Real-Time Influenza Forecasts during the 2012–2013 Season

[1]  Alicia Karspeck,et al.  Week 49 Influenza Forecast for the 2012-2013 U.S. Season , 2012 .

[2]  J. Shaman,et al.  Forecasting seasonal outbreaks of influenza , 2012, Proceedings of the National Academy of Sciences.

[3]  Cecile Viboud,et al.  Improving the Estimation of Influenza-Related Mortality Over a Seasonal Baseline , 2012, Epidemiology.

[4]  Gerardo Chowell,et al.  Epidemiological characterization of a fourth wave of pandemic A/H1N1 influenza in Mexico, winter 2011-2012: age shift and severity. , 2012, Archives of medical research.

[5]  M. Lipsitch,et al.  The El Niño–Southern Oscillation (ENSO)–pandemic Influenza connection: Coincident or causal? , 2012, Proceedings of the National Academy of Sciences.

[6]  M. Lipsitch,et al.  The ENSO-pandemic influenza connection: coincident or causal? , 2011 .

[7]  Influenza, Seasonal , 2011, My Child Is Sick!, 2nd Ed.

[8]  Alessandro Vespignani,et al.  Human Mobility Networks, Travel Restrictions, and the Global Spread of 2009 H1N1 Pandemic , 2011, PloS one.

[9]  Jeffrey L. Anderson.  A Non-Gaussian Ensemble Filter Update for Data Assimilation , 2010 .

[10]  R. Eggo,et al.  Spatial dynamics of the 1918 influenza pandemic in England, Wales and the United States , 2010, Journal of The Royal Society Interface.

[11]  Peter J. Bickel,et al.  Comparison of Ensemble Kalman Filters under Non-Gaussianity , 2010 .

[12]  Cécile Viboud,et al.  Absolute Humidity and the Seasonal Onset of Influenza in the Continental United States , 2010, PLoS biology.

[13]  Cecile Viboud,et al.  Absolute Humidity and the Seasonal Onset of Influenza in the Continental US , 2009, PLoS currents.

[14]  Jeffrey Shaman,et al.  Absolute humidity modulates influenza survival, transmission, and seasonality , 2009, Proceedings of the National Academy of Sciences.

[15]  Jeremy Ginsberg,et al.  Detecting influenza epidemics using search engine query data , 2009, Nature.

[16]  Casey M. Bergman.  Faculty Opinions recommendation of Detecting influenza epidemics using search engine query data. , 2008 .

[17]  Andy Blackburn,et al.  Google Flu trends , 2008 .

[18]  Gerardo Chowell,et al.  The 1918–1919 influenza pandemic in England and Wales: spatial patterns in transmissibility and mortality impact , 2008, Proceedings of the Royal Society B: Biological Sciences.

[19]  E L Ionides,et al.  Inference for nonlinear dynamical systems , 2006, Proceedings of the National Academy of Sciences.

[20]  D. Cummings,et al.  Strategies for mitigating an influenza pandemic , 2006, Nature.

[21]  Mark A. Miller,et al.  Synchrony, Waves, and Spatial Hierarchies in the Spread of Influenza , 2006, Science.

[22]  David D. Parrish,et al.  NORTH AMERICAN REGIONAL REANALYSIS , 2006 .

[23]  D. Cummings,et al.  Strategies for containing an emerging influenza pandemic in Southeast Asia , 2005, Nature.

[24]  A. Nizam,et al.  Containing Pandemic Influenza at the Source , 2005, Science.

[25]  J. Robins,et al.  Transmissibility of 1918 pandemic influenza , 2004, Nature.

[26]  J. D. Tarpley,et al.  Real‐time and retrospective forcing in the North American Land Data Assimilation System (NLDAS) project , 2003 .

[27]  Cécile Viboud,et al.  Prediction of the spread of influenza epidemics by the method of analogues. , 2003, American journal of epidemiology.

[28]  R. Tsunoda,et al.  Simulation of the nonlinear evolution of the sporadic‐E layer instability in the nighttime midlatitude ionosphere , 2003 .

[29]  Neil J. Gordon,et al.  A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking , 2002, IEEE Trans. Signal Process..

[30]  Jeffrey L. Anderson.  An Ensemble Adjustment Kalman Filter for Data Assimilation , 2001 .