Full Genome Characterization of Respiratory Syncytial Virus Causing a Fatal Infection in an Immunocompromised Patient in Tunisia.

Human orthopneumovirus (HRSV) is a virus belonging to the Pneumovirus genus that causes lower respiratory tract infections (LRTI) in infants worldwide. In Tunisia, thousands of infants hospitalized for LRTI are found to be positive for HRSV but no whole genome sequences of HRSV strains circulating in this country are available thus far. In this study, five nasal swab samples collected at different time points from a three-month-old female baby with severe immunodeficiency that was hospitalized for acute bronchiolitis were investigated by next generation sequencing. The Tunisian sequences from this study originated from samples collected in 2021, belong to the ON1 genotype of HRSV-A, and are clustered with European sequences from 2019 and not from 2020 or 2021. This is most likely related to local region-specific transmission of different HRSV-A variants due to the COVID-19 related travel restrictions. Overall, this is the first report describing the whole genome sequence of HRSV from Tunisia. However, more sequence data is needed to better understand the genetic diversity and transmission dynamic of HRSV.

Phylogenetic and amino acid signature analysis of the SARS-CoV-2s lineages circulating in Tunisia.

Since the beginning of the Coronavirus disease-2019 pandemic, there has been a growing interest in exploring SARS-CoV-2 genetic variation to understand the origin and spread of the pandemic, improve diagnostic methods and develop the appropriate vaccines. The objective of this study was to identify the SARS-CoV-2s lineages circulating in Tunisia and to explore their amino acid signature in order to follow their genome dynamics. Whole genome sequencing and genetic analyses of fifty-eight SARS-CoV-2 samples collected during one-year between March 2020 and March 2021 from the National Influenza Center were performed using three sampling strategies.. Multiple lineage introductions were noted during the initial phase of the pandemic, including B.4, B.1.1, B.1.428.2, B.1.540 and B.1.1.189. Subsequently, lineages B1.160 (24.2%) and B1.177 (22.4%) were dominant throughout the year. The Alpha variant (B.1.1.7 lineage) was identified in February 2021 and firstly observed in the center of our country. In addition, A clear diversity of lineages was observed in the North of the country. A total of 335 mutations including 10 deletions were found. The SARS-CoV-2 proteins ORF1ab, Spike, ORF3a, and Nucleocapsid were observed as mutation hotspots with a mutation frequency exceeding 20%. The 2 most frequent mutations, D614G in S protein and P314L in Nsp12 appeared simultaneously and are often associated with increased viral infectivity. Interestingly, deletions in coding regions causing consequent deletions of amino acids and frame shifts were identified in NSP3, NSP6, S, E, ORF7a, ORF8 and N proteins. These findings contribute to define the COVID-19 outbreak in Tunisia. Despite the country's limited resources, surveillance of SARS-CoV-2 genomic variation should be continued to control the occurrence of new variants.

Applying the moving epidemic method to determine influenza epidemic and intensity thresholds using influenza-like illness surveillance data 2009-2018 in Tunisia.

BACKGROUND: Defining the start and assessing the intensity of influenza seasons are essential to ensure timely preventive and control measures and to contribute to the pandemic preparedness. The present study aimed to determine the epidemic and intensity thresholds of influenza season in Tunisia using the moving epidemic method. METHODS: We applied the moving epidemic method (MEM) using the R Language implementation (package "mem"). We have calculated the epidemic and the different intensity thresholds from historical data of the past nine influenza seasons (2009-2010 to 2017-2018) and assessed the impact of the 2009-2010 pandemic year. Data used were the weekly influenza-like illness (ILI) proportions compared with all outpatient acute consultations. The goodness of the model was assessed using a cross validation procedure. RESULTS: The average duration of influenza epidemic during a typical season was 20 weeks and ranged from 11 weeks (2009-2010 season) to 23 weeks (2015-2016 season). The epidemic threshold with the exclusion of the pandemic season was 6.25%. It had a very high sensitivity of 85% and a high specificity of 69%. The different levels of intensity were established as follows: low, if ILI proportion is below 9.74%, medium below 12.05%; high below 13.27%; and very high above this last rate. CONCLUSIONS: This is the first mathematically based study of seasonal threshold of influenza in Tunisia. As in other studies in different countries, the model has shown both good specificity and sensitivity, which allows timely and accurate detection of the start of influenza seasons. The findings will contribute to the development of more efficient measures for influenza prevention and control.