The spread of molecular markers of artemisinin partial resistance and diagnostic evasion in Eritrea: a retrospective molecular epidemiology study
Eritrea, located in the Horn of Africa, has low and seasonal transmission of Plasmodium falciparum and Plasmodium vivax malaria. From 2006, the Eritrean National Malaria Control Programme successfully implemented a range of malaria interventions, including integrated vector control, the introduction of quality malaria rapid diagnostic tests (RDTs), and the deployment of artemisinin combination therapy (ACT). However, between 2015 and 2022, malaria incidence and mortality rates increased by more than 40%. The emergence of mutant parasites capable of evading diagnostic tests and developing partial resistance to artemisinin drugs, plus the invasion of Anopheles stephensi , pose major challenges to malaria control programmes in Eritrea. Research in context Evidence before this study We have previously reported a high prevalence of mutant Plasmodium falciparum parasites with pfhrp2/3 deletions causing a high rate of rapid diagnostic test failures in samples collected in Eritrea in 2016 and 2019–20. We searched PubMed using the search terms “artemisinin”, “k13”, and “Africa” for publications from Jan 2, 2014, to Dec 4, 2023, resulting in 114 papers. We focused on 12 papers describing findings in the five countries in the Horn of Africa (ie, Djibouti, Eritrea, Ethiopia, Somalia, and Kenya). The most recent publication reported an increasing prevalence of P falciparum parasites carrying an R622I mutation in pfk13 between 2017 and 2019 at five sentinel sites within one district zone (Gash Barka) in Eritrea. This mutation was validated as a molecular marker for partial artemisinin resistance and was associated with pfhrp2/3 deletions. The R622I mutation was also reported to spread in neighbouring Ethiopia where high prevalence of pfhrp2/3 deletions was detected but was found to be negatively associated with pfhrp2/3 deletions. In Somalia, where the prevalence of pfhrp2/3 deletions is unknown, R622I was detected in one of 138 participant samples. A major gap exists in the understanding of the spatial distribution and dynamics of the R622I mutation and its interactions with pfhrp2/3 deletions in other zones in Eritrea. Added value of this study This study is the first to document the presence of pfk13 R622I and its co-evolution with pfhrp2/3 gene deletions in two new administrative zones (ie, Anseba and Debub) and 11 new subzones in Eritrea. This observation signifies the expansion of pfk13 R622I in Eritrean territory. Importantly, two of the newly identified subzones carry notable regional significance as they border Sudan and Ethiopia, requiring concerted regional response. Furthermore, this study included a substantial sample size collected in 2019, which allows statistical power for analysis of association between pfhrp2/3 deletion and pfk13 mutation. Overall, our study independently substantiates the evidence of de novo multiple emergence of pfk13 R622I, along with the correlation of pfhrp2/3 deletions within the Eritrean context and their progress augmentation over time and geographical expansion. Implications of all the available evidence The pfk13 R622I variants are spreading in the Horn of Africa, and pfhrp2/3 deletions might have contributed to their initial clonal expansion and spread, which was further enhanced by selective drug pressure. Continuous monitoring of trends in pfk13 and pfhrp2/3 variants is needed to inform effective malaria control and elimination strategies in the region. In 2006, Eritrea introduced a histidine rich protein 2 (HRP2)-based combination RDT as a diagnostic tool for malaria case management. However, within a decade, the country reported a high prevalence (62·0%) of P falciparum parasites carrying double pfhrp2/3 gene deletions causing high rates of false-negative HRP2-based RDT results among patients with symptoms. As a result, in 2016, Eritrea switched from HRP2-based RDTs to non-HRP2-based alternative RDTs. In 2019, approximately 2·5 years after the RDT switch, the prevalence of pfhrp2 and pfhrp3 deletions remained high (9·4% and 41·7%, respectively). As negligible HRP proteins were detected from double pfhrp2/3 -deleted and single pfhrp2 -deleted parasites, these parasites were expected to be undetectable by HRP2-based RDTs. In 2007, following the introduction of RDTs, the Eritrean National Malaria Control Programme switched first-line treatment of uncomplicated P falciparum malaria from chloroquine plus sulfadoxine–pyrimethamine to artesunate–amodiaquine due to a high rate of treatment failure associated with chloroquine plus sulfadoxine–pyrimethamine. To monitor the efficacy of artesunate–amodiaquine, therapeutic efficacy studies have been conducted in Eritrea. These studies, conducted at various sentinel