Forecast Publications
2024
Mathis, S.,…, S. Kandula, S. Pei, J. Shaman, R. Yaari, T.K. Yamana ,…, R.K. Borchering, 2024: Evaluation of FluSight influenza in 2021-22 and 2022-23 seasons with a new forecasting target: laboratory-confirmed influenza hospitalizations . Nature Communication, 15 :6289, doi:10.1038/s41467-024-50601-9.
2023
Pei, S., S. Blumberg, J. Cascante Vega, T. Robin, J. Shaman , 2023: Challenges in forecasting antimicrobial resistance . Emerging Infectious Diseases, 29(4) :679-685, doi:10.3201/eid2904.221552.
2021
2020
Bomfim, R., S. Pei, J. Shaman, T. Yamana , H. A. Makse, J. S. Andrade Jr., A. S. Lima Neto and V. Furtado, 2020: Predicting dengue outbreaks at neighborhood level using human mobility in urban areas . Journal of the Royal Society Interface, 17(171) :20200691, doi:10.1098/rsif.2020.0691.
Pei, S. and J. Shaman, 2020: Aggregating forecasts of multiple respiratory pathogens supports more accurate forecasting of influenza-like illness . PLOS Computational Biology, 16(10) :e1008301, dos:10.1371/journal.pcbi.1008301.Kramer, S.C., S. Pei and J. Shaman, 2020: Forecasting influenza in Europe using a meta population model incorporating cross-border commuting and air travel . PLOS Computational Biology, 16(10) :e1008233, dos:10.1371/journal.pcbi.1008233.Heaney, A.K., K. Alexander and J. Shaman , 2020: Ensemble Forecast and Parameter Inference of Childhood Diarrhea in Chobe District, Botswana . Epidemics, 30 :100372, doi:10.1016.jepidem.2019.100372.Yamana, T. and J. Shaman , 2020: A framework for evaluating the effects observational type and quality on vector-borne disease forecast . Epidemics, 30 :100359, doi:10.1016.jepidem.2019.100359.
2019
Reich NG, C. McGowan, T. Yamana , A. Tushar, E. Ray, D. Osthus, S. Kandula , S. Fox, L. Brooks, W. Crawford-Crudell, G.C. Gibson, E. Moore, R. Silva, M. Biggerstaff, M.A. Johansson, R. Rosenfeld and J. Shaman , 2019: A collaborative multi-model ensemble for real-time influenza forecasting in the U.S.: Results from the 2017/2018 season. PLOS Computational Biology , 15(11) :e1007486, dos:10.1371/journal.pcbi.1007486.
Johansson, M.A., …, T. Yamana, J. Shaman , … et al., 2019: Advancing probabilistic epidemic forecasting through an open challenge: The Dengue Forecasting Project . Proceedings of the National Academy of Sciences, 116(48) :24268-24274, doi:10.1073/pnas.1909865116.
Reich, N.G., D. Osthus, E. Ray, T. Yamana, M. Biggerstaff, M.A. Johansson, R. Rosenfeld and J. Shaman , 2019: Reply to Bracher: Scoring probabilistic forecasts to maximize public health interpretability. Proceedings of the National Academy of Sciences, 116(42) :20811-20812, doi:10.1073/pnas.1912694116.
George D., W. Taylor, J. Shaman , C. Rivers, B. Paul, T. O’Toole, M.A. Johansson, L. Hirschman, M. Biggerstaff, J. Asher and N. Reich, 2019: Technology to advance infectious disease forecasting for outbreak management . Nature Communications, 10 : Article Number 3932, doi:10.1038/s41467-019-11901-7.
Kandula, S., S. Pei and J. Shaman ,2019: Improved forecasts of influenza-associated hospitalization rates with Google search trends . Journal of the Royal Society Interface, 16 :20190080, doi:10.1098/rsif.2019.0080.Kandula, S. and J. Shaman Near-term forecasts of influenza-like illness: an evaluation of autoregressive time series approaches . Epidemics, 27 :41-51, doi:10.1016/j.epidem.2019.01.002.DeFelice, N.B. , R. Birger, N. DeFelice, A. Gagner, S.R. Campbell, C. Romano, M. Santoriello, J. Henke, J. Wittie, B. Cole, C. Kaiser and J. Shaman , 2019: Real time 2017 West Nile virus forecast: operational challenges . JAMA Network Open, 2(4) :e193175, doi:10.1001/jamanetworkopen.2019.3175.Reis, J., T. Yamana, S. Kandula and J. Shaman. Superensemble forecast of respiratory syncytial virus outbreaks at regional, state and municipal levels. Epidemics, 26 :1-8, doi:10.1016/j.epidem.2018.07.001.Kramer, S. and J. Shaman . Development and validation of influenza forecasting for 64 temperate and tropical countries . PLOS Computational Biology, 15(2) :e1006742, doi:10.1371/journal.pcbi.1006742.Pei, S., M. Cane and J. Shaman , 2019: Predictability in process-based ensemble forecast of influenza . PLOS Computational Biology, 15(2) :e1006783, doi:10.1371/journal.pcbi.1006783.Reich, N.G., L. Brooks, F. Spencer, S. Kandula, C. McGowan, E. Moore, D. Osthus, E. Ray, A. Tushar, T. Yamana, M. Biggerstaff, M.A. Johansson, R. Rosenfeld and J. Shaman , 2019: Forecasting seasonal influenza in the U.S.: a collaborative multi-year, multi-model assessment of forecast performance . Proceedings of the National Academy of Sciences, 116(8) :3146-3154, doi:10.1073/pnas.1812594116.
