Assessing lifestyle interventions to improve cardiovascular health using an agent-based model

Yan Li, Nan Kong, Mark Lawley, Jose A. Pagan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Cardiovascular disease (CVD) is the leading cause of death in the United States (US) and places a heavy economic burden on the healthcare system. Recognizing the importance of CVD prevention, in recent years the American Heart Association (AHA) began to emphasize the need to increase awareness of key risk factors of CVD and proposed a new concept called ideal cardiovascular health. Based on this concept, we developed an agent-based model that is designed to capture individual health progression and study emergent CVD-related population health outcomes (diabetes, myocardial infarction, stroke and death) over a specified time period. We present some preliminary numerical results, which demonstrate the predictive validity of the model and show how the model could be used in practice by assessing the impact of a set of hypothetical lifestyle interventions on CVD-related health outcomes. Our model is designed to help policy-makers assess and compare different intervention programs targeting CVD prevention for the population of their interest.

Original languageEnglish (US)
Title of host publicationProceedings of the 2014 Winter Simulation Conference, WSC 2014
EditorsAndreas Tolk, Levent Yilmaz, Saikou Y. Diallo, Ilya O. Ryzhov
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1221-1232
Number of pages12
ISBN (Electronic)9781479974863
DOIs
StatePublished - Jan 23 2015
Event2014 Winter Simulation Conference, WSC 2014 - Savannah, United States
Duration: Dec 7 2014Dec 10 2014

Publication series

NameProceedings - Winter Simulation Conference
Volume2015-January
ISSN (Print)0891-7736

Other

Other2014 Winter Simulation Conference, WSC 2014
Country/TerritoryUnited States
CitySavannah
Period12/7/1412/10/14

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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