sites, have consistently shown that the efficacy of artesunate–amodiaquine exceeded 90% on day 28 in all sites. , , However, the rate of parasite positivity in patients on day 3 increased between 2016 and 2019, indicating reduced efficacy of the artesunate component of artesunate–amodiaquine. Molecular surveillance was also done to monitor markers associated with partial resistance to artemisinin (mutations in pfk13 ) and resistance to chloroquine (mutations in pfcrt ) and amodiaquine (mutations in pfcrt and pfmdr1 ). These surveillance activities were conducted in the administrative zones Gash Barka and Debub (Mendefera) in 2013–14, , and in Gash Barka and Semenawi Keyih Bahri in 2016–19. The surveys showed that in spite of a high prevalence of mutant pfcrt and pfmdr1 alleles being continuously detected, the prevalence of pfk13 mutations was low in 2013–14, with one Arg622Ile mutation and one Thr535Met mutation detected among 119 samples from Gash Barka. However, the prevalence of the pfk13 Arg622Ile mutation in isolates before treatment was reported to have reached 8·6% in 2016 and increased to 21·0% in 2019. The pfk13 Arg622Ile mutation was first reported in a single sample collected in Zambia during 2012–14 and was subsequently reported in two individual samples collected in Mozambique and Somalia. In northern Ethiopia, the Arg622Ile mutation was reported in three (2·4%) of 25 samples collected in 2013–14 and eight (9·3%) of 86 samples collected in 2017–18, indicating an expansion of the mutation in the area. The Arg622Ile mutation has been linked to an increased risk of day-3 positivity and recrudescence following ACT treatment in Eritrea. In gene-edited parasites, the Arg622Ile mutation confers low levels of resistance to artemisinin in vitro. Hence, the Arg622Ile mutation is considered a validated marker of artemisinin partial resistance by WHO. Co-occurrence between the pfhrp2/3 deletion and pfk13 Arg622Ile mutation has been reported in Ethiopia and recently in Eritrea, but it is unclear whether the phenomenon widely exists in Eritrea and whether there is an interplay between these two variants. In theory, there is potential for mutual effect on the spread and persistence of the two variants within communities given the co-location of the pfhrp3 and pfk13 genes within the same chromosome. Data suggest that the predominant factor for the high prevalence of pfhrp2/3 deletions in Eritrea is probably the use of HRP2-based RDTs. However, additional factors, such as resistance to ACT, might also contribute to the rapid increase of these variants. Consequently, pfhrp2/3 deletions could spread in communities by hitch-hiking alongside the spread of pfk13 mutations, or vice versa. To better understand the spatial distribution and dynamics of the pfk13 Arg622Ile mutation and its interactions with pfhrp2/3 deletions in the main malaria-endemic administrative zones in Eritrea, we conducted a retrospective analysis of pfk13 mutations using existing samples collected from patients with symptoms seeking care at more than ten health facilities across four administrative zones. These samples were collected before and after the nationwide switch of RDTs, thus allowing exploration on the interactions between the pfk13 Arg622Ile mutation and pfhrp2/3 deletions, with and without selection pressure from HRP2-based RDTs. This study also included a substantial sample size collected in 2019, enabling us to explore interactions between pfk13 mutations and pfhrp2/3 deletions. 

We have previously reported a high prevalence of mutant Plasmodium falciparum parasites with pfhrp2/3 deletions causing a high rate of rapid diagnostic test failures in samples collected in Eritrea in 2016 and 2019–20. We searched PubMed using the search terms “artemisinin”, “k13”, and “Africa” for publications from Jan 2, 2014, to Dec 4, 2023, resulting in 114 papers. We focused on 12 papers describing findings in the five countries in the Horn of Africa (ie, Djibouti, Eritrea, Ethiopia, Somalia, and Kenya). The most recent publication reported an increasing prevalence of P falciparum parasites carrying an R622I mutation in pfk13 between 2017 and 2019 at five sentinel sites within one district zone (Gash Barka) in Eritrea. This mutation was validated as a molecular marker for partial artemisinin resistance and was associated with pfhrp2/3 deletions. The R622I mutation was also reported to spread in neighbouring Ethiopia where high prevalence of pfhrp2/3 deletions was detected but was found to be negatively associated with pfhrp2/3 deletions. In Somalia, where the prevalence of pfhrp2/3 deletions is unknown, R622I was detected in one of 138 participant samples. A major gap exists in the understanding of the spatial distribution and dynamics of the R622I mutation and its interactions with pfhrp2/3 deletions in other zones in Eritrea. 

