Comparison of Filtering Methods for the Modeling and Retrospective Forecasting of Influenza Epidemics

PLoS Computational Biology

Volumn 10, Issue 4, 2014, Pages

  Yang, Wan ^a   Karspeck, Alicia ^b   Shaman, Jeffrey ^a  

^a Department of Medicine   (United States)

^b NATIONAL CENTER FOR ATMOSPHERIC RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DISTRIBUTED COMPUTER SYSTEMS; EPIDEMIOLOGY; FORECASTING; KALMAN FILTERS; MARKOV PROCESSES; MAXIMUM LIKELIHOOD ESTIMATION; MONTE CARLO METHODS; PARAMETER ESTIMATION;

ENGINEERING DESIGN; ENSEMBLE FILTER; FILTERING METHOD; INFLUENZA EPIDEMICS; MODELING PARAMETERS; PARTICLE FILTER; PARTICLE MARKOV CHAIN MONTE CARLO; RECURSIVE ESTIMATION; SYSTEM STATE VARIABLES; TIMES SERIES;

TIME SERIES;

ANALYTICAL ERROR; ARTICLE; DISEASE ACTIVITY; ENSEMBLE ADJUSTMENT KALMAN FILTER; ENSEMBLE KALMAN FILTER; EPIDEMIC; FILTRATION; INCIDENCE; INFLUENZA; INTERMETHOD COMPARISON; ITERATED FILTERING; MEASUREMENT ACCURACY; MODEL; PARTICLE FILTER; PARTICLE MARKOV CHAIN MONTE CARLO; PARTICULATE MATTER; PREDICTION AND FORECASTING; PREVALENCE; RANK HISTOGRAM FILTER; SUSCEPTIBLE INFECTIOUS RECOVERED SUSCEPTIBLE MODEL; TIME SERIES ANALYSIS; VALIDATION PROCESS; COMPARATIVE STUDY; EPIDEMIOLOGY; FORECASTING; HUMAN; INFLUENZA, HUMAN; RETROSPECTIVE STUDY; THEORETICAL MODEL; UNITED STATES; VALIDATION STUDY;

FORECASTING; HUMANS; INFLUENZA, HUMAN; MODELS, THEORETICAL; RETROSPECTIVE STUDIES; UNITED STATES;

EID: 84901348387     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1003583     Document Type: Article

References (32)

