All recommended treatments against malaria include a drug called artemisinin or some of its derivatives. However, there are concerns that Plasmodium falciparum, the parasite that causes most cases of malaria, will eventually develop widespread resistance to the drug. A strain of P. falciparum partially resistant to artemisinin was seen in Cambodia in 2008, and it has since spread across Southeast Asia. The resistance appears to be frequently linked to a mutation known as pfk13 C580Y.

Southeast Asia and Amazonia are considered to be hotspots for antimalarial drug resistance, and the pfk13 C580Y mutation was detected in the South American country of Guyana in 2010. To examine whether the mutation was still circulating in this part of the world, Mathieu et al. collected and analyzed 854 samples across Guyana between 2016 and 2017. Overall, 1.6% of the samples had the pfk13 C580Y mutation, but this number was as high as 8.8% in one region. Further analyses revealed that the mutation in Guyana had not spread from Southeast Asia, but that it had occurred in Amazonia independently.

To better understand the impact of the pfk13 C580Y mutation, Mathieu et al. introduced this genetic change into non-resistant parasites from a country neighbouring Guyana. As expected, the mutation made P. falciparum highly resistant to artemisinin, but it also slowed the growth rate of the parasite. This disadvantage may explain why the mutation has not spread more rapidly through Guyana in recent years.

Artemisinin and its derivatives are always associated with other antimalarial drugs to slow the development of resistance; there are concerns that reduced susceptibility to artemisinin leads to the parasites becoming resistant to the partner drugs. Further research is needed to evaluate how the pfk13 C580Y mutation affects the parasite’s response to the typical combination of drugs that are given to patients.

Malaria is an important parasitic disease that causes a high level of mortality worldwide. In 2018, malaria was estimated to have caused 405,000 deaths, most of them attributable to the virulent Plasmodium falciparum parasite species (World Health Organization, 2019). Most malaria cases occur in Sub-Saharan Africa, but Southeast Asia and South America are also affected. Since 2001, Artemisinin-based Combination Therapies (ACTs) have been the recommended first-line therapy for P. falciparum infection for almost all malaria-endemic areas (World Health Organization, 2001). ACTs combine an artemisinin derivative and one partner drug (most commonly lumefantrine, mefloquine, amodiaquine, piperaquine or pyronaridine). These treatments have contributed to a major reduction in malaria-related mortality and morbidity (Eastman and Fidock, 2009; Carrara et al., 2006; Bhatt et al., 2015). However, in 2008, the first instances of reduced artemisinin efficacy were described in western Cambodia (Dondorp et al., 2009; Ashley et al., 2014). Subsequent studies have documented the rapid spread of resistance throughout Southeast Asia (Dondorp et al., 2009; Ashley et al., 2014; World Health Organization, 2018). Resistance to artemisinin is partial and affects only rings (World Health Organization, 2018). Clinically, this partial resistance trait manifests as a parasite clearance half-life that exceeds 5.5 hr (WWARN K13 Genotype-Phenotype Study Group, 2019). This half-life represents the time required to achieve a two-fold reduction of the parasite biomass. Partial resistance also manifests as persistent parasitemia on day three with a complete clearance of parasites following full treatment with an artesunate monotherapy lasting seven days or with an ACT (World Health Organization, 2018). An analysis of P. falciparum parasites selected for artemisinin resistance in vitro as well as parasites from patients experiencing slow parasite clearance led to the identification of a genetic locus linked to resistance: a kelch domain-containing protein located on chromosome 13 (pfk13) (Ariey et al., 2014). To date, many missense mutations have been described in the BTP/POZ or kelch propeller domain-containing parts of this protein in clinical isolates, however only nine of them have been validated for artemisinin resistance (F446I, N458Y, M476I, Y493H, R539T, I543T, P553L, R561H and C580Y) (World Health Organization, 2018; Ariey et al., 2014; Straimer et al., 2015). A larger number have been associated with delayed parasite clearance (WWARN K13 Genotype-Phenotype Study Group, 2019). In most locations, the pfk13 C580Y mutation has overtaken other resistance-inducing variants, and it is now the most prevalent pfk13 variant in Southeast Asia (Ashley et al., 2014; Ariey et al., 2014).

South America has historically been a second hotspot outside Southeast Asia for the evolution of antimalarial drug resistance. For example, chloroquine and sulfadoxine-pyrimethamine resistance evolved simultaneously in both regions (Wootton et al., 2002; Roper et al., 2004). The Guiana Shield region of South America, which includes Guyana, Suriname, French Guiana and parts of Brazil, Venezuela and Colombia, is important as a potential source of emerging antimalarial drug resistance. In this region, the subsoil is rich in gold and other minerals, leading to extensive mining activities in forested areas. These mining activities favor malaria transmission, particularly P. falciparum (Douine et al., 2016; Heemskerk, 2011). Mining also generates human population movement and inappropriate use of ACTs, as people generally work deep in the forest, far from medical care (Pribluda et al., 2014; Douine et al., 2018). This erratic use of ACTs, as well as self-medication using ACTs of substandard quality or artemisinin monotherapies, may promote the emergence of resistance to artemisinin.

In Guyana in 2010, 5.1% (5 out of 98) of P. falciparum-infected clinical samples, sharing a common haplotype different from their Cambodian counterparts, exhibited the pfk13 C580Y mutation (Chenet et al., 2016). However, no clinical or in vitro resistance phenotypes were measured or associated with the genotype data. The most recent therapeutic efficacy study conducted in Guyana in 2014 with 50 patients failed to identify pfk13 mutations or delayed parasite clearance time after artemether/lumefantrine treatment (Rahman et al., 2016). The sample size, however, was too small to ensure detection of low-frequency resistance mutations. The objective of the present study was to evaluate whether pfk13 variants (C580Y or others) have persisted in Guyana since 2010, and if so, to evaluate their prevalence in 2016–2017. In the absence of available clinical phenotypes associated with the pfk13 C580Y variant from patients infected and treated in this region, we evaluated the impact of two pfk13 mutations, C580Y and R539T, on in vitro resistance and the rate of parasite growth in a South American parasite genetic background.

Results presented herein confirm the de novo emergence and long-term persistence of the pfk13 C580Y artemisinin resistance mutation in Guyana, South America. Six years after their first identification, pfk13 C580Y mutant parasites continue to circulate in Guyana at low prevalence (1.6%; 14/854). Parasites bearing this mutation belong to a single clonal lineage and are of autochthonous origin. Gene editing studies on French Guianan parasites, closely related to parasites from Guyana, showed that the pfk13 C580Y mutation is able to mediate artemisinin resistance in vitro at levels observed in Southeast Asian parasites harboring this mutation. An adverse impact of this pfk13 mutation on asexual blood stage growth rates of pfk13-edited French Guianan parasite lines in culture was also observed, providing evidence of a fitness cost similar to that previously described for Southeast Asian lines (Nair et al., 2018; Li et al., 2019).