This study is the first to document the presence of pfk13 R622I and its co-evolution with pfhrp2/3 gene deletions in two new administrative zones (ie, Anseba and Debub) and 11 new subzones in Eritrea. This observation signifies the expansion of pfk13 R622I in Eritrean territory. Importantly, two of the newly identified subzones carry notable regional significance as they border Sudan and Ethiopia, requiring concerted regional response. Furthermore, this study included a substantial sample size collected in 2019, which allows statistical power for analysis of association between pfhrp2/3 deletion and pfk13 mutation. Overall, our study independently substantiates the evidence of de novo multiple emergence of pfk13 R622I, along with the correlation of pfhrp2/3 deletions within the Eritrean context and their progress augmentation over time and geographical expansion. 

The pfk13 R622I variants are spreading in the Horn of Africa, and pfhrp2/3 deletions might have contributed to their initial clonal expansion and spread, which was further enhanced by selective drug pressure. Continuous monitoring of trends in pfk13 and pfhrp2/3 variants is needed to inform effective malaria control and elimination strategies in the region. 

Study design and samples In this retrospective analysis of pfk13 mutations and pfhrp2/3 deletions, P falciparum -infected blood samples were collected from two studies. The first study , obtained blood samples from two cross-sectional surveys designed to investigate the prevalence of pfhrp2/3 deletions among symptomatic patients before treatment. The first survey was conducted at two hospitals (Ghindae Hospital and Massawa Hospital) in Semenawi Keyih Bahri in March 1–31, 2016. The second survey was done between Jan 4, 2019, and March 19, 2020, in nine hospitals or health centres in three zones: Gash Baka (Agordat, Shambuko, Tesseney, Tekobmia and Barentu), Anseba (Keren and Hagaz) and Debub (Mendefera and Maimine). In the present study, we selected a subset of the samples from the second survey, selected to represent all health facilities and pfhrp2/3 status. The second study (unpublished) aimed to investigate the impact of pfhrp2/3 deletions on clinical outcomes in Eritrea . P falciparum -infected blood samples were collected from eight health facilities across three zones: Gash Barka (Agordat, Barentu and Mulki), Anseba (Keren), and Debub (Mendefera, Areza, Dubarwa, and Emni-Haily). The surveys of pfhrp2/3 deletions were approved by the Eritrean Ministry of Health Research and Ethical Committee. Written informed consent was obtained from participants at enrolment in the original studies. , Laboratory analyses on collected samples received approval from the Australian Departments of Defence and Veterans' Affairs Human Research Ethics Committee (#15–004). Additionally, the severe malaria study was approved by the London School of Hygiene and Tropical Medicine Ethics Review Committee (#11979). Procedures For data analysis, P falciparum -infected blood samples collected between 2018 and 2020 were merged according to health facilities where they were collected. Genomic DNA was extracted from samples collected from the first study , and the second study using a previously reported method . For blood samples collected from the first study, a fragment (codons 435–680) of the propeller region of the pfk13 gene was amplified using published primers and conditions  and sequenced using Sanger sequencing from both ends using 3130xl Genetic Analyzers and BigDye reagents from Applied Biosystems (Foster City, CA, USA). For blood samples collected from the second study, a 1033 bp fragment (codons 380–724) spanning the propeller region of pfk13 was amplified and visualised using gel electrophoresis. Subsequently, amplicon pooling and cleaning were carried out as previously described. Library preparation and adaptor ligation were done using the Oxford Nanopore native barcoding kit (sqk-nbd-112–96) following manufacturer’s protocol (Oxford Nanopore, UK). These methods are detailed in the . Seven neutral microsatellite markers (TA1, PolyA, PfPK2, TA109, 2490, 313, and 383) were analysed as part of previous studies to determine parasite haplotypes. , Seven-loci-haplotype data were available for 184 samples from the first study and were included in this retrospective analysis: 50 samples from 2016 and 134 from 2019–20. To assess the genetic diversity (expected