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BMC Infect Dis. 2019 Mar 12;19(1):244. doi: 10.1186/s12879-019-3870-1.

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

Author information

1
Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia. 078yayu@gmail.com.
2
Department of Epidemiology and Biostatistics, Institute of Public Health, University of Gondar, Gondar, Ethiopia. 078yayu@gmail.com.
3
Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
4
Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, Queensland, Australia.
5
Department of Medicine at Royal Melbourne Hospital, University of Melbourne, Melbourne, Victoria, Australia.
6
The Victorian Tuberculosis Program at the Peter Doherty Institute, Melbourne, Victoria, Australia.
7
Department of Microbiology and Immunology, University of Melbourne, Melbourne, Victoria, Australia.
8
Department of Health and Human Services, Health Protection branch, Melbourne, Victoria, Australia.

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.

KEYWORDS:

Negative binomial distribution; Super-spreading; Tuberculosis; Victoria

PMID:
30866840
PMCID:
PMC6417041
DOI:
10.1186/s12879-019-3870-1
[Indexed for MEDLINE]
Free PMC Article

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