During the 1990s, analyses of resistant parasites retrospectively suggested the simultaneous emergence of resistance to chloroquine and sulfadoxine/pyrimethamine in parasites from Southeast Asia and the Amazonian region of South America (Wootton et al., 2002; Roper et al., 2004; Vinayak et al., 2010). With artemisinin, the same scenario is occurring with evidence of an independent emergence of resistance mutation in South America. For artemisinin resistance, there is an opportunity to dissect the first steps of resistance selection in South America in ‘real time’, relying on genetic markers and phenotypic assays (genotypic surveys, therapeutic efficacy studies, and in vitro phenotyping through the Ring-stage Survival Assay (RSA_0-3h)) developed in Southeast Asia (Ariey et al., 2014; Witkowski et al., 2013). These genetic and phenotypic tools can help address the critical questions of why in vitro resistance to artemisinin has emerged in Region 1 in Guyana, a country with fewer than 20,000 malaria cases in 2018, and why this resistance is not increasing more quickly. In 2004, Guyana was one of the first South American malaria-endemic countries to adopt and implement artemether-lumefantrine (Coartem), the current first-line therapy against P. falciparum. Six years later, in 2010, pfk13 C580Y mutants were first identified. Until now, no further signals of artemisinin resistance or pfk13 mutations had been identified, despite studies incorporating pfk13 genotyping in Guyana (n = 50), Suriname (n = 40) and French Guiana (n = 198) (Rahman et al., 2016; Ménard et al., 2016; Chenet et al., 2017). Other than pfk13 C580Y, no other pfk13 propeller domain mutations have been observed in Guyana. In Southeast Asia, two molecular epidemiological profiles are currently observed. In Western Cambodia, one C580Y linage (KEL1) has displaced other mutations and has rapidly become the dominant pfk13 genotype in that population (>80%) (Amato et al., 2018; Takala-Harrison et al., 2015). This lineage has merged with a multicopy plasmepsin 2 and 3 lineage (PLA1) that is associated with piperaquine resistance (Amato et al., 2018). Nowadays, this co-lineage has colonized northeastern Thailand and southern Laos (Imwong et al., 2017). On the other side, in western Thailand, at the border with Myanmar, a six-year period was required for distinct mutant pfk13 parasite lineages to collectively reach a population prevalence of 20% (Amato et al., 2018; Anderson et al., 2017). At the present time, a patchwork of pfk13 genotypes co-circulates in that population and the prevalence of C580Y lineages fluctuates around 20–30% (Kobasa et al., 2018). In Myanmar, pfk13 mutants are more diverse and the F446I mutation presently dominates the pfk13 mutant parasite population in certain sites, with this mutation being associated with an intermediate resistance phenotype (Han et al., 2020; Bonnington et al., 2017).

Given this history of pfk13 propeller domain mutations in Southeast Asia, beginning with a soft sweep and transitioning to a hard sweep, we might have expected an increase in the prevalence of pfk13 C580Y mutant parasites during this 2010-2016/2017 period in Guyana. However, the situation in this part of the world differs from Southeast Asia. First, efforts to monitor pfk13 mutations in Guyana were not systematically conducted between 2010 and 2017. Sample size could therefore explain why the C580Y mutation was only sporadically observed. Nonetheless, the present study indicates that the mutation has not drastically increased in the parasite population. Differences in the resistance profile to artemisinin partner drugs could also account for the heterogeneity in pfk13 mutational trajectories in Southeast Asia vs. Guyana, a region where markers of resistance have historically reached fixation (Pelleau et al., 2015; Legrand et al., 2012). In Southeast Asia, the rapid spread of artemisinin-resistant genomic lineages can be explained in part by a multidrug-resistant profile, which includes pfk13 variants as well as mutations conferring resistance to the partner drug piperaquine (Amato et al., 2018; Ross et al., 2018; Kim et al., 2019). Our genomic analysis of a panel of Guyanese isolates identified the common South American profile for known drug resistance markers (pfcrt, pfdhps, pfdhfr and pfmdr1) in both mutant and wild-type pfk13 samples (Wootton et al., 2002; Roper et al., 2004; Vinayak et al., 2010; Legrand et al., 2012). In the Guiana Shield, lumefantrine remains a highly effective partner drug for artemisinin, and no mutations or phenotypes associated with lumefantrine resistance have been observed (Legrand et al., 2012). High efficacy of the partner drug could therefore be an important factor limiting the spread of pfk13 C580Y in Guyana. Finally, both the low synonymous pairwise genetic diversity (π_syn = 3.4 x 10⁻⁴) and the low complexity of infection (COI, 2.2% of samples with a COI > 1) in Guyana are in keeping with the expectation that the P. falciparum population in South America is smaller and more recently established than in Southeast Asia (Yalcindag et al., 2012).

The genomic structure of the Guyana parasite population could also help explain why the mutation arose there, rather than other settings in South America. The present findings indicate high outcrossing rates and few clonal lineages in Guyana (0.54% pairs with IBD >0.75). This clonal diversity is relatively high, especially within a South American context. Previous studies have found much higher proportions of non-unique haplotype backgrounds (>30% of samples) within parasite populations from Colombia (Echeverry et al., 2013), Peru (Dharia et al., 2010), and Ecuador (Sáenz et al., 2015; Sáenz et al., 2017). These prior analyses used fewer genomic markers, but the results still suggest that clonal diversity may be greater in the Guiana Shield relative to the rest of the continent, possibly driven by the high P. falciparum transmission level observed in mining areas (Douine et al., 2016; Ministry of Public Health, 2018). As genomic background likely plays a key role in the persistence of resistance mutations like C580Y, this haplotype richness may increase the likelihood that resistance mutations can successfully establish themselves in a permissive background. Subsequently, a low recombination rate may allow these beneficial combinations to then persist within the population. A more definitive exploration of this hypothesis, and of whether Guyana’s current clonal structure represents recent demographic change or historic population subdivision, will be possible as more whole-genome sequence data become available for the continent. The slower trajectory of pfk13 C580Y may also be due to an impaired asexual blood-stage growth rate, and the absence of compensatory mutations that have been hypothesized to aid the spread of the C580Y mutation in Southeast Asia (Amato et al., 2018; Li et al., 2019).

We chose to introduce two pfk13 mutations by gene editing: C580Y mutation because of its presence in Guyana and its dominance in Southeast Asia, and R539T as a positive control for in vitro resistance, as it exhibits the highest RSA observed in Southeast Asian strains along with I543T (Ariey et al., 2014; Straimer et al., 2015). Introducing these mutations conferred high levels of in vitro artemisinin resistance and both mutations negatively impacted growth rates in vitro in our parasite isolates from French Guiana, a neighboring country of Guyana. These growth rate differences provide a surrogate marker of fitness and do not necessarily predict in vivo success of the mutations, as multiple other parameters are also important including gametocyte production, impacts on transmission, and immunity. Our data show that the C580Y mutation was associated with a more severe growth defect compared to the R539T mutation in these asexual blood stage parasites. A similar finding was also recently reported in C580Y-edited isolates from the Thailand-Myanmar border (Nair et al., 2018), although disparate results were obtained for C580Y-edited isolates from Cambodia (Straimer et al., 2017). These contrasting data underline the influence of the parasite’s genomic background, which potentially involves compensatory mutations that impact the overall growth. Further studies will be needed to screen for potential secondary mutations that may be offsetting these fitness costs. It will also be important to examine factors that could drive the persistence of mutant pfk13 in Guyana despite the apparent fitness cost, including a consideration of local antimalarial drug usage and quality, transmission levels, and population movement.

The World Health Organization (WHO) has categorized countries regarding artemisinin resistance based on pfk13 mutant prevalence and the clinical response to artemisinin derivatives (World Health Organization, 2017). The threshold of 5% of pfk13 mutants has been met on several occasions in Guyana, first in 2010 (Chenet et al., 2016), then punctually in 2016–2017 in Region 1. The situation is evolving and a marker could disappear for reasons that are currently unclear. Nonetheless, in light of these findings, Guyana has the status of suspected resistance to artemisinin derivatives (World Health Organization, 2017). The clinical and public health significance of the presence of these mutations on the therapeutic efficacy of artemisinin-based combination therapies in Guyana, and more precisely artemether/lumefantrine - first line in the country, should be directly evaluated. We note that our study had limitations including the small number of analyzed samples and the in vitro phenotypic impact evaluated in parasites from nearby French Guiana and not Guyana itself. Nonetheless, we observed that pfk13 mutants still circulated in 2016–2017. Given their decreased susceptibility to DHA in vitro, these mutants are likely to expose the partner drug to the risk of emerging resistance. This situation could defeat P. falciparum elimination strategies in this region. Therefore, national health authorities should continue to work together in order to overcome difficulties coming from their multiplicity of regulations, malaria control strategies and transmission levels in the context of major human migrations across borders. The Guiana Shield initiative launched by the Pan American Health Organization (PAHO) and the WHO in 2016 will have a crucial role to reinforce and to coordinate the different malaria control measures.

