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A stacked ensemble method for forecasting influenza-like illness visit volumes at emergency departments
- Source :
- PLoS ONE, PLoS ONE, Vol 16, Iss 3, p e0241725 (2021)
- Publication Year :
- 2020
-
Abstract
- Accurate and reliable short-term forecasts of influenza-like illness (ILI) visit volumes at emergency departments can improve staffing and resource allocation decisions within hospitals. In this paper, we developed a stacked ensemble model that averages the predictions from various competing methodologies in the current frontier for ILI-related forecasts. We also constructed a back-of-the-envelope prediction interval for the stacked ensemble, which provides a conservative characterization of the uncertainty in the stacked ensemble predictions. We assessed the accuracy and reliability of our model with 1 to 4 weeks ahead forecast targets using real-time hospital-level data on weekly ILI visit volumes during the 2012-2018 flu seasons in the Alberta Children’s Hospital, located in Calgary, Alberta, Canada. Our results suggest the forecasting performance of the stacked ensemble meets or exceeds the performance of the individual models over all forecast targets.
- Subjects :
- Male
RNA viruses
Viral Diseases
Critical Care and Emergency Medicine
Operations research
Computer science
Physiology
Geographical locations
Alberta
Disease Outbreaks
Animal Diseases
Medical Conditions
Mathematical and Statistical Techniques
Zoonoses
Medicine and Health Sciences
Child
Pathology and laboratory medicine
Multidisciplinary
Statistics
Medical microbiology
Hospitals, Pediatric
Infectious Diseases
Physiological Parameters
Influenza A virus
Child, Preschool
Physical Sciences
Viruses
Medicine
Regression Analysis
Female
Swine Influenza
Seasons
Pathogens
Emergency Service, Hospital
Research Article
Canada
Adolescent
Science
Staffing
Linear Regression Analysis
Research and Analysis Methods
Microbiology
Animal Influenza
Influenza, Human
Humans
Influenza viruses
Statistical Methods
Influenza-like illness
Models, Statistical
Ensemble forecasting
Body Weight
Infant, Newborn
Organisms
Viral pathogens
Prediction interval
Infant
Biology and Life Sciences
Bayes Theorem
Influenza
Microbial pathogens
North America
Linear Models
Resource allocation
People and places
Zoology
Mathematics
Forecasting
Orthomyxoviruses
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 16
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- PloS one
- Accession number :
- edsair.doi.dedup.....d9a6b74025a7c5e9fd3dcbcc12c74a25