Travel-related malaria is regularly encountered in the United States, and the U.S. Centers for Disease Control and Prevention (CDC) characterizes drug-resistance genotypes routinely for travel-related cases. An important aspect of antimalarial drug resistance is understanding its geographic distribution. However, specimens submitted to CDC laboratories may have missing, incomplete, or inaccurate travel data. To complement genotyping for drug-resistance markers , , , , , and at CDC, amplicons of and are also sequenced as markers of geographic origin. Here, a bi-allele likelihood (BALK) classifier was trained using and sequences from published genomes of known geographic origin to classify clinical genotypes to a continent. Among -positive blood samples received at CDC for drug-resistance genotyping from 2018 to 2021 ( = 380), 240 included a travel history with the submission materials, though 6 were excluded due to low sequence quality. Classifications obtained for the remaining 234 were compared to their travel histories. Classification results were over 96% congruent with reported travel for clinical samples, and with collection sites for field isolates. Among travel-related samples, only two incongruent results occurred; a specimen submitted citing Costa Rican travel classified to Africa, and a specimen with travel referencing Sierra Leone classified to Asia. Subsequently, the classifier was applied to specimens with unreported travel histories ( = 140; 5 were excluded due to low sequence quality). For the remaining 135 samples, geographic classification data were paired with results generated using CDC's Malaria Resistance Surveillance (MaRS) protocol, which detects single-nucleotide polymorphisms in and generates haplotypes for , , , , , and . Given the importance of understanding the geographic distribution of antimalarial drug resistance, this work will complement domestic surveillance efforts by expanding knowledge on the geographic origin of drug-resistant entering the USA.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11619247 | PMC |
http://dx.doi.org/10.1128/aac.01203-24 | DOI Listing |
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