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TB clusters can be difficult to identify and investigate.

Contact histories and strain typing do not always tell the whole story.

Genomics can give more resolution but drawing conclusions about transmission from WGS data has some caveats and requires knowledge of the background diversity between different TB isolates and integration of genome data with other epidemiological information.

So what?

Using WGS has the potential to rule out transmission early in an investigation and therefore enable investigation and control measures to be targeted more appropriately. Use of WGS could identify pseudo-outbreaks.

Using WGS has the ability to demonstrate relatedness between isolates in the absence of epidemiological data and thereby identify possible transmission and to be combined with other data.

Researchers have demonstrated that we can relate the level of diversity (as measured by SNPs) between cases in clusters with differing levels of epidemiological linkage to the probability of transmission.

Diversity among isolates from the same patient (at one time and over a period of time) and among isolates from the same household has also been shown to be predictable.

More genomes need to be sequenced and compared in order to be able to draw robust conclusions about the direction of transmission.

Now what?

In order to make decisions, some scientists have applied thresholds to the number of SNPs. These thresholds are arbitrary and have been applied to the data that is currently available. As more genomes are collected, it is likely that these thresholds may change and genomics may be able to provide meaningful probabilistic estimates of relatedness.

Public health action should not be taken using genomic data alone, it is important to combine this information with epidemiological and clinical information when making decisions regarding the investigation and control of TB clusters.

You have now completed this case study. You should now be able to:

  • Critically evaluate the benefits and limitations of genomics to health protection and epidemiology practice;

  • Apply the principles of genomics and key genomics resources to solving a problem in health protection and epidemiology practice;

  • Understand how to communicate effectively and work collaboratively with microbiology and bioinformatics experts in PHE and partner organisations to investigate and solve a problem in health protection and epidemiology practice;

  • Reflect on how genomics may be integrated with and applied to health protection and epidemiology in your own working context.

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