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

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BMC Public Health. 2019 Dec 10;19(1):1659. doi: 10.1186/s12889-019-7966-8. Applying infectious disease forecasting to public health: a path forward using influenza forecasting examples.

Lutz CS^1,2,3, Huynh MP⁴, Schroeder M⁴, Anyatonwu S⁵, Dahlgren FS⁶, Danyluk G⁷, Fernandez D⁸, Greene SK⁹, Kipshidze N¹⁰, Liu L¹¹, Mgbere O¹², McHugh LA¹³, Myers JF¹⁴, Siniscalchi A¹⁵, Sullivan AD¹⁶, West N¹⁷, Johansson MA¹⁸, Biggerstaff M⁶.
Author information

1 Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, 30329, USA. chelsea.lutz@jhu.edu. 2 Oak Ridge Institute for Science and Education, United States Department of Energy, Oak Ridge, TN, 37830, USA. chelsea.lutz@jhu.edu. 3 Department of International Health, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, 21205, USA. chelsea.lutz@jhu.edu. 4 Infectious Disease Program, Council of State and Territorial Epidemiologists, Atlanta, GA, 30345, USA. 5 PHI/CDC Global Health Fellowship Program, Public Health Institute, Oakland, CA, 94607, USA. 6 Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, 30329, USA. 7 Florida Department of Health in Polk County, Bartow, FL, 33830, USA. 8 Epidemiology, Disease Control, and Immunization Services, Florida Department of Health in Miami-Dade County, Miami, FL, 33126, USA. 9 Bureau of Communicable Disease, New York City Department of Health and Mental Hygiene, Queens, New York, NY, 11101, USA. 10 New York University, New York, NY, 100003, USA. 11 Office of Science, Surveillance, and Technology, Harris County Public Health, Houston, TX, 77027, USA. 12 Disease Prevention and Control Division, Houston Health Department, Houston, TX, 77054, USA. 13 Communicable Disease Service, New Jersey Department of Health, Trenton, NJ, 08608, USA. 14 Infectious Diseases Branch, California Department of Public Health, Richmond, CA, 94804, USA. 15 Infectious Disease Section, Epidemiology & Emerging Infections Program, State of Connecticut Department of Health, Hartford, CT, 06134, USA. 16 Division of Prevention and Community Health, Washington State Department of Health, Olympia, WA, 98504, USA. 17 Acute and Communicable Disease Prevention, Oregon Health Authority, Portland, OR, 97232, USA. 18 Division of Vector-Borne Diseases, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, San Juan, PR, 00920, USA.

Abstract

BACKGROUND:

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.
MAIN BODY:

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.
CONCLUSIONS:

These efforts, along with other infectious disease forecasting initiatives, can foster the continued advancement of forecasting science.


KEYWORDS:

Decision making; Disease outbreaks; Emergency preparedness; Forecast; Infectious disease; Influenza; Pandemic

PMID: 31823751 DOI: 10.1186/s12889-019-7966-8
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