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A Comparison of Methods to Detect and Quantify the Markers of Antimalarial Drug Resistance

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  • Molecular and Biochemical Parasitology, Liverpool School of Tropical Medicine, Liverpool, United Kingdom; Biostatistics and Computational Sciences, Swiss Tropical and Public Health Institute, Basel, Switzerland
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We compare, contrast, and evaluate methods to quantify genetic markers of antimalarial drug resistance. Frequency estimates should be reported along with crude prevalence. There are four main potential methods to estimate frequencies in blood samples: simple counting of single nucleotide polymorphisms (SNPs) and haplotypes in samples with multiplicity of infection (MOI) = 1; SNP counting in samples with MOI ≤ 2; SNP and haplotypes counting in samples with unambiguous genotypes; statistical inference using SNP and MOI data from all samples. Large differences between the methods became apparent when analyzing field data with high MOI. Simple counting dramatically reduced sample size and estimate precision, and we show that analysis of unambiguous samples is biased, leaving maximum likelihood or similar statistical inference as the only practical option. It is essential to account for genotyping missing minor clones; ignoring this phenomenon resulted in a 2-fold underestimation of SNPs and haplotypes present at low frequencies.

Author Notes

*Address correspondence to Ian M. Hastings, Molecular and Biochemical Parasitology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool L3 5QA, UK. E-mail: hastings@liverpool.ac.uk

Financial support: This work was supported by the Bill and Melinda Gates Foundation Grant 37999.01, the Liverpool School of Tropical Medicine, and the Université de Neuchâtel. The molecular analysis was financed by the Schweizerische Nationalfonds (SNF; Grant 3100-AO-103968) for the Papua New Guinea samples and the Geigy foundation for Tanzanian samples. The morbidity surveillance in PNG was first supported by United States Agency for International Development (USAID) and then by Australian Agency for International Development (AusAID) within the Malaria Vaccine Epidemiology and Evaluation Project.

Authors' addresses: Ian M. Hastings, Molecular and Biochemical Parasitology, Liverpool School of Tropical Medicine, Liverpool, UK, E-mail: hastings@liverpool.ac.uk. Christian Nsanzabana, Division of Infectious Diseases, Department of Medicine, University of California, San Francisco, CA, E-mail: nsanzabanac@medsfgh.ucsf.edu. Tom A. Smith, Biostatistics and Computational Sciences, Swiss Tropical and Public Health Institute, Basel, Switzerland, E-mail: Thomas-A.Smith@unibas.ch.

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