heterozygosity, H E ) and genetic relatedness of parasite haplotypes with different pfk13 variants, we used FSTAT and PHYLOViZ online software (version 2.0) following developers’ instructions. The status of pfhrp2 and pfhrp3 genes in all samples was evaluated using a published multiplex quantitative PCR (qPCR) method with minor modifications introduced for survey samples. Primer and probe sequences , qPCR reagents and conditions, and the equipment used are detailed in the . Samples were classified as having a pfhrp2 deletion or pfhrp3 deletion (or both gene deletions) if Δ Cq values are of 3 or greater, where Δ Cq = Cq p f h r p 2 – Cq p f l d h (for the pfhrp2 deletion) or Δ Cq = Cq p f h r p 3 – Cq p f l d h (for the pfhrp3 deletion) and Cq pfhrp2 is the qPCR quantification cycle for pfhrp2 , Cq pfhrp3 for pfhrp 3 , and Cq pfldh for pfldh . Samples with Cq pfldh values exceeding 35 cycles were deemed indeterminate due to insufficient DNA. The relative ratio of parasite DNA to human DNA in survey samples was estimated by calculating the ΔCq value using the human tubulin gene as a reference, where Δ Cq = Cq p f l d h – Cq h u m a n t u b u l i n . For severe malaria samples, parasite density was estimated against the WHO International Standard, as previously described. Outcomes The primary outcome was prevalence of pfk13 mutations in health facilities and administrative zones. The secondary outcomes were the genetic relatedness of pfk13 mutants, the proportion of pfhrp2/3 deletions, and the interactions between pfk13 mutation and pfhrp3 deletions. Data analysis Sequences of pfk13 from samples of the first study were aligned using MEGA version 7.0.26. Single nucleotide polymorphisms were identified by comparing these alignments with the pfk13 sequence in P falciparum strain 3D7 (PF3D7_1343700). For samples of the second study, amplicon reads were analysed using Python and well established bioinformatics tools, as described previously, with some slight modifications. Sequencing alignment was performed using minimap2 software (version 2.22) using -ax and map-ont, and other default parameters. Mutation prevalence analysis was done using the R packages vcfR (version 1.12.0) and plyr (version 1.8.6). A coverage cutoff value of 10% was used to confirm that a given single nucleotide polymorphism was a mutation. To compare mutation prevalence and proportions between sample groups, we used the χ 2 test and odds ratio (OR) analysis. Comparisons of median (95% CIs) parasite DNA concentrations and parasite densities among sample groups were done using the Mann–Whitney test; p values of less than 0·05 were considered significant. Role of the funding source The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. 

In this retrospective analysis of pfk13 mutations and pfhrp2/3 deletions, P falciparum -infected blood samples were collected from two studies. The first study , obtained blood samples from two cross-sectional surveys designed to investigate the prevalence of pfhrp2/3 deletions among symptomatic patients before treatment. The first survey was conducted at two hospitals (Ghindae Hospital and Massawa Hospital) in Semenawi Keyih Bahri in March 1–31, 2016. The second survey was done between Jan 4, 2019, and March 19, 2020, in nine hospitals or health centres in three zones: Gash Baka (Agordat, Shambuko, Tesseney, Tekobmia and Barentu), Anseba (Keren and Hagaz) and Debub (Mendefera and Maimine). In the present study, we selected a subset of the samples from the second survey, selected to represent all health facilities and pfhrp2/3 status. The second study (unpublished) aimed to investigate the impact of pfhrp2/3 deletions on clinical outcomes in Eritrea . P falciparum -infected blood samples were collected from eight health facilities across three zones: Gash Barka (Agordat, Barentu and Mulki), Anseba (Keren), and Debub (Mendefera, Areza, Dubarwa, and Emni-Haily). The surveys of pfhrp2/3 deletions were approved by the Eritrean Ministry of Health Research and Ethical Committee. Written informed consent was obtained from participants at enrolment in the original studies. , Laboratory analyses on collected samples received approval from the Australian Departments of Defence and Veterans' Affairs Human Research Ethics Committee (#15–004). Additionally, the severe malaria study was approved by the London School of Hygiene and Tropical Medicine Ethics Review Committee (#11979). 