McGowan, C., M. Biggerstaff, M. Johansson, K.M. Apfeldorf, M. Ben-Nun, L. Brooks, M. Convertino, M. Erraguntla, D.C. Farrow, J. Freeze, S. Ghosh, S. Hyun, S. Kandula , J. Lega, Y. Liu, N. Michaud, H. Morita , J. Niemi, N. Ramakrishnan, E.L. Ray, N.G. Reich, P. Riley, J. Shaman , R. Tibshirani, A. Vespignani, Q. Zhang and C. Reed, 2019: Collaborative efforts to forecast seasonal influenza in the United States, 2015-2016 . Scientific Reports, 9 :683, doi:10.1038/s41598-018-36361-9.
2018
Morita, H., S. Kramer, A. Heaney , H. Gil and J. Shaman , 2018: Influenza forecast optimization when using different surveillance data types and geographic scales. Influenza and Other Respiratory Viruses, 12(6) :755-764, doi:10.1111/irv.12594.Biggerstaff, M., M. Johansson, D. Alper, L. C. Brooks, P. Chakraborty, D. C. Farrow, S. Hyun, S. Kandula , C. McGowan, N. Ramakrishnan, R. Rosenfeld, J. Shaman , R. Tibshirani, R. J. Tibshirani, A. Vespignani, W. Yang , Q. Zhang and C. Reed, 2018: Results from the second year of a collaborative effort to forecast influenza seasons in the United States. Epidemics, 24 :43-48, doi:10.1016/j.epidem.2018.02.003.
Doms, C., S. Kramer and J. Shaman , 2018. Assessing the use of influenza forecasts and epidemiological modeling in public health . Scientific Reports, 8 :12406, doi:1038/s41598-018-30378-w.Kandula, S., T. Yamana, S. Pei, W. Yang, H. Morita and J. Shaman , 2018: Evaluation of mechanistic and statistical methods in forecasting influenza-like illness . Journal of the Royal Society Interface, 15 :20180174, doi:10.1098/rsif.2018.0174.DeFelice, N. B., Z. D. Schneider, E. Little , C. Barker, K. A. Callout, S. R. Campbell, D. Damian, P. Irwin, H. M. P. Jones, J. Townsend and J. Shaman , 2018: Use of temperature to improve West Nile virus forecasts . PLOS Computational Biology, 14(3) :e1006047, doi:10.1371/journal.pcbi.1006047.Pei, S., S. Kandula, W. Yang and J. Shaman , 2018: Forecasting the spatial transmission of influenza in the United States . Proceedings of the National Academy of Sciences 115(11) :2752-2757, doi:10.1073/pnas.1708856115.Shaman, J. , 2018: Pandemic preparedness and forecast . Nature Microbiology, 3 :265-267. doi:10.1038/s41564-018-0117-7.
2017
Shaman, J., S. Kandula, W. Yang and A. Karspeck: The use of ambient humidity conditions to improve influenza forecast . PLOS Computational Biology, 13(11) : e1005844. https://doi.org/10.1371/journal.pcbi.1005844.Yamana, T., S. Kandula and J. Shaman , 2017: Individual versus superensemble forecasts of seasonal influenza outbreaks in the United States . PLOS Computational Biology , 13(11) :e1005801. doi:10.1371/journal.pcbi.1005801.Pei, S. and J. Shaman , 2017: Counteracting structural errors in ensemble forecast of influenza outbreaks . Nature Communications, 8 , Article Number 925, doi:10.1038/s41467-017-01033-1.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.DeFelice, N. B., E. Little, S.R. Campbell and J. Shaman , 2017: Ensemble forecast of human West Nile virus cases and mosquito infection rates . Nature Communications, 8 , Article Number 14592, doi:10.1038/ncomms14592.Li, R., 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: http://dx.doi.org/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.Yamana, T., S. Kandula , and J. Shaman , 2016: Superensemble forecasts of dengue outbreaks . Journal of the Royal Society Interface, 13 :20160410. doi:10.1098/rsif.2016.0410Reis, J. J. Shaman Retrospective parameter estimation and forecast of respiratory syncytial virus in the United States. PLOS Computational Biology, 12(10) : e1005133. doi:10.1371/journal.pcbi.1005133.Little, E., S.R. Campbell and J. Shaman , 2016: Development and validation of a climate-based ensemble prediction model for West Nile virus infection rates in Culex mosquitoes, Suffolk County, New York . Parasites & Vectors, 9 :443, doi: 10.1186/s13071-016-1720-1.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.
2015
Shaman, J. and S. Kandula , 2015: Improved Discrimination of Influenza Forecast Accuracy using Consecutive Predictions . PLOS Currents Outbreaks, 2015 Oct 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) : e1004383, doi:10.1371/journal.pcbi.1004383Yang, W., M. Lipsitch and J. Shaman , 2015: Inference of seasonal and pandemic influenza transmission dynamics . Proceedings of the National Academy of Sciences, 112(9) :2723-2728, doi: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 Oct 31. Edition 1 . doi: 10.1371/currents.outbreaks.3408774290b1a0f2dd7cae877c8b8ff6.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.1003583Chretien, 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. 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.
