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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
medicine
Multiple Category-Lot Quality Assurance Sampling: A New Classification System with Application to Schistosomiasis Control
PLoS Neglected Tropical Diseases, Volume 6, No. 9, Article e1806, Year 2012
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Description
Background: Originally a binary classifier, Lot Quality Assurance Sampling (LQAS) has proven to be a useful tool for classification of the prevalence of Schistosoma mansoni into multiple categories (≤10%, >10 and <50%, ≥50%), and semi-curtailed sampling has been shown to effectively reduce the number of observations needed to reach a decision. To date the statistical underpinnings for Multiple Category-LQAS (MC-LQAS) have not received full treatment. We explore the analytical properties of MC-LQAS, and validate its use for the classification of S. mansoni prevalence in multiple settings in East Africa. Methodology: We outline MC-LQAS design principles and formulae for operating characteristic curves. In addition, we derive the average sample number for MC-LQAS when utilizing semi-curtailed sampling and introduce curtailed sampling in this setting. We also assess the performance of MC-LQAS designs with maximum sample sizes of n = 15 and n = 25 via a weighted kappa-statistic using S. mansoni data collected in 388 schools from four studies in East Africa. Principle Findings: Overall performance of MC-LQAS classification was high (kappa-statistic of 0.87). In three of the studies, the kappa-statistic for a design with n = 15 was greater than 0.75. In the fourth study, where these designs performed poorly (kappa-statistic less than 0.50), the majority of observations fell in regions where potential error is known to be high. Employment of semi-curtailed and curtailed sampling further reduced the sample size by as many as 0.5 and 3.5 observations per school, respectively, without increasing classification error. Conclusion/Significance: This work provides the needed analytics to understand the properties of MC-LQAS for assessing the prevalance of S. mansoni and shows that in most settings a sample size of 15 children provides a reliable classification of schools. © 2012 Olives et al.
Available Materials
https://efashare.b-cdn.net/share/pmc/articles/PMC3435238/bin/pntd.0001806.s001.docx
Authors & Co-Authors
Olives, Casey
Unknown Affiliation
Valadez, Joseph James
Unknown Affiliation
Brooker, Simon J.
Unknown Affiliation
Pagano, Marcello A.
Unknown Affiliation
Statistics
Citations: 24
Authors: 4
Affiliations: 6
Identifiers
Doi:
10.1371/journal.pntd.0001806
ISSN:
19352727
e-ISSN:
19352735
Research Areas
Infectious Diseases
Maternal And Child Health
Study Design
Cross Sectional Study
Study Locations
Multi-countries