For data analysis, P falciparum -infected blood samples collected between 2018 and 2020 were merged according to health facilities where they were collected. Genomic DNA was extracted from samples collected from the first study , and the second study using a previously reported method . For blood samples collected from the first study, a fragment (codons 435–680) of the propeller region of the pfk13 gene was amplified using published primers and conditions  and sequenced using Sanger sequencing from both ends using 3130xl Genetic Analyzers and BigDye reagents from Applied Biosystems (Foster City, CA, USA). For blood samples collected from the second study, a 1033 bp fragment (codons 380–724) spanning the propeller region of pfk13 was amplified and visualised using gel electrophoresis. Subsequently, amplicon pooling and cleaning were carried out as previously described. Library preparation and adaptor ligation were done using the Oxford Nanopore native barcoding kit (sqk-nbd-112–96) following manufacturer’s protocol (Oxford Nanopore, UK). These methods are detailed in the . Seven neutral microsatellite markers (TA1, PolyA, PfPK2, TA109, 2490, 313, and 383) were analysed as part of previous studies to determine parasite haplotypes. , Seven-loci-haplotype data were available for 184 samples from the first study and were included in this retrospective analysis: 50 samples from 2016 and 134 from 2019–20. To assess the genetic diversity (expected heterozygosity, H E ) and genetic relatedness of parasite haplotypes with different pfk13 variants, we used FSTAT and PHYLOViZ online software (version 2.0) following developers’ instructions. The status of pfhrp2 and pfhrp3 genes in all samples was evaluated using a published multiplex quantitative PCR (qPCR) method with minor modifications introduced for survey samples. Primer and probe sequences , qPCR reagents and conditions, and the equipment used are detailed in the . Samples were classified as having a pfhrp2 deletion or pfhrp3 deletion (or both gene deletions) if Δ Cq values are of 3 or greater, where Δ Cq = Cq p f h r p 2 – Cq p f l d h (for the pfhrp2 deletion) or Δ Cq = Cq p f h r p 3 – Cq p f l d h (for the pfhrp3 deletion) and Cq pfhrp2 is the qPCR quantification cycle for pfhrp2 , Cq pfhrp3 for pfhrp 3 , and Cq pfldh for pfldh . Samples with Cq pfldh values exceeding 35 cycles were deemed indeterminate due to insufficient DNA. The relative ratio of parasite DNA to human DNA in survey samples was estimated by calculating the ΔCq value using the human tubulin gene as a reference, where Δ Cq = Cq p f l d h – Cq h u m a n t u b u l i n . For severe malaria samples, parasite density was estimated against the WHO International Standard, as previously described. 

The primary outcome was prevalence of pfk13 mutations in health facilities and administrative zones. The secondary outcomes were the genetic relatedness of pfk13 mutants, the proportion of pfhrp2/3 deletions, and the interactions between pfk13 mutation and pfhrp3 deletions. 

Sequences of pfk13 from samples of the first study were aligned using MEGA version 7.0.26. Single nucleotide polymorphisms were identified by comparing these alignments with the pfk13 sequence in P falciparum strain 3D7 (PF3D7_1343700). For samples of the second study, amplicon reads were analysed using Python and well established bioinformatics tools, as described previously, with some slight modifications. Sequencing alignment was performed using minimap2 software (version 2.22) using -ax and map-ont, and other default parameters. Mutation prevalence analysis was done using the R packages vcfR (version 1.12.0) and plyr (version 1.8.6). A coverage cutoff value of 10% was used to confirm that a given single nucleotide polymorphism was a mutation. To compare mutation prevalence and proportions between sample groups, we used the χ 2 test and odds ratio (OR) analysis. Comparisons of median (95% CIs) parasite DNA concentrations and parasite densities among sample groups were done using the Mann–Whitney test; p values of less than 0·05 were considered significant. 

The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. 

