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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.

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.

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.

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.

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 in Nigeria is principally due to Plasmodium falciparum and, to a lesser extent to Plasmodium malariae and Plasmodium ovale . Plasmodium vivax is thought to be absent in Nigeria in particular and sub-Saharan Africa in general, due to the near fixation of the Duffy negative gene in this population. Nevertheless, there are frequent reports of P. vivax infection in Duffy negative individuals in the sub-region, including reports from two countries sharing border with Nigeria to the west (Republic of Benin) and east (Cameroon). Additionally, there were two cases of microscopic vivax-like malaria from Nigerian indigenous population. Hence molecular surveillance of the circulating Plasmodium species in two states (Lagos and Edo) of southwestern Nigeria was carried out. Methods A cross-sectional survey between September 2016 and March 2017 was conducted. 436 febrile patients were included for the present work. Venous blood of these patients was subjected to RDT as well as microscopy. Further, parasite DNA was isolated from positive samples and PCR diagnostic was employed followed by direct sequencing of the 18S rRNA of Plasmodium species as well as sequencing of a portion of the promoter region of the Duffy antigen receptor for chemokines. Samples positive for P. vivax were re-amplified several times and finally using the High Fidelity Taq to rule out any bias introduced. Results Of the 256 (58.7%) amplifiable malaria parasite DNA, P. falciparum was, as expected, the major cause of infection, either alone 85.5% (219/256; 97 from Edo and 122 from Lagos), or mixed with P. malariae 6.3% (16/256) or with P. vivax 1.6% (4/256). Only one of the five P. vivax isolates was found to be a single infection. DNA sequencing and subsequent alignment of the 18S rRNA of P. vivax with the reference strains displayed very high similarities (100%). Remarkably, the T-33C was identified in all P. vivax samples, thus confirming that all vivax-infected patients in the current study are Duffy negative. Conclusion The present study gave the first molecular evidence of P. vivax in Nigeria in Duffy negative individuals. Though restricted to two states; Edo in South–South and Lagos in South-west Nigeria, the real burden of this species in Nigeria and sub-Saharan Africa might have been underestimated, hence there is need to put in place a country-wide, as well as a sub-Saharan Africa-wide surveillance and appropriate control measures.

Background Malaria control and elimination strategies are based on levels of transmission that are usually determined by data collected from health facilities. In endemic areas, asymptomatic Plasmodium infection is thought to represent the majority of infections, though they are not diagnosed nor treated. Therefore, there might be an underestimation of the malaria reservoir, resulting in inadequate control strategies. In addition, these untreated asymptomatic Plasmodium infections maintain transmission, making it difficult or impossible to reach malaria elimination goals. Thus, the aim of this study was to determine the prevalence of asymptomatic Plasmodium infections in southeastern Senegal. Methods A cross sectional study was conducted among asymptomatic individuals (N = 122) living in the village of Andiel located in Bandafassi, Kédougou, which consisted of about 200 inhabitants during the malaria transmission season in late October 2019. For each individual without malaria-related symptoms and who consented to participate, a rapid diagnostic test (RDT) was performed in the field. Results were confirmed in the laboratory with photo-induced electron transfer (PET-PCR). Results Malaria prevalence was 70.3% by PET-PCR and 41.8% by RDT. During the same period, the health post of the area reported 49. 1% test positivity rate by RDT. The majority of the infected study population, 92.9%, was infected with a single species and 7.1% had two or three species of Plasmodium . Plasmodium falciparum was predominant and represented 90.2% of the infections, while 6.5% were due to Plasmodium ovale and 3.3% to Plasmodium malariae . 59.4% of children targeted for SMC (zero to ten years old) were infected. Conclusion In southeastern Senegal, where the transmission is the highest, malaria control strategies should address asymptomatic Plasmodium infections at the community level. The results suggest that this area could be eligible for mass drug administration. Moreover, non-falciparum species could be more common and its prevalence should be determined countrywide.

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.

Significance Traditional methods for estimating malaria transmission based on mosquito sampling are not standardized and are unavailable in many countries in sub-Saharan Africa. Such studies are especially difficult to implement when transmission is low, and low transmission is the goal of malaria elimination. Malaria-control efforts in Senegal have resulted in changes in population genomics evidenced by increased allele sharing among parasite genomes, often including genomic identity between independently sampled parasites. Fitting an epidemiological model to the observed data indicates falling transmission from 2006–2010 with a significant rebound in 2012–2013, an inference confirmed by incidence data. These results demonstrate that genomic approaches may help monitor transmission to assess initial and ongoing effectiveness of interventions to control malaria. To study the effects of malaria-control interventions on parasite population genomics, we examined a set of 1,007 samples of the malaria parasite Plasmodium falciparum collected in Thiès, Senegal between 2006 and 2013. The parasite samples were genotyped using a molecular barcode of 24 SNPs. About 35% of the samples grouped into subsets with identical barcodes, varying in size by year and sometimes persisting across years. The barcodes also formed networks of related groups. Analysis of 164 completely sequenced parasites revealed extensive sharing of genomic regions. In at least two cases we found first-generation recombinant offspring of parents whose genomes are similar or identical to genomes also present in the sample. An epidemiological model that tracks parasite genotypes can reproduce the observed pattern of barcode subsets. Quantification of likelihoods in the model strongly suggests a reduction of transmission from 2006–2010 with a significant rebound in 2012–2013. The reduced transmission and rebound were confirmed directly by incidence data from Thièès. These findings imply that intensive intervention to control malaria results in rapid and dramatic changes in parasite population genomics. The results also suggest that genomics combined with epidemiological modeling may afford prompt, continuous, and cost-effective tracking of progress toward malaria elimination.

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.