Standardizing Plasmodium falciparum infection prevalence measured via microscopy versus rapid diagnostic test. (December 2015)

• Record Type: Journal Article
• Authors: Mappin, Bonnie; Cameron, Ewan; Dalrymple, Ursula; Weiss, Daniel; Bisanzio, Donal; Bhatt, Samir; Gething, Peter
• Is Part Of: Malaria journal. Volume 14:Number 1(2015)
• Page Start: 1
• Page End: 10
• Publication Date: 2015-12
• Subjects: Malaria -- Plasmodium falciparum -- Africa -- RDT -- Microscopy -- Diagnostics; Malaria -- Periodicals; 616.9362
• DOI: 10.1186/s12936-015-0984-9
• Languages: English
• ISSNs: 1475-2875

Abstract

Abstract Background Large-scale mapping ofPlasmodium falciparum infection prevalence relies on opportunistic assemblies of infection prevalence data arising from thousands ofP. falciparum parasite rate (Pf PR) surveys conducted worldwide. Variance in these data is driven by both signal, the true underlying pattern of infection prevalence, and a range of factors contributing to 'noise', including sampling error, differing age ranges of subjects and differing parasite detection methods. Whilst the former two noise components have been addressed in previous studies, the effect of different diagnostic methods used to determinePf PR in different studies has not. In particular, the majority ofPf PR data are based on positivity rates determined by either microscopy or rapid diagnostic test (RDT), yet these approaches are not equivalent; therefore a method is needed for standardizing RDT and microscopy-based prevalence estimates prior to use in mapping. Methods Twenty-five recent Demographic and Health surveys (DHS) datasets from sub-Saharan Africa provide child diagnostic test results derived using both RDT and microscopy for each individual. These prevalence estimates were aggregated across level one administrative zones and a Bayesian probit regression model fit to the microscopy- versus RDT-derived prevalence relationship. An errors-in-variables approach was employed to account for sampling error in both the dependent and independent variables. In addition to the diagnostic outcome, RDT type, fever status and recent anti-malarial treatment were extracted from the datasets in order to analyse their effect on observed malaria prevalence. Results A strong non-linear relationship between the microscopy and RDT-derived prevalence was found. The results of regressions stratified by the additional diagnostic variables (RDT type, fever status and recent anti-malarial treatment) indicate that there is a distinct and consistent difference in the relationship when the data are stratified by febrile status and RDT brand. Conclusions The relationships defined in this research can be applied to RDT-derivedPf PR data to effectively convert them to an estimate of the parasite prevalence expected using microscopy (or vice versa), thereby standardizing the dataset and improving the signal-to-noise ratio. Additionally, the results provide insight on the importance of RDT brands, febrile status and recent anti-malarial treatment for explaining inconsistencies between observed prevalence derived from different diagnostics.