initial waves of the 2009 influenza pandemic, mathematical models were used to track the spread of the virus, predict the time course of the pandemic and assess the likely impact of large-scale vaccination. While mathematical modeling has made substantial contributions to influenza pandemic preparedness, its use as a realtime tool for pandemic control is currently limited by the lack of essential surveillance information such as serological data. Mathematical modeling provided a useful framework for analyzing and interpreting surveillance data during the 2009 influenza pandemic, for highlighting limitations in existing pandemic surveillance systems, and for guiding how these systems should be strengthened in order to cope with future epidemics of influenza or other emerging infectious diseases.
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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.