A dynamic Markov model for forecasting diabetes prevalence in the United States through 2050

A dynamic Markov model for forecasting diabetes prevalence in the United States through 2050

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Article ID: iaor20042144
Country: Netherlands
Volume: 6
Issue: 3
Start Page Number: 155
End Page Number: 164
Publication Date: Sep 2003
Journal: Health Care Management Science
Authors: , , , , , ,
Keywords: markov processes, simulation: applications
Abstract:

This study develops forecasts of the number of people with diagnosed diabetes and diagnosed diabetes prevalence in the United States through the year 2050. A Markov modeling framework is used to generate forecasts by age, race and ethnicity, and sex. The model forecasts the number of individuals in each of three states (diagnosed with diabetes, not diagnosed with diabetes, and death) in each year using inputs of estimated diagnosed diabetes prevalence and incidence; the relative risk of mortality from diabetes compared with no diabetes; and US Census Bureau estimates of current population, live births, net migration, and the mortality rate of the general population. The projected number of people with diagnosed diabetes rises from 12.0 million in 2000 to 39.0 million in 2050, implying an increase in diagnosed diabetes prevalence from 4.4% in 2000 to 9.7% in 2050.

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