Novel application of one-step pooled molecular testing and maximum likelihood approaches to estimate the prevalence of malaria parasitaemia among rapid diagnostic test negative samples in western Kenya

• Published in: Malaria journal Vol. 21; no. 1; p. 319
• Main Authors: Shah, Monica P, Chebore, Winnie, Lyles, Robert H, Otieno, Kephas, Zhou, Zhiyong, Plucinski, Mateusz, Waller, Lance A, Odongo, Wycliffe, Lindblade, Kim A, Kariuki, Simon, Samuels, Aaron M, Desai, Meghna, Mitchell, Rebecca M, Shi, Ya Ping
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 06.11.2022; BioMed Central; BMC
• Subjects: Blood & organ donations; Clinical Trials as Topic; Cost control; Diagnostic tests; Diagnostic Tests, Routine; Estimates; Group testing; Human diseases; Humans; Infections; Kenya - epidemiology; Laboratories; Likelihood Functions; Malaria; Malaria - diagnosis; Malaria - epidemiology; Malaria, Falciparum - epidemiology; Microscopy; Molecular Diagnostic Techniques; Nucleotide sequence; Parasitemia - diagnosis; Parasitemia - epidemiology; Parasites; Polymerase chain reaction; Pooled testing; Prevalence; Random sampling; Sensitivity and Specificity; Specificity; Subpatent malaria parasitemia; Testing; Trends; Validation studies; Vector-borne diseases; Kenya; United States > US; Group testing; Pooled testing; Subpatent malaria parasitemia
• ISSN: 1475-2875; 1475-2875
• DOI: 10.1186/s12936-022-04323-2

Detection of malaria parasitaemia in samples that are negative by rapid diagnostic tests (RDTs) requires resource-intensive molecular tools. While pooled testing using a two-step strategy provides a cost-saving alternative to the gold standard of individual sample testing, statistical adjustments are needed to improve accuracy of prevalence estimates for a single step pooled testing strategy. A random sample of 4670 malaria RDT negative dried blood spot samples were selected from a mass testing and treatment trial in Asembo, Gem, and Karemo, western Kenya. Samples were tested for malaria individually and in pools of five, 934 pools, by one-step quantitative polymerase chain reaction (qPCR). Maximum likelihood approaches were used to estimate subpatent parasitaemia (RDT-negative, qPCR-positive) prevalence by pooling, assuming poolwise sensitivity and specificity was either 100% (strategy A) or imperfect (strategy B). To improve and illustrate the practicality of this estimation approach, a validation study was constructed from pools allocated at random into main (734 pools) and validation (200 pools) subsets. Prevalence was estimated using strategies A and B and an inverse-variance weighted estimator and estimates were weighted to account for differential sampling rates by area. The prevalence of subpatent parasitaemia was 14.5% (95% CI 13.6-15.3%) by individual qPCR, 9.5% (95% CI (8.5-10.5%) by strategy A, and 13.9% (95% CI 12.6-15.2%) by strategy B. In the validation study, the prevalence by individual qPCR was 13.5% (95% CI 12.4-14.7%) in the main subset, 8.9% (95% CI 7.9-9.9%) by strategy A, 11.4% (95% CI 9.9-12.9%) by strategy B, and 12.8% (95% CI 11.2-14.3%) using inverse-variance weighted estimator from poolwise validation. Pooling, including a 20% validation subset, reduced costs by 52% compared to individual testing. Compared to individual testing, a one-step pooled testing strategy with an internal validation subset can provide accurate prevalence estimates of PCR-positivity among RDT-negatives at a lower cost.