Quantification of markers of antimalarial drug resistance from an area of high malaria transmission: Comparing frequency with prevalence

Abstract

Molecular monitoring of markers of antimalarial drug resistance offers an affordable alternative to the in vivo method for the detection of resistance, and has the potential to guide public health policy in a timely manner. However, the optimal way of analyzing and reporting these data, particularly those emanating from areas of moderate to high malaria transmission, has never been fully explored or agreed upon, given the potential of being confounded by coinfections. By using large number of real field samples, we quantified the difference between prevalence and frequency when reporting field data on antimalarial drug resistance obtained by direct counting of haplotypes. Polymerase chain reaction (PCR) and sequence specific oligonucleotide probing was used to generate point mutations which were used to construct haplotypes. Results indicate that frequency underestimates haplotypes present at low levels while also amplifying haplotypes present at high levels; prevalence on the other hand behaved in a vice versa manner. Both prevalence and frequency are therefore essential, as each may have relevance in different contexts in high malaria transmission settings. Frequency is essential to gauge the impact of intervention on antimalarial drug resistance while prevalence may be more relevant when the aim is to determine parasite clearance.

Estimation of malaria haplotype and genotype frequencies: a statistical approach to overcome the challenge associated with multiclonal infections

“…Using prevalence data, various counting strategies have been used to estimate the frequency of the marker in the parasite population [22,23]. To assess these approaches, the frequency estimates from the statistical model were compared with those from commonly used counting methods using the data from Uganda (see Section 3, Additional file 2 for full details).…”

“…Additional counting methods to estimate gene frequency also exist [22,23]. These include discarding all discernibly multiclonal blood samples, which can lead to large losses of data; or discounting minority alleles at mixed SNPs.…”

Artemether-Lumefantrine and Dihydroartemisinin-Piperaquine Exert Inverse Selective Pressure on Plasmodium Falciparum Drug Sensitivity-Associated Haplotypes in Uganda

“…It is important to note that our model generates frequency estimates, not empirical results. Alternative nonmodel-based haplotype analyses tend to collapse data from multiclonal samples into parsimonious haplotype assignments or to omit multiclonal samples [ 9 , 10 , 22 , 23 ]. These analyses may lead to incorrect assignments (as cautioned against in [ 9 ]), or biased estimates and data loss [ 22 , 23 ], but have the advantage of being empirical.…”

Comparative assessment on the prevalence of mutations in the Plasmodium falciparum drug-resistant genes in two different ecotypes of Odisha state, India

“…Needless to mention, such information will be of enormous benefit to the local malaria control program (Dash et al, 2008). This is because, in high malaria transmission areas resistance against CQ and SP in the malaria parasite Plasmodium falciparum spreads fast, whereas in low transmission areas, drug pressure plays a much crucial role (Hastings and Watkins, 2005; Malisa et al, 2016; Mallick et al, 2013a; Mallick et al, 2013b; Talisuna et al, 2002). It has further been proposed that the predominance of tribal groups along with unrestricted use of inappropriate antimalarials, population movements, resettlements, and presence of sylvatic mosquito vectors promote rapid evolution of antimalarial resistance and therefore high malaria transmission settings encompassing this type of ecotype were proposed to be centre of origin of drug resistance (Chareonviriyaphap et al, 2000; Kar et al, 2014; Keiser et al, 2005; Malakooti et al, 1998; Singh, N. et al, 2009).…”

“…Tracking the patterns of mutations, estimating genetic diversities at the Single Nucleotide Polymorphism (SNP) level and asserting linkage among the SNPs in populations are the most efficient ways to understand the evolution of that particular gene (Carlton et al, 2015; Malisa et al, 2016; Pelleau et al, 2015; Sutar et al, 2013). Several studies following these methodologies in genes conferring resistance to antimalarials in P. falciparum have indicated evolutionary potential of these genes both at the global scale and also in India (Awasthi et al, 2011; Brown et al, 2015; Das and Dash, 2007; Kumar et al, 2015; Li et al, 2015; Rouhani et al, 2015).…”