Contextualizing the algorithm for ACF campaign

A good screening algorithm should have the following characteristics:

• High specificity (to reduce the number of false positives, ideally around 70%)
• High sensitivity (to reduce the number of false negatives, ideally around 90%)
• Low Number Needed to Screen (NNS)
• Low cost
• Rapid and simple to apply
• High client acceptability

The algorithm should be optimised so that the maximum number of cases can be detected with available resources.

Usually verbal screening using  symptom complex (4S) are used. However ACF campaigns targeting key and vulnerable populations (household contact persons, elderly homes etc.)can consider using X ray also as a screening tool. Chest X ray helps in picking up sub-clinical TB cases also which will be usually missed through verbal screening of symptoms.   

A more sensitive test like NAAT is preferred over sputum microscopy in ACF campaigns as the cases will be in early stage and may be missed by testing using Microscopy.

References

• Optimising Active Case Finding – Implementation Lessons from South-East Asia. WHO SEAR, 2021.
• WHO Consolidated Guidelines on Tuberculosis – Module 2: Screening, WHO, 2021.
• High-priority Target Product Profiles for New Tuberculosis Diagnostics: Report of a Consensus Meeting, 28–29 April 2014, Geneva, Switzerland. Geneva: World Health Organisation, 2014.

Assessment