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

Monica P Shah; Winnie Chebore; Robert H Lyles; Kephas Otieno; Zhiyong Zhou; Mateusz Plucinski; Lance A Waller; Wycliffe Odongo; Kim A Lindblade; Simon Kariuki; Aaron M Samuels; Meghna Desai; Rebecca M Mitchell; Ya Ping Shi

doi:10.1186/s12936-022-04323-2

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

Malar J. 2022 Nov 6;21(1):319. doi: 10.1186/s12936-022-04323-2.

Authors

Monica P Shah^{1

2}, Winnie Chebore³, Robert H Lyles⁴, Kephas Otieno³, Zhiyong Zhou^{5

6}, Mateusz Plucinski^{5

6}, Lance A Waller⁴, Wycliffe Odongo³, Kim A Lindblade^{5

6}, Simon Kariuki³, Aaron M Samuels^{5

6}, Meghna Desai^{5

6}, Rebecca M Mitchell⁷, Ya Ping Shi^{8

9}

Affiliations

¹ Division of Parasitic Diseases and Malaria, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, GA, USA. MShah2@cdc.gov.
² Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA. MShah2@cdc.gov.
³ Kenya Medical Research Institute, Centre for Global Health Research, Kisumu, Kenya.
⁴ Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
⁵ Division of Parasitic Diseases and Malaria, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, GA, USA.
⁶ Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
⁷ Department of Computer Science, Emory University, Atlanta, GA, USA.
⁸ Division of Parasitic Diseases and Malaria, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, GA, USA. yps0@cdc.gov.
⁹ Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA. yps0@cdc.gov.

Abstract

Background: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Keywords: Group testing; Pooled testing; Subpatent malaria parasitemia.

MeSH terms

Clinical Trials as Topic
Diagnostic Tests, Routine
Humans
Kenya / epidemiology
Likelihood Functions
Malaria* / diagnosis
Malaria* / epidemiology
Malaria, Falciparum* / epidemiology
Molecular Diagnostic Techniques
Parasitemia / diagnosis
Parasitemia / epidemiology
Prevalence
Sensitivity and Specificity