Mimi P. Huynh

Council of State and Territorial Epidemiologists

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Danielle Fernández

Centers for Disease Control and Prevention

Michael A. Johansson

Puerto Rico Department of Health

Leann Liu

Harris Health System

Lisa McHugh

University of Queensland

Monica Schroeder

Council of State and Territorial Epidemiologists

Osaro Mgbere

Houston Health and Human Services Department

Matthew Biggerstaff

National Center for Immunization and Respiratory Diseases

Chelsea S. Lutz

National Center for Immunization and Respiratory Diseases

Nodar Kipshidze

Yale University

F. Scott Dahlgren

Delft University of Technology

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Centers for Disease Control and Prevention

National Center for Immunization and Respiratory Diseases

Public Health Institute

Florida Department of Health

University of Colorado System

University of Colorado Boulder

National Center for Emerging and Zoonotic Infectious Diseases

Government of Western Australia Department of Health

Council of State and Territorial Epidemiologists

Emory University

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

BMC Public Health (2019)

Chelsea S. Lutz Mimi P. Huynh Monica Schroeder Sophia Anyatonwu F. Scott Dahlgren

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.

Pandemic

Biostatistics

10.1186/s12889-019-7966-8

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