VTechWorks staff will be away for the winter holidays starting Tuesday, December 24, 2024, through Wednesday, January 1, 2025, and will not be replying to requests during this time. Thank you for your patience, and happy holidays!
 

A systematic review of studies on forecasting the dynamics of influenza outbreaks

Simple item page
dc.contributorVirginia Techen
dc.contributor.authorNsoesie, Elaine O.en
dc.contributor.authorBrownstein, John S.en
dc.contributor.authorRamakrishnan, Narenen
dc.contributor.authorMarathe, Madhav V.en
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2017-10-23T14:52:09Zen
dc.date.available2017-10-23T14:52:09Zen
dc.date.issued2013-12-23en
dc.description.abstractForecasting the dynamics of influenza outbreaks could be useful for decision-making regarding the allocation of public health resources. Reliable forecasts could also aid in the selection and implementation of interventions to reduce morbidity and mortality due to influenza illness. This paper reviews methods for influenza forecasting proposed during previous influenza outbreaks and those evaluated in hindsight. We discuss the various approaches, in addition to the variability in measures of accuracy and precision of predicted measures. PubMed and Google Scholar searches for articles on influenza forecasting retrieved sixteen studies that matched the study criteria. We focused on studies that aimed at forecasting influenza outbreaks at the local, regional, national, or global level. The selected studies spanned a wide range of regions including USA, Sweden, Hong Kong, Japan, Singapore, United Kingdom, Canada, France, and Cuba. The methods were also applied to forecast a single measure or multiple measures. Typical measures predicted included peak timing, peak height, daily/weekly case counts, and outbreak magnitude. Due to differences in measures used to assess accuracy, a single estimate of predictive error for each of the measures was difficult to obtain. However, collectively, the results suggest that these diverse approaches to influenza forecasting are capable of capturing specific outbreak measures with some degree of accuracy given reliable data and correct disease assumptions. Nonetheless, several of these approaches need to be evaluated and their performance quantified in real-time predictions.en
dc.description.sponsorshipThis work is supported by the Intelligence Advanced Research Projects Activity (IARPA) via Department of Interior National Business Center (DoI/NBC) contract number D12PC000337, and the US Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon.en
dc.identifier.doihttps://doi.org/10.1111/irv.12226en
dc.identifier.issue3en
dc.identifier.urihttp://hdl.handle.net/10919/79733en
dc.identifier.volume8en
dc.language.isoen_USen
dc.publisherWileyen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectCompartmental modelsen
dc.subjectindividual-based modelsen
dc.subjectinfectious diseases, influenza forecastingen
dc.subjectpandemicsen
dc.subjecttime series modelsen
dc.titleA systematic review of studies on forecasting the dynamics of influenza outbreaksen
dc.title.serialInfluenza and Other Respiratory Virusesen
dc.typeArticle - Refereeden

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
elaine-flu-review-2014.pdf
Size:
239.3 KB
Format:
Adobe Portable Document Format
Description:
Download

Collections

Destination Area: Global Systems Science (GSS)
Scholarly Works, Computer Science