Evaluating the performance of Plasmodium falciparum genetic metrics for inferring National Malaria Control Programme reported incidence 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.

Ex vivo RSA and pfkelch13 targeted-amplicon deep sequencing reveal parasites susceptibility to artemisinin in Senegal, 2017.

BACKGROUND: Malaria control is highly dependent on the effectiveness of artemisinin-based combination therapy (ACT), the current frontline malaria curative treatment. Unfortunately, the emergence and spread of parasites resistant to artemisinin (ART) derivatives in Southeast Asia and South America, and more recently in Rwanda and Uganda (East Africa), compromise their long-term use in sub-Saharan Africa, where most malaria deaths occur. METHODS: Here, ex vivo susceptibility to dihydroartemisinin (DHA) was evaluated from 38 Plasmodium falciparum isolates collected in 2017 in Thiès (Senegal) expressed in the Ring-stage Survival Assay (RSA). Both major and minor variants were explored in the three conserved-encoding domains of the pfkelch13 gene, the main determinant of ART resistance using a targeted-amplicon deep sequencing (TADS) approach. RESULTS: All samples tested in the ex vivo RSA were found to be susceptible to DHA (parasite survival rate < 1%). The non-synonymous mutations K189T and K248R in pfkelch13 were observed each in one isolate, as major (99%) or minor (5%) variants, respectively. CONCLUSION: The results suggest that ART is still fully effective in the Thiès region of Senegal in 2017. Investigations combining ex vivo RSA and TADS are a useful approach for monitoring ART resistance in Africa.

Quality assessment of malaria microscopic diagnosis at the Aristide Le Dantec University Hospital of Dakar, Senegal, in 2020.

BACKGROUND: Following WHO guidelines, microscopy is the gold standard for malaria diagnosis in endemic countries. The Parasitology-Mycology laboratory (LPM) is the National Reference Laboratory and is currently undergoing ISO 15189 accreditation. In this context, we assessed the performance of the laboratory by confirming the reliability and the accuracy of results obtained in accordance with the requirements of the ISO 15189 standards. This study aimed to verify the method of microscopic diagnosis of malaria at the LPM, in the Aristide Le Dantec hospital (HALD) in Dakar, Senegal. METHODS: This is a validation/verification study conducted from June to August 2020. Twenty (20) microscopic slides of thick/thin blood smear with known parasite densities (PD) selected from the Cheick Anta Diop University malaria slide bank in Dakar were used for this assessment. Six (6) were used to assess microscopists' ability to determine PD and fourteen (14) slides were used for detection (positive vs negative) and identification of parasites. Four (4) LPM-HALD microscopists read and recorded their results on prepared sheets. Data analysis was done with Microsoft Excel 2010 software. RESULTS: A minimum threshold of 50% concordance was used for comparison. Of the twenty (20) slides read, 100% concordance was obtained on eight (8) detection (positive vs negative) slides. Four (4) out of the six (6) parasite density evaluation slides obtained a concordance of less than 50%. Thirteen (13) out of the fourteen (14) identification slides obtained a concordance greater than 50%. Only one (1) identification slide obtained zero agreement from the microscopists. For species identification a concordance greater than 80% was noted and the microscopists obtained scores between 0.20 and 0.4 on a scale of 0 to 1 for parasite density reading. The microscopists obtained 100% precision, sensitivity, specificity and both negative and positive predictive values. CONCLUSION: This work demonstrated that the microscopic method of malaria diagnosis used in the LPM/HALD is in accordance with the requirements of WHO and ISO 15189. Further training of microscopists may be needed to maintain competency.

Ex vivo RSA and Pfkelch13 targeted-amplicon deep sequencing reveal parasites susceptibility to artemisinin in Senegal, 2017.

INTRODUCTION: Malaria control is highly dependent on the effectiveness of artemisinin-based combination therapies (ACTs), the current frontline malaria curative treatments. Unfortunately, the emergence and spread of parasites resistant to artemisinin (ART) derivatives in Southeast Asia and South America, and more recently in Rwanda and Uganda (East Africa), compromise their long-term use in Sub-Saharan Africa where most malaria deaths occur. METHODS: Here, we evaluated ex vivo susceptibility to dihydroartemisinin (DHA) from 38 P. falciparum isolates collected in 2017 in Thiès (Senegal) expressed with the Ring-stage Survival Assay (RSA). We explored major and minor variants in the full Pfkelch13 gene, the main determinant of ART resistance using a targeted-amplicon deep sequencing (TADS) approach. RESULTS: All samples tested in the ex vivo RSA were found to be susceptible to DHA. Both non-synonymous mutations K189T and K248R were observed each in one isolate, as major (99%) or minor (5%) variants, respectively. CONCLUSION: Altogether, investigations combining ex vivo RSA and TADS are a useful approach for monitoring ART resistance in Africa.

Two decades of molecular surveillance in Senegal reveal changes in known drug resistance mutations associated with historical drug use and seasonal malaria chemoprevention.

Drug resistance in Plasmodium falciparum is a major threat to malaria control efforts. We analyzed data from two decades (2000-2020) of continuous molecular surveillance of P. falciparum parasite strains in Senegal to determine how historical changes in drug administration policy may have affected parasite evolution. We profiled several known drug resistance markers and their surrounding haplotypes using a combination of single nucleotide polymorphism (SNP) molecular surveillance and whole-genome sequence (WGS) based population genomics. We observed rapid changes in drug resistance markers associated with the withdrawal of chloroquine and introduction of sulfadoxine-pyrimethamine in 2003. We also observed a rapid increase in Pfcrt K76T and decline in Pfdhps A437G starting in 2014, which we hypothesize may reflect changes in resistance or fitness caused by seasonal malaria chemoprevention (SMC). Parasite populations evolve rapidly in response to drug use, and SMC preventive efficacy should be closely monitored.

Evaluating the performance of Plasmodium falciparum genetics for inferring National Malaria Control Program reported incidence in Senegal.

Genetic surveillance of the Plasmodium falciparum parasite shows great promise for helping National Malaria Control Programs (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. Here, we examined parasites from 3,147 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, we constructed a series of Poisson generalized linear mixed-effects models 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. We compared the model-predicted incidence 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 [‰]). 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 ‰, we found that many of the correlations between parasite genetics and incidence were reversed, which we hypothesize reflects the disproportionate impact of importation and focal transmission on parasite genetics when local transmission levels are low.