The authors declare that the data supporting the findings of this study are available within the paper and its supplementary information. Whole genome sequencing data from this study are available from the NCBI Sequence Read Archive under BioProject ID PRJNA543530. Genome data from the Pf3K project are available at https://www.malariagen.net/projects/pf3k.

1. 1. Early A
   2. Mathieu L
   3. Cox H
   4. Musset L
   5. Neafsey DE

   (2018) NCBI BioProject

   ID PRJNA543530. Whole Genome Sequencing of P. falciparum collecte in Guyana, 2016-2017.

   https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA543530

1. 1. Kwiatkowski DP

   (2019) Malaria Gen

   MALARIAGEN: Malaria Genomic Epidemiology Network.

   https://www.malariagen.net/projects/pf3k

1. 1. Adjalley SH
   2. Lee MC
   3. Fidock DA

   (2010) A method for rapid genetic integration into Plasmodium falciparum utilizing mycobacteriophage Bxb1 integrase

   Methods in Molecular Biology 634:87–100.

   https://doi.org/10.1007/978-1-60761-652-8_6

   • PubMed
   • Google Scholar
2. 1. Amato R
   2. Pearson RD
   3. Almagro-Garcia J
   4. Amaratunga C
   5. Lim P
   6. Suon S
   7. Sreng S
   8. Drury E
   9. Stalker J
   10. Miotto O
   11. Fairhurst RM
   12. Kwiatkowski DP

   (2018) Origins of the current outbreak of multidrug-resistant malaria in Southeast Asia: a retrospective genetic study

   The Lancet Infectious Diseases 18:337–345.

   https://doi.org/10.1016/S1473-3099(18)30068-9

   • PubMed
   • Google Scholar
3. 1. Anderson TJ
   2. Nair S
   3. McDew-White M
   4. Cheeseman IH
   5. Nkhoma S
   6. Bilgic F
   7. McGready R
   8. Ashley E
   9. Pyae Phyo A
   10. White NJ
   11. Nosten F

   (2017) Population parameters underlying an ongoing soft sweep in southeast asian malaria parasites

   Molecular Biology and Evolution 34:131–144.

   https://doi.org/10.1093/molbev/msw228

   • PubMed
   • Google Scholar
4. 1. Ariey F
   2. Witkowski B
   3. Amaratunga C
   4. Beghain J
   5. Langlois A-C
   6. Khim N
   7. Kim S
   8. Duru V
   9. Bouchier C
   10. Ma L
   11. Lim P
   12. Leang R
   13. Duong S
   14. Sreng S
   15. Suon S
   16. Chuor CM
   17. Bout DM
   18. Ménard S
   19. Rogers WO
   20. Genton B
   21. Fandeur T
   22. Miotto O
   23. Ringwald P
   24. Le Bras J
   25. Berry A
   26. Barale J-C
   27. Fairhurst RM
   28. Benoit-Vical F
   29. Mercereau-Puijalon O
   30. Ménard D

   (2014) A molecular marker of artemisinin-resistant Plasmodium falciparum malaria

   Nature 505:50–55.

   https://doi.org/10.1038/nature12876

   • Google Scholar
5. 1. Ashley EA
   2. Dhorda M
   3. Fairhurst RM
   4. Amaratunga C
   5. Lim P
   6. Suon S
   7. Sreng S
   8. Anderson JM
   9. Mao S
   10. Sam B
   11. Sopha C
   12. Chuor CM
   13. Nguon C
   14. Sovannaroth S
   15. Pukrittayakamee S
   16. Jittamala P
   17. Chotivanich K
   18. Chutasmit K
   19. Suchatsoonthorn C
   20. Runcharoen R
   21. Hien TT
   22. Thuy-Nhien NT
   23. Thanh NV
   24. Phu NH
   25. Htut Y
   26. Han KT
   27. Aye KH
   28. Mokuolu OA
   29. Olaosebikan RR
   30. Folaranmi OO
   31. Mayxay M
   32. Khanthavong M
   33. Hongvanthong B
   34. Newton PN
   35. Onyamboko MA
   36. Fanello CI
   37. Tshefu AK
   38. Mishra N
   39. Valecha N
   40. Phyo AP
   41. Nosten F
   42. Yi P
   43. Tripura R
   44. Borrmann S
   45. Bashraheil M
   46. Peshu J
   47. Faiz MA
   48. Ghose A
   49. Hossain MA
   50. Samad R
   51. Rahman MR
   52. Hasan MM
   53. Islam A
   54. Miotto O
   55. Amato R
   56. MacInnis B
   57. Stalker J
   58. Kwiatkowski DP
   59. Bozdech Z
   60. Jeeyapant A
   61. Cheah PY
   62. Sakulthaew T
   63. Chalk J
   64. Intharabut B
   65. Silamut K
   66. Lee SJ
   67. Vihokhern B
   68. Kunasol C
   69. Imwong M
   70. Tarning J
   71. Taylor WJ
   72. Yeung S
   73. Woodrow CJ
   74. Flegg JA
   75. Das D
   76. Smith J
   77. Venkatesan M
   78. Plowe CV
   79. Stepniewska K
   80. Guerin PJ
   81. Dondorp AM
   82. Day NP
   83. White NJ
   84. Tracking Resistance to Artemisinin Collaboration (TRAC)

   (2014) Spread of artemisinin resistance in Plasmodium falciparum malaria

   The New England Journal of Medicine 371:411–423.

   https://doi.org/10.1056/NEJMoa1314981

   • PubMed
   • Google Scholar
6. 1. Assefa SA
   2. Preston MD
   3. Campino S
   4. Ocholla H
   5. Sutherland CJ
   6. Clark TG

   (2014) estMOI: estimating multiplicity of infection using parasite deep sequencing data

   Bioinformatics 30:1292–1294.

   https://doi.org/10.1093/bioinformatics/btu005

   • PubMed
   • Google Scholar
7. 1. Bhatt S
   2. Weiss DJ
   3. Cameron E
   4. Bisanzio D
   5. Mappin B
   6. Dalrymple U
   7. Battle K
   8. Moyes CL
   9. Henry A
   10. Eckhoff PA
   11. Wenger EA
   12. Briët O
   13. Penny MA
   14. Smith TA
   15. Bennett A
   16. Yukich J
   17. Eisele TP
   18. Griffin JT
   19. Fergus CA
   20. Lynch M
   21. Lindgren F
   22. Cohen JM
   23. Murray CLJ
   24. Smith DL
   25. Hay SI
   26. Cibulskis RE
   27. Gething PW

   (2015) The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015

   Nature 526:207–211.

   https://doi.org/10.1038/nature15535

   • PubMed
   • Google Scholar
8. 1. Bonnington CA
   2. Phyo AP
   3. Ashley EA
   4. Imwong M
   5. Sriprawat K
   6. Parker DM
   7. Proux S
   8. White NJ
   9. Nosten F

   (2017) Plasmodium falciparum kelch 13 mutations and treatment response in patients in Hpa-Pun district, northern kayin state, Myanmar

   Malaria Journal 16:480.

   https://doi.org/10.1186/s12936-017-2128-x

   • PubMed
   • Google Scholar
9. 1. Carrara VI
   2. Sirilak S
   3. Thonglairuam J
   4. Rojanawatsirivet C
   5. Proux S
   6. Gilbos V
   7. Brockman A
   8. Ashley EA
   9. McGready R
   10. Krudsood S
   11. Leemingsawat S
   12. Looareesuwan S
   13. Singhasivanon P
   14. White N
   15. Nosten F

