Consolidated Guidelines

1.6 Target audience

This guideline is intended for personnel working in national TB programmes, national HIV/AIDS programmes or their equivalents, and other relevant national health programmes in ministries of health; other relevant ministries working in public health and screening; and for other health policymakers, clinicians and public health practitioners working on TB, HIV and infectious diseases in the public and private sectors. The recommendations provided here must be adapted to local settings. An accompanying operational handbook, WHO operational handbook on tuberculosis.

1.5 Objectives of the guideline update

The specific objectives of the guideline update are:

1. to support Member States in implementing effective TB screening interventions by providing updated information about the expected impact of TB screening on patient-important outcomes and the epidemiology of TB, the expected yield of screening interventions and the expected performance of different screening tools and algorithms;

3.2.2 Implementation considerations

The evaluations reviewed by the GDG demonstrated substantial variation in the diagnostic accuracy (sensitivity and specificity) of CAD programmes across settings, even when using the same technology set to the same threshold. Thus, it will be essential to calibrate the threshold to be used for any given software for each setting and population in which it will be used in order to ensure that the accuracy, predictive values, overall yield and requirements for further diagnostic testing are as expected.

2.3.1 Summary of evidence and rationale

People living with HIV are approximately 19 times more likely to develop TB disease than those without HIV; in 2019, an estimated 44% of people living with HIV who also had TB disease did not reach care, and 30% of all HIV-related deaths were due to TB (1). Thus, ensuring early detection and treatment for TB among all people living with HIV is crucial for reducing morbidity and mortality in this group.

2.2.1 Summary of evidence and rationale

Populations with structural risk factors for TB are those that are at increased risks of TB and of poor health outcomes from TB due to structural determinants in their environment, defined as the conditions that generate or reinforce social stratification (e.g. socioeconomic inequalities, population growth, urbanization), and therefore give rise to an unequal distribution of key social determinants of TB epidemiology, such as poor housing, poverty and malnutrition, which in turn influence exposure to risk, vulnerability and ability to recover after developing the disease (16,17).

2.1.2 Implementation considerations

The magnitude and balance of desirable and undesirable effects vary according the epidemiological conditions (the prevalence of TB and of risk factors) and the intensity of the screening intervention being implemented (the coverage of the population and the sensitivity of the screening test and algorithm). There is currently no evidence that population-wide screening using less sensitive screening algorithms that begin with symptom screening are effective at reducing the population prevalence or transmission of TB.

5.3 Operational research

Standard monitoring and evaluation procedures may be complemented by operational research aimed at improving the performance of screening in the local setting as well as research aimed at improving the global evidence base for screening. Topics that may be explored include:

2.4.2 Implementation considerations

Contact screening should always be done when a person with TB has any of the following characteristics: bacteriologically confirmed pulmonary TB, proven or presumed multidrug-resistant TB or extensively drug-resistant TB, is a person living with HIV or is a child younger than 5 years. Among contacts of patients with bacteriologically confirmed TB, the weighted pooled prevalence of TB was 3.4% (95% CI: 2.9–3.8). Among contacts of patients with multidrug-resistant or extensively drug-resistant TB the weighted pooled prevalence of TB was 3.7% (95% CI: 2.4–5.3).

5.2.1 Computer-aided detection

Further evidence is needed about the performance of CAD software stratified according to the characteristics of the individual being evaluated (e.g. by smear status, HIV status, age cohort, history of TB, smoking status, sex) to allow for better setting-specific and patient-specific calibration of CAD programmes.

More research on users’ perspectives is needed about CAD technologies in TB screening and triage, including their perceived acceptability to patients, providers and other stakeholders.