A general framework to support cost-efficient fecal egg count methods and study design choices for large-scale STH deworming programs-monitoring of therapeutic drug efficacy as a case study

Abstract

Background: Soil-transmitted helminth (STH) control programs currently lack evidence-based recommendations for cost-efficient survey designs for monitoring and evaluation. Here, we present a framework to provide evidence-based recommendations, using a case study of therapeutic drug efficacy monitoring based on the examination of helminth eggs in stool.

Methods: We performed an in-depth analysis of the operational costs to process one stool sample for three diagnostic methods (Kato-Katz, Mini-FLOTAC and FECPAKG2). Next, we performed simulations to determine the probability of detecting a truly reduced therapeutic efficacy for different scenarios of STH species (Ascaris lumbricoides, Trichuris trichiura and hookworms), pre-treatment infection levels, survey design (screen and select (SS); screen, select and retest (SSR) and no selection (NS)) and number of subjects enrolled (100-5,000). Finally, we integrated the outcome of the cost assessment into the simulation study to estimate the total survey costs and determined the most cost-efficient survey design.

Principal findings: Kato-Katz allowed for both the highest sample throughput and the lowest cost per test, while FECPAKG2 required both the most laboratory time and was the most expensive. Counting of eggs accounted for 23% (FECPAKG2) or ≥80% (Kato-Katz and Mini-FLOTAC) of the total time-to-result. NS survey designs in combination with Kato-Katz were the most cost-efficient to assess therapeutic drug efficacy in all scenarios of STH species and endemicity.

Conclusions/significance: We confirm that Kato-Katz is the fecal egg counting method of choice for monitoring therapeutic drug efficacy, but that the survey design currently recommended by WHO (SS) should be updated. Our generic framework, which captures laboratory time and material costs, can be used to further support cost-efficient choices for other important surveys informing STH control programs. In addition, it can be used to explore the value of alternative diagnostic techniques, like automated egg counting, which may further reduce operational costs.

Trial registration: ClinicalTrials.gov NCT03465488.

Fig 1. Overview of the different operational steps for the different FEC methods.

The distinctive steps to perform a Kato-Katz (KK), Mini-FLOTAC or FECPAK^G2 on a single stool sample are provided in chronological order per method. The procedures are grouped per main subject (blue: entry of demographic data; green: preparation of the sample; yellow: reading of the slide/device or the image to count STH eggs; red: entry of fecal egg count data). Waiting steps included in the procedure are indicated in grey and represent a fixed amount of time. The small clock symbol indicates what steps have been timed as part of this experiment. Clock clip art from https://openclipart.org/detail/125725/time-temps.

Fig 2. Time required to quantify soil-transmitted helminth infections in stool by four fecal egg count methods.

The height of the bars represents the mean time (in sec) needed to enter demographic data (blue), to perform the preparation phase (green), to count eggs (yellow) and to enter egg count data (red) for a single (1xKK) and duplicate Kao-Katz (2xKK), Mini-FLOTAC (MF) and FECPAK^G2 (FP). The relative proportion (in %) of total time required to perform the preparation phase and to count is reported inside the bars.

Fig 3. The reading time as a function of the number of STH eggs counted in a sample.

This figure represents the reading time as a function of the number of STH eggs counted in a sample for single Kato-Katz (KK), Mini-FLOTAC and FECPAK^G2 separately. All egg counts represent raw egg counts (not in eggs per gram of stool). The red line represents the linear regression line. The function of the regression line is also provided.

Fig 4. The failure rate, the probability of correctly concluding reduced drug efficacy and the total survey cost across six survey designs.

This figure shows the impact of the survey design and sample size on the failure rate (Panel A), probability of correctly detecting truly reduced efficacy (prob_reduced; Panel B) and the mean total survey cost (cost_total; Panel C). To gain more insights into the most cost-efficient survey design, the probability of correctly detecting reduced drug efficacy prob_reduced was plotted as a function of the mean cost_total (Panel D). For each of the four panels, we only consider the use of Kato-Katz in areas with low levels of hookworm infection (mean FEC = 3.7 EPG). NS = no selection; SS = screen and select; SSR = screen, select, and retest. Note, for panel A, all survey designs other than SS1x2/1x2 are identical to SSR1x1/1x2.

Fig 5. The probability of correctly detecting presence of reduced drug efficacy and the total survey cost for three FEC methods across six survey designs.

This figure plots the probability of correctly identifying reduced therapeutic efficacy (prob_reduced) as a function of the mean total survey costs (cost_total) for the three different FEC methods (Kato-Katz thick smear (KK), Mini-FLOTAC and FECPAK^G2; colored lines) and six survey designs (different panels). For each panel, we only consider areas that are low endemic for hookworm (mean FEC = 3.7 EPG). NS = no selection; SS = screen and select; SSR = screen, select, and retest.

Fig 6. The probability of correctly detecting presence of reduced drug efficacy and the total survey cost for six survey designs across four levels of endemicity when deploying Kato-Katz.

This figure plots the probability of correctly identifying reduced therapeutic efficacy (prob_reduced) as a function of the mean total survey costs (cost_total) across six survey designs for the three soil-transmitted helminth species and four levels of endemicity (see Table 1).