Fig 1.
Required sensitivity and specificity when making adequate and ideal program decisions in the presence of logistic constraints.
The figure indicates the required sensitivity and specificity for adequate ( and
; Panel A) and ideal decision-making (
and
; Panel B) when sampling 100 children per school for different number of schools (colored lines). The black dot represents the diagnostic performance of the Baermann method (sensitivity = 50.0% and specificity = 98.0%).
Table 1.
Required specificity and sensitivity for adequate and ideal decision-making when deploying LFA and Ab-ELISA/plasma in the presence of both logistic and budget constraints. The table summarizes the sensitivity and specificity for the LFA and Ab-ELISA/plasma to achieve adequate ( and
) and ideal program decision-making (
= 5% and
= 10%). Each of these combinations result in a total survey cost that does not exceed that of a Baermann-based survey (assuming a specificity of 98% and sensitivity of 50% for the Baermann method). Ab-ELISA/plasma: Ab-ELISA assays that are based on plasma. Note that the blank cells indicate that there were no combinations of sensitivity and specificity that resulted in sufficiently low risk of incorrect decision-making.
Fig 2.
The maximum cost per test for an LFA and Ab-ELISA/plasma for adequate decision making.
This figure presents the maximum cost per test for all possible combinations of sensitivity and specificity, sample throughput (number of samples that can be analyzed by one technician in one hour) that allowed for adequate ( and
) decision-making for an LFA (Panel A: sample throughput of five samples per hour; Panel B: sample throughput of 40 samples per hour) and Ab-ELISA format (Panel C: sample throughput of five samples per hour; Panel D: sample throughput of 40 samples per hour). Note that the maximum cost per test is the true maximum cost per test that could work in at least one logistically feasible survey design that is not more expensive than the benchmark cost based on the Baermann method. Absence of tiles indicates that the combination of sensitivity and specificity was inadequate for decision-making, given the logistic and budget constraints.
Fig 3.
The maximum cost per test for an LFA and Ab-ELISA/plasma for ideal decision making.
This figure represents all possible combinations of sensitivity and specificity, sample throughput (number of samples that can be analyzed by one technician in one hour), and the maximum cost per test (in EUR) that allowed for ideal ( and
) decision-making for an LFA (Panel A: sample throughput of five samples per hour; Panel B: sample throughput of 40 samples per hour) and Ab-ELISA format (Panel C: sample throughput of five samples per hour; Panel D: sample throughput of 40 samples per hour). Note that the maximum cost per test is the true maximum cost per test that could work in at least one logistically feasible survey design that is not more expensive than the benchmark cost based on the Baermann method. Absence of tiles indicates that the combination of sensitivity and specificity was inadequate for decision-making, given the logistic and budget constraints.
Table 2.
The most cost-efficient survey design to initiate large-scale deworming against strongyloidiasis when deploying Baermann method and existing Ab-based assays. This table represents the required sample size (), the decision cutoff
, and the total survey cost to assess whether the true prevalence of strongyloidiasis is under or above 10% for adequate and ideal decision-making. Bordier Ab-ELISA represents a commercially available Strongyloides ratti IgG ELISA (Bordier Affinity Products, Crissier, Switzerland) applied on either plasma (Bordier Ab-ELISA/plasma) or dried blood samples (Bordier Ab-ELISA/DBS). NIE-LFA is a prototype (research use only) lateral flow assay (LFA) developed by the Institute for Research in Molecular Medicine of the Universiti Sains Malaysia. This LFA is based on the recombinant antigen NIE.