2020
DOI: 10.22541/au.159015516.68850426
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Monitoring Plasmodium falciparum and Plasmodium vivax using microsatellite markers indicates limited changes in population structure after substantial transmission decline in Papua New Guinea

Abstract: Monitoring the genetic structure of pathogen populations may be an economical and sensitive approach to quantify the impact of control on transmission dynamics, highlighting the need for a better understanding of changes in population genetic parameters as transmission declines. Here we describe the first population genetic analysis of the major human malaria parasites, Plasmodium falciparum (Pf) and Plasmodium vivax (Pv) populations following nationwide distribution of long-lasting insecticide treated nets (L… Show more

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“…Panels of multiallelic microsatellites have been widely used to look at P. falciparum population genetics in a range of transmission settings to define linkage disequilibrium ( Anderson et al, 2000 ; Machado et al, 2004 ; Anthony et al, 2005 ; Mobegi et al, 2012 ; Yalcindag et al, 2012 ; Barry et al, 2013 ; Vera-Arias et al, 2019 ; Kattenberg et al, 2020 ). Most recently, biallelic single nucleotide polymorphisms (SNPs) have been used by malariologists working in low- to moderate-transmission settings to look at diversity and population structure of clinical infections in response to interventions ( Daniels et al, 2013 ; Nkhoma et al, 2013 ; Daniels et al, 2015 ; Bei et al, 2018 ).…”
Section: Introductionmentioning
confidence: 99%
“…Panels of multiallelic microsatellites have been widely used to look at P. falciparum population genetics in a range of transmission settings to define linkage disequilibrium ( Anderson et al, 2000 ; Machado et al, 2004 ; Anthony et al, 2005 ; Mobegi et al, 2012 ; Yalcindag et al, 2012 ; Barry et al, 2013 ; Vera-Arias et al, 2019 ; Kattenberg et al, 2020 ). Most recently, biallelic single nucleotide polymorphisms (SNPs) have been used by malariologists working in low- to moderate-transmission settings to look at diversity and population structure of clinical infections in response to interventions ( Daniels et al, 2013 ; Nkhoma et al, 2013 ; Daniels et al, 2015 ; Bei et al, 2018 ).…”
Section: Introductionmentioning
confidence: 99%