Bibliography

We found the following publications to be particularly relevant to epi-forcasting. This list is work-in-progress and not meant to ever be exhaustive. We share it here in the hope that anyone looking for recent epi-forecasting literature will have a place to start. If there is a particular publication that you think ought to be included, please let us know.

• Modeling the Past, Present, and Future of Influenza.
  David C. Farrow - PhD Thesis
  Carnegie Mellon University (2016)

• Flexible Modeling of Epidemics with an Empirical Bayes Framework.
  Logan C. Brooks, David C. Farrow, Sangwon Hyun, Ryan J. Tibshirani, and Roni Rosenfeld.
  PLoS Computational Biology 11(8): e1004382 (2015) DOI: 10.1371/journal.pcbi.1004382

• Computational Characterization of Transient Strain-Transcending Immunity against Influenza A.
  David C. Farrow, Donald S. Burke, and Roni Rosenfeld.
  PLoS ONE 10(5): e0125047 (2015) DOI: 10.1371/journal.pone.0125047

• What Can Digital Disease Detection Learn from (an External Revision to) Google Flu Trends?
  Santillana, Mauricio, D. Wendong Zhang, Benjamin M. Althouse, and John W. Ayers.
  American Journal of Preventive Medicine (2014)

• Risk of Dengue for Tourists and Teams during the World Cup 2014 in Brazil.
  Willem G. van Panhuis, Sangwon Hyun, Kayleigh Blaney, Ernesto T. A. Marques, Jr, Giovanini E. Coelho, João Bosco Siqueira, Jr, Ryan Tibshirani, Jarbas B. da Silva, Jr, Roni Rosenfeld.
  PLoS Neglected Tropical Diseases July; 8(7): e3063. (2014) DOI: 10.1371/journal.pntd.0003063.

• A predictive fitness model for influenza.
  Łuksza, Marta, and Michael Lässig.
  Nature 507, no. 7490 (2014): 57-61.

• Dengue outlook for the World Cup in Brazil: an early warning model framework driven by real-time seasonal climate forecasts.
  Lowe, Rachel, Christovam Barcellos, Caio AS Coelho, Trevor C. Bailey, Giovanini Evelim Coelho, Richard Graham, Tim Jupp et al.
  The Lancet infectious diseases (2014)

• The parable of Google Flu: Traps in big data analysis.
  Lazer, David M., Ryan Kennedy, Gary King, and Alessandro Vespignani.
  (2014)

• Influenza: Prediction is worth a shot.
  Koelle, Katia, and David A. Rasmussen.
  Nature (2014)

• A systematic review of studies on forecasting the dynamics of influenza outbreaks.
  Nsoesie, Elaine O., John S. Brownstein, Naren Ramakrishnan, and Madhav V. Marathe.
  Influenza and other respiratory viruses (2014)

• Temporal Patterns and a Disease Forecasting Model of Dengue Hemorrhagic Fever in Jakarta Based on 10 Years of Surveillance Data.
  Sitepu, Monika S., Jaranit Kaewkungwal, Nathanej Luplerdlop, Ngamphol Soonthornworasiri, Tassanee Silawan, Supawadee Poungsombat, and Saranath Lawpoolsri.
  The Southeast Asian journal of tropical medicine and public health 44, no. 2 (2013): 206-217.

• Forecasting peaks of seasonal influenza epidemics.
  Nsoesie, Elaine, Madhav Mararthe, and John Brownstein.
  PLoS currents 5 (2013)

• Targeting surveillance for zoonotic virus discovery.
  Levinson, Jordan, Tiffany L. Bogich, Kevin J. Olival, Jonathan H. Epstein, Christine K. Johnson, William Karesh, and Peter Daszak.
  Emerging infectious diseases 19, no. 5 (2013): 743.

• Predicting hotspots for influenza virus reassortment.
  Fuller, Trevon L., Marius Gilbert, Vincent Martin, Julien Cappelle, Parviez Hosseini, Kevin Y. Njabo, Soad Abdel Aziz, Xiangming Xiao, Peter Daszak, and Thomas B. Smith.
  On the Cover (2013): 581.

• Influenza forecasting with Google flu trends.
  Dugas, Andrea Freyer, Mehdi Jalalpour, Yulia Gel, Scott Levin, Fred Torcaso, Takeru Igusa, and Richard E. Rothman.
  PloS one 8, no. 2 (2013): e56176.

• Using network theory to identify the causes of disease outbreaks of unknown origin.
  Bogich, Tiffany L., Sebastian Funk, Trent R. Malcolm, Nok Chhun, Jonathan H. Epstein, Aleksei A. Chmura, A. Marm Kilpatrick et al.
  Journal of The Royal Society Interface 10, no. 81 (2013): 20120904.

