Applying infectious disease forecasting to public health: a path forward using influenza forecasting examples

Lutz, Chelsea S.; Huynh, Mimi P.; Schroeder, Monica; Anyatonwu, Sophia; Dahlgren, F. Scott; Danyluk, Gregory; Fernandez, Danielle; Greene, Sharon K.; Kipshidze, Nodar; Liu, Leann; Mgbere, Osaro; McHugh, Lisa A.; Myers, Jennifer F.; Siniscalchi, Alan; Sullivan, Amy D.; West, Nicole; Johansson, Michael A.; Biggerstaff, Matthew

doi:10.1186/s12889-019-7966-8

Applying infectious disease forecasting to public health: a path forward using influenza forecasting examples

Journal Article · Mon Dec 09 23:00:00 EST 2019 · BMC Public Health (Online)

DOI:https://doi.org/10.1186/s12889-019-7966-8· OSTI ID:1905018

^[1]; Huynh, Mimi P. ^[2]; Schroeder, Monica ^[2]; Anyatonwu, Sophia ^[3]; Dahlgren, F. Scott ^[4]; Danyluk, Gregory ^[5]; Fernandez, Danielle ^[6]; Greene, Sharon K. ^[7]; Kipshidze, Nodar ^[8]; Liu, Leann ^[9]; Mgbere, Osaro ^[10]; McHugh, Lisa A. ^[11]; Myers, Jennifer F. ^[12]; Siniscalchi, Alan ^[13]; Sullivan, Amy D. ^[14]; West, Nicole ^[15]; Johansson, Michael A. ^[16]; Biggerstaff, Matthew ^[4]

Centers for Disease Control and Prevention (CDC), Atlanta, GA (United States); Oak Ridge Inst. for Science and Education (ORISE), Oak Ridge, TN (United States); Johns Hopkins Univ., Baltimore, MD (United States); OSTI
Council of State and Territorial Epidemiologists, Atlanta, GA (United States)
Public Health Institute, Oakland, CA (United States)
Centers for Disease Control and Prevention (CDC), Atlanta, GA (United States)
Florida Department of Health, Bartow, FL (United States)
Florida Department of Health, Miami, FL (United States)
New York City Department of Health and Mental Hygiene, NY (United States)
New York Univ. (NYU), NY (United States)
Harris County Public Health, Houston, TX (United States)
Houston Health Department, Houston, TX (United States)
New Jersey Department of Health, Trenton, NJ (United States)
California Department of Public Health, Richmond, CA (United States)
State of Connecticut Department of Health, Hartford, CT (United States)
Washington State Department of Health, Olympia, WA (United States)
Oregon Health Authority, Portland, OR (United States)
Centers for Disease Control and Prevention, San Juan, PR (United States)

Infectious disease forecasting aims to predict characteristics of both seasonal epidemics and future pandemics. Accurate and timely infectious disease forecasts could aid public health responses by informing key preparation and mitigation efforts. For forecasts to be fully integrated into public health decision-making, federal, state, and local officials must understand how forecasts were made, how to interpret forecasts, and how well the forecasts have performed in the past. Since the 2013–14 influenza season, the Influenza Division at the Centers for Disease Control and Prevention (CDC) has hosted collaborative challenges to forecast the timing, intensity, and short-term trajectory of influenza-like illness in the United States. Additional efforts to advance forecasting science have included influenza initiatives focused on state-level and hospitalization forecasts, as well as other infectious diseases. Using CDC influenza forecasting challenges as an example, this paper provides an overview of infectious disease forecasting; applications of forecasting to public health; and current work to develop best practices for forecast methodology, applications, and communication. These efforts, along with other infectious disease forecasting initiatives, can foster the continued advancement of forecasting science.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC); Centers for Disease Control and Prevention (CDC)

Grant/Contract Number:: SC0014664

OSTI ID:: 1905018

Journal Information:: BMC Public Health (Online), Journal Name: BMC Public Health (Online) Journal Issue: 1 Vol. 19; ISSN 1471-2458

