Identification and treatment of latent tuberculosis infection (LTBI) can substantially reduce the risk of developing active disease. However, there is no diagnostic gold standard for LTBI. Two tests are available for identification of LTBI: the tuberculin skin test (TST) and the gamma interferon (IFN-γ) release assay (IGRA). Evidence suggests that both TST and IGRA are acceptable but imperfect tests. They represent indirect markers of Mycobacterium tuberculosis exposure and indicate a cellular immune response to M. tuberculosis. Neither test can accurately differentiate between LTBI and active TB, distinguish reactivation from reinfection, or resolve the various stages within the spectrum of M. tuberculosis infection. Both TST and IGRA have reduced sensitivity in immunocompromised patients and have low predictive value for progression to active TB. To maximize the positive predictive value of existing tests, LTBI screening should be reserved for those who are at sufficiently high risk of progressing to disease. Such high-risk individuals may be identifiable by using multivariable risk prediction models that incorporate test results with risk factors and using serial testing to resolve underlying phenotypes. In the longer term, basic research is necessary to identify highly predictive biomarkers.

Digital technologies are increasingly harnessed to support treatment of persons with tuberculosis (TB). Since in-person directly observed treatment (DOT) can be resource intensive and challenging to implement, these technologies may have the potential to improve adherence and clinical outcomes. We reviewed the effect of these technologies on TB treatment adherence and patient outcomes.We searched several bibliographical databases for studies reporting the effect of digital interventions, including short message service (SMS), video-observed therapy (VOT) and medication monitors (MMs), to support treatment for active TB. Only studies with a control group and which reported effect estimates were included.Four trials showed no statistically significant effect on treatment completion when SMS was added to standard care. Two observational studies of VOT reported comparable treatment completion rates when compared with in-person DOT. MMs increased the probability of cure (RR 2.3, 95% CI 1.6-3.4) in one observational study, and one trial reported a statistically significant reduction in missed treatment doses relative to standard care (adjusted means ratio 0.58, 95% CI 0.42-0.79).Evidence of the effect of digital technologies to improve TB care remains limited. More studies of better quality are needed to determine how such technologies can enhance programme performance.