Skip to main content
OSTI.GOVU.S. Department of Energy Office of Scientific and Technical Information
U.S. Department of Energy
Office of Scientific and Technical Information
 

A collaborative multiyear, multimodel assessment of seasonal influenza forecasting in the United States

Journal Article · · Proceedings of the National Academy of Sciences of the United States of America
 [1];  [2];  [3];  [4];  [5];  [1];  [6];  [7];  [1];  [4];  [5];  [8];  [2];  [4]
  1. Univ. of Massachusetts, Amherst, MA (United States)
  2. Carnegie Mellon Univ., Pittsburgh, PA (United States)
  3. Univ. of Texas, Austin, TX (United States)
  4. Columbia Univ., New York, NY (United States)
  5. Centers for Disease Control and Prevention, Atlanta, GA (United States)
  6. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  7. Mount Holyoke College, South Hadley, MA (United States)
  8. Centers for Disease Control and Prevention, San Juan, PR (United States)
+ Show Author Affiliations
Influenza infects an estimated 9–35 million individuals each year in the United States and is a contributing cause for between 12,000 and 56,000 deaths annually. Seasonal outbreaks of influenza are common in temperate regions of the world, with highest incidence typically occurring in colder and drier months of the year. Real-time forecasts of influenza transmission can inform public health response to outbreaks. We present the results of a multiinstitution collaborative effort to standardize the collection and evaluation of forecasting models for influenza in the United States for the 2010/2011 through 2016/2017 influenza seasons. For these seven seasons, we assembled weekly real-time forecasts of seven targets of public health interest from 22 different models. We compared forecast accuracy of each model relative to a historical baseline seasonal average. Across all regions of the United States, over half of the models showed consistently better performance than the historical baseline when forecasting incidence of influenza-like illness 1 wk, 2 wk, and 3 wk ahead of available data and when forecasting the timing and magnitude of the seasonal peak. In some regions, delays in data reporting were strongly and negatively associated with forecast accuracy. More timely reporting and an improved overall accessibility to novel and traditional data sources are needed to improve forecasting accuracy and its integration with real-time public health decision making.
Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
89233218CNA000001
OSTI ID:
1634978
Report Number(s):
LA--UR-20-22023
Journal Information:
Proceedings of the National Academy of Sciences of the United States of America, Journal Name: Proceedings of the National Academy of Sciences of the United States of America Journal Issue: 8 Vol. 116; ISSN 0027-8424
Publisher:
National Academy of SciencesCopyright Statement
Country of Publication:
United States
Language:
English

References (32)

Mortality Associated With Influenza and Respiratory Syncytial Virus in the United States journal January 2003
Infectious disease prediction with kernel conditional density estimation: Infectious disease prediction with kernel conditional density estimation journal September 2017
Predicting lymphatic filariasis transmission and elimination dynamics using a multi-model ensemble framework journal March 2017
The RAPIDD ebola forecasting challenge: Synthesis and lessons learnt journal March 2018
Results from the second year of a collaborative effort to forecast influenza seasons in the United States journal September 2018
Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series journal April 1990
Estimating the impact of school closure on influenza transmission from Sentinel data journal April 2008
Counteracting structural errors in ensemble forecast of influenza outbreaks journal October 2017
Forecasting the spatial transmission of influenza in the United States journal February 2018
Systematic Assessment of Multiple Routine and Near Real-Time Indicators to Classify the Severity of Influenza Seasons and Pandemics in the United States, 2003–2004 Through 2015–2016 journal October 2017
Big Data for Infectious Disease Surveillance and Modeling journal November 2016
Evaluation of mechanistic and statistical methods in forecasting influenza-like illness journal July 2018
Urbanization and humidity shape the intensity of influenza epidemics in U.S. cities journal October 2018
Evolution-informed forecasting of seasonal influenza A (H3N2) journal October 2017
Results from the centers for disease control and prevention’s predict the 2013–2014 Influenza Season Challenge journal July 2016
Variation in loss of immunity shapes influenza epidemics and the impact of vaccination journal September 2017
Strictly Proper Scoring Rules, Prediction, and Estimation journal March 2007
Dynamic Bayesian Influenza Forecasting in the United States with Hierarchical Discrepancy (with Discussion) journal March 2019
Comparison of Filtering Methods for the Modeling and Retrospective Forecasting of Influenza Epidemics journal April 2014
Flexible Modeling of Epidemics with an Empirical Bayes Framework journal August 2015
Individual versus superensemble forecasts of seasonal influenza outbreaks in the United States journal November 2017
Prediction of infectious disease epidemics via weighted density ensembles journal February 2018
Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions journal June 2018
Risk factors and short-term projections for serotype-1 poliomyelitis incidence in Pakistan: A spatiotemporal analysis journal June 2017
Intermediate levels of vaccination coverage may minimize seasonal influenza outbreaks journal June 2018
Influenza Virus Transmission Is Dependent on Relative Humidity and Temperature journal October 2007
Subregional Nowcasts of Seasonal Influenza Using Search Trends journal January 2017
Prediction of infectious disease epidemics via weighted density ensembles text January 2017
Advancing Epidemic Prediction and Forecasting: A New US Government Initiative journal February 2015
Evaluation of mechanistic and statistical methods in forecasting influenza-like illness text January 2018
Comparison of Filtering Methods for the Modeling and Retrospective Forecasting of Influenza Epidemics text January 2014
Individual versus superensemble forecasts of seasonal influenza outbreaks in the United States text January 2017

Cited By (10)

Accuracy of real-time multi-model ensemble forecasts for seasonal influenza in the U.S. journal November 2019
The future of influenza forecasts journal February 2019
On the multibin logarithmic score used in the FluSight competitions journal September 2019
Reply to Bracher: Scoring probabilistic forecasts to maximize public health interpretability journal September 2019
Coordinating the real‐time use of global influenza activity data for better public health planning journal December 2019
A novel sub-epidemic modeling framework for short-term forecasting epidemic waves journal August 2019
Forecasting dengue and influenza incidences using a sparse representation of Google trends, electronic health records, and time series data journal November 2019
Nowcasting by Bayesian Smoothing: A flexible, generalizable model for real-time epidemic tracking journal April 2020
Nonpharmaceutical Measures for Pandemic Influenza in Nonhealthcare Settings—Social Distancing Measures journal May 2020
On the multibin logarithmic score used in the FluSight competitions text January 2019

Figures / Tables (8)

Fig. 1(p. 3)figure Fig. 1
Table 1(p. 4)table Table 1
Fig. 2(p. 5)figure Fig. 2
Fig. 3(p. 5)figure Fig. 3
Fig. 4(p. 6)figure Fig. 4
Fig. 5(p. 6)figure Fig. 5
Fig. 6(p. 7)figure Fig. 6
Table 2(p. 7)table Table 2

Similar Records

Accuracy of real-time multi-model ensemble forecasts for seasonal influenza in the U.S.
Journal Article · Thu Nov 21 19:00:00 EST 2019 · PLoS Computational Biology (Online) · OSTI ID:1604056
Forecasting seasonal influenza with a state-space SIR model
Journal Article · Fri Apr 07 20:00:00 EDT 2017 · The Annals of Applied Statistics · OSTI ID:1406200

Related Subjects

60 APPLIED LIFE SCIENCES
Biological Science
Forecasting
Infectious disease
Influenza
Mathematics
Public health
Statistics