Clinical sensitivity and time-to-result of a cascaded pooled testing approach for assessing the prevalence and intensity of Schistosoma haematobium infection.

Abstract

BackgroundThis study compared the clinical sensitivity and the time-to-result of an individual testing (IT) and a cascaded pooled testing approach (CPT; a positive test result in a pooled sample triggers examination of smaller-sized pools or individual samples) for assessing the prevalence and the intensity of Schistosoma haematobium infection. We also compared the sensitivity of the CPT in detecting S. haematobium infection when deploying urine filtration microscopy (UFM) vs. urine reagent strips (URS), and testing 10 mL vs. 15 mL of urine.Methodology/principal findingsBetween October 2021 and April 2022, S. haematobium eggs were counted in urine samples collected from school-aged children living in the Afar and Gambella Regional States of Ethiopia. Urine samples were collected at baseline (n = 1,288), and one month after administration of praziquantel (n = 118). All urine samples were processed through both an IT and a CPT approach (pools of 5, 10, 20, and 40 individual samples), deploying UFM (10 mL) and URS (10 mL). In addition, 15 mL urine was processed through the CPT deploying UFM. At baseline, the prevalence of S. haematobium infection estimated when using UFM and deploying a CPT approach was significantly lower (17.3%) compared to an IT approach (31.5%). The clinical sensitivity of the CPT in detecting S. haematobium eggs was 51.7%. The sensitivity increased significantly as a function of increasing log transformed urine egg counts (UECs) of the individual samples (OR 2.71, 95%CI 1.63 - 4.52). The sensitivity was comparable when the amount of urine examined was 10 mL (51.7%) vs. 15 ml (50.8%), and when UFM was used for testing vs. URS (51.5%). The mean log UECs estimated following the CPT approach was lower compared to the estimate by the IT (p Conclusions/significanceCPT based on UFM and URS techniques may help to rapidly identify areas with higher prevalence of S. haematobium infection (hotspots) in a population. However, the performance of this approach in estimating the prevalence of infection may be compromised, particularly in endemic areas with low intensity infection.