Publisher:: BioMed CentralCopyright Statement

Country of Publication:: United States

Language:: English

References (37)

Influenza Virus Evolution, Host Adaptation, and Pandemic Formation Taubenberger, Jeffery K.; Kash, John C. Cell Host & Microbe, Vol. 7, Issue 6 https://doi.org/10.1016/j.chom.2010.05.009	journal	June 2010
Modeling and public health emergency responses: Lessons from SARS Glasser, John W.; Hupert, Nathaniel; McCauley, Mary M. Epidemics, Vol. 3, Issue 1 https://doi.org/10.1016/j.epidem.2011.01.001	journal	March 2011
Results from the second year of a collaborative effort to forecast influenza seasons in the United States Biggerstaff, Matthew; Johansson, Michael; Alper, David Epidemics, Vol. 24 https://doi.org/10.1016/j.epidem.2018.02.003	journal	September 2018
The annual impact of seasonal influenza in the US: Measuring disease burden and costs Molinari, Noelle-Angelique M.; Ortega-Sanchez, Ismael R.; Messonnier, Mark L. Vaccine, Vol. 25, Issue 27, p. 5086-5096 https://doi.org/10.1016/j.vaccine.2007.03.046	journal	June 2007
Assessing the Use of Influenza Forecasts and Epidemiological Modeling in Public Health Decision Making in the United States Doms, Colin; Kramer, Sarah C.; Shaman, Jeffrey Scientific Reports, Vol. 8, Issue 1 https://doi.org/10.1038/s41598-018-30378-w	journal	August 2018
Collaborative efforts to forecast seasonal influenza in the United States, 2015–2016 McGowan, Craig J.; Biggerstaff , Matthew; Johansson, Michael Scientific Reports, Vol. 9, Issue 1 https://doi.org/10.1038/s41598-018-36361-9	journal	January 2019
The Measurement of Performance in Probabilistic Diagnosis Hilden, J.; Habbema, J. D. F.; Bjerregaard, B. Methods of Information in Medicine, Vol. 17, Issue 04 https://doi.org/10.1055/s-0038-1636442	journal	October 1978
Mitigation strategies for pandemic influenza in the United States Germann, T. C.; Kadau, K.; Longini, I. M. Proceedings of the National Academy of Sciences, Vol. 103, Issue 15 https://doi.org/10.1073/pnas.0601266103	journal	April 2006
Surveillance for Influenza during the 2009 Influenza A (H1N1) Pandemic-United States, April 2009-March 2010 Brammer, L.; Blanton, L.; Epperson, S. Clinical Infectious Diseases, Vol. 52, Issue Supplement 1 https://doi.org/10.1093/cid/ciq009	journal	December 2010
Infectious Disease Modeling Methods as Tools for Informing Response to Novel Influenza Viruses of Unknown Pandemic Potential Gambhir, Manoj; Bozio, Catherine; O'Hagan, Justin J. Clinical Infectious Diseases, Vol. 60, Issue suppl_1 https://doi.org/10.1093/cid/civ083	journal	April 2015
Epidemic Forecasting is Messier Than Weather Forecasting: The Role of Human Behavior and Internet Data Streams in Epidemic Forecast Moran, Kelly R.; Fairchild, Geoffrey; Generous, Nicholas Journal of Infectious Diseases, Vol. 214, Issue suppl 4 https://doi.org/10.1093/infdis/jiw375	journal	November 2016
How emergency managers (mis?)interpret forecasts Wernstedt, Kris; Roberts, Patrick S.; Arvai, Joseph Disasters, Vol. 43, Issue 1 https://doi.org/10.1111/disa.12293	journal	June 2018
A systematic review of studies on forecasting the dynamics of influenza outbreaks Nsoesie, Elaine O.; Brownstein, John S.; Ramakrishnan, Naren Influenza and Other Respiratory Viruses, Vol. 8, Issue 3 https://doi.org/10.1111/irv.12226	journal	December 2013
