Search

The European Nucleotide Archive (ENA; https://www.ebi.ac.uk/ena), maintained by the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI), offers those producing data an open and supported platform for the management, archiving, publication, and dissemination of data; and to the scientific community as a whole, it offers a globally comprehensive data set through a host of data discovery and retrieval tools. Here, we describe recent updates to the ENA’s submission and retrieval services as well as focused efforts to improve connectivity, reusability, and interoperability of ENA data and metadata.

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.