Annual Mycobacterium tuberculosis Infection Risk and Interpretation of Clustering Statistics
Several recent studies have used proportions of tuberculosis cases sharing identical DNA fingerprint patterns (i.e., isolate clustering) to estimate the extent of disease attributable to recent transmission. Using a model of introduction and transmission of strains with different DNA fingerprint pat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Centers for Disease Control and Prevention
2003-02-01
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| Series: | Emerging Infectious Diseases |
| Subjects: | |
| Online Access: | https://wwwnc.cdc.gov/eid/article/9/2/01-0530_article |
| _version_ | 1828385506051751936 |
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| author | Emilia Vynnycky Martien W. Borgdorff Dick van Soolingen Paul E.M. Fine |
| author_facet | Emilia Vynnycky Martien W. Borgdorff Dick van Soolingen Paul E.M. Fine |
| author_sort | Emilia Vynnycky |
| collection | DOAJ |
| description | Several recent studies have used proportions of tuberculosis cases sharing identical DNA fingerprint patterns (i.e., isolate clustering) to estimate the extent of disease attributable to recent transmission. Using a model of introduction and transmission of strains with different DNA fingerprint patterns, we show that the properties and interpretation of clustering statistics may differ substantially between settings. For some unindustrialized countries, where the annual risk for infection has changed little over time, 70% to 80% of all age groups may be clustered during a 3-year period, which underestimates the proportion of disease attributable to recent transmission. In contrast, for a typical industrialized setting (the Netherlands), clustering declines with increasing age (from 75% to 15% among young and old patients, respectively) and underestimates the extent of recent transmission only for young patients. We conclude that, in some settings, clustering is an unreliable indicator of the extent of recent transmission. |
| first_indexed | 2024-12-10T05:21:14Z |
| format | Article |
| id | doaj.art-8af8feb9f5ba4073beac00f671b26b81 |
| institution | Directory Open Access Journal |
| issn | 1080-6040 1080-6059 |
| language | English |
| last_indexed | 2024-12-10T05:21:14Z |
| publishDate | 2003-02-01 |
| publisher | Centers for Disease Control and Prevention |
| record_format | Article |
| series | Emerging Infectious Diseases |
| spelling | doaj.art-8af8feb9f5ba4073beac00f671b26b812022-12-22T02:00:47ZengCenters for Disease Control and PreventionEmerging Infectious Diseases1080-60401080-60592003-02-019217618310.3201/eid0902.010530Annual Mycobacterium tuberculosis Infection Risk and Interpretation of Clustering StatisticsEmilia VynnyckyMartien W. BorgdorffDick van SoolingenPaul E.M. FineSeveral recent studies have used proportions of tuberculosis cases sharing identical DNA fingerprint patterns (i.e., isolate clustering) to estimate the extent of disease attributable to recent transmission. Using a model of introduction and transmission of strains with different DNA fingerprint patterns, we show that the properties and interpretation of clustering statistics may differ substantially between settings. For some unindustrialized countries, where the annual risk for infection has changed little over time, 70% to 80% of all age groups may be clustered during a 3-year period, which underestimates the proportion of disease attributable to recent transmission. In contrast, for a typical industrialized setting (the Netherlands), clustering declines with increasing age (from 75% to 15% among young and old patients, respectively) and underestimates the extent of recent transmission only for young patients. We conclude that, in some settings, clustering is an unreliable indicator of the extent of recent transmission.https://wwwnc.cdc.gov/eid/article/9/2/01-0530_articletuberculosismolecular epidemiologyDNA fingerprintingclusteringmathematical modelinginfection risk |
| spellingShingle | Emilia Vynnycky Martien W. Borgdorff Dick van Soolingen Paul E.M. Fine Annual Mycobacterium tuberculosis Infection Risk and Interpretation of Clustering Statistics Emerging Infectious Diseases tuberculosis molecular epidemiology DNA fingerprinting clustering mathematical modeling infection risk |
| title | Annual Mycobacterium tuberculosis Infection Risk and Interpretation of Clustering Statistics |
| title_full | Annual Mycobacterium tuberculosis Infection Risk and Interpretation of Clustering Statistics |
| title_fullStr | Annual Mycobacterium tuberculosis Infection Risk and Interpretation of Clustering Statistics |
| title_full_unstemmed | Annual Mycobacterium tuberculosis Infection Risk and Interpretation of Clustering Statistics |
| title_short | Annual Mycobacterium tuberculosis Infection Risk and Interpretation of Clustering Statistics |
| title_sort | annual mycobacterium tuberculosis infection risk and interpretation of clustering statistics |
| topic | tuberculosis molecular epidemiology DNA fingerprinting clustering mathematical modeling infection risk |
| url | https://wwwnc.cdc.gov/eid/article/9/2/01-0530_article |
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