Malaria programs rely upon a variety of diagnostic assays, including rapid diagnostic tests (RDTs), microscopy, polymerase chain reaction (PCR), and bead-based immunoassays (BBA), to monitor malaria prevalence and support control and elimination efforts. Data comparing these assays are limited, especially from high-burden countries like the Democratic Republic of the Congo (DRC). Using cross-sectional and routine data, we compared diagnostic performance and Plasmodium falciparum prevalence estimates across health areas of varying transmission intensity to illustrate the relevance of assay performance to malaria control programs. Data and samples were collected between March-June 2018 during a cross-sectional household survey across three health areas with low, moderate, and high transmission intensities within two health zones of Kinshasa province, DRC. Samples from 1,431 participants were evaluated using RDT, microscopy, PCR, and BBA. P. falciparumparasite prevalence varied between diagnostic methods across all health areas, with the highest prevalence estimates observed in Bu (57.4-72.4% across assays), followed by Kimpoko (32.6-53.2%), and Voix du Peuple (3.1-8.4%). Using latent class analysis to compare these diagnostic methods against an “alloyed gold standard,” the most sensitive diagnostic method was BBA in Bu (high prevalence) and Voix du Peuple (low prevalence), while PCR diagnosis was most sensitive in Kimpoko (moderate prevalence). RDTs were consistently the most specific diagnostic method in all health areas. Among 9.0 million people residing in Kinshasa Province in 2018, the estimated P. falciparum prevalence by microscopy, PCR, and BBA were nearly double that of RDT. Comparison of malaria RDT, microscopy, PCR, and BBA results confirmed differences in sensitivity and specificity that varied by endemicity, with PCR and BBA performing best for detecting any P. falciparuminfection. Prevalence estimates varied widely depending on assay type for parasite detection. Inherent differences in assay performance should be carefully considered when using community survey and surveillance data to guide policy decisions.

JBP reports financial support from Gilead Sciences and non-financial support from Abbott Diagnostics, both outside the scope of this work.

This work was funded by NIH R01AI132547 to JJJ and RRD and R01AI129812 to AT, with partial support from NIH K24AI134990 to JJJ and T32AI070114 to KEB and RS, and from the American Society of Tropical Medicine and Hygiene/Burroughs Wellcome Fund to JBP.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The study was approved by the Ethical Committee of the Kinshasa School of Public Health (# ESP/CE/021/2017) and the University of North Carolina (UNC) Institutional Review Board (# 17-1588) and determined to be an activity not involving human subject research by the Human Subjects office of the Centers for Disease Control and Prevention (project 0900f3eb81bec92c).

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De-identified data analyzed as part of this study will be made available through the Carolina Digital Repository at the University of North Carolina at Chapel Hill.