Multivariate Markovian Modeling of Tuberculosis: Forecast for the United States

We have developed a computer-implemented, multivariate Markov chain model to project tuberculosis (TB) incidence in the United States from 1980 to 2010 in disaggregated demographic groups. Uncertainty in model parameters and in the projections is represented by fuzzy numbers. Projections are made un...

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Main Authors: Sara M. Debanne, Roger A. Bielefeld, George M. Cauthen, Thomas M. Daniel, Douglas Y. Rowland
Format: Article
Language:English
Published: Centers for Disease Control and Prevention 2000-04-01
Series:Emerging Infectious Diseases
Subjects:
Online Access:https://wwwnc.cdc.gov/eid/article/6/2/00-0207_article
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spelling doaj-e793824093134be28d4e8c0e232aa5f22020-11-24T22:07:38ZengCenters for Disease Control and PreventionEmerging Infectious Diseases1080-60401080-60592000-04-016214815710.3201/eid0602.000207Multivariate Markovian Modeling of Tuberculosis: Forecast for the United StatesSara M. DebanneRoger A. BielefeldGeorge M. CauthenThomas M. DanielDouglas Y. RowlandWe have developed a computer-implemented, multivariate Markov chain model to project tuberculosis (TB) incidence in the United States from 1980 to 2010 in disaggregated demographic groups. Uncertainty in model parameters and in the projections is represented by fuzzy numbers. Projections are made under the assumption that current TB control measures will remain unchanged for the projection period. The projections of the model demonstrate an intermediate increase in national TB incidence (similar to that which actually occurred) followed by continuing decline. The rate of decline depends strongly on geographic, racial, and ethnic characteristics. The model predicts that the rate of decline in the number of cases among Hispanics will be slower than among white non-Hispanics and black non-Hispanics--a prediction supported by the most recent data.https://wwwnc.cdc.gov/eid/article/6/2/00-0207_articleMultivariate Markovian modelingTuberculosisUnited States
collection DOAJ
language English
format Article
sources DOAJ
author Sara M. Debanne
Roger A. Bielefeld
George M. Cauthen
Thomas M. Daniel
Douglas Y. Rowland
spellingShingle Sara M. Debanne
Roger A. Bielefeld
George M. Cauthen
Thomas M. Daniel
Douglas Y. Rowland
Multivariate Markovian Modeling of Tuberculosis: Forecast for the United States
Emerging Infectious Diseases
Multivariate Markovian modeling
Tuberculosis
United States
author_facet Sara M. Debanne
Roger A. Bielefeld
George M. Cauthen
Thomas M. Daniel
Douglas Y. Rowland
author_sort Sara M. Debanne
title Multivariate Markovian Modeling of Tuberculosis: Forecast for the United States
title_short Multivariate Markovian Modeling of Tuberculosis: Forecast for the United States
title_full Multivariate Markovian Modeling of Tuberculosis: Forecast for the United States
title_fullStr Multivariate Markovian Modeling of Tuberculosis: Forecast for the United States
title_full_unstemmed Multivariate Markovian Modeling of Tuberculosis: Forecast for the United States
title_sort multivariate markovian modeling of tuberculosis: forecast for the united states
publisher Centers for Disease Control and Prevention
series Emerging Infectious Diseases
issn 1080-6040
1080-6059
publishDate 2000-04-01
description We have developed a computer-implemented, multivariate Markov chain model to project tuberculosis (TB) incidence in the United States from 1980 to 2010 in disaggregated demographic groups. Uncertainty in model parameters and in the projections is represented by fuzzy numbers. Projections are made under the assumption that current TB control measures will remain unchanged for the projection period. The projections of the model demonstrate an intermediate increase in national TB incidence (similar to that which actually occurred) followed by continuing decline. The rate of decline depends strongly on geographic, racial, and ethnic characteristics. The model predicts that the rate of decline in the number of cases among Hispanics will be slower than among white non-Hispanics and black non-Hispanics--a prediction supported by the most recent data.
topic Multivariate Markovian modeling
Tuberculosis
United States
url https://wwwnc.cdc.gov/eid/article/6/2/00-0207_article
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