Evaluation of a Urine Pooling Strategy for the Rapid and Cost-Efficient Prevalence Classification of Schistosomiasis

Abstract

Background: A key epidemiologic feature of schistosomiasis is its focal distribution, which has important implications for the spatial targeting of preventive chemotherapy programs. We evaluated the diagnostic accuracy of a urine pooling strategy using a point-of-care circulating cathodic antigen (POC-CCA) cassette test for detection of Schistosoma mansoni, and employed simulation modeling to test the classification accuracy and efficiency of this strategy in determining where preventive chemotherapy is needed in low-endemicity settings.

Methodology: We performed a cross-sectional study involving 114 children aged 6-15 years in six neighborhoods in Azaguié Ahoua, south Côte d'Ivoire to characterize the sensitivity and specificity of the POC-CCA cassette test with urine samples that were tested individually and in pools of 4, 8, and 12. We used a Bayesian latent class model to estimate test characteristics for individual POC-CCA and quadruplicate Kato-Katz thick smears on stool samples. We then developed a microsimulation model and used lot quality assurance sampling to test the performance, number of tests, and total cost per school for each pooled testing strategy to predict the binary need for school-based preventive chemotherapy using a 10% prevalence threshold for treatment.

Principal findings: The sensitivity of the urine pooling strategy for S. mansoni diagnosis using pool sizes of 4, 8, and 12 was 85.9%, 79.5%, and 65.4%, respectively, when POC-CCA trace results were considered positive, and 61.5%, 47.4%, and 30.8% when POC-CCA trace results were considered negative. The modeled specificity ranged from 94.0-97.7% for the urine pooling strategies (when POC-CCA trace results were considered negative). The urine pooling strategy, regardless of the pool size, gave comparable and often superior classification performance to stool microscopy for the same number of tests. The urine pooling strategy with a pool size of 4 reduced the number of tests and total cost compared to classical stool microscopy.

Conclusions/significance: This study introduces a method for rapid and efficient S. mansoni prevalence estimation through examining pooled urine samples with POC-CCA as an alternative to widely used stool microscopy.

Fig 1. Modeled estimation of the sensitivity of the urine pooling strategy.

Positive urine sample confirmed by quadruplicate Kato-Katz thick smears and single POC-CCA urine cassette test were combined with three (n = 4), seven (n = 8), or 11 (n = 12) negative urine samples. A logistic regression was used to model sensitivity of the pooled urine samples (n = 4, 8, and 12) as a function of the infection intensity (EPG) of the one infected urine. The distribution of S. mansoni infections used in this model included light, moderate, and heavy intensity infections (figure inset).

Fig 2. Operating characteristic curves for microsimulation analysis of urine pooling strategy to rapidly map the prevalence of schistosomiasis and inform preventive chemotherapy.

Using primary data on urine pooling strategies (n = 4, 8, and 12 samples), we used a microsimulation to model the proportion (Pr) of correct binary classification around a prevalence threshold to indicate need for school-based preventive chemotherapy according to WHO (10% prevalence). The interpretation of the curves is provided in (a). The results are presented for: (b) 20 tests; (c) 50 tests; and (d) 250 tests. We compared traditional stool microscopy (duplicate Kato-Katz thick smears derived from one stool sample), single POC-CCA test, and the three urine pooling strategies (pool sizes of 4, 8, and 12) using the WHO 10% prevalence threshold. The strategies performed well within the center of a prevalence categorization, but poorly at the boundary between two prevalence categories. Increased number of tests resulted in lower classification error.

Fig 3. Number of tests and total costs per school from microsimulation analysis of urine pooling strategy and traditional stool microscopy.

The urine pooling strategy (n = 4, 8, and 12 pool) was compared against stool microscopy to estimate (a) the total number of tests per school and (b) total cost per school for identical level of certainty in binary classification on need for preventive chemotherapy. We used a 10% prevalence threshold in this base case analysis. A loess algorithm was applied for visualization.

Fig 4. One-way sensitivity analysis of microsimulation.

This analysis tested the effect of changing individual model parameters on the total cost of the urine pooling strategy for (a) pool of 4 and (b) pool of 8. The horizontal bar represents the total cost to achieve 90% level of certainty (±5% around the prevalence threshold) in classification across a range of values for the tested parameter. The y-axis (solid black line) represents the total cost of the urine pooling strategy under base case assumptions. The vertical dashed blue line represents the total cost of traditional stool microscopy under base case assumptions, and all strategies to the left of this line indicate a cost saving advantage of the urine pooling strategy.