
Matthew Biggerstaff
Epidemiologist/Team Lead
U.S. Department of Health and Human Services Continue Reading Matthew Biggerstaff
Improving Pandemic Response: Employing Mathematical Modeling to Confront COVID-19.
Modeling complements surveillance data to inform COVID-19 public health decision making and policy development. This includes the use of modeling to improve situational awareness, to assess epidemiological characteristics, and to inform the evidence base for prevention strategies. To enhance modeling utility in future public health emergencies, the Centers for Disease Control and Prevention (CDC) launched the Infectious Disease Modeling and Analytics Initiative. The initiative objectives are to: (1) strengthen leadership in infectious disease modeling, epidemic forecasting, and advanced analytic work; (2) build and cultivate a community of skilled modeling and analytics practitioners and consumers across CDC; (3) strengthen and support internal and external applied modeling and analytic work; and, (4) working with partners, coordinate government-wide advanced data modeling and analytics for infectious diseases. These efforts are critical to help prepare CDC, the country, and the world to respond effectively to present and future infectious disease threats.
Clinical infectious diseases : an official publication of the Infectious Diseases Society of America

Epidemiologist/Team Lead
U.S. Department of Health and Human Services Continue Reading Matthew Biggerstaff

Research Professor
U.S. Department of Health and Human Services Continue Reading Michael Johansson

Director, Office of Mathematical Modeling, Division of Healthcare Quality Promotion
U.S. Department of Health and Human Services Continue Reading Rachel Slayton