Two-stage lot quality assurance sampling framework for monitoring and evaluation of neglected tropical diseases, allowing for imperfect diagnostics and spatial heterogeneity.
Background Monitoring and evaluation (M&E) is a key component of large-scale neglected tropical diseases (NTD) control programs. Diagnostic tests deployed in these M&E surveys are often imperfect, and it remains unclear how this affects the population-based program decision-making. Methodolo...
Published in: | PLOS Neglected Tropical Diseases |
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Main Authors: | , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Public Library of Science (PLoS)
2022
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Subjects: | |
Online Access: | https://doi.org/10.1371/journal.pntd.0010353 https://doaj.org/article/6da267e0f09043b5bdb25d791cf3b209 |
Summary: | Background Monitoring and evaluation (M&E) is a key component of large-scale neglected tropical diseases (NTD) control programs. Diagnostic tests deployed in these M&E surveys are often imperfect, and it remains unclear how this affects the population-based program decision-making. Methodology We developed a 2-stage lot quality assurance sampling (LQAS) framework for decision-making that allows for both imperfect diagnostics and spatial heterogeneity of infections. We applied the framework to M&E of soil-transmitted helminth control programs as a case study. For this, we explored the impact of the diagnostic performance (sensitivity and specificity), spatial heterogeneity (intra-cluster correlation), and survey design on program decision-making around the prevalence decisions thresholds recommended by WHO (2%, 10%, 20% and 50%) and the associated total survey costs. Principal findings The survey design currently recommended by WHO (5 clusters and 50 subjects per cluster) may lead to incorrect program decisions around the 2% and 10% prevalence thresholds, even when perfect diagnostic tests are deployed. To reduce the risk of incorrect decisions around the 2% prevalence threshold, including more clusters (≥10) and deploying highly specific diagnostic methods (≥98%) are the most-cost saving strategies when spatial heterogeneity is moderate-to-high (intra-cluster correlation >0.017). The higher cost and lower throughput of improved diagnostic tests are compensated by lower required sample sizes, though only when the cost per test is <6.50 US$ and sample throughput is ≥3 per hour. Conclusion/significance Our framework provides a means to assess and update M&E guidelines and guide product development choices for NTD. Using soil-transmitted helminths as a case study, we show that current M&E guidelines may severely fall short, particularly in low-endemic and post-control settings. Furthermore, specificity rather than sensitivity is a critical parameter to consider. When the geographical ... |
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