• Forecasting seasonal outbreaks of influenza.
  Shaman, Jeffrey, and Alicia Karspeck.
  Proceedings of the National Academy of Sciences 109, no. 50 (2012): 20425-20430.

• Prediction and prevention of the next pandemic zoonosis.
  Morse, Stephen S., Jonna AK Mazet, Mark Woolhouse, Colin R. Parrish, Dennis Carroll, William B. Karesh, Carlos Zambrana-Torrelio, W. Ian Lipkin, and Peter Daszak.
  The Lancet 380, no. 9857 (2012): 1956-1965.

• Forecast of dengue incidence using temperature and rainfall.
  Hii, Yien Ling, Huaiping Zhu, Nawi Ng, Lee Ching Ng, and Joacim Rocklöv.
  PLoS neglected tropical diseases 6, no. 11 (2012): e1908.

• Climate-based models for understanding and forecasting dengue epidemics.
  Descloux, Elodie, Morgan Mangeas, Christophe Eugène Menkes, Matthieu Lengaigne, Anne Leroy, Temaui Tehei, Laurent Guillaumot et al.
  PLoS neglected tropical diseases 6, no. 2 (2012): e1470.

• Forecasting incidence of dengue in Rajasthan, using time series analyses.
  Bhatnagar, Sunil, Vivek Lal, Shiv D. Gupta, and Om P. Gupta.
  Indian journal of public health 56, no. 4 (2012): 281.

• A SARIMA forecasting model to predict the number of cases of dengue in Campinas, State of São Paulo, Brazil.
  Martinez, Edson Zangiacomi, Elisângela Aparecida Soares da Silva, and Amaury Lelis Dal Fabbro.
  Revista da Sociedade Brasileira de Medicina Tropical 44, no. 4 (2011): 436-440.

• Spatio-temporal modelling of climate-sensitive disease risk: Towards an early warning system for dengue in Brazil.
  Lowe, Rachel, Trevor C. Bailey, David B. Stephenson, Richard J. Graham, Caio AS Coelho, Marilia Sá Carvalho, and Christovam Barcellos.
  Computers & Geosciences 37, no. 3 (2011): 371-381.

• Improving the evidence base for decision making during a pandemic: the example of 2009 influenza A/H1N1.
  Lipsitch, Marc, Lyn Finelli, Richard T. Heffernan, Gabriel M. Leung, and Stephen C. Redd; for the 2009 H1N1 Surveillance Group.
  Biosecurity and bioterrorism: biodefense strategy, practice, and science 9, no. 2 (2011): 89-115.

• Predicting the epidemic sizes of influenza A/H1N1, A/H3N2, and B: a statistical method.
  Goldstein, Edward, Sarah Cobey, Saki Takahashi, Joel C. Miller, and Marc Lipsitch.
  PLoS medicine 8, no. 7 (2011): e1001051.

• Absolute humidity and the seasonal onset of influenza in the continental United States.
  Shaman, Jeffrey, Virginia E. Pitzer, Cécile Viboud, Bryan T. Grenfell, and Marc Lipsitch.
  PLoS biology 8, no. 2 (2010): e1000316.

• Real-time epidemic monitoring and forecasting of H1N1-2009 using influenza-like illness from general practice and family doctor clinics in Singapore.
  Ong, Jimmy Boon Som, I. Mark, Cheng Chen, Alex R. Cook, Huey Chyi Lee, Vernon J. Lee, Raymond Tzer Pin Lin, Paul Ananth Tambyah, and Lee Gan Goh.
  PloS one 5, no. 4 (2010): e10036.

• Incidence of 2009 pandemic influenza A H1N1 infection in England: a cross-sectional serological study.
  Miller, Elizabeth, Katja Hoschler, Pia Hardelid, Elaine Stanford, Nick Andrews, and Maria Zambon.
  The Lancet 375, no. 9720 (2010): 1100-1108.

• Vaccination against pandemic influenza A/H1N1v in England: a real-time economic evaluation.
  Baguelin, Marc, Albert Jan Van Hoek, Mark Jit, Stefan Flasche, Peter J. White, and W. John Edmunds.
  Vaccine 28, no. 12 (2010): 2370-2384.

• Absolute humidity modulates influenza survival, transmission, and seasonality.
  Shaman, Jeffrey, and Melvin Kohn.
  Proceedings of the National Academy of Sciences 106, no. 9 (2009): 3243-3248.

• Detecting influenza epidemics using search engine query data.
  Ginsberg, Jeremy, Matthew H. Mohebbi, Rajan S. Patel, Lynnette Brammer, Mark S. Smolinski, and Larry Brilliant.
  Nature 457, no. 7232 (2009): 1012-1014.

• Potential for a global dynamic of Influenza A (H1N1).
  Flahault, Antoine, Elisabeta Vergu, and Pierre-Yves Boëlle.
  BMC infectious diseases 9, no. 1 (2009): 129.

