TB Manual

The following techniques are key programmatic tools for outbreak detection and response, along with standard field epidemiology data.^81,82

Mycobacterial interspersed repetitive units: Variable Number Tandem Repeats (MIRU-VNTR) involves counting the number of repeats in up to 24 sites in the Mycobacterium tuberculosis (M. tuberculosis) genome and using this information to generate a signature pattern. If the MIRU-VNTR patterns of isolates from two persons are different, this usually means there was no transmission, while if the patterns are the same, this may support recent transmission between them, that can then be refuted or confirmed by the epidemiologic investigation. This technique can also be used to help determine whether recurrent TB is a relapse or new infection, and to investigate potential specimen mix-ups in the lab.

Whole genome sequencing: Whole genome sequencing (WGS) provides information on nearly 100% of the M. tuberculosis genome. Single base-pair changes, called single nucleotide polymorphisms (SNPs), in one patient’s M. tuberculosis genome can be compared to another’s to help rule out transmission, by applying a specific threshold of similarity as measured in SNPs. In Canada, WGS for TB was first applied to an outbreak in British Columbia more than a decade ago.⁵⁰ WGS identified two separate transmission clusters, whereas only one was identified with MIRU-VNTR. WGS has since been applied in a variety of settings, including to investigate transmission among persons experiencing homelessness in Toronto⁸³ and in Northern Canada.^84–87

At present, MIRU-VNTR offers some advantages when compared to WGS: MIRU is already performed as part of public health surveillance in Canada; provincial and national laboratories have extensive experience with this method; turnaround times are relatively short (2-4 weeks); and most public health teams have experience in interpreting the results. In regions with high M. tuberculosis genetic diversity due to immigration and importation of global M. tuberculosis lineages, such as major Canadian urban centers, MIRU-VNTR may be sufficient for surveillance of transmission or discrimination of relapse versus reinfection based on the high probability of seeing different M. tuberculosis lineages. However, in many Northern communities, the genetic diversity of M. tuberculosis is extremely low, and all isolates have the same or very similar MIRU-VNTR pattern simply because the relevant strain has been circulating in this population for decades. Hence, MIRU-VNTR is not useful for discriminating recent transmission from reactivation or relapse from reinfection in these settings; WGS is needed.^84,87,88 For evaluating TB transmission, WGS can substantially reduce the amount of false clustering⁸⁹ and is demonstrably more consistent with epidemiologic data.⁹⁰ WGS has also been shown to provide higher resolution for discriminating relapse from reinfection.^91–93 However, it is important to emphasize that epidemiological confirmation is always necessary in the interpretation of results of either MIRU-VNTR or WGS.

Isolates from all patients in an outbreak share the same MIRU-VNTR pattern. However, with WGS, (particularly for outbreaks with long duration), individual SNPs that accumulate over time in each patient’s bacteria can be used to understand transmission within the outbreak. This can better identify source cases⁹⁴ and super spreading events,^84,86 and help discriminate different chains or sub-groups of transmission.^84,86,87 Linkage with corresponding clinical and epidemiological data can then be used to identify associated risk factors and inform targeted interventions. In program evaluation, WGS can be useful in estimating the proportion of cases due to recent transmission versus reactivation; the proportion of recurrences due to relapse versus reinfection; or the impact of community-wide interventions on transmission.^{84,92,93,95,131}

Given these advantages, WGS is now recognized as the gold standard for identifying TB transmission and discrimination of relapse/reinfection. In recent years, a number of jurisdictions have transitioned to routine WGS for their TB surveillance programs, including the UK,⁹⁶ USA,⁹⁷ Netherlands⁹⁸ and the state of Victoria in Australia (Dr. Gonçalves da Silva, personal communication). However, WGS has not yet been widely adopted by TB diagnostic laboratories in Canada because of concerns about cost compared to MIRU-VNTR, need for bioinformatics infrastructure and lengthy turnaround times. Importantly, costs of WGS can be offset by eliminating redundant molecular diagnostic tests. For example, New York State⁹⁹ estimated an incremental cost for WGS of only US$60 per isolate in 2017. ⁹⁹ In the past 2 years, substantial laboratory and bioinformatics analytic capacity has also been developed for genomics of SARS-Cov-2. Given this and the availability of published M. tuberculosis-specific bioinformatics pipelines,¹⁰⁰ this infrastructure seems within reach. Finally, the turn-around time for WGS-based reporting for resistance was as little as 15 days from early culture positivity in New York State⁹⁹ and Australia.¹⁰¹ A UK-based study found no difference in time to results with MIRU or WGS but estimated that WGS results could have been available 21 days earlier than MIRU results if done under more realistic conditions.¹⁰⁰

Hence, we suggest consideration be given to transitioning from classical genotyping methods to WGS for routine surveillance of transmission and for outbreak investigations. This transition would provide most immediate advantages in settings with limited M. tuberculosis strain diversity (i.e., Northern Canada), and could then be applied more widely as costs decrease.

Social network analysis is an extension of traditional field epidemiology; it systematically examines the social relationships between cases and contacts to identify settings and behaviors that characterize transmission events, and can be used to visualize or quantify the strength of these connections. Social network analysis has been used extensively in TB outbreaks, most often together with genotyping/WGS; computer software programs for formal social network analysis are available.^{48,50,102–104}

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