   (2006) Deployment of early diagnosis and mefloquine- Artesunate treatment of falciparum malaria in Thailand: the tak malaria initiative

   PLOS Medicine 3:e183.

   https://doi.org/10.1371/journal.pmed.0030183

   • Google Scholar
10. 1. Cerqueira GC
    2. Cheeseman IH
    3. Schaffner SF
    4. Nair S
    5. McDew-White M
    6. Phyo AP
    7. Ashley EA
    8. Melnikov A
    9. Rogov P
    10. Birren BW
    11. Nosten F
    12. Anderson TJC
    13. Neafsey DE

    (2017) Longitudinal genomic surveillance of Plasmodium falciparum malaria parasites reveals complex genomic architecture of emerging artemisinin resistance

    Genome Biology 18:78.

    https://doi.org/10.1186/s13059-017-1204-4

    • PubMed
    • Google Scholar
11. 1. Chang HH
    2. Worby CJ
    3. Yeka A
    4. Nankabirwa J
    5. Kamya MR
    6. Staedke SG
    7. Dorsey G
    8. Murphy M
    9. Neafsey DE
    10. Jeffreys AE
    11. Hubbart C
    12. Rockett KA
    13. Amato R
    14. Kwiatkowski DP
    15. Buckee CO
    16. Greenhouse B

    (2017) THE REAL McCOIL: a method for the concurrent estimation of the complexity of infection and SNP allele frequency for malaria parasites

    PLOS Computational Biology 13:e1005348.

    https://doi.org/10.1371/journal.pcbi.1005348

    • PubMed
    • Google Scholar
12. 1. Cheeseman IH
    2. Miller BA
    3. Nair S
    4. Nkhoma S
    5. Tan A
    6. Tan JC
    7. Al Saai S
    8. Phyo AP
    9. Moo CL
    10. Lwin KM
    11. McGready R
    12. Ashley E
    13. Imwong M
    14. Stepniewska K
    15. Yi P
    16. Dondorp AM
    17. Mayxay M
    18. Newton PN
    19. White NJ
    20. Nosten F
    21. Ferdig MT
    22. Anderson TJ

    (2012) A major genome region underlying artemisinin resistance in malaria

    Science 336:79–82.

    https://doi.org/10.1126/science.1215966

    • PubMed
    • Google Scholar
13. 1. Chenet SM
    2. Akinyi Okoth S
    3. Huber CS
    4. Chandrabose J
    5. Lucchi NW
    6. Talundzic E
    7. Krishnalall K
    8. Ceron N
    9. Musset L
    10. Macedo de Oliveira A
    11. Venkatesan M
    12. Rahman R
    13. Barnwell JW
    14. Udhayakumar V

    (2016) Independent Emergence of the Plasmodium falciparum Kelch Propeller Domain Mutant Allele C580Y in Guyana

    Journal of Infectious Diseases 213:1472–1475.

    https://doi.org/10.1093/infdis/jiv752

    • Google Scholar
14. 1. Chenet SM
    2. Okoth SA
    3. Kelley J
    4. Lucchi N
    5. Huber CS
    6. Vreden S
    7. Macedo de Oliveira A
    8. Barnwell JW
    9. Udhayakumar V
    10. Adhin MR

    (2017) Molecular profile of malaria drug resistance markers of Plasmodium falciparum in Suriname

    Antimicrobial Agents and Chemotherapy 61:e02655.

    https://doi.org/10.1128/AAC.02655-16

    • Google Scholar
15. 1. DePristo MA
    2. Banks E
    3. Poplin R
    4. Garimella KV
    5. Maguire JR
    6. Hartl C
    7. Philippakis AA
    8. del Angel G
    9. Rivas MA
    10. Hanna M
    11. McKenna A
    12. Fennell TJ
    13. Kernytsky AM
    14. Sivachenko AY
    15. Cibulskis K
    16. Gabriel SB
    17. Altshuler D
    18. Daly MJ

    (2011) A framework for variation discovery and genotyping using next-generation DNA sequencing data

    Nature Genetics 43:491–498.

    https://doi.org/10.1038/ng.806

    • PubMed
    • Google Scholar
16. 1. Dharia NV
    2. Plouffe D
    3. Bopp SE
    4. González-Páez GE
    5. Lucas C
    6. Salas C
    7. Soberon V
    8. Bursulaya B
    9. Kochel TJ
    10. Bacon DJ
    11. Winzeler EA

    (2010) Genome scanning of amazonian Plasmodium falciparum shows subtelomeric instability and clindamycin-resistant parasites

    Genome Research 20:1534–1544.

    https://doi.org/10.1101/gr.105163.110

    • PubMed
    • Google Scholar
17. 1. Dondorp AM
    2. Nosten F
    3. Yi P
    4. Das D
    5. Phyo AP
    6. Tarning J
    7. Lwin KM
    8. Ariey F
    9. Hanpithakpong W
    10. Lee SJ
    11. Ringwald P
    12. Silamut K
    13. Imwong M
    14. Chotivanich K
    15. Lim P
    16. Herdman T
    17. An SS
    18. Yeung S
    19. Singhasivanon P
    20. Day NP
    21. Lindegardh N
    22. Socheat D
    23. White NJ

    (2009) Artemisinin resistance in Plasmodium falciparum malaria

    The New England Journal of Medicine 361:455–467.

    https://doi.org/10.1056/NEJMoa0808859

    • PubMed
    • Google Scholar
18. 1. Douine M
    2. Musset L
    3. Corlin F
    4. Pelleau S
    5. Pasquier J
    6. Mutricy L
    7. Adenis A
    8. Djossou F
    9. Brousse P
    10. Perotti F
    11. Hiwat H
    12. Vreden S
    13. Demar M
    14. Nacher M

    (2016) Prevalence of plasmodium spp. in illegal gold miners in French Guiana in 2015: a hidden but critical malaria reservoir

    Malaria Journal 15:315.

    https://doi.org/10.1186/s12936-016-1367-6

    • PubMed
    • Google Scholar
19. 1. Douine M
    2. Lazrek Y
    3. Blanchet D
    4. Pelleau S
    5. Chanlin R
    6. Corlin F
    7. Hureau L
    8. Volney B
    9. Hiwat H
    10. Vreden S
    11. Djossou F
    12. Demar M
    13. Nacher M
    14. Musset L

    (2018) Predictors of antimalarial self-medication in illegal gold miners in french guiana: a pathway towards artemisinin resistance

    Journal of Antimicrobial Chemotherapy 73:231–239.

    https://doi.org/10.1093/jac/dkx343

    • PubMed
    • Google Scholar
20. 1. Eastman RT
    2. Fidock DA

    (2009) Artemisinin-based combination therapies: a vital tool in efforts to eliminate malaria

    Nature Reviews Microbiology 7:864–874.

    https://doi.org/10.1038/nrmicro2239

    • PubMed
    • Google Scholar
21. 1. Echeverry DF
    2. Nair S
    3. Osorio L
    4. Menon S
    5. Murillo C
    6. Anderson TJ

    (2013) Long term persistence of clonal malaria parasite Plasmodium falciparum lineages in the Colombian Pacific region

    BMC Genetics 14:2.

    https://doi.org/10.1186/1471-2156-14-2

    • PubMed
    • Google Scholar
22. 1. Fidock DA
    2. Wellems TE

    (1997) Transformation with human dihydrofolate reductase renders malaria parasites insensitive to WR99210 but does not affect the intrinsic activity of proguanil

    PNAS 94:10931–10936.

