Publications

This page lists papers and archived postings developed for a project entitled Influenza Outbreak Prediction: Applying Data Assimilation Methodologies to Make Skillful Forecasts of an Inherently Chaotic, Nonlinear System, which is funded through the NIH (NIGMS)/NSF (DMS) joint initiative to support research at the interface of the biological and mathematical sciences. The title is a bit of a mouthful (as is the funding program name); basically, we are using data assimilation methods, as commonly employed in numerical weather prediction, in conjunction with real-time observations of influenza incidence to train and optimize model simulations of influenza transmission dynamics on the fly and then use those optimized models to generate real-time forecasts of influenza outcomes. Additional funding comes from the Biomedical Advanced Research and Development Authority of the Department of Health and Human Services, as well as the Models of Infectious Disease Agent Study (MIDAS) program of the the NIH.

2017

Tamerius, J., S. Ojeda, C. K. Uejio, J. Shaman, B. Lopez, N. Sanchez and A. Gordo, 2017: Influenza transmission during extreme indoor conditions in a low-resource tropical setting. International Journal of Biometeorology, 61(4):613-622. doi:10.1007/s00484-016-1238-4.
Kandula, S., W. Yang, and J. Shaman, 2017: Type- and Subtype-Specific Influenza Forecast. American Journal of Epidemiology, 185(5):395-402. doi:10.1093/aje/kww211
Li, R., Y. Bai, A. Heaney, S. Kandula, J. Cai, X. Zhao, B. Xu and J. Shaman, 2017: Inference and forecast of H7N9 influenza in China, 2013 to 2015. Eurosurveillance, 22(7):pii=30462. doi: 10.2807/1560-7917.ES.2017.22.7.30462

2016

Yang, W., D. R. Olson, and J. Shaman, 2016: Forecasting influenza outbreaks in boroughs and neighborhoods of New York City. PLoS Computational Biology, 12(11):e1005201. doi:10.1371/journal.pcbi.1005201.
Biggerstaff M., D. Alper, M. Dredge, S. Fox, I.C.-H. Fung, K.S. Hickman, B. Leis, R. Rosenfield, J. Shaman, M.-H. Tsou, P. Velardi, A. Vespignani, and L. Finelli for the Influenza Forecasting Contest Working Group, 2016: Results from the Centers for Disease Control and Prevention’s Predict the 2013-2014 Influenza Season Challenge. BMC Infectious Diseases, 16:357. doi:10.1186/S12879-016-1669-x
Nguyen, J.L., W. Yang, K. Ito, T. Matte, J. Shaman, and P. L. Kinney, 2016: Seasonal Influenza Infections and Cardiovascular Disease Mortality. JAMA Cardiology, 1(3):274-281. doi:10.1001/jamacardio.2016.0433

2015

Shaman, J. and S. Kandula , 2015: Improved Discrimination of Influenza Forecast Accuracy using Consecutive Predictions. PLOS Currents Outbreaks, 2015 October 5. Edition 1. doi: 10.1371/currents.outbreaks.8a6a3df285af7ca973fab4b22e10911e.
Yang W., B. J. Cowling, E. H. Y. Lau and J. Shaman: Forecasting influenza epidemics in Hong Kong. PLOS Computational Biology, 11(7) doi:10.1371/journal.pcbi.1004383
Yang, W., M. Lipsitch and J. Shaman, 2015: Inference of seasonal and pandemic influenza transmission dynamics using ‘big’ surveillance data. Proceedings of the National Academy of Sciences, 112(9):2723-2728, dpi:10.1073/pnas.1415012112.

2014

Shaman, J., W. Yang and S. Kandula, 2014: Inference and Forecast of the Current West African Ebola Outbreak in Guinea, Sierra Leone and Liberia. PLOS Currents Outbreaks, 2014 October 31. Edition 1. doi: 10.1371/currents.outbreaks.3408774290b1a0f2dd7cae877c8b8ff6.
Chretien, J.-P., D. George, J. Shaman, R.A. Chitale and F. E. McKenzie, 2014: Influenza forecasting in human populations: a scoping review. PLOS ONE, 9(4): e94130. doi:10.1371/journal.pone.0094130
Yang, W., A. Karspeck, and J. Shaman, 2014: Comparison of filtering methods for the modeling and retrospective forecasting of influenza epidemics. PLOS Computational Biology, 10(4): e1003583, doi:10.1371/journal.pcbi.1003583 [Code]
Yang, W. and J. Shaman, 2014: A simple modification for improving inference of non-linear dynamical systems. ArXiv:1403.6804 [stat.ME].

2013

Shaman, J, A. Karspeck, W. Yang, J. Tamerius, and M. Lipsitch, 2013: Real-Time influenza Forecasts during the 2012-2013 Season. Nature communications, 4: Article Number 2837, doi:10.1038/ncomms3837.
Shaman, J, A. Karspeck, and M. Lipsitch, 2013: Week 1 Influenza Forecast for the 2012-2013 U.S. Season ArXiv:1301.3110 [q-bio.PE].
Shaman, J, A. Karspeck, and M. Lipsitch, 2013: Week 52 Influenza Forecast for the 2012-2013 U.S. Season ArXiv:1301.1111 [q-bio.PE].

2012

Shaman, J, A. Karspeck, and M. Lipsitch, 2012: Week 51 Influenza Forecast for the 2012-2013 U.S. Season ArXiv:1212.6678 [q-bio.PE].
Shaman, J, A. Karspeck, and M. Lipsitch, 2012: Week 50 Influenza Forecast for the 2012-2013 U.S. Season ArXiv:1212.5750 [q-bio.PE].
Shaman, J, A. Karspeck, and M. Lipsitch, 2012: Week 49 Influenza Forecast for the 2012-2013 U.S. Season ArXiv:1212.4678 [q-bio.PE].
Shaman, J. and A. Karspeck, 2012: Forecasting Seasonal Outbreaks of Influenza. Proceedings of the National Academy of Sciences, 109(50): 20425-20430, doi:10.1073/pnas.1208772109.