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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Centers for Disease Control and Prevention
2000-04-01
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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 |
work_keys_str_mv |
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