In March, 2016, 50 P falciparum -infected blood samples were collected from the first survey in the first study and sequence analysis revealed a wild-type pfk13 gene in all samples. Between January, 2019, and March, 2020, 714 P falciparum -infected blood samples were collected from the second survey in the first study, of which 471 samples were used. Between September, 2018, and November, 2019, 116 samples were collected from the second study. From the combined pool of 587 blood samples collected in 2018–20, five different non-synonymous mutations—encoding Glu605Lys, Arg622Ile, Asn657Lys, Lys658Glu, and Ser679Leu—were identified . Notably, each mutant pfk13 sequence encoded only a single amino acid substitution. Among these substitutions, Arg622Ile had the highest overall prevalence of 11·9% (70 of 587 samples; range 5·9–28·0% among health facilities where sample numbers were greater than five). The prevalence of the Asn657Lys mutation was 0·3% (two of 587 samples). The Glu605Lys, Lys658Glu, and Ser679Leu mutations were each detected in a single sample, resulting in a 0·2% prevalence (one of 587 samples; ). The samples carrying the Glu605Lys, Lys658Glu, Ser679Leu, and Asn657Lys mutations were exclusively collected from the Gash Barka zone. However, the Arg622Ile mutation was identified in samples collected from all nine health facilities in the three zones where there were more than five samples, with a prevalence exceeding 10·0% in seven of these health facilities . The prevalence of the Arg622Ile mutation was highest in Hagaz (seven [28·0%] of 25 samples) in the Anseba zone, whereas the lowest prevalence was in Mendefera (three [5·9%] of 51) in the Debub zone. The prevalence of the Arg622Ile mutation was significantly higher in Hagaz than in Mendefera (p=0·0078), Keren (p=0·021), and Barentu (p=0·034). However, no significant differences were observed between zones overall (p>0·05). The prevalence for the Arg622Ile mutation was 12·1% (45 of 373 samples) in Gash Barka, 13·8% (16 of 116) in Anseba, and 9·2% (nine of 98) in the Debub zone . Analysis of the proportion of the amplicon sequence reads showed that the mean proportion of the Arg622Ile mutation was 25·0% (SD 17·6, range 11·3–70·8) within a sample. To understand whether the Arg622Ile mutants shared a common ancestry and whether they were undergoing expansion, we analysed microsatellite haplotypes obtained from previous studies. , Among 184 samples from the first study that were microsatellite genotyped, 26 samples carried the pfk13 Arg622Ile mutation. Among these 26 samples, we identified 22 unique haplotypes, with all but two found in one sample each. The remaining two haplotypes were shared between three samples . By contrast, among the remaining 158 samples with the wild-type 622Arg, we identified 87 unique haplotypes. The overall genetic diversity (measured as H E value, determined after 20 permutations) did not differ significantly between Arg622Ile mutants (H E 0·4774 [95% CI 0·1873–0·7676]) and 622Arg wild-type parasites (0·5773 [0·3760–0·7786]; p=0·050; ). Genetic relatedness analysis revealed that although 13 (59·1%) of the 22 Arg622Ile mutant haplotypes were closely related within a cluster, the remaining nine (40·9%) mutant haplotypes were not closely related to each other, suggesting multiple independent genetic origins . Of the 87 wild-type haplotypes, 43 (49·4%) were within the cluster and 44 (50·6%) were outside the cluster. These findings indicate that parasites carrying the Arg622Ile mutation had evolved from different genetic backgrounds, involving clonal expansion and independent emergence. To investigate whether the pfk13 mutations had an effect on parasite fitness, we analysed the relative quantity of parasite DNA estimated for samples from the first study and found similar Δ Cq between samples carrying the Arg622Ile mutation (2·02 [95% CI 1·34–2·91]) and those carrying the wild-type 622R mutation (2·04 [1·66–2·35]; p=0·68; ). The median parasite density was also similar (4674 parasites per μL [95% CI 419·0–11430] vs 4242 parasites per μL [2436–5444]; p=0·94) between the two pfk13 genotypes in samples from the second study . These results suggest that the presence of pfk13 mutations did not lead to significant differences in parasite density. Among 587 samples collected between 2018 and 2020 with pfk13 sequences, 578 had pfhrp2 and pfhrp3 status determined. Among these, 17 samples (2·9%) displayed a single pfhrp2 deletion, 255 samples (44·1%) had a single pfhrp3 deletion, 145 samples (25·1%) had a double pfhrp2/3 deletion, and 161 samples (27·9%) had no deletions . The remaining nine samples were indeterminate due to insufficient parasite DNA (Cq pldh >35 cycles). Samples with single pfhrp3 deletion not only had four of five pfk13 mutations (except Glu605Lys), but also showed a significantly higher prevalence of the Arg622Ile mutation (46 [18·0%] of 255 samples) than did samples without pfhrp2/3 deletions (ten [6·2%] of 161 samples; OR 3·89 [95% CI 1·59–7·61]; p=0·0006) or those with dual pfhrp2/3 deletions (13 [9·0%] of 145; 2·23 [1·13–4·68]; p=0·018). The prevalence of the Arg622Ile mutation was similar between samples with single pfhrp3 deletion and samples with single pfhrp2 deletion (one [5·9%] of 17; 3·51 [0·52–150]; p=0·32; ). The proportion of single pfhrp3 deletion was significantly higher (p<0·0001) in the Arg622Ile mutants than in parasites with wild-type 622Arg, whereas the proportion of no deletions (p=0·0071) was significantly lower in the Arg622Ile mutants than in parasites with wild-type 622Arg. The proportions of single pfhrp2 deletion (p=0·43) and dual pfhrp2/3 deletions (p=0·18) did not differ significantly between parasites with mutant versus wild-type pfk13 . 

