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The role of super-spreading events in Mycobacterium tuberculosis transmission: evidence from contact tracing

BACKGROUND: In current epidemiology of tuberculosis (TB), heterogeneity in infectiousness among TB patients is a challenge, which is not well studied. We aimed to quantify this heterogeneity and the presence of “super-spreading” events that can assist in designing optimal public health interventions...

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Autores principales: Melsew, Yayehirad A., Gambhir, Manoj, Cheng, Allen C., McBryde, Emma S., Denholm, Justin T., Tay, Ee Laine, Trauer, James M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417041/
https://www.ncbi.nlm.nih.gov/pubmed/30866840
http://dx.doi.org/10.1186/s12879-019-3870-1
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author Melsew, Yayehirad A.
Gambhir, Manoj
Cheng, Allen C.
McBryde, Emma S.
Denholm, Justin T.
Tay, Ee Laine
Trauer, James M.
author_facet Melsew, Yayehirad A.
Gambhir, Manoj
Cheng, Allen C.
McBryde, Emma S.
Denholm, Justin T.
Tay, Ee Laine
Trauer, James M.
author_sort Melsew, Yayehirad A.
collection PubMed
description BACKGROUND: In current epidemiology of tuberculosis (TB), heterogeneity in infectiousness among TB patients is a challenge, which is not well studied. We aimed to quantify this heterogeneity and the presence of “super-spreading” events that can assist in designing optimal public health interventions. METHODS: TB epidemiologic investigation data notified between 1 January 2005 and 31 December 2015 from Victoria, Australia were used to quantify TB patients’ heterogeneity in infectiousness and super-spreading events. We fitted a negative binomial offspring distribution (NBD) for the number of secondary infections and secondary active TB disease each TB patient produced. The dispersion parameter, k, of the NBD measures the level of heterogeneity, where low values of k (e.g. k < 1) indicate over-dispersion. Super-spreading was defined as patients causing as many or more secondary infections as the 99th centile of an equivalent homogeneous distribution. Contact infection was determined based on a tuberculin skin test (TST) result of ≥10 mm. A NBD model was fitted to identify index characteristics that were associated with the number of contacts infected and risk ratios (RRs) were used to quantify the strength of this association. RESULTS: There were 4190 (2312 pulmonary and 1878 extrapulmonary) index TB patients and 18,030 contacts. A total of 15,522 contacts were tested with TST, of whom 3213 had a result of ≥10 mm. The dispersion parameter, k for secondary infections was estimated at 0.16 (95%CI 0.14–0.17) and there were 414 (9.9%) super-spreading events. From the 3213 secondary infections, 2415 (75.2%) were due to super-spreading events. There were 226 contacts who developed active TB disease and a higher level of heterogeneity was found for this outcome than for secondary infection, with k estimated at 0.036 (95%CI 0.025–0.046). In regression analyses, we found that infectiousness was greater among index patients found by clinical presentation and those with bacteriological confirmation. CONCLUSION: TB transmission is highly over dispersed and super-spreading events are responsible for a substantial majority of secondary infections. Heterogeneity of transmission and super-spreading are critical issues to consider in the design of interventions and models of TB transmission dynamics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-019-3870-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-64170412019-03-25 The role of super-spreading events in Mycobacterium tuberculosis transmission: evidence from contact tracing Melsew, Yayehirad A. Gambhir, Manoj Cheng, Allen C. McBryde, Emma S. Denholm, Justin T. Tay, Ee Laine Trauer, James M. BMC Infect Dis Research Article BACKGROUND: In current epidemiology of tuberculosis (TB), heterogeneity in infectiousness among TB patients is a challenge, which is not well studied. We aimed to quantify this heterogeneity and the presence of “super-spreading” events that can assist in designing optimal public health interventions. METHODS: TB epidemiologic investigation data notified between 1 January 2005 and 31 December 2015 from Victoria, Australia were used to quantify TB patients’ heterogeneity in infectiousness and super-spreading events. We fitted a negative binomial offspring distribution (NBD) for the number of secondary infections and secondary active TB disease each TB patient produced. The dispersion parameter, k, of the NBD measures the level of heterogeneity, where low values of k (e.g. k < 1) indicate over-dispersion. Super-spreading was defined as patients causing as many or more secondary infections as the 99th centile of an equivalent homogeneous distribution. Contact infection was determined based on a tuberculin skin test (TST) result of ≥10 mm. A NBD model was fitted to identify index characteristics that were associated with the number of contacts infected and risk ratios (RRs) were used to quantify the strength of this association. RESULTS: There were 4190 (2312 pulmonary and 1878 extrapulmonary) index TB patients and 18,030 contacts. A total of 15,522 contacts were tested with TST, of whom 3213 had a result of ≥10 mm. The dispersion parameter, k for secondary infections was estimated at 0.16 (95%CI 0.14–0.17) and there were 414 (9.9%) super-spreading events. From the 3213 secondary infections, 2415 (75.2%) were due to super-spreading events. There were 226 contacts who developed active TB disease and a higher level of heterogeneity was found for this outcome than for secondary infection, with k estimated at 0.036 (95%CI 0.025–0.046). In regression analyses, we found that infectiousness was greater among index patients found by clinical presentation and those with bacteriological confirmation. CONCLUSION: TB transmission is highly over dispersed and super-spreading events are responsible for a substantial majority of secondary infections. Heterogeneity of transmission and super-spreading are critical issues to consider in the design of interventions and models of TB transmission dynamics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12879-019-3870-1) contains supplementary material, which is available to authorized users. BioMed Central 2019-03-12 /pmc/articles/PMC6417041/ /pubmed/30866840 http://dx.doi.org/10.1186/s12879-019-3870-1 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Melsew, Yayehirad A.
Gambhir, Manoj
Cheng, Allen C.
McBryde, Emma S.
Denholm, Justin T.
Tay, Ee Laine
Trauer, James M.
The role of super-spreading events in Mycobacterium tuberculosis transmission: evidence from contact tracing
title The role of super-spreading events in Mycobacterium tuberculosis transmission: evidence from contact tracing
title_full The role of super-spreading events in Mycobacterium tuberculosis transmission: evidence from contact tracing
title_fullStr The role of super-spreading events in Mycobacterium tuberculosis transmission: evidence from contact tracing
title_full_unstemmed The role of super-spreading events in Mycobacterium tuberculosis transmission: evidence from contact tracing
title_short The role of super-spreading events in Mycobacterium tuberculosis transmission: evidence from contact tracing
title_sort role of super-spreading events in mycobacterium tuberculosis transmission: evidence from contact tracing
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417041/
https://www.ncbi.nlm.nih.gov/pubmed/30866840
http://dx.doi.org/10.1186/s12879-019-3870-1
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