References in the content below refer to the PBMEF Guide.
Definitions
The number needed to test (NNT) is the number of individuals that must be tested with a bacteriological test to identify one person with TB during the reporting period. These tests include all WHO-recommended rapid diagnostic (WRD) testing options, including: FluoroType® MTB (Hain), Loopamp™ MTBC detection kit (TB-LAMP), Xpert® MTB/RIF, Xpert® MTB/RIF Ultra, Truenat® MTB, RealTime MTB (Abbott), BD MAX™ MDR-TB, cobas® MTB (Roche), or LF-LAM.
Calculation: Numerator/Denominator
Numerator
Denominator
Ref # |
NNT
(Previously AF-8) |
Tier Level |
Project Level Indicators
|
Category |
Reach
|
Type |
Output
|
Unit of Measure |
Number of people
|
Data Type |
Integer
|
Disaggregations |
Age
Sex
Setting
|
Reporting Level |
National, subnational
|
Reporting Frequency |
Quarterly, monthly
|
The data sources are basic management unit TB register, screening register, presumptive TB register, laboratory register, or electronic management information systems available at the health facility and district level.
USAID invests in a variety of diagnostic technologies and case finding approaches with the goal of closing the gap between the number of estimated and notified people with TB. This indicator is important to help identify the most promising case finding strategies that will reach the population in need in the most efficient manner.
The screening and testing algorithm used influences the percentage of evaluated people who are diagnosed with TB. An algorithm that identifies only people at high risk for TB (e.g. cough lasting more than 2 weeks) may result in a low number NNT, but it also misses many people with TB that do not have such strong signs of TB risk. An approach that identifies more people for testing (e.g., any TB symptom and/or abnormal chest x-ray [CXR]) may result in a higher number NNT, but it may also be successful in diagnosing more people. As the incidence of TB falls, it should become more difficult to find active TB. As a result, it is reasonable to expect that if the comprehensive approach to TB succeeds in reducing TB incidence over time, the percentage of people diagnosed with TB will decrease. This is not to say that active case finding efforts should be halted.
Example charts/graphs:
- Trends over time comparisons
- Comparisons public vs private, rural vs urban and high risk subgroups
Indicator Visualizations
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