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We describe Plasmodium falciparum genetic diversity in coastal Kenya, typing S-antigen and the merozoite surface proteins 1 and 2 (MSP-1 and MSP-2) in field isolates by the polymerase chain reaction (PCR). Malaria in coastal Kenya is characterized by low seasonal transmission, and a relatively high incidence of severe disease, which tends to occur in time-space clusters. We chose the highly polymorphic S-antigen as a marker for localized parasite diversity because it has been shown to vary in serotype prevalence in time and space. A total of 261 children (up to nine years of age) in two neighboring locations with different transmission rates were sampled for blood-stage parasites in cross-sectional surveys before and after the main transmission period in 1991, and also in a concomitant one-year longitudinal survey tracing clinical infections. Six major sequence types of S-antigen were identified, which were subdivided into 70 alleles; however, only 50% of isolates were typeable. The S-antigen sequence types varied qualitatively between locations, over time, and between asymptomatic and clinical disease infections, but not between different age groups. The MSP-1 and MSP-2 sequence type prevalences, in contrast, did not differ in any of these comparisons. We describe the use of the Mantel test for assessing clustering of individual parasite alleles at the household level, and demonstrate low-level clustering of MSP-1 and MSP-2 alleles and S-antigen sequence types, at the end of a long period of low transmission.

Original publication




Journal article


Am J Trop Med Hyg

Publication Date





205 - 215


Age Factors, Alleles, Animals, Antigens, Protozoan, Child, Child, Preschool, Cross-Sectional Studies, Genes, Protozoan, Humans, Infant, Infant, Newborn, Kenya, Longitudinal Studies, Malaria, Falciparum, Merozoite Surface Protein 1, Molecular Epidemiology, Plasmodium falciparum, Polymerase Chain Reaction, Polymorphism, Genetic, Prevalence, Protein Precursors, Protozoan Proteins, Sensitivity and Specificity, Sequence Analysis, DNA, Time Factors