The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineages that carry mutations in the spike gene are of concern for potential impact to treatment and prevention efforts. To monitor for new SARS-CoV-2 mutations, a panel of specimens were sequenced from both wave one (N = 96), and wave two (N = 117) of the pandemic in Senegal by whole genome next generation sequencing. Amongst these genomes, new combinations of SARS-CoV-2 spike mutations were identified, with E484K + N501T, L452R + N501Y, and L452M + S477N exclusively found in second wave specimens. These sequences are evidence of local diversification over the course of the pandemic and parallel evolution of escape mutations in different lineages.

This study investigated the seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) immunoglobulin G (IgG) during the first pandemic wave in Senegal. The seroprevalence rate of SARS-CoV-2 IgG was assessed in 10 cities in Senegal by testing plasma from volunteers attending healthcare clinics for reasons unrelated to coronavirus disease 2019 ( n = 3231) between June and October 2020. The overall positivity rate was 20.4% and large geographical differences in seropositivity (6-41.9%) were observed, suggesting that the true number of infections was substantially higher than the official estimate of 8.5%.

Background: Delayed Plasmodium falciparum parasite clearance has been associated with Single Nucleotide Polymorphisms (SNPs) in the kelch protein propeller domain (coded by pfk13 gene). SNPs in the Plasmodium falciparum multidrug resistance gene 1 (pfmdr1) are associated with multi-drug resistance including the combination artemether-lumefantrine. To our knowledge, this is the first work providing information on the prevalence of k13-propeller and pfmdr1 mutations from Sédhiou, a region in the south of Senegal. Methods: 147 dried blood spots on filter papers were collected from symptomatic patients attending a hospital located in Bounkiling City, Sédhiou Region, Southern Senegal. All samples were collected between 2015–2017 during the malaria transmission season. Specific regions of the gene pfk13 and pfmdr1 were analyzed using PCR amplification and Sanger sequencing. Results: The majority of parasites (92.9%) harboured the pfk13 wild type sequence and 6 samples harboured synonymous changes. Regarding pfmdr1, wild-type alleles represented the majority except at codon 184. Overall, prevalence of 86Y was 11.9%, 184F was 56.3% and 1246Y was 1.5%. The mutant allele 184F decreased from 73.7% in 2015 to 40.7% in 2017. The prevalence of haplotype NFD decreased from 71.4% in 2015 to 20.8% in 2017. Conclusions: This study provides the first description of pfk13 and pfmdr1 genes variations in Bounkiling, a city in the Sédhiou Region of Senegal, contributing to closing the gap of information on anti-malaria drug resistance molecular markers in southern Senegal.

The coronavirus disease 2019 (COVID-19) is a contagious disease caused by a new coronavirus called SARS-CoV-2. The first case was discovered in Wuhan, China, in December 2019, raising concerns about the emergence of a new coronavirus that poses a significant public health risk. The objective of this study, based on data collected and sequenced at the Institut de Recherche en Santé, de Surveillance Epidémiologique et de Formations (IRESSEF), is to characterize the pandemic evolution, establish a relationship between the different strains in each wave, and finally determine the phylodynamic evolution of the pandemic, utilizing microreact simulations. The study shows that SARS-CoV-2 strains have evolved over time and the variability of the virus is characterized by sequencing during each wave, as is its contagiousness (the speed at which it spreads). The pandemic has spread at a rate of 44.34 cases/week during the first wave. Twelve weeks later it has risen to 185.33 cases/week during the second wave. Twenty-three weeks into the pandemic, the numbers have reached 681.77 cases/week during the third wave. During the fourth wave, the rate of infection was found to decrease slightly at 646 cases/week between early December 2021 and mid-January 2022. Data collected during this study also provided us with a geographical distribution of COVID-19, indicating that the epidemic started in Dakar before spreading inland.

