On the Effects of Malaria Treatment on Parasite Drug Resistance – Probability Modelling of Genotyped Malaria Infections

Kum Cletus Kwa (), Thorburn Daniel (), Ghilagaber Gebrenegus (), Gil Pedro () and Björkman Anders ()
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Kum Cletus Kwa: Department of Statistics, Stockholm University, Stockholm, Sweden; Department of Mathematics/Computer Science, Faculty of Science, University of Dschang, Dschang, Cameroon
Thorburn Daniel: Department of Statistics, Stockholm University, Stockholm, Sweden
Ghilagaber Gebrenegus: Department of Statistics, Stockholm University, Stockholm, Sweden
Gil Pedro: Division of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden
Björkman Anders: Division of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden

The International Journal of Biostatistics, 2013, vol. 9, issue 1, 135-148

Abstract: We compare the frequency of resistant genes of malaria parasites before treatment and at first malaria incidence after treatment. The data come from a clinical trial at two health facilities in Tanzania and concerns single nucleotide polymorphisms (SNPs) at three positions believed to be related to resistance to malaria treatment. A problem is that mixed infections are common, which both obscures the underlying frequency of alleles at each locus as well as the associations between loci in samples where alleles are mixed. We use combinatorics and quite involved probability methods to handle multiple infections and multiple haplotypes. The infection with the different haplotypes seemed to be independent of each other. We showed that at two of the three studied SNPs, the proportion of resistant genes had increased after treatment with sulfadoxine–pyrimethamine alone but when treated in combination with artesunate, no effect was noticed. First recurrences of malaria associated more with sulfadoxine–pyrimethamine alone as treatment than when in combination with artesunate. We also found that the recruited children had two different ongoing malaria infections where the parasites had different gene types.

Keywords: genotyped malaria; efficacy; combinatorics; parametric model; haplotype; single nucleotide polymorphism (SNP) (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1515/ijb-2012-0016

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