Figure 1.
The (unique) treatment threshold (or decision threshold).
Figure 2.
main factors influencing the decision threshold.
Figure 3.
the test threshold and the test treatment threshold.
Figure 4.
maximal theoretical effect of tests: odds ratio.
Legend: OR: log10odds ratio; LR: log10likelihood ratio. Log10positive and negative likelihood summed make the log10odds ratio, shown on a log10odds scale. The width between test-treatment threshold and decision threshold is determined by the negative likelihood ratio of the test. Mutatis mutandis, the distance between the test treatment and the decision threshold are given by the positive likelihood ratio.
Figure 5.
Summary of the relations between the pre-test probabilities and the thresholds.
These are calculated both with and without considering costs (see text). When costs are considered, the test is no more an option in the rainy season (see article), while in the dry season the test field becomes very narrow as the two thresholds tend to coincide.
Figure 6.
illustrative case 3: a febrile adult in the dry season.
The pre test probability is at 2%, a positive RDT will never reach the decision threshold at 52.6 since its positive likelihood ratio is only 4.43.
Table 1.
A comparison of the general WHO guidelines with the possible recommendations for the study area, based on threshold analysis.