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Molecular epidemiology using genomic data can help identify relationships between malaria parasite population structure, malaria transmission intensity, and ultimately help generate actionable data to assess the effectiveness of malaria control strategies. Genomic data, coupled with geographic information systems data, can further identify clusters or hotspots of malaria transmission, parasite genetic and spatial connectivity, and parasite movement by human or mosquito mobility over time and space. In this study, we performed longitudinal genomic surveillance in a cohort of 70 participants over four years from different neighborhoods and households in Thiès, Senegal—a region of exceptionally low malaria transmission (entomological inoculation rate less than 1). Genetic identity (identity by state, IBS) was established using a 24-single nucleotide polymorphism molecular barcode, identity by descent was calculated from whole genome sequence data, and a hierarchical Bayesian regression model was used to establish genetic and spatial relationships. Our results show clustering of genetically similar parasites within households and a decline in genetic similarity of parasites with increasing distance. One household showed extremely high diversity and warrants further investigation as to the source of these diverse genetic types. This study illustrates the utility of genomic data with traditional epidemiological approaches for surveillance and detection of trends and patterns in malaria transmission not only by neighborhood but also by household. This approach can be implemented regionally and countrywide to strengthen and support malaria control and elimination efforts.

In 2006, Senegal adopted artemisinin-based combination therapy (ACT) as first-line treatment in the management of uncomplicated malaria. This study aimed to update the status of antimalarial efficacy more than ten years after their first introduction. This was a randomized, three-arm, open-label study to evaluate the efficacy and safety of artemether-lumefantrine (AL), artesunate-amodiaquine (ASAQ) and dihydroartemisinin-piperaquine (DP) in Senegal. Malaria suspected patients were screened, enrolled, treated, and followed for 28 days for AL and ASAQ arms or 42 days for DP arm. Clinical and parasitological responses were assessed following antimalarial treatment. Genotyping ( msp1 , msp2 and 24 SNP-based barcode) were done to differentiate recrudescence from re-infection; in case of PCR-confirmed treatment failure, Pfk13 propeller and Pfcoronin genes were sequenced. Data was entered and analyzed using the WHO Excel-based application. A total of 496 patients were enrolled. In Diourbel, PCR non-corrected/corrected adequate clinical and parasitological responses (ACPR) was 100.0% in both the AL and ASAQ arms. In Kedougou, PCR corrected ACPR values were 98.8%, 100% and 97.6% in AL, ASAQ and DP arms respectively. No Pfk13 or Pfcoronin mutations associated with artemisinin resistance were found. This study showed that AL, ASAQ and DP remain efficacious and well-tolerated in the treatment of uncomplicated P. falciparum malaria in Senegal.

Background Genetic surveillance of the Plasmodium falciparum parasite shows great promise for helping National Malaria Control Programmes (NMCPs) assess parasite transmission. Genetic metrics such as the frequency of polygenomic (multiple strain) infections, genetic clones, and the complexity of infection (COI, number of strains per infection) are correlated with transmission intensity. However, despite these correlations, it is unclear whether genetic metrics alone are sufficient to estimate clinical incidence. Methods This study examined parasites from 3147 clinical infections sampled between the years 2012–2020 through passive case detection (PCD) across 16 clinic sites spread throughout Senegal. Samples were genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode that detects parasite strains, distinguishes polygenomic (multiple strain) from monogenomic (single strain) infections, and identifies clonal infections. To determine whether genetic signals can predict incidence, a series of Poisson generalized linear mixed-effects models were constructed to predict the incidence level at each clinical site from a set of genetic metrics designed to measure parasite clonality, superinfection, and co-transmission rates. Results Model-predicted incidence was compared with the reported standard incidence data determined by the NMCP for each clinic and found that parasite genetic metrics generally correlated with reported incidence, with departures from expected values at very low annual incidence (< 10/1000/annual [‰]). Conclusions When transmission is greater than 10 cases per 1000 annual parasite incidence (annual incidence > 10‰), parasite genetics can be used to accurately infer incidence and is consistent with superinfection-based hypotheses of malaria transmission. When transmission was < 10‰, many of the correlations between parasite genetics and incidence were reversed, which may reflect the disproportionate impact of importation and focal transmission on parasite genetics when local transmission levels are low.

