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Among the numerous variants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that have been reported worldwide, the emergence of the Omicron variant has drastically changed the landscape of the coronavirus disease (COVID-19) pandemic. Here, we analyzed the genetic diversity of Moroccan SARS-CoV-2 genomes with a focus on Omicron variant after one year of its detection in Morocco in order to understand its genomic dynamics, features and its potential introduction sources. From 937 Omicron genomes, we identified a total of 999 non-unique mutations distributed across 92 Omicron lineages, of which 13 were specific to the country. Our findings suggest multiple introductory sources of the Omicron variant to Morocco. In addition, we found that four Omicron clades are more infectious in comparison to other Omicron clades. Remarkably, a clade of Omicron is particularly more transmissible and has become the dominant variant worldwide. Moreover, our assessment of Receptor-Binding Domain (RBD) mutations showed that the Spike K444T and N460K mutations enabled a clade higher ability of immune vaccine escape. In conclusion, our analysis highlights the unique genetic diversity of the Omicron variant in Moroccan SARS-CoV-2 genomes, with multiple introductory sources and the emergence of highly transmissible clades. The distinctiveness of the Moroccan strains compared to global ones underscores the importance of ongoing surveillance and understanding of local genomic dynamics for effective response strategies in the evolving COVID-19 pandemic.

The advent of COVID-19 has brought the use of computer tools to the fore in health research. In recent years, computational methods have proven to be highly effective in a variety of areas, including genomic surveillance, host range prediction, drug target identification, and vaccine development. They were also instrumental in identifying new antiviral compounds and repurposing existing therapeutics to treat COVID-19. Using computational approaches, researchers have made significant advances in understanding the molecular mechanisms of COVID-19 and have developed several promising drug candidates and vaccines. This chapter highlights the critical importance of computational drug design strategies in elucidating various aspects of COVID-19 and their contribution to advancing global drug design efforts during the pandemic. Ultimately, the use of computing tools will continue to play an essential role in health research, enabling researchers to develop innovative solutions to combat new and emerging diseases., (© 2024. The Author(s), under exclusive license to Springer Nature Switzerland AG.)

In this paper, we propose a new method for epidemic risk modelling and prediction, based on uncertainty quantification (UQ) approaches. In UQ, we consider the state variables as members of a convenient separable Hilbert space, and we look for their representation in finite dimensional subspaces generated by truncations of a suitable Hilbert basis. The coefficients of the finite expansion can be determined by approaches established in the literature, adapted to the determination of the probability distribution of epidemic risk variables. Here, we consider two approaches: collocation (COL) and moment matching (MM). Both are applied to the case of SARS-CoV-2 in Morocco, as an epidemic risk example. For all the epidemic risk indicators computed in this study (number of detections, number of deaths, number of new cases, predictions and human impact probabilities), the proposed models were able to estimate the values of the state variables with precision, i.e., with very low root mean square errors (RMSE) between predicted values and observed ones. Finally, the proposed approaches are used to generate a decision-making tool for future epidemic risk management, or, more generally, a quantitative disaster management approach in the humanitarian supply chain.

Introduction: Since the COVID-19 pandemic began in December 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continuously evolved with many variants of concern emerging across the world., Methodology: In order to monitor the evolution of these variants in Morocco, we analyzed a total of 2130 genomes of the delta variant circulating around the world. We also included 164 Moroccan delta variant sequences in our analysis., Results: Our findings suggest at least four introductions from multiple international sources and a rise of a dominant delta sub-lineage AY.33 in Morocco. Moreover, we report three mutations in the N-terminal domain of the S protein specific to the Moroccan AY.33 isolates, T29A, T250I and T299I. The effect of these mutations on the secondary structure and the dynamic behavior of the S protein N-terminal domain was further determined., Conclusions: We conclude that these mutations might have functional consequences on the S protein of SARS-CoV-2., Competing Interests: No Conflict of Interest is declared, (Copyright (c) 2022 Safae El Mazouri, Houda Bendani, Nasma Boumajdi, Tarik Aanniz, Ilham Kandoussi, Saaid Amzazi, Lahcen Belyamani, Azeddine Ibrahimi, Mouna Ouadghiri.)

The progression of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in Africa has so far been heterogeneous, and the full impact is not yet well understood. In this study, we describe the genomic epidemiology using a dataset of 8746 genomes from 33 African countries and two overseas territories. We show that the epidemics in most countries were initiated by importations predominantly from Europe, which diminished after the early introduction of international travel restrictions. As the pandemic progressed, ongoing transmission in many countries and increasing mobility led to the emergence and spread within the continent of many variants of concern and interest, such as B.1.351, B.1.525, A.23.1, and C.1.1. Although distorted by low sampling numbers and blind spots, the findings highlight that Africa must not be left behind in the global pandemic response, otherwise it could become a source for new variants.

Since December 2019, the coronavirus disease (COVID-19) pandemic has catapulted the world into a marked health crisis, with over 29 million cases and >930,000 deaths. To better detect affected individuals at an early stage and stop disease progression to an advanced stage, several studies have been conducted to identify the clinical, biological, and radiological characteristics of COVID-19. This study aimed to enrich the literature by critically analyzing the clinical and biological characteristics of 134 patients from the North African Mediterranean region, including numerous genetic, epigenetic, and environmental factors that may influence disease evolution. This single-center retrospective study included all patients older than 18 years confirmed to have COVID-19 and hospitalized at the Cheikh Khalifa University Hospital affiliated with Mohammed VI University of Health Sciences, Casablanca, Morocco. Clinical, demographic, and biological data were analyzed in a cohort of severe and non-severe patients. Univariate analysis was performed to identify factors predictive of severity. There were 134 patients: the median age was 53 years, and 54.5% were male. Of these, 89 had mild to moderate disease; 45 had severe to critical disease, of which 14 died and 31 survived. Advanced age, presence of comorbidities, male sex, and infection in ethnic or family groups were risk factors for progression to severe disease. The presence of abnormalities in the following parameters were strongly associated with progression to severe disease: white blood cells (WBC), neutrophils, lymphocytes, C-reactive protein (CRP), procalcitonin, D-dimers, lactate dehydrogenase (LDH), ferritin, creatinine, aspartate aminotransferase (ASAT), and alanine aminotransferase (ALAT) during both admission and hospitalization. Based on these results and an extensive literature review, we recommend that clinicians closely monitor the biological parameters identified herein and perform immunological and genetic studies., Competing Interests: The authors have declared that no competing interests exist.