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Abstract Background Drug resistance in Plasmodium falciparum is a major threat to malaria control efforts. Pathogen genomic surveillance could be invaluable for monitoring current and emerging parasite drug resistance. Methods Data from two decades (2000–2020) of continuous molecular surveillance of P. falciparum parasites from Senegal were retrospectively examined to assess historical changes in malaria drug resistance mutations. Several known drug resistance markers and their surrounding haplotypes were profiled using a combination of single nucleotide polymorphism (SNP) molecular surveillance and whole genome sequence based population genomics. Results This dataset was used to track temporal changes in drug resistance markers whose timing correspond to historically significant events such as the withdrawal of chloroquine (CQ) and the introduction of sulfadoxine-pyrimethamine (SP) in 2003. Changes in the mutation frequency at Pfcrt K76T and Pfdhps A437G coinciding with the 2014 introduction of seasonal malaria chemoprevention (SMC) in Senegal were observed. In 2014, the frequency of Pfcrt K76T increased while the frequency of Pfdhps A437G declined. Haplotype-based analyses of Pfcrt K76T showed that this rapid increase was due to a recent selective sweep that started after 2014. Discussion (Conclusion) The rapid increase in Pfcrt K76T is troubling and could be a sign of emerging amodiaquine (AQ) resistance in Senegal. Emerging AQ resistance may threaten the future clinical efficacy of artesunate-amodiaquine (ASAQ) and AQ-dependent SMC chemoprevention. These results highlight the potential of molecular surveillance for detecting rapid changes in parasite populations and stress the need to monitor the effectiveness of AQ as a partner drug for artemisinin-based combination therapy (ACT) and for chemoprevention.

Abstract 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‰), parasite genetics can be used to accurately infer incidence and is consistent with superinfection-based hypotheses of malaria transmission. When transmission was

Abstract 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.

Abstract Background Malaria elimination efforts can be undermined by imported malaria infections. Imported infections are classified based on travel history. Methods A genetic strategy was applied to better understand the contribution of imported infections and to test for local transmission in the very low prevalence region of Richard Toll, Senegal. Results Genetic relatedness analysis, based upon molecular barcode genotyping data derived from diagnostic material, provided evidence for both imported infections and ongoing local transmission in Richard Toll. Evidence for imported malaria included finding that a large proportion of Richard Toll parasites were genetically related to parasites from Thiès, Senegal, a region of moderate transmission with extensive available genotyping data. Evidence for ongoing local transmission included finding parasites of identical genotype that persisted across multiple transmission seasons as well as enrichment of highly related infections within the households of non-travellers compared to travellers. Conclusions These data indicate that, while a large number of infections may have been imported, there remains ongoing local malaria transmission in Richard Toll. These proof-of-concept findings underscore the value of genetic data to identify parasite relatedness and patterns of transmission to inform optimal intervention selection and placement.

Abstract Background Plasmodium falciparum malaria remains a major health challenge in Nigeria despite the global decline of its incidence and mortality rates. Although significant progress has been made in preventing the transmission of P. falciparum and controlling the spread of the infection, there is much to be done in the area of proper monitoring, surveillance of the parasite, investigating the population dynamics and drug resistance profiling of the parasite as these are important to its eventual eradication. Polymorphic loci of msp1, msp2 and/or glurp genes or microsatellites have been traditionally used to characterize P. falciparum population structure in various parts of Nigeria. The lack of standardization in the interpretation of results, as well as the inability of these methods to distinguish closely related parasites, remains a limitation of these techniques. Conversely, the recently developed 24 single nucleotide polymorphism (SNP)-based molecular barcode assay has the possibility of differentiating between closely related parasites and offer additional information in determining the population diversity of P. falciparum within and between parasite populations. This study is therefore aimed at defining the population diversity of P. falciparum in and between two localities in Nigeria using the SNPs barcode technique. Methods The 24-SNP high-resolution melt (HRM) barcode assay and msp2 genotyping was used to investigate both intra and inter population diversity of the parasite population in two urban cities of Nigeria. Results Based on SNP barcode analysis, polygenomic malaria infections were observed in 17.9% and 13.5% of population from Enugu and Ibadan, respectively, while msp2 analyses showed 21% and 19.4% polygenomic infections in Enugu and Ibadan, respectively. Low levels of genetic diversity (π) of 0.328 and 0.318 were observed in Enugu and Ibadan parasite populations, respectively, while the FST value of 0.02 (p = 0.055) was obtained when the genetic divergence of both populations was considered. Conclusions The 24-SNP barcode assay was effective in analysing P. falciparum population diversity. This study also showed that P. falciparum populations in Enugu and Ibadan had a degree of intra-population diversity, but very low divergence between the population. A low degree of polygenomic infections were also observed in the two parasite populations unlike previous years. This maybe as a result of the effect of artemisinin-based combination therapy (ACT), long-lasting insecticide-treated nets (LLITNs) and intermittent preventive treatments in the study populations.