Background The diagnosis of malaria cases in regions where the malaria burden has decreased significantly and prevalence is very low is more challenging, in part because of reduced clinical presumption of malaria. The appearance of a cluster of malaria cases with atypical symptoms in Mbounguiel, a village in northern Senegal where malaria transmission is low, in September 2018 exemplifies this scenario. The collaboration between the National Malaria Control Programme (NMCP) at the Senegal Ministry of Health and the Laboratory of Parasitology and Mycology at Cheikh Anta Diop University worked together to evaluate this cluster of malaria cases using molecular and serological tools. Methods Malaria cases were diagnosed primarily by rapid diagnostic test (RDT), and confirmed by photo-induced electron transfer-polymerase chain reaction (PET-PCR). 24 single nucleotide polymorphisms (SNPs) barcoding was used for Plasmodium falciparum genotyping. Unbiased metagenomic sequencing and Luminex-based multi-pathogen antibody and antigen profiling were used to assess exposure to other pathogens. Results Nine patients, of 15 suspected cases, were evaluated, and all nine samples were found to be positive for P. falciparum only. The 24 SNPs molecular barcode showed the predominance of polygenomic infections, with identifiable strains being different from one another. All patients tested positive for the P. falciparum antigens. No other pathogenic infection was detected by either the serological panel or metagenomic sequencing. Conclusions This work, undertaken locally within Senegal as a collaboration between the NMCP and a research laboratory at University of Cheikh Anta Diop (UCAD) revealed that a cluster of malaria cases were caused by different strains of P. falciparum . The public health response in real time demonstrates the value of local molecular and genomics capacity in affected countries for disease control and elimination.

Background Molecular epidemiology can provide important information regarding the genetic diversity and transmission of Plasmodium falciparum , which can assist in designing and monitoring elimination efforts. However, malaria molecular epidemiology including understanding the genetic diversity of the parasite and performing molecular surveillance of transmission has been poorly documented in Senegal. Next Generation Sequencing (NGS) offers a practical, fast and high-throughput approach to understand malaria population genetics. This study aims to unravel the population structure of P. falciparum and to estimate the allelic diversity, multiplicity of infection (MOI), and evolutionary patterns of the malaria parasite using the NGS platform. Methods Multiplex amplicon deep sequencing of merozoite surface protein 1 (PfMSP1) and merozoite surface protein 2 (PfMSP2) in fifty-three P. falciparum isolates from two epidemiologically different areas in the South and North of Senegal, was carried out. Results A total of 76 Pfmsp1 and 116 Pfmsp2 clones were identified and 135 different alleles were found, 56 and 79 belonged to the pfmsp1 and pfmsp2 genes, respectively. K1 and IC3D7 allelic families were most predominant in both sites. The local haplotype diversity (Hd) and nucleotide diversity (π) were higher in the South than in the North for both genes. For pfmsp1 , a high positive Tajima’s D (TD) value was observed in the South (D = 2.0453) while negative TD value was recorded in the North (D = − 1.46045) and F-Statistic (Fst) was 0.19505. For pfmsp2 , non-directional selection was found with a highly positive TD test in both areas and Fst was 0.02111. The mean MOI for both genes was 3.07 and 1.76 for the South and the North, respectively, with a statistically significant difference between areas ( p  =  0.001 ). Conclusion This study revealed a high genetic diversity of pfmsp1 and pfmsp2 genes and low genetic differentiation in P. falciparum population in Senegal. The MOI means were significantly different between the Southern and Northern areas. Findings also showed that multiplexed amplicon deep sequencing is a useful technique to investigate genetic diversity and molecular epidemiology of P. falciparum infections.