Seasonal and pandemic influenza surveillance considerations for constructing multicomponent systems Brammer, Lynnette; Budd, Alicia; Cox, Nancy Influenza and Other Respiratory Viruses, Vol. 3, Issue 2 https://doi.org/10.1111/j.1750-2659.2009.00077.x	journal	March 2009
Modeling infectious disease dynamics in the complex landscape of global health Heesterbeek, H.; Anderson, R. M.; Andreasen, V. Science, Vol. 347, Issue 6227 https://doi.org/10.1126/science.aaa4339	journal	March 2015
Communicating Uncertainty in Weather Forecasts: A Survey of the U.S. Public Morss, Rebecca E.; Demuth, Julie L.; Lazo, Jeffrey K. Weather and Forecasting, Vol. 23, Issue 5 https://doi.org/10.1175/2008waf2007088.1	journal	October 2008
Combination strategies for pandemic influenza response - a systematic review of mathematical modeling studies Lee, Vernon J.; Lye, David C.; Wilder-Smith, Annelies BMC Medicine, Vol. 7, Issue 1 https://doi.org/10.1186/1741-7015-7-76	journal	December 2009
Results from the centers for disease control and prevention’s predict the 2013–2014 Influenza Season Challenge Biggerstaff, Matthew; Alper, David; Dredze, Mark BMC Infectious Diseases, Vol. 16, Issue 1 https://doi.org/10.1186/s12879-016-1669-x	journal	July 2016
Agent-based models of malaria transmission: a systematic review Smith, Neal R.; Trauer, James M.; Gambhir, Manoj Malaria Journal, Vol. 17, Issue 1 https://doi.org/10.1186/s12936-018-2442-y	journal	August 2018
Strictly Proper Scoring Rules, Prediction, and Estimation Gneiting, Tilmann; Raftery, Adrian E. Journal of the American Statistical Association, Vol. 102, Issue 477 https://doi.org/10.1198/016214506000001437	journal	March 2007
Improved Discrimination of Influenza Forecast Accuracy Using Consecutive Predictions Shaman, Jeffrey; Kandula, Sasikiran PLoS Currents https://doi.org/10.1371/currents.outbreaks.8a6a3df285af7ca973fab4b22e10911e	journal	January 2015
Comparison of Filtering Methods for the Modeling and Retrospective Forecasting of Influenza Epidemics Yang, Wan; Karspeck, Alicia; Shaman, Jeffrey PLoS Computational Biology, Vol. 10, Issue 4 https://doi.org/10.1371/journal.pcbi.1003583	journal	April 2014
Forecasting Influenza Outbreaks in Boroughs and Neighborhoods of New York City Yang, Wan; Olson, Donald R.; Shaman, Jeffrey PLOS Computational Biology, Vol. 12, Issue 11 https://doi.org/10.1371/journal.pcbi.1005201	journal	November 2016
Influenza Forecasting in Human Populations: A Scoping Review Chretien, Jean-Paul; George, Dylan; Shaman, Jeffrey PLoS ONE, Vol. 9, Issue 4 https://doi.org/10.1371/journal.pone.0094130	journal	April 2014
Nowcasting the Spread of Chikungunya Virus in the Americas Johansson, Michael A.; Powers, Ann M.; Pesik, Nicki PLoS ONE, Vol. 9, Issue 8 https://doi.org/10.1371/journal.pone.0104915	journal	August 2014
Influenza Activity — United States, 2015–16 Season and Composition of the 2016–17 Influenza Vaccine Davlin, Stacy L.; Blanton, Lenee; Kniss, Krista MMWR. Morbidity and Mortality Weekly Report, Vol. 65, Issue 22 https://doi.org/10.15585/mmwr.mm6522a3	journal	June 2016
Update: Influenza Activity in the United States During the 2016–17 Season and Composition of the 2017–18 Influenza Vaccine Blanton, Lenee; Alabi, Noreen; Mustaquim, Desiree MMWR. Morbidity and Mortality Weekly Report, Vol. 66, Issue 25 https://doi.org/10.15585/mmwr.mm6625a3	journal	June 2017
