title: Understanding the relationship between Plasmodium falciparum growth rate and multiplicity of infection.
abstract: Natural infections with Plasmodium falciparum are often composed of multiple concurrent genetically distinct parasite clones. Such multiclonal infections are more common in areas of high transmission, and the frequency of multiclonal infection also varies with age. A number of studies have suggested that multiclonal infection predicts the risk of subsequent clinical malaria. The multiplicity of infection is determined by the rate of new infections, the number of clones inoculated at each mosquito bite, and the duration of infections. Here, we used a mathematical modeling approach to understand how variation in the growth rate of blood-stage parasites affects the observed multiplicity of infection (MOI), as well as the relationship between the MOI and the risk of subsequent malaria. We then analyzed data from a study of multiclonal infection and malaria in an malaria-endemic area in Tanzania and show that the proportion of multiclonal infections varies with age and that the observed relationship between multiclonal infection and subsequent clinical events can be explained by a reduction in blood-stage parasite growth with age in this population.
authors.affiliation: Centre for Vascular Research, University of New South Wales, Sydney, Australia.
authors.forename: Mykola
authors.initials: M
authors.lastname: Pinkevych
authors.affiliation: Centre for Vascular Research, University of New South Wales, Sydney, Australia.
authors.forename: Janka
authors.initials: J
authors.lastname: Petravic
authors.affiliation: Unit of Infectious Diseases, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
authors.forename: Sandor
authors.initials: S
authors.lastname: Bereczky
authors.affiliation: Unit of Infectious Diseases, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
authors.forename: Ingegerd
authors.initials: I
authors.lastname: Rooth
authors.affiliation: Unit of Infectious Diseases, Department of Medicine, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.
authors.forename: Anna
authors.initials: A
authors.lastname: Färnert
authors.affiliation: Centre for Vascular Research, University of New South Wales, Sydney, Australia.
authors.forename: Miles P
authors.initials: MP
authors.lastname: Davenport
mesh_terms: D000293:Adolescent; D000367:Age Factors; D000953:Antigens, Protozoan / Q000235:genetics*; D002648:Child; D002675:Child, Preschool; D015331:Cohort Studies; D060085:Coinfection; D003430:Cross-Sectional Studies; D005838:Genotype; D006801:Humans; D016778:Malaria, Falciparum / Q000453:epidemiology / Q000401:mortality / Q000469:parasitology*; D008297:Male; D008962:Models, Theoretical; D018512:Parasitemia; D010963:Plasmodium falciparum / Q000235:genetics / Q000254:growth & development* / Q000472:pathogenicity; D016012:Poisson Distribution; D015800:Protozoan Proteins / Q000235:genetics*; D012306:Risk; D016019:Survival Analysis; D013636:Tanzania / Q000453:epidemiology
chemical_list: D000953:Antigens, Protozoan; D015800:Protozoan Proteins; C065974:merozoite surface protein 2, Plasmodium
keywords: P. falciparum; malaria; mathematical modeling; statistical analysis