Estimating Prevalence and Infection Intensity of Soil-Transmitted Helminths Using Quantitative Polymerase Chain Reaction and Kato-Katz in School-Age Children in Angola.

Abstract

Quantitative polymerase chain reaction (qPCR) is gaining recognition in soil-transmitted helminth (STH) diagnostics, especially for Strongyloides stercoralis and differentiating hookworm species. However, sample preservation and DNA extraction may influence qPCR performance. We estimated STH prevalence and infection intensity by using qPCR in schoolchildren from Huambo, Uige, and Zaire, Angola, and compared its performance with that of the Kato-Katz technique (here termed Kato-Katz). Stool samples from 3,063 children (219 schools) were preserved in 96% ethanol and analyzed by qPCR, of which 2,974 children (215 schools) had corresponding Kato-Katz results. Cluster-adjusted prevalence and infection intensity estimates were calculated by qPCR and Kato-Katz, with cycle threshold values converted to eggs per gram for qPCR. Cohen's kappa statistic evaluated agreement between qPCR and Kato-Katz. DNA extraction and qPCR were repeated on 191 (of 278) samples that were initially qPCR negative but Kato-Katz positive, of which 112 (58.6%) became positive. Similar prevalence for Ascaris lumbricoides (37.5% versus 34.6%) and Trichuris trichiura (6.5% versus 6.1%) were found by qPCR and Kato-Katz, respectively, while qPCR detected a higher hookworm prevalence (11.9% versus 2.9%). The prevalence of moderate- or high-intensity infections was higher by Kato-Katz than by qPCR. Agreement between qPCR and Kato-Katz was very good for A. lumbricoides, moderate for T. trichiura, and fair for hookworm. Strongyloides stercoralis prevalence was 4.7% (municipality range, 0-14.3%), and no Ancylostoma ceylanicum was detected by qPCR. Despite suboptimal performance, presumably due to fixative choice, qPCR was fundamental in detecting S. stercoralis and excluding zoonotic A. ceylanicum. Further evaluations on sample fixatives and DNA extraction methods are needed to optimize and standardize the performance of qPCR.