Accuracy of Plasmodium falciparum genetic data for estimating parasite prevalence and malaria incidence in Uganda

Microhaplotype-based metrics of within-host diversity, particularly COI and eCOI, reliably reflected spatial variation in malaria prevalence across Uganda, while between-host relatedness provided complementary information and was the strongest predictor of incidence. These findings indicate that parasite genomic metrics derived from polyallelic microhaplotypes can capture broad differences in transmission intensity reflected by parasite prevalence, but may have more limited ability to predict incidence. Integration of genomic metrics with harmonized epidemiologic data and expanded sampling of asymptomatic infections will be important next steps to understand the potential utility of parasite genetic metrics for malaria surveillance and subnational stratification.

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Publication Details

Journal
Malaria Journal
Published
2026-02-21
DOI
https://doi.org/10.1186/s12936-026-05836-w
Primary Topic
Malaria Research and Control
Type
article
Field-Weighted Citation Impact
0.00
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article

Accuracy of Plasmodium falciparum genetic data for estimating parasite prevalence and malaria incidence in Uganda

Gerald Mboowa, Kisakye Diana Kabbale, Caroline Mwubaha, Victor Asua et al.
Malaria Journal
Malaria Research and Control
article

Accuracy of Plasmodium falciparum genetic data for estimating parasite prevalence and malaria incidence in Uganda

Gerald Mboowa, Kisakye Diana Kabbale, Caroline Mwubaha, Victor Asua, Eric Watyekele, Andres Aranda-Diaz, Melissa D. Conrad, Bienvenu Nsengimaana, Isaac Ssewanyana, Grant Dorsey, Monica Mbabazi, Stephen Tukwasibwe, Thomas Katairo, Alisen Ayitewala, Innocent Wiringilimaana, Francis Ddumba Semakuba, Joyce Nakatumba Nabende, David Patrick Kateete, Daudi Jjingo, Jerry Mulondo, Philip J. Rosenthal, Samuel Lubwama Nsobya, Jackie Nakasaanya, Moses Robert Kamya, Bryan Greenhouse, Bosco Agaba, Catherine Maiteki-Sebuguzi, Shahiid Kiyaga, Jessica Briggs, Charles Batte
article en

Abstract

Microhaplotype-based metrics of within-host diversity, particularly COI and eCOI, reliably reflected spatial variation in malaria prevalence across Uganda, while between-host relatedness provided complementary information and was the strongest predictor of incidence. These findings indicate that parasite genomic metrics derived from polyallelic microhaplotypes can capture broad differences in transmission intensity reflected by parasite prevalence, but may have more limited ability to predict incidence. Integration of genomic metrics with harmonized epidemiologic data and expanded sampling of asymptomatic infections will be important next steps to understand the potential utility of parasite genetic metrics for malaria surveillance and subnational stratification.

Malaria JournalVol. 25(1)
Broad Institute (US), Mbarara University of Science and Technology (UG), University of California, San Francisco (US), Africa Center (US), University of California System (US), Ministry of Health (UG), Infectious Diseases Institute (UG), Infectious Diseases Research Collaboration (UG), Barcelona Institute for Global Health (ES), Makerere University (UG), University of Tübingen (DE), Uganda Christian University (UG)
Good health and well-being
Openalex Percentile: Top 50%
Malaria Research and Control
DOIOpen Access PDFOpenAlex
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