    https://doi.org/10.1073/pnas.94.20.10931

    • PubMed
    • Google Scholar
23. 1. Galinsky K
    2. Valim C
    3. Salmier A
    4. de Thoisy B
    5. Musset L
    6. Legrand E
    7. Faust A
    8. Baniecki ML
    9. Ndiaye D
    10. Daniels RF
    11. Hartl DL
    12. Sabeti PC
    13. Wirth DF
    14. Volkman SK
    15. Neafsey DE

    (2015) COIL: a methodology for evaluating malarial complexity of infection using likelihood from single nucleotide polymorphism data

    Malaria Journal 14:4.

    https://doi.org/10.1186/1475-2875-14-4

    • PubMed
    • Google Scholar
24. 1. Goodyer ID
    2. Taraschi TF

    (1997) Plasmodium falciparum: a simple, rapid method for detecting parasite clones in microtiter plates

    Experimental Parasitology 86:158–160.

    https://doi.org/10.1006/expr.1997.4156

    • PubMed
    • Google Scholar
25. 1. Han KT
    2. Lin K
    3. Myint MK
    4. Thi A
    5. Aye KH
    6. Han ZY
    7. Moe M
    8. Bustos MD
    9. Rahman MM
    10. Ringwald P
    11. Simmons R
    12. Markwalter CF
    13. Plowe CV
    14. Nyunt MM

    (2020) Artemether-Lumefantrine and Dihydroartemisinin-Piperaquine retain high efficacy for treatment of uncomplicated Plasmodium falciparum Malaria in Myanmar

    The American Journal of Tropical Medicine and Hygiene 102:598–604.

    https://doi.org/10.4269/ajtmh.19-0692

    • PubMed
    • Google Scholar
26. Report

    1. Heemskerk

    (2011)

    Small-scale gold mining in the transboundary areas of Brazil, Suriname and French Guiana. Social and Environmental Issues. Report

    Paramaribo, Suriname: United Nations Development Programme.

    • Google Scholar
27. 1. Imwong M
    2. Suwannasin K
    3. Kunasol C
    4. Sutawong K
    5. Mayxay M
    6. Rekol H
    7. Smithuis FM
    8. Hlaing TM
    9. Tun KM
    10. van der Pluijm RW
    11. Tripura R
    12. Miotto O
    13. Menard D
    14. Dhorda M
    15. Day NPJ
    16. White NJ
    17. Dondorp AM

    (2017) The spread of artemisinin-resistant Plasmodium falciparum in the Greater Mekong subregion: a molecular epidemiology observational study

    The Lancet Infectious Diseases 17:491–497.

    https://doi.org/10.1016/S1473-3099(17)30048-8

    • Google Scholar
28. 1. Kim J
    2. Tan YZ
    3. Wicht KJ
    4. Erramilli SK
    5. Dhingra SK
    6. Okombo J
    7. Vendome J
    8. Hagenah LM
    9. Giacometti SI
    10. Warren AL
    11. Nosol K
    12. Roepe PD
    13. Potter CS
    14. Carragher B
    15. Kossiakoff AA
    16. Quick M
    17. Fidock DA
    18. Mancia F

    (2019) Structure and drug resistance of the Plasmodium falciparum transporter PfCRT

    Nature 576:315–320.

    https://doi.org/10.1038/s41586-019-1795-x

    • PubMed
    • Google Scholar
29. 1. Kobasa T
    2. Talundzic E
    3. Sug-aram R
    4. Boondat P
    5. Goldman IF
    6. Lucchi NW
    7. Dharmarak P
    8. Sintasath D
    9. Fukuda M
    10. Whistler T
    11. MacArthur J
    12. Udhayakumar V
    13. Prempree P
    14. Chinanonwait N

    (2018) Emergence and Spread of kelch13 Mutations Associated with Artemisinin Resistance in Plasmodium falciparum Parasites in 12 Thai Provinces from 2007 to 2016

    Antimicrobial Agents and Chemotherapy 62:e02141.

    https://doi.org/10.1128/AAC.02141-17

    • Google Scholar
30. 1. Legrand E
    2. Yrinesi J
    3. Ekala M-T
    4. Péneau J
    5. Volney B
    6. Berger F
    7. Bouchier C
    8. Bertani S
    9. Musset L
    10. Meynard J-B
    11. Mercereau-Puijalon O

    (2012) Discordant Temporal Evolution of Pfcrt and Pfmdr1 Genotypes and Plasmodium falciparum in vitro drug susceptibility to 4-aminoquinolines after drug policy change in French Guiana

    Antimicrobial Agents and Chemotherapy 56:1382–1389.

    https://doi.org/10.1128/AAC.05280-11

    • Google Scholar
31. Preprint

    1. Li H

    (2013) Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM

    aArXiv.

    https://arxiv.org/abs/1303.3997

    • Google Scholar
32. 1. Li X
    2. Kumar S
    3. McDew-White M
    4. Haile M
    5. Cheeseman IH
    6. Emrich S
    7. Button-Simons K
    8. Nosten F
    9. Kappe SHI
    10. Ferdig MT
    11. Anderson TJC
    12. Vaughan AM

    (2019) Genetic mapping of fitness determinants across the malaria parasite Plasmodium falciparum life cycle

    PLOS Genetics 15:e1008453.

    https://doi.org/10.1371/journal.pgen.1008453

    • PubMed
    • Google Scholar
33. 1. McKenna A
    2. Hanna M
    3. Banks E
    4. Sivachenko A
    5. Cibulskis K
    6. Kernytsky A
    7. Garimella K
    8. Altshuler D
    9. Gabriel S
    10. Daly M
    11. DePristo MA

    (2010) The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data

    Genome Research 20:1297–1303.

    https://doi.org/10.1101/gr.107524.110

    • PubMed
    • Google Scholar
34. 1. Ménard D
    2. Khim N
    3. Beghain J
    4. Adegnika AA
    5. Shafiul-Alam M
    6. Amodu O
    7. Rahim-Awab G
    8. Barnadas C
    9. Berry A
    10. Boum Y
    11. Bustos MD
    12. Cao J
    13. Chen JH
    14. Collet L
    15. Cui L
    16. Thakur GD
    17. Dieye A
    18. Djallé D
    19. Dorkenoo MA
    20. Eboumbou-Moukoko CE
    21. Espino FE
    22. Fandeur T
    23. Ferreira-da-Cruz MF
    24. Fola AA
    25. Fuehrer HP
    26. Hassan AM
    27. Herrera S
    28. Hongvanthong B
    29. Houzé S
    30. Ibrahim ML
    31. Jahirul-Karim M
    32. Jiang L
    33. Kano S
    34. Ali-Khan W
    35. Khanthavong M
    36. Kremsner PG
    37. Lacerda M
    38. Leang R
    39. Leelawong M
    40. Li M
    41. Lin K
    42. Mazarati JB
    43. Ménard S
    44. Morlais I
    45. Muhindo-Mavoko H
    46. Musset L
    47. Na-Bangchang K
    48. Nambozi M
    49. Niaré K
    50. Noedl H
    51. Ouédraogo JB
    52. Pillai DR
    53. Pradines B
    54. Quang-Phuc B
    55. Ramharter M
    56. Randrianarivelojosia M
    57. Sattabongkot J
    58. Sheikh-Omar A
    59. Silué KD
    60. Sirima SB
    61. Sutherland C
    62. Syafruddin D
    63. Tahar R
    64. Tang LH
    65. Touré OA
    66. Tshibangu-wa-Tshibangu P
    67. Vigan-Womas I
    68. Warsame M
    69. Wini L
    70. Zakeri S
    71. Kim S
    72. Eam R
    73. Berne L
    74. Khean C
    75. Chy S
    76. Ken M
    77. Loch K
    78. Canier L
    79. Duru V
    80. Legrand E
    81. Barale JC
    82. Stokes B
    83. Straimer J
    84. Witkowski B
    85. Fidock DA
    86. Rogier C
    87. Ringwald P
    88. Ariey F
    89. Mercereau-Puijalon O
    90. KARMA Consortium

    (2016) A worldwide map of Plasmodium falciparum K13-Propeller Polymorphisms

    The New England Journal of Medicine 374:2453–2464.

    https://doi.org/10.1056/NEJMoa1513137

    • PubMed
    • Google Scholar
35. Report

    1. Menard D
    2. Ariey F

    (2013)

    PCR-Sequencing for Genotyping SNPs PF3D7_1343700 Kelch Protein Propeller Domain

    Institut Pasteur du Cambodge – Institut Pasteur, Paris Procedure.