Background: In Senegal, the incidence of SARS-CoV-2 evolved with four successive epidemic waves. The first wave started in March 2020 with low virus variability, whilst the second outbreak, which started in December 2020, was dominated by the Alpha variant. The third wave took place in June 2021, and the fourth at the end of November 2021. Our interest was to investigate the involvement of variants of concern during these four waves and to track the viral diversity of SARS-CoV-2. Methodology: During the four waves of the pandemic, 276,876 nasopharyngeal swabs were analyzed at the Institut de Recherche en Santé, de Surveillance Epidémiologique et de Formation (IRESSEF). Of these, 22,558 samples tested positive for SARS-CoV-2 by RT-PCR. Then, the virus genomes were sequenced in 817 positive samples using the ARTIC Network of Oxford Nanopore Technologies (ONT). In addition, 10% of the negative samples in RT-PCR new variants were also targeted for the detection of new and previously undescribed variants. Results: Our data have overall shown that the Senegalese strains are very similar to each other or closely related to other strains, such as Gambia, France etc. During the first wave, the most common clade found was 19A (67.5%) and a majority of the samples were of the B.1 (50%) lineage. We noted more diversity during the second wave where clade 20A (38.4%) was more frequent, followed by clade 20B (31.52%) and 20I (9.74%). At the level of lineages, we identified variants of concern as B.1.1.7 (9.74%) and B.1.617.2 (0.86%). In the third wave, we observed at the clade level with mainly 21A (32.63%) and 21J (16.84%). During the fourth wave at the end of November 2021, we mainly identified clade 21K Omicron variant 21K (B.1.1.529 and BA.1) (80.47%) and Delta variant (21A, 21J, and 21I) (AY.103, AY.122, AY.122.1, AY.26, AY.34, AY.36, AY.4, AY.48, AY.57, AY.61, and AY.87) (14.06%). Impact: SARS-CoV-2 diversity may affect the virus’s properties, such as how it spreads, disease severity, or the performance of vaccines, tools, or other public health and social measures. Therefore, such tracking of SARS-CoV-2 variants is not only of public interest, but also highlights the role some African institutes such as IRESSEF with surveillance capabilities through the real-time sequencing of SARS-CoV-2 genomes in the local context. Conclusion: In Senegal, the SARS-CoV-2 pandemic has disrupted the organization of the health system. IRESSEF contributed to put in place strategies to respond effectively to the expectations of medical authorities by providing them with data on the strains circulating in Senegal at each moment of the epidemic.

The growth of the malaria parasite Plasmodium falciparum in human blood causes all the symptoms of malaria. To proliferate, non-motile parasites must have access to susceptible red blood cells, which they invade using pairs of parasite ligands and host receptors that define invasion pathways. Parasites can switch invasion pathways, and while this flexibility is thought to facilitate immune evasion, it may also reflect the heterogeneity of red blood cell surfaces within and between hosts. Host genetic background affects red blood cell structure, for example, and red blood cells also undergo dramatic changes in morphology and receptor density as they age. The in vivo consequences of both the accessibility of susceptible cells, and their heterogeneous susceptibility, remain unclear. Here, we measured invasion of laboratory strains of P. falciparum relying on distinct invasion pathways into red blood cells of different ages. We estimated invasion efficiency while accounting for red blood cell accessibility to parasites. This approach revealed different tradeoffs made by parasite strains between the fraction of cells they can invade and their invasion rate into them, and we distinguish “specialist” strains from “generalist” strains in this context. We developed a mathematical model to show that generalist strains would lead to higher peak parasitemias in vivo compared to specialist strains with similar overall proliferation rates. Thus, the ecology of red blood cells may play a key role in determining the rate of P. falciparum parasite proliferation and malaria virulence. The growth of the malaria parasite Plasmodium falciparum in human blood causes all the symptoms of malaria. Parasites invade red blood cells using pathways defined by a parasite ligand and a corresponding host receptor. As red blood cells age, they undergo changes, affecting which pathways can be used by parasites for invasion. We studied laboratory parasites relying on distinct pathways and measured their ability to invade red blood cells of different ages. We found that parasites trade-off between the proportion of red blood cells they can invade and the efficiency of the invasion process. Using a mathematical model, we predict that these trade-offs affect parasite growth in vivo, with important consequences for virulence.