1. Molinari N-AM, Ortega-Sanchez IR, Messonnier ML, Thompson WW, Wortley PM, et al. (2007) The annual impact of seasonal influenza in the US: Measuring disease burden and costs. Vaccine 25: 5086-5096.
2. Ong JB, Chen MI, Cook AR, Lee HC, Lee VJ, et al. (2010) Real-time epidemic monitoring and forecasting of H1N1-2009 using influenza-like illness from general practice and family doctor clinics in Singapore. PLoS One 5: e10036.
3. Dukic V, Lopes HF, Polson NG, (2012) Tracking epidemics with google flu trends data and a state-space SEIR model. Journal of the American Statistical Association 107: 1410-1426.
4. Shaman J, Karspeck A, (2012) Forecasting seasonal outbreaks of influenza. Proc Natl Acad Sci USA 109: 20425-20430.
5. Skvortsov A, Ristic B, (2012) Monitoring and prediction of an epidemic outbreak using syndromic observations. Mathematical Biosciences 240: 12-19.
6. Shaman J, Karspeck A, Lipsitch M (2013) Week 1 Influenza Forecast for the 2012-2013 US Season. arXiv: 1301.3110.
7. Shaman J, Karspeck A, Yang W, Tamerius J, Lipsitch M, (2013) Real-time influenza forecasts during the 2012-2013 season. Nat Commun 4: 2837.
8. Centers for Disease Control and Prevention (2013) FluView. http://www.cdc.gov/flu/weekly/.
9. Goldstein E, Cobey S, Takahashi S, Miller JC, Lipsitch M, (2011) Predicting the Epidemic Sizes of Influenza A/H1N1, A/H3N2, and B: A Statistical Method. PLoS Med 8: e1001051.
10. Google.org (2013) Google Flu Trend. http://www.google.org/flutrends.
11. Shaman J, Pitzer VE, Viboud C, Grenfell BT, Lipsitch M, (2010) Absolute Humidity and the Seasonal Onset of Influenza in the Continental United States. PLoS Biol 8: e1000316.
12. Shaman J, Kohn M, (2009) Absolute humidity modulates influenza survival, transmission, and seasonality. Proc Natl Acad Sci USA 106: 3243-3248.
13. Anderson JL, (2010) A non-Gaussian ensemble filter update for data assimilation. Mon Weather Rev 138: 4186-4198.
14. Evensen G (2008) Sequential data assimilation. Data Assimilation: The ensemble Kalman filter. 2nd ed. New York: Springer. pp. 27-46.
15. Dukic VM, Lopes HF, Polson N (2009) Tracking Flu Epidemics Using Google Flu Trends and Particle Learning. SSRN: http://ssrn.com/abstract=1513705 or http://dx.doi.org/10.2139/ssrn.1513705.
16. Ionides EL, Breto C, King AA, (2006) Inference for nonlinear dynamical systems. Proc Natl Acad Sci U S A 103: 18438-18443.
17. Rasmussen DA, Ratmann O, Koelle K, (2011) Inference for nonlinear epidemiological models using genealogies and time series. PLoS Comput Biol 7: e1002136.
18. Arulampalam MS, Maskell S, Gordon N, Clapp T, (2002) A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Trans Signal Process 50: 174-188.
19. van Leeuwen PJ, (2009) Particle Filtering in Geophysical Systems. Mon Weather Rev 137: 4089-4114.
20. Andrieu C, Doucet A, Holenstein R, (2010) Particle Markov chain Monte Carlo methods. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 72: 269-342.
21. Anderson JL, (2001) An Ensemble Adjustment Kalman Filter for Data Assimilation. Mon Weather Rev 129: 2884-2903.
22. Ionides EL, Bhadra A, Atchade Y, King A, (2011) Iterated filtering. Ann Stat 39: 1776-1802.
23. King AA, Ionides EL, Pascual M, Bouma MJ, (2008) Inapparent infections and cholera dynamics. Nature 454: 877-880.
24. He D, Ionides EL, King AA, (2010) Plug-and-play inference for disease dynamics: measles in large and small populations as a case study. Journal of The Royal Society Interface 7: 271-283.
25. He DH, Dushoff J, Day T, Ma JL, Earn DJD, (2011) Mechanistic modelling of the three waves of the 1918 influenza pandemic. Theor Ecol 4: 283-288.
26. Kalman RE, (1960) A new approach to linear filtering and prediction problems. Journal of basic Engineering 82: 35-45.
27. Karspeck AR, Anderson JL, (2007) Experimental Implementation of an Ensemble Adjustment Filter for an Intermediate ENSO Model. J Climate 20: 4638-4658.
28. Snyder C, Bengtsson T, Bickel P, Anderson J, (2008) Obstacles to High-Dimensional Particle Filtering. Mon Weather Rev 136: 4629-4640.
29. Wallinga J, Lipsitch M, (2007) How generation intervals shape the relationship between growth rates and reproductive numbers. Proc R Soc B 274: 599-604.
30. Olson DR, Konty KJ, Paladini M, Viboud C, Simonsen L, (2013) Reassessing google flu trends data for detection of seasonal and pandemic influenza: a comparative epidemiological study at three geographic scales. PLoS Comput Biol 9: e1003256.
31. Cook S, Conrad C, Fowlkes AL, Mohebbi MH, (2011) Assessing Google Flu Trends Performance in the United States during the 2009 Influenza Virus A (H1N1) Pandemic. PLoS One 6: e23610.
32. Lei J, Bickel P, Snyder C, (2010) Comparison of Ensemble Kalman Filters under Non-Gaussianity. Mon Weather Rev 138: 1293-1306.