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

Abstract 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 inter...

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Main Authors: Yayehirad A. Melsew, Manoj Gambhir, Allen C. Cheng, Emma S. McBryde, Justin T. Denholm, Ee Laine Tay, James M. Trauer
Format: Article
Language:English
Published: BMC 2019-03-01
Series:BMC Infectious Diseases
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12879-019-3870-1
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spelling doaj-60725c0e6ab845aa8f178054e4b7e6442020-11-25T02:47:52ZengBMCBMC Infectious Diseases1471-23342019-03-011911910.1186/s12879-019-3870-1The role of super-spreading events in Mycobacterium tuberculosis transmission: evidence from contact tracingYayehirad A. Melsew0Manoj Gambhir1Allen C. Cheng2Emma S. McBryde3Justin T. Denholm4Ee Laine Tay5James M. Trauer6Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash UniversityDepartment of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash UniversityDepartment of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash UniversityAustralian Institute of Tropical Health and Medicine, James Cook UniversityThe Victorian Tuberculosis Program at the Peter Doherty InstituteDepartment of Health and Human Services, Health Protection branchDepartment of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash UniversityAbstract 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.http://link.springer.com/article/10.1186/s12879-019-3870-1TuberculosisSuper-spreadingNegative binomial distributionVictoria
collection DOAJ
language English
format Article
sources DOAJ
author Yayehirad A. Melsew
Manoj Gambhir
Allen C. Cheng
Emma S. McBryde
Justin T. Denholm
Ee Laine Tay
James M. Trauer
spellingShingle Yayehirad A. Melsew
Manoj Gambhir
Allen C. Cheng
Emma S. McBryde
Justin T. Denholm
Ee Laine Tay
James M. Trauer
The role of super-spreading events in Mycobacterium tuberculosis transmission: evidence from contact tracing
BMC Infectious Diseases
Tuberculosis
Super-spreading
Negative binomial distribution
Victoria
author_facet Yayehirad A. Melsew
Manoj Gambhir
Allen C. Cheng
Emma S. McBryde
Justin T. Denholm
Ee Laine Tay
James M. Trauer
author_sort Yayehirad A. Melsew
title 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_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_sort role of super-spreading events in mycobacterium tuberculosis transmission: evidence from contact tracing
publisher BMC
series BMC Infectious Diseases
issn 1471-2334
publishDate 2019-03-01
description Abstract 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.
topic Tuberculosis
Super-spreading
Negative binomial distribution
Victoria
url http://link.springer.com/article/10.1186/s12879-019-3870-1
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