• Temporal patterns and forecast of dengue infection in Northeastern Thailand.
  Silawan, Tassanee, Pratap Singhasivanon, Jaranit Kaewkungwal, Suchitra Nimmanitya, and Wanapa Suwonkerd.
  (2008)

• Global trends in emerging infectious diseases.
  Jones, Kate E., Nikkita G. Patel, Marc A. Levy, Adam Storeygard, Deborah Balk, John L. Gittleman, and Peter Daszak.
  Nature 451, no. 7181 (2008): 990-993.

• Investigating transmission in a two-wave epidemic of Chikungunya fever, Reunion Island.
  Boëlle, P-Y., Guy Thomas, Elisa Vergu, Philippe Renault, A-J. Valleron, and Antoine Flahault.
  Vector-Borne and Zoonotic Diseases 8, no. 2 (2008): 207-218.

• Use of prediction markets to forecast infectious disease activity.
  Polgreen, Philip M., Forrest D. Nelson, George R. Neumann, and Robert A. Weinstein.
  Clinical Infectious Diseases 44, no. 2 (2007): 272-279.

• Online detection and quantification of epidemics.
  Pelat, Camille, Pierre-Yves Boëlle, Benjamin J. Cowling, Fabrice Carrat, Antoine Flahault, Séverine Ansart, and Alain-Jacques Valleron.
  BMC medical informatics and decision making 7, no. 1 (2007): 29.

• Real-time epidemic forecasting for pandemic influenza.
  Hall, I. M., R. Gani, H. E. Hughes, and S. Leach.
  Epidemiology and Infection 135, no. 03 (2007): 372-385.

• Synchrony, waves, and spatial hierarchies in the spread of influenza.
  Viboud, Cécile, Ottar N. Bjørnstad, David L. Smith, Lone Simonsen, Mark A. Miller, and Bryan T. Grenfell.
  science 312, no. 5772 (2006): 447-451.

• Medication sales and syndromic surveillance, France.
  Vergu, Elisabeta, Rebecca F. Grais, Hélène Sarter, Jean-Paul Fagot, Bruno Lambert, Alain-Jacques Valleron, and Antoine Flahault.
  Emerging infectious diseases 12, no. 3 (2006): 416.

• Predictability and preparedness in influenza control.
  Smith, Derek J.
  science 312, no. 5772 (2006): 392-394.

• Key strategies for reducing spread of avian influenza among commercial poultry holdings: lessons for transmission to humans.
  Le Menach, Arnaud, Elisabeta Vergu, Rebecca F. Grais, David L. Smith, and Antoine Flahault.
  Proceedings of the Royal Society B: Biological Sciences 273, no. 1600 (2006): 2467-2475.

• Virtual surveillance of communicable diseases: a 20-year experience in France.
  Flahault, A., T. Blanchon, Y. Dorleans, L. Toubiana, J. F. Vibert, and A. J. Valleron.
  Statistical methods in medical research 15, no. 5 (2006): 413-421.

• Modelling responses to a smallpox epidemic taking into account uncertainty.
  Legrand, J., C. Viboud, P. Y. Boelle, A. J. Valleron, and A. Flahault.
  Epidemiology and infection 132, no. 01 (2004): 19-25.

• Prediction of the spread of influenza epidemics by the method of analogues.
  Viboud, Cécile, Pierre-Yves Boëlle, Fabrice Carrat, Alain-Jacques Valleron, and Antoine Flahault.
  American Journal of Epidemiology 158, no. 10 (2003): 996-1006.

• Dengue hemorrhagic fever epidemiology in Thailand: description and forecasting of epidemics.
  Barbazan, Philippe, Sutee Yoksan, and Jean-Paul Gonzalez.
  Microbes and infection 4, no. 7 (2002): 699-705.

• Storms, Chapter 6: Storms Forecasting for Emergency Response.
  Wernley, Donald, and Louis W. Uccellini.
  Publisher: Routledge, 2000, ISBN: 0415212863, 9780415212861. Chapter 6 in "Storms"; 1999, pp. 70-97

• Forecasting disease risk for increased epidemic preparedness in public health.
  Myers, M. F., D. J. Rogers, J. Cox, A. Flahault, and S. I. Hay.
  Advances in Parasitology 47 (2000): 309-330.

• Probabilistic hydrometeorological forecasts: Toward a new era in operational forecasting.
  Krzysztofowicz, Roman.
  Bulletin of the American Meteorological Society 79, no. 2 (1998): 243-251.

• Probabilistic quantitative precipitation forecasts for river basins.
  Krzysztofowicz, Roman, William J. Drzal, Theresa Rossi Drake, James C. Weyman, and Louis A. Giordano.
  Weather and forecasting 8, no. 4 (1993): 424-439.