This study reports the prevalence and trends of pfk13 mutations in the P falciparum population in Eritrea from 2016 to 2020. Additionally, the study explores potential associations between these mutations and pfhrp2/3 deletions. In 2016, a decade after the introduction of HRP2-based RDTs and 9 years after artesunate–amodiaquine use in Eritrea, 31 (62%) of 50 patients in the Semenawi Keyih Bahri zone whose samples were included in this study were infected with parasites lacking both pfhrp2 and pfhrp3 genes, rendering them undetectable by HRP2-based RDTs. Notably, in these samples, no mutation was detected in the pfk13 gene. Despite the relatively small sample size (n=50), the data suggest that in 2016 pfk13 mutations were either absent or present as minor variants below the detection limit, indicating low frequencies at the two study sites during the survey period. This finding aligns with an earlier study conducted in 2013–14, which reported a low prevalence (0·8%) of the Arg622Ile mutation in samples collected in Agordat and Barentu in the Gash Barka zone despite having different sample collection sites and sequencing technologies. By contrast, a more recent study reported a higher prevalence (8·2%) of Arg622Ile mutation among 280 samples collected during a 2016 therapeutic efficacy study conducted in the Gash Barka zone. This finding suggests high geographical heterogeneity in the distribution of the Arg622Ile mutation in Eritrea in 2016. In 2018–20, 2 years after the discontinuation of the use of HRP2-based RDTs in Eritrea, we identified pfk13 Arg622Ile mutations in samples from all health facilities across three zones in Eritrea, with a prevalence exceeding 10% at more than three-quarters of health facilities. In Agordat and Barentu, the prevalence of the Arg622Ile mutation had reached 13·7% and 11·0%, respectively, which is markedly higher than 5 years earlier. The prevalence and wide distribution of the Arg622Ile mutation detected in this study, combined with that reported from therapeutic efficacy studies, show the Arg622Ile mutation has become highly prevalent throughout Eritrea since 2017. Microsatellite genotyping results revealed that the increase in Arg622Ile prevalence was likely due to a combination of clonal expansion of the mutant parasites and multiple independent emergence events from different genetic backgrounds, suggesting complex evolutionary dynamics similar to those reported in Ethiopia. These mutations probably evolved locally in Eritrea, rather than spread from neighbouring countries, as genetic analysis using the same haplotype data indicated differences between Eritrean parasite lineages, both with and without pfhrp2/3 deletions, and those from Sudan, Ethiopia, and Djibouti. Our study found that the Arg622Ile mutation was more prevalent in parasites with single pfhrp3 deletions ( pfhrp2 positive) and in parasites with double pfhrp2/3 deletions than in parasites without deletions in Eritrea. This observation is consistent with results from therapeutic efficacy studies in Eritrea, but contrasts with the findings in Ethiopia, where Art622Ile was more prevalent in parasites without pfhrp2/3 deletions. This difference might be related to the types of RDTs used in these countries at the time of the survey. Although both countries had a high prevalence of pfhrp2/3 deletions, Eritrea switched to parasite lactate dehydrogenase-based RDTs in 2016, whereas Ethiopia continued to use HRP2-based RDTs. Our data support a two-step evolution hypothesis in Eritrea. The first step includes the initial emergence of the pfk13 Arg622Ile mutation in parasites with the pfhrp2/3 deletion and the expansion of this mutant population under HRP2-based RDT selection pressure due to survival advantage. This step is supported by a higher prevalence of the pfhrp2/3 deletion than of the Arg622Ile mutation. In the second step, the Arg622Ile mutants spread under ACT selection pressure after withdrawal of RDT selection pressure, which could also have contributed to further spread of pfhrp3 deletions, given their co-localisation on the same chromosome. The driving force for a close association between the pfhrp3 deletion and the pfk13 Arg622Ile mutation, and between the pfhrp2/3 deletion and the pfk13 Arg622Ile mutation, might be related to fitness gains in parasites with both the pfhrp3 deletion and pfk13 R622I mutations. Although the data suggest that the mutation does not appear to be associated with parasite density in peripheral blood, it could potentially alter other characteristics, such as transmissibility. The influence of pfhrp2/3 deletions on parasite fitness in infected individuals remains uncertain. Previous studies using genomic data from genetic crosses indicated no fitness cost, which reduces heritability associated with these deletions in the mosquito and liver