Marked heterogeneity in malaria infection rate in a Malian longitudinal cohort

Emily LaVerriere, Zachary M. Johnson, Meg Shieh, Nadege Nziza, Galit Alter, Caroline O. Buckee, Peter D. Crompton, Boubacar Traore, Tuan M. Tran and Daniel E. Neafsey ()
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Emily LaVerriere: Harvard T.H. Chan School of Public Health
Zachary M. Johnson: Harvard T.H. Chan School of Public Health
Meg Shieh: Harvard T.H. Chan School of Public Health
Nadege Nziza: Ragon Institute of MGH, MIT, and Harvard
Galit Alter: Ragon Institute of MGH, MIT, and Harvard
Caroline O. Buckee: Harvard T.H. Chan School of Public Health
Peter D. Crompton: National Institutes of Health
Boubacar Traore: University of Sciences, Technique and Technology of Bamako
Tuan M. Tran: Indiana University School of Medicine
Daniel E. Neafsey: Harvard T.H. Chan School of Public Health

Nature Communications, 2025, vol. 16, issue 1, 1-13

Abstract: Abstract Variation in malaria infection risk, a product of disease exposure and immunity, is poorly understood. We genotypically profiled over 13,000 blood samples from a six-year longitudinal cohort in Mali to characterize malaria infection dynamics with detail. We generated Plasmodium falciparum amplicon sequencing data from 464 participants (aged 3 months – 25 years) across the six-month 2011 transmission season and profiled a subset of 120 participants across the subsequent five annual transmission seasons. We measured infection rate as the molecular force of infection (molFOI, number of genetically distinct parasites acquired over time). We found that molFOI varied extensively among individuals (0–55 in 2011) but was independent of age and consistent within individuals over multiple seasons. Reported bednet usage was nearly universal. The HbS allele was associated with lower molFOI, and functional antibody signatures for the CSP C-term and RH5 antigens were correlated with low molFOI participants, identifying candidate immune correlates of protection. The large inter-individual variability in molFOI and consistency of intra-individual infection rate over time exhibits much greater dynamic range than malaria case incidence, and is most likely due to heterogeneous exposure to infectious mosquito bites. This and other factors contributing to variable infection risk should be considered in future clinical trials and implementation of malaria interventions.

Date: 2025
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DOI: 10.1038/s41467-025-61462-1

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