About: Seasonal Influenza Forecasting in Real Time Using the Incidence Decay With Exponential Adjustment Model

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Seasonal Influenza Forecasting in Real Time Using the Incidence Decay With Exponential Adjustment Model
Creator	Fisman, David Peci, Adriana Tuite, Ashleigh Gubbay, Jonathan Hatchette, Todd Friedman, Dara Garber, Gary Nasserie, Tahmina Whitmore, Lindsay Drews, Steven Kwong, Jeffrey Canada, Provlab, Alberta Scotia, Nova Services, Alberta
Source	Medline; PMC
abstract	BACKGROUND: Seasonal influenza epidemics occur frequently. Rapid characterization of seasonal dynamics and forecasting of epidemic peaks and final sizes could help support real-time decision-making related to vaccination and other control measures. Real-time forecasting remains challenging. METHODS: We used the previously described “incidence decay with exponential adjustment” (IDEA) model, a 2-parameter phenomenological model, to evaluate the characteristics of the 2015–2016 influenza season in 4 Canadian jurisdictions: the Provinces of Alberta, Nova Scotia and Ontario, and the City of Ottawa. Model fits were updated weekly with receipt of incident virologically confirmed case counts. Best-fit models were used to project seasonal influenza peaks and epidemic final sizes. RESULTS: The 2015–2016 influenza season was mild and late-peaking. Parameter estimates generated through fitting were consistent in the 2 largest jurisdictions (Ontario and Alberta) and with pooled data including Nova Scotia counts (R(0) approximately 1.4 for all fits). Lower R(0) estimates were generated in Nova Scotia and Ottawa. Final size projections that made use of complete time series were accurate to within 6% of true final sizes, but final size was using pre-peak data. Projections of epidemic peaks stabilized before the true epidemic peak, but these were persistently early (~2 weeks) relative to the true peak. CONCLUSIONS: A simple, 2-parameter influenza model provided reasonably accurate real-time projections of influenza seasonal dynamics in an atypically late, mild influenza season. Challenges are similar to those seen with more complex forecasting methodologies. Future work includes identification of seasonal characteristics associated with variability in model performance.
has issue date	2017-09-27(xsd:dateTime)
bibo:doi	10.1093/ofid/ofx166
bibo:pmid	29497629
has license	cc-by-nc-nd
sha1sum (hex)	9bad339dd5a9605d61cc773ecfe0c65d4402f4b7
schema:url	https://doi.org/10.1093/ofid/ofx166
resource representing a document's title	Seasonal Influenza Forecasting in Real Time Using the Incidence Decay With Exponential Adjustment Model
has PubMed Central identifier	PMC5781299
has PubMed identifier	29497629
schema:publication	Open Forum Infect Dis
resource representing a document's body	covid:9bad339dd5a9605d61cc773ecfe0c65d4402f4b7#body_text
is schema:about of	named entity 'HEALTH AUTHORITY' named entity 'Real-time' named entity 'decision-making' named entity 'Nova Scotia' named entity 'CAPITAL DISTRICT' named entity 'SIZES' named entity 'FREQUENTLY' named entity 'DECISION-MAKING' named entity 'VACCINATION' named entity 'EPIDEMIC' named entity 'FORECASTING' named entity 'NOVA SCOTIA' named entity 'SEASONAL INFLUENZA' named entity 'RAPID' named entity 'CONTROL' named entity 'RELATED' named entity 'CHARACTERIZATION' named entity 'REAL-TIME' named entity 'PEAKS' named entity 'EPIDEMICS' named entity 'BACKGROUND' named entity 'SEASONAL' named entity 'OCCUR' named entity 'SUPPORT' named entity 'DYNAMICS' named entity 'FINAL' named entity 'MEASURES' named entity 'HELP' covid:arg/9bad339dd5a9605d61cc773ecfe0c65d4402f4b7 named entity 'Seasonal influenza' named entity 'epidemic' named entity 'decision-making' named entity 'Nova Scotia' named entity 'Microbiology' named entity 'Ontario' named entity 'influenza season' named entity 'Ontario' named entity 'Canadian' named entity 'Ontario' named entity 'historical data' named entity 'Northern Hemisphere' named entity '1.2' named entity 'cough' named entity 'Influenza Season' named entity 'Central Zone' named entity 'time series' named entity 'influenza infection' named entity 'influenza' named entity 'influenza' named entity 'decision-making' named entity 'Nova Scotia' named entity 'epidemic' named entity 'confidence intervals' named entity 'Middle East respiratory syndrome' named entity 'November 22, 2015' named entity 'phenomenological model' named entity 'influenza A and B viruses' named entity 'influenza epidemic' named entity 'Alberta' named entity 'exponential growth' named entity 'virology' named entity 'QE2' named entity 'Ontario' named entity 'MERS' named entity 'Nova Scotia' named entity 'influenza' named entity 'Seasonal influenza'

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