    • Google Scholar
36. 1. Miles A
    2. Iqbal Z
    3. Vauterin P
    4. Pearson R
    5. Campino S
    6. Theron M
    7. Gould K
    8. Mead D
    9. Drury E
    10. O'Brien J
    11. Ruano Rubio V
    12. MacInnis B
    13. Mwangi J
    14. Samarakoon U
    15. Ranford-Cartwright L
    16. Ferdig M
    17. Hayton K
    18. Su XZ
    19. Wellems T
    20. Rayner J
    21. McVean G
    22. Kwiatkowski D

    (2016) Indels, structural variation, and recombination drive genomic diversity in Plasmodium falciparum

    Genome Research 26:1288–1299.

    https://doi.org/10.1101/gr.203711.115

    • PubMed
    • Google Scholar
37. Website

    1. Ministry of Public Health

    (2018) National malaria programme strategic plan 2015-2020

    Accessed April 30, 2019.

    http://docs.bvsalud.org/biblioref/2018/07/906525/arbo-guy-005.pdf
38. 1. Miotto O
    2. Almagro-Garcia J
    3. Manske M
    4. Macinnis B
    5. Campino S
    6. Rockett KA
    7. Amaratunga C
    8. Lim P
    9. Suon S
    10. Sreng S
    11. Anderson JM
    12. Duong S
    13. Nguon C
    14. Chuor CM
    15. Saunders D
    16. Se Y
    17. Lon C
    18. Fukuda MM
    19. Amenga-Etego L
    20. Hodgson AV
    21. Asoala V
    22. Imwong M
    23. Takala-Harrison S
    24. Nosten F
    25. Su XZ
    26. Ringwald P
    27. Ariey F
    28. Dolecek C
    29. Hien TT
    30. Boni MF
    31. Thai CQ
    32. Amambua-Ngwa A
    33. Conway DJ
    34. Djimdé AA
    35. Doumbo OK
    36. Zongo I
    37. Ouedraogo JB
    38. Alcock D
    39. Drury E
    40. Auburn S
    41. Koch O
    42. Sanders M
    43. Hubbart C
    44. Maslen G
    45. Ruano-Rubio V
    46. Jyothi D
    47. Miles A
    48. O'Brien J
    49. Gamble C
    50. Oyola SO
    51. Rayner JC
    52. Newbold CI
    53. Berriman M
    54. Spencer CC
    55. McVean G
    56. Day NP
    57. White NJ
    58. Bethell D
    59. Dondorp AM
    60. Plowe CV
    61. Fairhurst RM
    62. Kwiatkowski DP

    (2013) Multiple populations of artemisinin-resistant Plasmodium falciparum in Cambodia

    Nature Genetics 45:648–655.

    https://doi.org/10.1038/ng.2624

    • PubMed
    • Google Scholar
39. 1. Miotto O
    2. Amato R
    3. Ashley EA
    4. MacInnis B
    5. Almagro-Garcia J
    6. Amaratunga C
    7. Lim P
    8. Mead D
    9. Oyola SO
    10. Dhorda M
    11. Imwong M
    12. Woodrow C
    13. Manske M
    14. Stalker J
    15. Drury E
    16. Campino S
    17. Amenga-Etego L
    18. Thanh TN
    19. Tran HT
    20. Ringwald P
    21. Bethell D
    22. Nosten F
    23. Phyo AP
    24. Pukrittayakamee S
    25. Chotivanich K
    26. Chuor CM
    27. Nguon C
    28. Suon S
    29. Sreng S
    30. Newton PN
    31. Mayxay M
    32. Khanthavong M
    33. Hongvanthong B
    34. Htut Y
    35. Han KT
    36. Kyaw MP
    37. Faiz MA
    38. Fanello CI
    39. Onyamboko M
    40. Mokuolu OA
    41. Jacob CG
    42. Takala-Harrison S
    43. Plowe CV
    44. Day NP
    45. Dondorp AM
    46. Spencer CC
    47. McVean G
    48. Fairhurst RM
    49. White NJ
    50. Kwiatkowski DP

    (2015) Genetic architecture of artemisinin-resistant Plasmodium falciparum

    Nature Genetics 47:226–234.

    https://doi.org/10.1038/ng.3189

    • PubMed
    • Google Scholar
40. 1. Nair S
    2. Li X
    3. Arya GA
    4. McDew-White M
    5. Ferrari M
    6. Nosten F
    7. Anderson TJC

    (2018) Fitness Costs and the Rapid Spread of kelch13 -C580Y Substitutions Conferring Artemisinin Resistance

    Antimicrobial Agents and Chemotherapy 62:e00605.

    https://doi.org/10.1128/AAC.00605-18

    • Google Scholar
41. 1. Oyola SO
    2. Ariani CV
    3. Hamilton WL
    4. Kekre M
    5. Amenga-Etego LN
    6. Ghansah A
    7. Rutledge GG
    8. Redmond S
    9. Manske M
    10. Jyothi D
    11. Jacob CG
    12. Otto TD
    13. Rockett K
    14. Newbold CI
    15. Berriman M
    16. Kwiatkowski DP

    (2016) Whole genome sequencing of Plasmodium falciparum from dried blood spots using selective whole genome amplification

    Malaria Journal 15:597.

    https://doi.org/10.1186/s12936-016-1641-7

    • PubMed
    • Google Scholar
42. 1. Pelleau S
    2. Moss EL
    3. Dhingra SK
    4. Volney B
    5. Casteras J
    6. Gabryszewski SJ
    7. Volkman SK
    8. Wirth DF
    9. Legrand E
    10. Fidock DA
    11. Neafsey DE
    12. Musset L

    (2015) Adaptive evolution of malaria parasites in french guiana: reversal of chloroquine resistance by acquisition of a mutation in pfcrt

    PNAS 112:11672–11677.

    https://doi.org/10.1073/pnas.1507142112

    • PubMed
    • Google Scholar
43. 1. Pribluda VS
    2. Evans L
    3. Barillas E
    4. Marmion J
    5. Lukulay P
    6. Chang J

    (2014) Were medicine quality and pharmaceutical management contributing factors in diminishing artemisinin efficacy in Guyana and Suriname?