Background In 2006, the Senegalese National Malaria Control Programme recommended artemisinin-based combination therapy (ACT) with artemether–lumefantrine as the first-line treatment for uncomplicated Plasmodium falciparum malaria. To date, multiple mutations associated with artemisinin delayed parasite clearance have been described in Southeast Asia in the Pfk13 gene, such as Y493H, R539T, I543T and C580Y. Even though ACT remains clinically and parasitologically efficacious in Senegal, the spread of resistance is possible as shown by the earlier emergence of resistance to chloroquine in Southeast Asia that subsequently spread to Africa. Therefore, surveillance of artemisinin resistance in malaria endemic regions is crucial and requires the implementation of sensitive tools, such as next-generation sequencing (NGS) which can detect novel mutations at low frequency. Methods Here, an amplicon sequencing approach was used to identify mutations in the Pfk13 gene in eighty-one P. falciparum isolates collected from three different regions of Senegal. Results In total, 10 SNPs around the propeller domain were identified; one synonymous SNP and nine non-synonymous SNPs, and two insertions. Three of these SNPs (T478T, A578S and V637I) were located in the propeller domain. A578S, is the most frequent mutation observed in Africa, but has not previously been reported in Senegal. A previous study has suggested that A578S could disrupt the function of the Pfk13 propeller region. Conclusion As the genetic basis of possible artemisinin resistance may be distinct in Africa and Southeast Asia, further studies are necessary to assess the new SNPs reported in this study.

Background The use of artemisinin as a monotherapy resulted in the emergence of artemisinin resistance in 2005 in Southeast Asia. Monitoring of artemisinin combination therapy (ACT) is critical in order to detect and prevent the spread of resistance in endemic areas. Ex vivo studies and genotyping of molecular markers of resistance can be used as part of this routine monitoring strategy. One gene that has been associated in some ACT partner drug resistance is the Plasmodium falciparum multidrug resistance protein 1 ( pfmdr1 ) gene. The purpose of this study was to assess the drug susceptibility of P. falciparum populations from Thiès, Senegal by ex vivo assay and typing molecular markers of resistance to drug components of ACT currently used for treatment. Methods The ex vivo susceptibility of 170 P. falciparum isolates to chloroquine, amodiaquine, lumefantrine, artesunate, and artemether was determined using the DAPI ex vivo assay. The high resolution melting technique was used to genotype the pfmdr1 gene at codons 86, 184 and 1246. Results A significant decrease in IC50 values was observed between 2012 and 2013: from 13.84 to 6.484 for amodiaquine, 173.4 to 113.2 for lumefantrine, and 39.72 to 18.29 for chloroquine, respectively. Increase of the wild haplotype NYD and the decrease of the mutant haplotype NFD (79 and 62.26 %) was also observed. A correlation was observed between the wild type allele Y184 in pfmdr1 and higher IC50 for all drugs, except amodiaquine. Conclusion This study has shown an increase in sensitivity over the span of two transmission seasons, marked by an increase in the WT alleles at pfmdr1 . Continuous the monitoring of the ACT used for treatment of uncomplicated malaria will be helpful.

Background The monitoring of Plasmodium falciparum sensitivity to anti-malarial drugs is a necessity for effective case management of malaria. This species is characterized by a strong resistance to anti-malarial drugs. In Senegal, the first cases of chloroquine resistance were reported in the Dakar region in 1988 with nearly 7% population prevalence, reaching 47% by 1990. It is in this context that sulfadoxine–pyrimethamine temporarily replaced chloroquine as first line treatment in 2003, pending the introduction of artemisinin-based combination therapy in 2006. The purpose of this study is to assess the ex vivo sensitivity to different anti-malarial drugs of the P. falciparum population from Pikine. Methods Fifty-four samples were collected from patients with non-complicated malaria and aged between 2 and 20 years in the Deggo health centre in Pikine in 2014. An assay in which parasites are stained with 4′, 6-di-amidino-2-phenylindole (DAPI), was used to study the ex vivo sensitivity of isolates to chloroquine, amodiaquine, piperaquine, pyrimethamine, and dihydroartemisinin. High resolution melting was used for genotyping of pfdhps , pfdhfr , pfmdr1 , and pfcrt genes. Results The mean IC 50 s of chloroquine, amodiaquine, piperaquine, dihydroartemisinin, and pyrimethamine were, respectively, 39.44, 54.02, 15.28, 2.23, and 64.70 nM. Resistance mutations in pfdhfr gene, in codon 437 of pfdhps gene, and an absence of mutation at position 540 of pfdhps were observed. Mutations in codons K76T of pfcrt and N86Y of pfmdr1 were observed at 51 and 11% population prevalence, respectively. A relationship was found between the K76T and N86Y mutations and ex vivo resistance to chloroquine. Conclusion An increase in sensitivity of isolates to chloroquine was observed. A high sensitivity to dihydroartemisinin was observed; whereas, a decrease in sensitivity to pyrimethamine was observed in the parasite population from Pikine.

