Frontiers in Public Health (Jul 2024)
Infectious disease surveillance needs for the United States: lessons from Covid-19
- Marc Lipsitch,
- Marc Lipsitch,
- Mary T. Bassett,
- John S. Brownstein,
- Paul Elliott,
- David Eyre,
- M. Kate Grabowski,
- James A. Hay,
- Michael A. Johansson,
- Stephen M. Kissler,
- Daniel B. Larremore,
- Daniel B. Larremore,
- Jennifer E. Layden,
- Justin Lessler,
- Ruth Lynfield,
- Duncan MacCannell,
- Lawrence C. Madoff,
- C. Jessica E. Metcalf,
- Lauren A. Meyers,
- Sylvia K. Ofori,
- Celia Quinn,
- Ana I. Bento,
- Nicholas G. Reich,
- Steven Riley,
- Roni Rosenfeld,
- Matthew H. Samore,
- Rangarajan Sampath,
- Rachel B. Slayton,
- David L. Swerdlow,
- Shaun Truelove,
- Jay K. Varma,
- Yonatan H. Grad
Affiliations
- Marc Lipsitch
- Center for Forecasting and Outbreak Analytics, US Centers for Disease Control and Prevention, Atlanta, GA, United States
- Marc Lipsitch
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, United States
- Mary T. Bassett
- François-Xavier Bagnoud Center for Health and Human Rights, Department of Social and Behavioral Sciences, Harvard T. H. Chan School of Public Health, Boston, MA, United States
- John S. Brownstein
- Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
- Paul Elliott
- Department of Epidemiology and Public Health Medicine, Imperial College London, London, United Kingdom
- David Eyre
- Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- M. Kate Grabowski
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
- James A. Hay
- Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- Michael A. Johansson
- Division of Vector-Borne Diseases, US Centers for Disease Control and Prevention, Atlanta, GA, United States
- Stephen M. Kissler
- Department of Computer Science, University of Colorado Boulder, Boulder, CO, United States
- Daniel B. Larremore
- Department of Computer Science, University of Colorado Boulder, Boulder, CO, United States
- Daniel B. Larremore
- 0BioFrontiers Institute, University of Colorado Boulder, Boulder, CO, United States
- Jennifer E. Layden
- 1Office of Public Health Data, Surveillance, and Technology, US Centers for Disease Control and Prevention, Atlanta, GA, United States
- Justin Lessler
- 2Department of Epidemiology, UNC Gillings School of Public Health, Chapel Hill, NC, United States
- Ruth Lynfield
- 3Minnesota Department of Health, Minneapolis, MN, United States
- Duncan MacCannell
- 4US Centers for Disease Control and Prevention, Office of Advanced Molecular Detection, Atlanta, GA, United States
- Lawrence C. Madoff
- 5Massachusetts Department of Public Health, Boston, MA, United States
- C. Jessica E. Metcalf
- 6Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, United States
- Lauren A. Meyers
- 7Department of Integrative Biology, University of Texas at Austin, Austin, TX, United States
- Sylvia K. Ofori
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, United States
- Celia Quinn
- 8Division of Disease Control, New York City Department of Health and Mental Hygiene, New York City, NY, United States
- Ana I. Bento
- 9Department of Public and Ecosystem Health, College of Veterinary Medicine, Cornell University, Ithaca, NY, United States
- Nicholas G. Reich
- 0Departments of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, United States
- Steven Riley
- 1United Kingdom Health Security Agency, London, United Kingdom
- Roni Rosenfeld
- 2Departments of Computer Science and Computational Biology, Carnegie Melon University, Pittsburgh, PA, United States
- Matthew H. Samore
- 3Division of Epidemiology, Department of Medicine, University of Utah, Salt Lake City, UT, United States
- Rangarajan Sampath
- 4Siemens Healthcare Diagnostics, Inc., San Diego, CA, United States
- Rachel B. Slayton
- 5Division of Healthcare Quality Promotion, US Centers for Disease Control and Prevention, Atlanta, GA, United States
- David L. Swerdlow
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, United States
- Shaun Truelove
- 2Department of Epidemiology, UNC Gillings School of Public Health, Chapel Hill, NC, United States
- Jay K. Varma
- 6SIGA Technologies, New York City, NY, United States
- Yonatan H. Grad
- 7Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, United States
- DOI
- https://doi.org/10.3389/fpubh.2024.1408193
- Journal volume & issue
-
Vol. 12
Abstract
The COVID-19 pandemic has highlighted the need to upgrade systems for infectious disease surveillance and forecasting and modeling of the spread of infection, both of which inform evidence-based public health guidance and policies. Here, we discuss requirements for an effective surveillance system to support decision making during a pandemic, drawing on the lessons of COVID-19 in the U.S., while looking to jurisdictions in the U.S. and beyond to learn lessons about the value of specific data types. In this report, we define the range of decisions for which surveillance data are required, the data elements needed to inform these decisions and to calibrate inputs and outputs of transmission-dynamic models, and the types of data needed to inform decisions by state, territorial, local, and tribal health authorities. We define actions needed to ensure that such data will be available and consider the contribution of such efforts to improving health equity.
Keywords
- pandemic
- COVID-19
- surveillance and forecast system
- public health
- infectious diseases
- mathematical model
