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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.

Dengue virus is a major and rapidly growing public health concern in tropic and subtropic regions across the globe. In late 2018, Senegal experienced its largest dengue virus outbreak to date, covering several regions. However, little is known about the genetic diversity of dengue virus (DENV) in Senegal. Here we report complete viral genomes from 17 previously undetected DENV cases from the city of Thiès. In total we identified 19 cases of DENV in a cohort of 198 individuals with fever collected in October and November 2018. We detected 3 co-circulating serotypes; DENV 3 was the most frequent accounting for 11/17 sequences (65%), 4 (23%) were DENV2 and 2 (12%) were DENV1. Sequences were most similar to recent sequences from West Africa, suggesting ongoing local circulation of viral populations; however, detailed inference is limited by the scarcity of available genomic data. We did not find clear associations with reported clinical signs or symptoms, highlighting the importance of testing for diagnosing febrile diseases. Overall, these findings expand the known range of DENV in Senegal, and underscore the need for better genomic characterization of DENV in West Africa.

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.

We here analyze data from the first year of an ongoing nationwide program of genetic surveillance of Plasmodium falciparum parasites in Senegal. The analysis is based on 1097 samples collected at health facilities during passive malaria case detection in 2019; it provides a baseline for analyzing parasite genetic metrics as they vary over time and geographic space. The study’s goal was to identify genetic metrics that were informative about transmission intensity and other aspects of transmission dynamics, focusing on measures of genetic relatedness between parasites. We found the best genetic proxy for local malaria incidence to be the proportion of polygenomic infections (those with multiple genetically distinct parasites), although this relationship broke down at low incidence. The proportion of related parasites was less correlated with incidence while local genetic diversity was uninformative. The type of relatedness could discriminate local transmission patterns: two nearby areas had similarly high fractions of relatives, but one was dominated by clones and the other by outcrossed relatives. Throughout Senegal, 58% of related parasites belonged to a single network of relatives, within which parasites were enriched for shared haplotypes at known and suspected drug resistance loci and at one novel locus, reflective of ongoing selection pressure. Senegal has initiated a national sentinel surveillance program for malaria parasite genetics. Here, the authors report data from the first year of the program and use it to investigate local malaria incidence, patterns of transmission, and genetic loci under selection.

The worldwide decline in malaria incidence is revealing the extensive burden of non-malarial febrile illness (NMFI), which remains poorly understood and difficult to diagnose. To characterize NMFI in Senegal, we collected venous blood and clinical metadata in a cross-sectional study of febrile patients and healthy controls in a low malaria burden area. Using 16S and untargeted sequencing, we detected viral, bacterial, or eukaryotic pathogens in 23% (38/163) of NMFI cases. Bacteria were the most common, with relapsing fever Borrelia and spotted fever Rickettsia found in 15.5% and 3.8% of cases, respectively. Four viral pathogens were found in a total of 7 febrile cases (3.5%). Sequencing also detected undiagnosed Plasmodium , including one putative P. ovale infection. We developed a logistic regression model that can distinguish Borrelia from NMFIs with similar presentation based on symptoms and vital signs (F1 score: 0.823). These results highlight the challenge and importance of improved diagnostics, especially for Borrelia , to support diagnosis and surveillance. Non-malarial febrile illnesses have a range of potential aetiologies which are difficult to diagnose and therefore treat. Here, the authors investigate the causes of acute febrile illness in a peri-urban area of Senegal with low malaria incidence using untargeted and targeted sequencing methods.

Background Malaria elimination in Senegal requires accurate diagnosis of all Plasmodium species. Plasmodium falciparum is the most prevalent species in Senegal, although Plasmodium malariae , Plasmodium ovale, and recently Plasmodium vivax have also been reported. Nonetheless, most malaria control tools, such as Histidine Rich Protein 2 rapid diagnosis test (PfHRP2-RDT,) can only diagnose P. falciparum . Thus, PfHRP2-RDT misses non-falciparum species and P. falciparum infections that fall below the limit of detection. These limitations can be addressed using highly sensitive Next Generation Sequencing (NGS). This study assesses the burden of the four different Plasmodium species in western and eastern regions of Senegal using targeted PCR amplicon sequencing. Methods Three thousand samples from symptomatic and asymptomatic individuals in 2021 from three sites in Senegal (Sessene, Diourbel region; Parcelles Assainies, Kaolack region; Gabou, Tambacounda region) were collected. All samples were tested using PfHRP2-RDT and photoinduced electron transfer polymerase chain reaction (PET-PCR), which detects all Plasmodium species. Targeted sequencing of the nuclear 18S rRNA and the mitochondrial cytochrome B genes was performed on PET-PCR positive samples. Results Malaria prevalence by PfHRP2-RDT showed 9.4% (94/1000) and 0.2% (2/1000) in Diourbel (DBL) and Kaolack (KL), respectively. In Tambacounda (TAM) patients who had malaria symptoms and had a negative PfHRP2-RDT were enrolled. The PET-PCR had a positivity rate of 23.5% (295/1255) overall. The PET-PCR positivity rate was 37.6%, 12.3%, and 22.8% in Diourbel, Kaolack, and Tambacounda, respectively. Successful sequencing of 121/295 positive samples detected P. falciparum ( 93%), P. vivax ( 2.6%), P. malariae ( 4.4%), and P. ovale wallikeri (0.9%). Plasmodium vivax was co-identified with P. falciparum in thirteen samples. Sequencing also detected two PfHRP2-RDT-negative mono-infections of P. vivax in Tambacounda and Kaolack. Conclusion The findings demonstrate the circulation of P. vivax in western and eastern Senegal, highlighting the need for improved malaria control strategies and accurate diagnostic tools to better understand the prevalence of non-falciparum species countrywide.

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 Characterizing the genetic diversity of malaria parasite populations in different endemic settings (from low to high) could be helpful in determining the effectiveness of malaria interventions. This study compared Plasmodium falciparum parasite population diversity from two sites with low (pre-elimination) and high transmission in Senegal and Nigeria, respectively. Methods Parasite genomic DNA was extracted from 187 dried blood spot collected from confirmed uncomplicated P. falciparum malaria infected patients in Senegal (94) and Nigeria (93). Allelic polymorphism at merozoite surface protein 1 ( msp1 ) and merozoite surface protein - 2 ( msp2 ) genes were assessed by nested PCR. Results The most frequent msp1 and msp2 allelic families are the K1 and IC3D7 allelotypes in both Senegal and Nigeria. Multiplicity of infection (MOI) of greater that 1 and thus complex infections was common in both study sites in Senegal (Thies:1.51/2.53; Kedougou:2.2/2.0 for msp 1/2) than in Nigeria (Gbagada: 1.39/1.96; Oredo: 1.35/1.75]). The heterozygosity of msp1 gene was higher in P. falciparum isolates from Senegal (Thies: 0.62; Kedougou: 0.53) than isolates from Nigeria (Gbagada: 0.55; Oredo: 0.50). In Senegal, K1 alleles was associated with heavy than with moderate parasite density. Meanwhile, equal proportions of K1 were observed in both heavy and moderate infection types in Nigeria. The IC3D7 subtype allele of the msp2 family was the most frequent in heavily parasitaemic individuals from both countries than in the moderately infected participants. Conclusion The unexpectedly low genetic diversity of infections high endemic Nigerian setting compared to the low endemic settings in Senegal is suggestive of possible epidemic outbreak in Nigeria.

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 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.