A general framework to support cost-efficient survey design choices for the control of soil-transmitted helminths when deploying Kato-Katz thick smear

Abstract

Background To monitor and evaluate soil-transmitted helminth (STH) control programs, the World Health Organization (WHO) recommends screening stools from 250 children, deploying Kato-Katz thick smear (KK). However, it remains unclear whether these recommendations are sufficient to make adequate decisions about stopping preventive chemotherapy (PC) (prevalence of infection <2%) or declaring elimination of STH as a public health problem (prevalence of moderate-to-heavy intensity (MHI) infections <2%). Methodology We developed a simulation framework to determine the effectiveness and cost of survey designs for decision-making in STH control programs, capturing the operational resources to perform surveys, the variation in egg counts across STH species, across schools, between and within individuals, and between repeated smears. Using this framework and a lot quality assurance sampling approach, we determined the most cost-efficient survey designs (number of schools, subjects, stool samples per subject, and smears per stool sample) for decision-making. Principal findings For all species, employing duplicate KK (sampling 4 to 6 schools and 64 to 70 subjects per school) was the most cost-efficient survey design to assess whether prevalence of any infection intensity was above or under 2%. For prevalence of MHI infections, single KK was the most cost-efficient (sampling 11 to 25 schools and 52 to 84 children per school). Conclusions/Significance KK is valuable for monitoring and evaluation of STH control programs, though we recommend deploying a duplicate KK on a single stool sample to stop PC, and a single KK to declare the elimination of STH as a public health problem.

Improving the Cost-efficiency of Preventive Chemotherapy: Impact of New Diagnostics on Stopping Decisions for Control of Schistosomiasis

“…The second approach would be a Monte Carlo simulation study of the cost and performance of spatial survey designs. Such a study would have to be informed by data on spatial heterogeneity in prevalences collected in an area where the average prevalence is around the decision threshold after multiple years of PC, analyzed with either mixed effects models [ 32 ] or geospatial models.…”

A comprehensive evaluation of an artificial intelligence based digital pathology to monitor large-scale deworming programs against soil-transmitted helminths: a study protocol

“…For this experiment, we built up on two general frameworks that were previously developed to support cost-efficient study design choices for large-scale STH deworming programs, including epidemiological surveys to reduce/stop large-scale deworming programs and to declare STH eliminated as a public health problem [41, 42], and to monitor the therapeutic drug efficacy [22]. Generally, these frameworks consist of three consecutive steps.…”

“…For the in-depth analysis of the operational costs to process one sample, we will both conduct an itemized cost assessment and determine the salary costs, which will be a function of the time-to-result (see section 2.4.3 ). For the simulation, we will deploy simulation frameworks previously published by both Kazienga et al (2023) and Coffeng et al (2023) [22, 41]. Both frameworks account for different sources of variation in egg counts, including (i) variability in mean egg intensity between schools; (ii) inter-individual variability in mean egg intensity due to variation in infection levels between individuals, where the level of aggregation is a linear function of the school-level mean egg intensity; (iii) day-to-day variability in mean egg intensity within an individual due to heterogeneous egg excretion over time; (iv) variability in egg counts between repeated aliquots of a stool sample due to the aggregated distribution of eggs in stool; (v) inter-individual variability in the effect of drug administration.…”

“…This is parUcularly relevant for STH control programs which operate in resource poor sekngs, and hence it will be important to ensure reliable and confident programmaUc decision making, while minimizing the operaUonal costs. Moreover, a complex interplay exists between the diagnosUc performance and the epidemiological sekng (e.g., clinical sensiUvity reduces in low endemic sekng [15,41], the sample throughput, and the operaUonal costs (e.g., improving the diagnosUc performance and the corresponding reduced sample sizes can compensate for more costly tests and lower sample throughput; there is a limit to the extent to which higher reagent costs can be compensated by lower sample throughput) [23,42]. In other words, it would be quite impossible to draw conclusions on whether any new diagnosUc method holds promise to inform large-scale deworming programs without fully exploring these aspects in more detail non-inferiority hypotheses without the need of other diagnosUc methods (e.g., qPCR) or more complex staUsUcal models that account for a gold standard.…”

“…Kazienga et al (2023) andCoffeng et al (2023) [22,41]. Both frameworks account for different sources of variaUon in egg counts, including (i) variability in mean egg intensity between schools; (ii) inter-individual variability in mean egg intensity due to variaUon in infecUon levels between individuals, where the level of aggregaUon is a linear funcUon of the school-level mean egg intensity; (iii) day-to-day variability in mean egg intensity within an individual due to heterogeneous egg excreUon over Ume; (iv) variability in egg counts between repeated aliquots of a stool sample due to the aggregated distribuUon of eggs in stool; (v) interindividual variability in the effect of drug administraUon.…”