    Malaria Journal 13:77.

    https://doi.org/10.1186/1475-2875-13-77

    • PubMed
    • Google Scholar
44. Software

    1. R Development Core Team

    (2016) R: A language and environment for statistical computing

    R Foundation for Statistical Computing, Vienna, Austria.

    https://www.R-project.org/
45. 1. Rahman R
    2. Martin MJ
    3. Persaud S
    4. Ceron N
    5. Kellman D
    6. Musset L
    7. Carter KH
    8. Ringwald P

    (2016) Continued sensitivity of Plasmodium falciparum to Artemisinin in Guyana, With Absence of Kelch Propeller Domain Mutant Alleles

    Open Forum Infectious Diseases 3:ofw185.

    https://doi.org/10.1093/ofid/ofw185

    • PubMed
    • Google Scholar
46. 1. Roper C
    2. Pearce R
    3. Nair S
    4. Sharp B
    5. Nosten F
    6. Anderson T

    (2004) Intercontinental spread of pyrimethamine-resistant malaria

    Science 305:1124.

    https://doi.org/10.1126/science.1098876

    • PubMed
    • Google Scholar
47. 1. Ross LS
    2. Dhingra SK
    3. Mok S
    4. Yeo T
    5. Wicht KJ
    6. Kümpornsin K
    7. Takala-Harrison S
    8. Witkowski B
    9. Fairhurst RM
    10. Ariey F
    11. Menard D
    12. Fidock DA

    (2018) Emerging southeast asian PfCRT mutations confer Plasmodium falciparum resistance to the first-line antimalarial piperaquine

    Nature Communications 9:3314.

    https://doi.org/10.1038/s41467-018-05652-0

    • PubMed
    • Google Scholar
48. 1. Sáenz FE
    2. Morton LC
    3. Okoth SA
    4. Valenzuela G
    5. Vera-Arias CA
    6. Vélez-Álvarez E
    7. Lucchi NW
    8. Castro LE
    9. Udhayakumar V

    (2015) Clonal population expansion in an outbreak of Plasmodium falciparum on the northwest coast of Ecuador

    Malaria Journal 13 Suppl 1:497.

    https://doi.org/10.1186/s12936-015-1019-2

    • PubMed
    • Google Scholar
49. 1. Sáenz FE
    2. Arévalo-Cortés A
    3. Valenzuela G
    4. Vallejo AF
    5. Castellanos A
    6. Poveda-Loayza AC
    7. Gutierrez JB
    8. Alvarez A
    9. Yan YH
    10. Benavides Y
    11. Castro LE
    12. Arévalo-Herrera M
    13. Herrera S

    (2017) Malaria epidemiology in low-endemicity Areas of the northern coast of Ecuador: high prevalence of asymptomatic infections

    Malaria Journal 16:300.

    https://doi.org/10.1186/s12936-017-1947-0

    • PubMed
    • Google Scholar
50. 1. Schaffner SF
    2. Taylor AR
    3. Wong W
    4. Wirth DF
    5. Neafsey DE

    (2018) hmmIBD: software to infer pairwise identity by descent between haploid genotypes

    Malaria Journal 17:196.

    https://doi.org/10.1186/s12936-018-2349-7

    • PubMed
    • Google Scholar
51. 1. Straimer J
    2. Gnädig NF
    3. Witkowski B
    4. Amaratunga C
    5. Duru V
    6. Ramadani AP
    7. Dacheux M
    8. Khim N
    9. Zhang L
    10. Lam S
    11. Gregory PD
    12. Urnov FD
    13. Mercereau-Puijalon O
    14. Benoit-Vical F
    15. Fairhurst RM
    16. Ménard D
    17. Fidock DA

    (2015) Drug resistance. K13-propeller mutations confer artemisinin resistance in Plasmodium falciparum clinical isolates

    Science 347:428–431.

    https://doi.org/10.1126/science.1260867

    • PubMed
    • Google Scholar
52. 1. Straimer J
    2. Gnädig NF
    3. Stokes BH
    4. Ehrenberger M
    5. Crane AA
    6. Fidock DA

    (2017) Plasmodium falciparum K13 mutations differentially impact ozonide susceptibility and parasite fitness In Vitro

    mBio 8:e00172.

    https://doi.org/10.1128/mBio.00172-17

    • PubMed
    • Google Scholar
53. 1. Takala-Harrison S
    2. Jacob CG
    3. Arze C
    4. Cummings MP
    5. Silva JC
    6. Dondorp AM
    7. Fukuda MM
    8. Hien TT
    9. Mayxay M
    10. Noedl H
    11. Nosten F
    12. Kyaw MP
    13. Nhien NT
    14. Imwong M
    15. Bethell D
    16. Se Y
    17. Lon C
    18. Tyner SD
    19. Saunders DL
    20. Ariey F
    21. Mercereau-Puijalon O
    22. Menard D
    23. Newton PN
    24. Khanthavong M
    25. Hongvanthong B
    26. Starzengruber P
    27. Fuehrer HP
    28. Swoboda P
    29. Khan WA
    30. Phyo AP
    31. Nyunt MM
    32. Nyunt MH
    33. Brown TS
    34. Adams M
    35. Pepin CS
    36. Bailey J
    37. Tan JC
    38. Ferdig MT
    39. Clark TG
    40. Miotto O
    41. MacInnis B
    42. Kwiatkowski DP
    43. White NJ
    44. Ringwald P
    45. Plowe CV

    (2015) Independent emergence of artemisinin resistance mutations among Plasmodium falciparum in Southeast Asia

    The Journal of Infectious Diseases 211:670–679.

    https://doi.org/10.1093/infdis/jiu491

    • PubMed
    • Google Scholar
54. 1. Talundzic E
    2. Chenet SM
    3. Goldman IF
    4. Patel DS
    5. Nelson JA
    6. Plucinski MM
    7. Barnwell JW
    8. Udhayakumar V

    (2015) Genetic analysis and species specific amplification of the artemisinin Resistance-Associated Kelch propeller domain in P. falciparum and P. vivax

    PLOS ONE 10:e0136099.

    https://doi.org/10.1371/journal.pone.0136099

    • PubMed
    • Google Scholar
55. 1. Van der Auwera GA
    2. Carneiro MO
    3. Hartl C
    4. Poplin R
    5. del Angel G
    6. Levy-Moonshine A
    7. Jordan T
    8. Shakir K
    9. Roazen D
    10. Thibault J
    11. Banks E
    12. Garimella KV
    13. Altshuler D
    14. Gabriel S
    15. DePristo MA

    (2013) From FastQ data to high confidence variant calls: the genome analysis toolkit best practices pipeline

    Curr Protoc Bioinformatics.  43:33.

    https://doi.org/10.1002/0471250953.bi1110s43

    • Google Scholar
56. 1. Vinayak S
    2. Alam MT
    3. Mixson-Hayden T
    4. McCollum AM
    5. Sem R
    6. Shah NK
    7. Lim P
    8. Muth S
    9. Rogers WO
    10. Fandeur T
    11. Barnwell JW
    12. Escalante AA
    13. Wongsrichanalai C
    14. Ariey F
    15. Meshnick SR
    16. Udhayakumar V

    (2010) Origin and evolution of sulfadoxine resistant Plasmodium falciparum

    PLOS Pathogens 6:e1000830.

    https://doi.org/10.1371/journal.ppat.1000830

    • PubMed
    • Google Scholar
57. 1. Witkowski B
    2. Amaratunga C
    3. Khim N
    4. Sreng S
    5. Chim P
    6. Kim S
    7. Lim P
    8. Mao S
    9. Sopha C
    10. Sam B
    11. Anderson JM
    12. Duong S
    13. Chuor CM
    14. Taylor WRJ
    15. Suon S
    16. Mercereau-Puijalon O
    17. Fairhurst RM
    18. Menard D

    (2013) Novel phenotypic assays for the detection of artemisinin-resistant Plasmodium falciparum malaria in Cambodia: in-vitro and ex-vivo drug-response studies

    The Lancet Infectious Diseases 13:1043–1049.

    https://doi.org/10.1016/S1473-3099(13)70252-4

    • Google Scholar
58. 1. Wootton JC
    2. Feng X
    3. Ferdig MT
    4. Cooper RA
    5. Mu J
    6. Baruch DI
    7. Magill AJ
    8. Su XZ

    (2002) Genetic diversity and chloroquine selective sweeps in Plasmodium falciparum

    Nature 418:320–323.

    https://doi.org/10.1038/nature00813

    • PubMed
    • Google Scholar
59. Website

    1. World Health Organization

    (2001) Antimalarial drug combination therapy

    Accessed April 11, 2017.

    http://apps.who.int/iris/bitstream/10665/66952/1/WHO_CDS_RBM_2001.35.pdf
60. Website

    1. World Health Organization

    (2017) Status report on artemisinin and artemisinin-based combination therapy resistance.

