ArticleOsong public health and research perspectives2011
Modeling for Estimating Influenza Patients from ILI Surveillance Data in Korea.
Article in Osong public health and research perspectives, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Doing mathematics with aftermath of pandemic influenza 2009.Osong public health and research perspectives · 2015Article
- Assessment of intensive vaccination and antiviral treatment in 2009 influenza pandemic in Korea.Osong public health and research perspectives · 2015Article
- How to Manage a Public Health Crisis and Bioterrorism in Korea.Osong public health and research perspectives · 2013Article
- Was the mass vaccination effective during the influenza pandemic 2009-2010 in Korea?Osong public health and research perspectives · 2013Article
- Years of Epidemics (2009-2011): Pandemic Influenza and Foot-and-Mouth Disease Epidemic in Korea.Osong public health and research perspectives · 2013Article
- A tale of two fields: mathematical and statistical modeling of infectious diseases.Osong public health and research perspectives · 2011Article
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivePrediction of influenza incidence among outpatients from an influenza surveillance system is important for public influenza strategy.
methodsWe developed two influenza prediction models through influenza surveillance data of the Korea Centers for Disease Control and Prevention (each year, each province and metropolitan city; total reported patients with influenza-like illness stratified by age) for 6 years from 2005 to 2010 and disease-specific data (influenza code J09-J11, monthly number of influenza patients, total number of outpatients and hospital visits) from the Health Insurance Review and Assessment service.
resultsIncidence of influenza in each area, year, and month was estimated from our prediction models, which were validated by simulation processes. For example, in November 2009, Seoul and Joenbuk, the final number of influenza patients calculated by prediction models A and B underestimated actual reported cases by 64 and 833 patients, respectively, in Seoul and 6 and 9 patients, respectively, in Joenbuk. R-square demonstrated that prediction model A was more suitable than model B for estimating the number of influenza patients.
conclusionOur prediction models from the influenza surveillance system could estimate the nationwide incidence of influenza. This prediction will provide important basic data for national quarantine activities and distributing medical resources in future pandemics.
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