Background Emergence and spread of drug resistance to every anti-malarial used to date, creates an urgent need for development of sensitive, specific and field-deployable molecular tools for detection and surveillance of validated drug resistance markers. Such tools would allow early detection of mutations in resistance loci. The aim of this study was to compare common population signatures and drug resistance marker frequencies between two populations with different levels of malaria endemicity and history of anti-malarial drug use: Tanzania and Sénégal. This was accomplished by implementing a high resolution melting assay to study molecular markers of drug resistance as compared to polymerase chain reaction–restriction fragment length polymorphism (PCR/RFLP) methodology. Methods Fifty blood samples were collected each from a lowly malaria endemic site (Sénégal), and a highly malaria endemic site (Tanzania) from patients presenting with uncomplicated Plasmodium falciparum malaria at clinic. Data representing the DHFR were derived using both PCR–RFLP and HRM assay; while genotyping data representing the DHPS were evaluated in Senegal and Tanzania using HRM. Msp genotyping analysis was used to characterize the multiplicity of infection in both countries. Results A high prevalence of samples harbouring mutant DHFR alleles was observed in both population using both genotyping techniques. HRM was better able to detect mixed alleles compared to PCR/RFLP for DHFR codon 51 in Tanzania; and only HRM was able to detect mixed infections from Senegal. A high prevalence of mutant alleles in DHFR (codons 51, 59, 108) and DHPS (codon 437) were found among samples from Sénégal while no mutations were observed at DHPS codons 540 and 581, from both countries. Overall, the frequency of samples harbouring either a single DHFR mutation (S108N) or double mutation in DHFR (C59R/S108N) was greater in Sénégal compared to Tanzania. Conclusion Here the results demonstrate that HRM is a rapid, sensitive, and field-deployable alternative technique to PCR–RFLP genotyping that is useful in populations harbouring more than one parasite genome (polygenomic infections). In this study, a high levels of resistance polymorphisms was observed in both dhfr and dhps , among samples from Tanzania and Sénégal. A routine monitoring by molecular markers can be a way to detect emergence of resistance involving a change in the treatment policy.

Background Malaria treatment efforts are hindered by the rapid emergence and spread of drug resistant parasites. Simple assays to monitor parasite drug response in direct patient samples ( ex vivo ) can detect drug resistance before it becomes clinically apparent, and can inform changes in treatment policy to prevent the spread of resistance. Methods Parasite drug responses to amodiaquine, artemisinin, chloroquine and mefloquine were tested in approximately 400 Plasmodium falciparum malaria infections in Thiès, Senegal between 2008 and 2011 using a DAPI-based ex vivo drug resistance assay. Drug resistance-associated mutations were also genotyped in pfcrt and pfmdr1 . Results Parasite drug responses changed between 2008 and 2011, as parasites became less sensitive to amodiaquine, artemisinin and chloroquine over time. The prevalence of known resistance-associated mutations also changed over time. Decreased amodiaquine sensitivity was associated with sustained, highly prevalent mutations in pfcrt , and one mutation in pfmdr1 – Y184F – was associated with decreased parasite sensitivity to artemisinin. Conclusions Directly measuring ex vivo parasite drug response and resistance mutation genotyping over time are useful tools for monitoring parasite drug responses in field samples. Furthermore, these data suggest that the use of amodiaquine and artemisinin derivatives in combination therapies is selecting for increased drug tolerance within this population.