Staying ahead of the curve : modeling and public health decision-making

Details

• Personal Author:
  Meyers, Lauren Ancel ; Meltzer, Martin I. ; Jernigan, Daniel B. ; Hatchett, Richard ; Iskander, John K. ; Thorpe, Phoebe ; Laird, Susan
• Corporate Authors:
  Centers for Disease Control and Prevention (U.S.). Office of the Associate Director for Communication. ; National Center for Emerging and Zoonotic Infectious Diseases (U.S.). Division of Preparedness and Emerging Infections. ; National Center for Immunization and Respiratory Diseases (U.S.). Influenza Division.
• Description:
  Where are infections spreading? How many people will be affected? What are some different ways to stop the spread of an epidemic? These are questions that the public and decision-makers, including health officials, often ask during an outbreak or emergency. In a process known as modeling, scientists analyze data using complex mathematical methods to provide answers to these and other questions during an emergency response. Just as models are used to predict the path of a hurricane, models can be used to predict the impact of interventions during an epidemic. Modeling is helpful in more than just emergency situations, though. For example, models are also used to predict when the next flu season will start and to decide which flu strains to include in the flu shot each year.
  
  Models provide the foresight that can help decision-makers better prepare for the future. Modelers attempt to use all available data to formulate predictions. As more data accumulate, the accuracy of predictions improves. Models can also help us understand situations that were unclear in the past by looking at old data in new ways. With models, decision-makers can look to the future with confidence in their ability to respond to outbreaks and public health emergencies.
  
  Tuesday, January 19, 2016 at 1pm ET
  
  Presented by: Lauren Ancel Meyers, PhD, Professor, Department of Integrative Biology, Department of Statistics and Data Sciences, University of Texas at Austin ["Modeling to Support Outbreak Preparedness, Surveillance and Response"]; Martin Meltzer, PhD, Lead, Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, CDC ["What Do Policy Makers Expect from Modelers during a Response?"]; Daniel Jernigan, MD, Director, Influenza Division, National Center for Immunization and Respiratory Diseases, CDC ["Application of Modeling and Forecasting for Preventing Influenza"]; Richard Hatchett, MD, Chief Medical Officer, Deputy Director for Strategic Sciences, Biomedical Advanced Research and Development Authority, Office of the Assistant Secretary for Preparedness and Response ["Explaining Phenomena, Providing Foresight, and Making Predictions"].
  
  Facilitated by: John Iskander, MD, MPH, Scientific Director, Public Health Grand Rounds; Phoebe Thorpe, MD, MPH, Deputy Scientific Director, Public Health Grand Rounds; Susan Laird, MSN, RN, Communications Director, Public Health Grand Rounds.
  
  
• Subjects:
  Disaster Planning Disease Outbreaks Epidemiologic Methods Models, Theoretical Public Health Surveillance
• Series:
  Public Health Grand Rounds
• Document Type:
  Text
• Genre:
  Presentation
• Pages in Document:
  63 numbered slides
• Citation:
  Public health grand rounds ; 2016 January 19
• Collection(s):
  Stephen B. Thacker CDC Library
• Main Document Checksum:
  urn:sha-512:6d9fa6677f861d2f7c67b2f3405beee0a41cfb9e9f6dd7a4488094fce2d9cc1893f7d35b3cea68c09513d42d660c17397ab08803a3bc5202182a76738ae6f43d
• Download URL:
  https://stacks.cdc.gov/view/cdc/37601/cdc_37601_DS1.pdf
• File Type:
  [PDF - 9.51 MB ]