    Accessed February 27, 2018.

    http://apps.who.int/iris/bitstream/10665/255213/1/WHO-HTM-GMP-2017.9-eng.pdf?ua=1
61. Website

    1. World Health Organization

    (2018) Status report on artemisinin resistance and artemisinin-based combination therapy

    Accessed September 14, 2018.

    http://apps.who.int/iris/bitstream/handle/10665/274362/WHO-CDS-GMP-2018.18-eng.pdf?ua=1
62. Website

    1. World Health Organization

    (2019) World Malaria Report

    Accessed January 7, 2020.

    https://www.who.int/news-room/feature-stories/detail/world-malaria-report-2019
63. 1. WWARN K13 Genotype-Phenotype Study Group

    (2019) Association of mutations in the Plasmodium falciparum Kelch13 gene (Pf3D7_1343700) with parasite clearance rates after artemisinin-based treatments-a WWARN individual patient data meta-analysis

    BMC Medicine 17:1.

    https://doi.org/10.1186/s12916-018-1207-3

    • PubMed
    • Google Scholar
64. 1. Yalcindag E
    2. Elguero E
    3. Arnathau C
    4. Durand P
    5. Akiana J
    6. Anderson TJ
    7. Aubouy A
    8. Balloux F
    9. Besnard P
    10. Bogreau H
    11. Carnevale P
    12. D'Alessandro U
    13. Fontenille D
    14. Gamboa D
    15. Jombart T
    16. Le Mire J
    17. Leroy E
    18. Maestre A
    19. Mayxay M
    20. Ménard D
    21. Musset L
    22. Newton PN
    23. Nkoghé D
    24. Noya O
    25. Ollomo B
    26. Rogier C
    27. Veron V
    28. Wide A
    29. Zakeri S
    30. Carme B
    31. Legrand E
    32. Chevillon C
    33. Ayala FJ
    34. Renaud F
    35. Prugnolle F

    (2012) Multiple independent introductions of Plasmodium falciparum in South America

    PNAS 109:511–516.

    https://doi.org/10.1073/pnas.1119058109

    • PubMed
    • Google Scholar
65. 1. Zhu SJ
    2. Hendry JA
    3. Almagro-Garcia J
    4. Pearson RD
    5. Amato R
    6. Miles A
    7. Weiss DJ
    8. Lucas TC
    9. Nguyen M
    10. Gething PW
    11. Kwiatkowski D
    12. McVean G
    13. Pf3k Project

    (2019) The origins and relatedness structure of mixed infections vary with local prevalence of P. falciparum malaria

    eLife 8:e40845.

    https://doi.org/10.7554/eLife.40845

    • PubMed
    • Google Scholar

Author details

1. Luana C Mathieu

   1. Laboratoire de parasitologie, Centre Nationale de Référence du Paludisme, World Health Organization Collaborating Center for surveillance of antimalarial drug resistance, Institut Pasteur de la Guyane, Cayenne, French Guiana
   2. Ecole Doctorale n°587, Diversités, Santé, et Développement en Amazonie, Université de Guyane, Cayenne, French Guiana

   Contribution

   Conceptualization, Data curation, Formal analysis, Validation, Investigation, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6021-468X

2. Horace Cox

   Ministry of Public Health, Georgetown, Guyana

   Contribution

   Conceptualization, Resources, Methodology, Project administration, Writing - review and editing, Coordinate sample collection

   Competing interests

   No competing interests declared

3. Angela M Early

   1. Broad Institute of MIT and Harvard, Cambridge, United States
   2. Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, United States

   Contribution

   Conceptualization, Software, Formal analysis, Validation, Investigation, Methodology, Writing - original draft, Writing - review and editing

   Contributed equally with

   Sachel Mok

   Competing interests

   No competing interests declared

4. Sachel Mok

   Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Validation, Investigation, Methodology, Writing - original draft, Writing - review and editing

   Contributed equally with

   Angela M Early

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-9605-0154

5. Yassamine Lazrek

   Laboratoire de parasitologie, Centre Nationale de Référence du Paludisme, World Health Organization Collaborating Center for surveillance of antimalarial drug resistance, Institut Pasteur de la Guyane, Cayenne, French Guiana

   Contribution

   Supervision, Investigation, Project administration

   Competing interests

   No competing interests declared

6. Jeanne-Celeste Paquet

   Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, United States

   Contribution

   Data curation, Investigation

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6046-0154

7. Maria-Paz Ade

   Department of Communicable Diseases and Environmental Determinants of Health, Pan American Health Organization/World Health Organization, Washington, United States

   Contribution

   Conceptualization, Supervision, Funding acquisition, Methodology, Project administration, Writing - review and editing, Coordinate sample collection

   Competing interests

   MPA, JSFA, and PR are staff members of the World Health Organization. The authors alone are responsible for the views expressed in this publication and they do not necessarily represent the decisions, policy or views of the World Health Organization.

8. Naomi W Lucchi

   Malaria Branch, Division of Parasitic Diseases and Malaria, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, United States

   Contribution

   Data curation, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

9. Quacy Grant

   Ministry of Public Health, Georgetown, Guyana

   Contribution

   Conceptualization, Supervision, Project administration

   Competing interests

   No competing interests declared

10. Venkatachalam Udhayakumar

    Malaria Branch, Division of Parasitic Diseases and Malaria, Center for Global Health, Centers for Disease Control and Prevention, Atlanta, United States

    Contribution

    Formal analysis, Supervision, Validation, Investigation, Methodology

    Competing interests

    No competing interests declared

11. Jean SF Alexandre

    Pan American Health Organization, Georgetown, Guyana

    Contribution

    Resources, Supervision, Funding acquisition, Project administration, Coordinate sample collection

    Competing interests

    MPA, JSFA, and PR are staff members of the World Health Organization. The authors alone are responsible for the views expressed in this publication and they do not necessarily represent the decisions, policy or views of the World Health Organization.

12. Magalie Demar

    1. Service de Maladies Infectieuses et Tropicales, Centre Hospitalier Andrée Rosemon, Cayenne, French Guiana
    2. Ecosystèmes Amazoniens et Pathologie Tropicale (EPAT), EA3593, Université de Guyane, Cayenne, French Guiana

    Contribution

    Supervision, Project administration

    Competing interests

    No competing interests declared

13. Pascal Ringwald

    Global Malaria Program, World Health Organization, Geneva, Switzerland

    Contribution

    Conceptualization, Resources, Formal analysis, Supervision, Validation, Project administration, Writing - review and editing

    Competing interests

    MPA, JSFA, and PR are staff members of the World Health Organization. The authors alone are responsible for the views expressed in this publication and they do not necessarily represent the decisions, policy or views of the World Health Organization.

14. Daniel E Neafsey

    1. Broad Institute of MIT and Harvard, Cambridge, United States
    2. Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, United States

    Contribution

    Conceptualization, Resources, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Writing - review and editing

    Contributed equally with

    David A Fidock

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-1665-9323

15. David A Fidock

    1. Department of Microbiology and Immunology, Columbia University Irving Medical Center, New York, United States
    2. Division of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, United States

    Contribution

    Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Methodology, Writing - review and editing

    Contributed equally with

    Daniel E Neafsey

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-6753-8938

16. Lise Musset

    Laboratoire de parasitologie, Centre Nationale de Référence du Paludisme, World Health Organization Collaborating Center for surveillance of antimalarial drug resistance, Institut Pasteur de la Guyane, Cayenne, French Guiana

    Contribution

    Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Methodology, Writing - original draft, Project administration, Writing - review and editing

    For correspondence

    lisemusset@gmail.com

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-0215-4110

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