Two-stage lot quality assurance sampling framework for monitoring and evaluation of neglected tropical diseases, allowing for imperfect diagnostics and spatial heterogeneity
Fig 5
Impact of the width of the grey zone on program decision-making when applying imperfect diagnostics.
This figure illustrates the impact of the width of the grey zone on the number of subjects per cluster (Panel A), the total number of subjects sampled across nclust clusters on the minimum required survey design for adequate program decision-making (Eovertreat = 25% and Eundertreat = 5%) (Panel B), the decision threshold c (Panel C), and the associated total survey cost (Panel D). We considered program prevalence threshold T of 2%, fixed the intra-cluster correlation ρi at 0.02 and assumed a theoretical diagnostic test Dt1 (sedt1 = 80% and spdt1 = 98%). The width of the grey zone is expressed as a proportion of program prevalence threshold T. The black bullet across the four panels indicates the chosen hypothetical reference grey zone width (T±50%), which was chosen to further illustrate the impact of the diagnostic performance (Fig 6) and geographical variation in prevalence between clusters on program decision-making (Fig 7), and the relative change in total survey cost based on newer diagnostic tests (Fig 8). All graphs are based on the same set of 10,000 Monte Carlo simulations.