Screening

Since 2011, WHO has recommended that people living with HIV be systematically screened for TB disease at each visit to a health facility. The recommendation is based on the high risk of this group for TB and mortality and a lingering gap in case detection in this population. In 2019, people with HIV were at 18 times greater risk for incident TB than people without HIV and close to one third of deaths from AIDS were due to TB (2). Only 56% of the total estimated number of HIV-positive incident TB cases were detected in 2019 (2).

CAD technologies for automated reading of digital CXR for TB detection offer a promising solution for high-TB burden countries; however, selecting the appropriate CAD product for a particular setting can be complex. When selecting a CAD product, TB programmes and implementers should consider multiple aspects of the technology and its interface with existing infrastructure, including:

The most desirable screening strategy is one with high total yield of true-positive TB cases, few false-positives, low NNS, low cost, a rapid and simple algorithm and high client acceptability. In practice, many of these factors can run in opposite directions, and multifactorial analysis is required. The ScreenTB online tool has been developed to assist in prioritizing risk groups for screening and choosing appropriate screening and diagnostic algorithms.

An algorithm for systematic TB screening should combine one or several screening tests and a separate diagnostic evaluation for TB disease, as recommended by WHO (12). A negative diagnostic test result may be followed up by further clinical evaluation if clinical suspicion of TB is still high. This could include re-testing with the same or another diagnostic method and/or close follow-up of clinical symptoms with or without chest imaging.

Screening tests should distinguish between people with a high likelihood of having TB disease from those who are unlikely to have TB. A screening test is not intended to be diagnostic but rather to identify the subgroup of people with the highest likelihood of disease. Screening must always be conducted with a screening and diagnostic algorithm; thus, if people screen positive, they are referred to the next step in the algorithm, which could be a subsequent screening tool or diagnostic evaluation with bacteriological testing to confirm or rule out TB disease.

The two complementary approaches for improving early detection of TB are illustrated in Fig. 2.1 The primary approach is to optimize the patient-initiated pathway to TB diagnosis and treatment (for details see 2.1.1). This approach does not constitute screening and is a passive form of case detection.

Tuberculosis (TB) is a major yet preventable airborne infectious disease. About one fourth of the world’s population is infected with TB bacilli, the vast majority of whom have no disease (1, 2). In 2019, an estimated 10 million new TB cases emerged worldwide, and more than 1.4 million people died of TB, making it the leading single infectious disease cause of death that year (2). Of the estimated 10 million people who fell ill with TB in 2019, TB was not diagnosed in an estimated 2.9 million, and they were not enrolled in quality-assured TB treatment (2).