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Oxford University Press - PMC COVID-19 Collection logoLink to Oxford University Press - PMC COVID-19 Collection
. 2021 Aug 3:ciab673. doi: 10.1093/cid/ciab673

Improving Pandemic Response: Employing Mathematical Modeling to Confront COVID-19

Matthew Biggerstaff 1,2,, Rachel B Slayton 1,2, Michael A Johansson 1,2, Jay C Butler 2
PMCID: PMC8385824  PMID: 34343282

Abstract

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.

Keywords: modeling, COVID-19, pandemic, forecasting, public health


Articles from Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America are provided here courtesy of Oxford University Press

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