Subregional Nowcasts of Seasonal Influenza Using Search Trends Kandula, Sasikiran; Hsu, Daniel; Shaman, Jeffrey Journal of Medical Internet Research, Vol. 19, Issue 11 https://doi.org/10.2196/jmir.7486	journal	January 2017
Accurate Influenza Monitoring and Forecasting Using Novel Internet Data Streams: A Case Study in the Boston Metropolis Lu, Fred Sun; Hou, Suqin; Baltrusaitis, Kristin JMIR Public Health and Surveillance, Vol. 4, Issue 1 https://doi.org/10.2196/publichealth.8950	journal	January 2018
Dating the emergence of pandemic influenza viruses Smith, Gavin J. D.; Bahl, Justin; Vijaykrishna, Dhanasekaran Proceedings of the National Academy of Sciences, Vol. 106, Issue 28 https://doi.org/10.1073/pnas.0904991106	journal	July 2009
Reply to Bracher: Scoring probabilistic forecasts to maximize public health interpretability Reich, Nicholas G.; Osthus, Dave; Ray, Evan L. Proceedings of the National Academy of Sciences, Vol. 116, Issue 42 https://doi.org/10.1073/pnas.1912694116	journal	September 2019
Forecasting influenza outbreak dynamics in Melbourne from Internet search query surveillance data Moss, Robert; Zarebski, Alexander; Dawson, Peter Influenza and Other Respiratory Viruses, Vol. 10, Issue 4 https://doi.org/10.1111/irv.12376	journal	March 2016
Communicating Uncertainty in Weather Forecasts: A Survey of the U.S. Public Morss, Rebecca E.; Demuth, Julie L.; Lazo, Jeffrey K. Weather and Forecasting, Vol. 23, Issue 5 https://doi.org/10.1175/2008WAF2007088.1	journal	October 2008
Estimating Influenza Disease Burden from Population-Based Surveillance Data in the United States Reed, Carrie; Chaves, Sandra S.; Daily Kirley, Pam PLOS ONE, Vol. 10, Issue 3 https://doi.org/10.1371/journal.pone.0118369	journal	March 2015
CDC Grand Rounds: Modeling and Public Health Decision-Making Fischer, Leah S.; Santibanez, Scott; Hatchett, Richard J. MMWR. Morbidity and Mortality Weekly Report, Vol. 65, Issue 48 https://doi.org/10.15585/mmwr.mm6548a4	journal	December 2016
Update: Influenza Activity in the United States During the 2017–18 Season and Composition of the 2018–19 Influenza Vaccine Garten, Rebecca; Blanton, Lenee; Elal, Anwar Isa Abd MMWR. Morbidity and Mortality Weekly Report, Vol. 67, Issue 22 https://doi.org/10.15585/mmwr.mm6722a4	journal	June 2018
Results from the centers for disease control and prevention’s predict the 2013–2014 Influenza Season Challenge Biggerstaff, Matthew; Alper, David; Dredze, Mark Figshare https://doi.org/10.6084/m9.figshare.c.3622391.v1	collection	January 2016

Similar Records

Accuracy of real-time multi-model ensemble forecasts for seasonal influenza in the U.S.

Journal Article · Thu Nov 21 23:00:00 EST 2019 · PLoS Computational Biology (Online) · OSTI ID:1604056

Forecasting seasonal influenza with a state-space SIR model

Journal Article · Sat Apr 08 00:00:00 EDT 2017 · The Annals of Applied Statistics · OSTI ID:1406200

Forecasting the 2013–2014 influenza season using Wikipedia

Journal Article · Thu May 14 00:00:00 EDT 2015 · PLoS Computational Biology (Online) · OSTI ID:1214725

Related Subjects

59 BASIC BIOLOGICAL SCIENCES
decision making
disease outbreaks
emergency preparedness
forecast
infectious disease
influenza
pandemic

Applying infectious disease forecasting to public health: a path forward using influenza forecasting examples

Citation Formats

References (37)

Similar Records

Related Subjects