stages. However, contradictory in-vitro results have shown fitness costs, suggesting these might be confined to the blood stages of the parasite lifecycle. Mutations in pfk13 might also affect parasite fitness. In-vitro experiments have indicated that the pfk13 Cys580Tyr mutation entails modest fitness costs when accompanied by multicopy pm2/3 whereas it remains fitness-neutral in the presence of single pm2/3 copies. The effect of pfk13 Arg622Ile mutation on parasite fitness, the correlation between pfhrp2/3 deletions and pfk13 mutations, as well as their collective effect on parasite fitness, remain unclear. We hypothesise a scenario of fitness–cost interplay between pfk13 mutations and pfhrp2/3 deletions. Further studies are required to decipher the interaction between pfhrp2/3 deletions and pfk13 mutations. The emergence of P falciparum with pfhrp2/3 deletions and pfk13 mutations presents a dual-threat scenario, conferring evasion to some diagnostic measures and resistance to therapeutic interventions. False-negative RDT results due to pfhrp2/3 deletion might result in treatment not being administered, thus allowing the variants to spread and potentially causing infections to progress to severe malaria and death. Indications of potential co-occurrence between pfhrp2/3 deletions and pfk13 mutations have been documented, notably in Ethiopia. The findings in this study have shed light on instances of co-occurring pfk13 Arg622Ile and pfhrp2/3 variants in Eritrea. This study has several strengths. First, this is the first study to document the presence of pfk13 Arg622Ile in two administrative zones (Anseba and Debub) and 11 subzones, in addition to those reported previously. This observation signifies the expansion of pfk13 Arg622Ile in Eritrean territory. Second, two of the newly identified subzones, Tesseney (located close to the Sudanese border) and Maimine (near the Ethiopian border), carry notable regional relevance, requiring concerted regional response. Finally, this study included a larger sample size than in a previous study for 2019, thus providing greater power for analysis of association between pfhrp2/3 deletions and pfk13 mutations. This study also has some limitations. First, samples collected before (2016) and after the RDT switch (2018–20) were obtained from different health facilities and zones, thus limiting direct comparisons in the prevalence of pfhrp2/3 deletions and pfk13 mutations between the two timepoints. Second, recent antimalarial treatment history, which might affect the frequency of pfk13 mutations, was not obtained at enrolment. Third, sequencing of pfk13 was conducted on a subset of samples collected in 2018–20. However, as all samples from the second study and a representative subset of samples from the 2019 survey in the first study (including 66–88% of pfhrp2/3 deletion and 59% of non-deletion samples) were sequenced, significant bias on the outcomes is unlikely. The therapeutic efficacy study conducted during the same timeframe reported similar results, thereby supporting the validity of our own findings. Fourth, this study focused on mutations within the propeller domain of pfk13 , excluding possible mutations outside of the propeller domain that might contribute to artemisinin resistance and interaction with gene deletions. Fifth, microsatellite data have limitations compared with whole genome data including the relatively small number of loci tested and their instability. Genome relatedness data could have provided a better picture of genetic relatedness of the mutant parasites, but this was not possible due to insufficient DNA. Finally, the samples for the second study were not representative of patients with malaria in each health facility, but there is no evidence that pfk13 and pfhrp2/3 variants differ between severe and non-severe malaria. The Arg622Ile mutation has primarily been reported in the Horn of Africa region, where very high prevalence of pfhrp2/3 deletions has been previously reported. , , , , Our study in Eritrea shows the expansion of pfk13 Arg622Ile mutations in the country, with the mutation being enriched in single pfhrp3 -deleted parasites. Although the emergence of pfk13 Arg622Ile is likely associated with increased ACT use and reduced transmission, its interaction with pfhrp2/3 deletions remains unclear. Continued monitoring of the trends in pfhrp2/3 deletions and pfK13 Arg622Ile mutations in Eritrea and the Horn of Africa with and without HRP2-based RDT use will provide further insight into the relationship between pfhrp2/3 deletions and pfK13 Arg622Ile mutations, which will inform future control and elimination efforts. 

pfk13, pfhrp2/3 deletion, and microsatellite genotype data analysed in this study can be found in the . Amplicon sequencing row data are available upon request. 

We declare no competing interests. 

