Mental health status of adults under institutional quarantine: a cross-sectional survey in Tunisia

Introduction: restrictive measures imposed during the COVID-19 pandemic, such as quarantine, may induce psychiatric outcomes among concerned individuals. The present study aimed to describe the mental health status of Tunisian adults under mandatory institutional quarantine imposed during the COVID-19 pandemic, and to determine factors influencing the occurrence of psychiatric symptoms. Methods: a cross-sectional phone survey was conducted from April to November 2020 using convenience sampling of persons who had experienced mandatory institutional quarantine. A standardized questionnaire was administered to participants including questions about socio-demographic characteristics and quarantine related information. Generalized anxiety disorder, depression symptoms, and sleep quality during quarantine were assessed using, respectively, the generalized anxiety disorder-7 (GAD-7), the centre for epidemiological studies depression (CES-D-10) and the insomnia severity index (ISI) scales. Bivariate and multivariate analyses were performed to determine factors associated with anxiety and/or depression and with clinical insomnia. Results: among 506 participants, 38.3% experienced anxiety and/or depression symptoms (anxiety:15.4%; depression:37.4%) and 19.2% had clinical insomnia. The prevalence of anxiety and/or depression symptoms and insomnia were higher among women those who spent three hours or above on COVID-19 news, those who had economic difficulties due to COVID-19 pandemic, those who were not satisfied by the accommodation conditions of quarantine facilities, and those who had experienced stigma. Conclusion: high prevalence of psychiatric symptoms among quarantined individuals was found in this study. Psychological interventions should thus be an integral part of the COVID-19 control strategy in order to provide adequate psychological support to persons quarantined due to COVID-19

Critical description of TA linguistic resources

International audienceThis paper presents a critical description of natural language processing for Tunisian Arabic. Indeed, several linguistic resources were proposed for the three types of Tunisian Arabic (intellectualized dialect, spontaneous dialect and electronic dialect). We present different linguistic resources (corpora, lexicons and linguistic analysis tools). This study can be used as a quick reference for the scientific community working on natural language processing in general and more precisely those studying Tunisian Arabic

Morphological disambiguation of Tunisian dialect

International audienceIn this paper, we propose a method to disambiguate the output of a morphological analyzer of the Tunisian dialect. We test three machine-learning techniques that classify the morphological analysis of each word token into two classes: true and false. The class label is assigned to each analysis according to the context of the corresponding word in a sentence. In failure cases, we combine the results of the proposed techniques with a bigram classifier to choose only one analysis for a given word. We disam-biguate the result of the morphological analyzer of the Tunisian Dialect Al-Khalil-TUN (Zribi et al., 2013b). We use the Spoken Tunisian Arabic Corpus STAC (Zribi et al., 2015) to train and test our method. The evaluation shows that the proposed method has achieved an accuracy performance of 87.32%. Ó 2017 The Authors. Production and hosting by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Sentence boundary detection for transcribed Tunisian Arabic

International audienceWe study, in this paper, the problem of detecting the sentence boundary in tran-scribed spoken Tunisian Arabic. We compare and contrast three different methods for detecting sentence bounda-ries in transcribed speech. The first method uses a set of handmade contex-tual patterns for identifying the limit of sentences. The second method aims to classify transcriptions words into four classes according to their position in a sentence. Both methods are based only on lexical and some prosodic information such as silent and filled pauses. Finally, we develop two techniques for mixing the results of the two proposed methods. We show that sentence boundary detec-tion system can improve the accuracy of a POS tagger system developed for tag-ging transcribed Tunisian Arabic

Orthographic Transcription for Spoken Tunisian Arabic

International audienc

Data_Sheet_3_The Delta variant wave in Tunisia: Genetic diversity, spatio-temporal distribution and evidence of the spread of a divergent AY.122 sub-lineage.PDF

IntroductionThe Delta variant posed an increased risk to global public health and rapidly replaced the pre-existent variants worldwide. In this study, the genetic diversity and the spatio-temporal dynamics of 662 SARS-CoV2 genomes obtained during the Delta wave across Tunisia were investigated.MethodsViral whole genome and partial S-segment sequencing was performed using Illumina and Sanger platforms, respectively and lineage assignemnt was assessed using Pangolin version 1.2.4 and scorpio version 3.4.X. Phylogenetic and phylogeographic analyses were achieved using IQ-Tree and Beast programs.ResultsThe age distribution of the infected cases showed a large peak between 25 to 50 years. Twelve Delta sub-lineages were detected nation-wide with AY.122 being the predominant variant representing 94.6% of sequences. AY.122 sequences were highly related and shared the amino-acid change ORF1a:A498V, the synonymous mutations 2746T>C, 3037C>T, 8986C>T, 11332A>G in ORF1a and 23683C>T in the S gene with respect to the Wuhan reference genome (NC_045512.2). Spatio-temporal analysis indicates that the larger cities of Nabeul, Tunis and Kairouan constituted epicenters for the AY.122 sub-lineage and subsequent dispersion to the rest of the country.DiscussionThis study adds more knowledge about the Delta variant and sub-variants distribution worldwide by documenting genomic and epidemiological data from Tunisia, a North African region. Such results may be helpful to the understanding of future COVID-19 waves and variants.</p

Data_Sheet_7_The Delta variant wave in Tunisia: Genetic diversity, spatio-temporal distribution and evidence of the spread of a divergent AY.122 sub-lineage.PDF

IntroductionThe Delta variant posed an increased risk to global public health and rapidly replaced the pre-existent variants worldwide. In this study, the genetic diversity and the spatio-temporal dynamics of 662 SARS-CoV2 genomes obtained during the Delta wave across Tunisia were investigated.MethodsViral whole genome and partial S-segment sequencing was performed using Illumina and Sanger platforms, respectively and lineage assignemnt was assessed using Pangolin version 1.2.4 and scorpio version 3.4.X. Phylogenetic and phylogeographic analyses were achieved using IQ-Tree and Beast programs.ResultsThe age distribution of the infected cases showed a large peak between 25 to 50 years. Twelve Delta sub-lineages were detected nation-wide with AY.122 being the predominant variant representing 94.6% of sequences. AY.122 sequences were highly related and shared the amino-acid change ORF1a:A498V, the synonymous mutations 2746T>C, 3037C>T, 8986C>T, 11332A>G in ORF1a and 23683C>T in the S gene with respect to the Wuhan reference genome (NC_045512.2). Spatio-temporal analysis indicates that the larger cities of Nabeul, Tunis and Kairouan constituted epicenters for the AY.122 sub-lineage and subsequent dispersion to the rest of the country.DiscussionThis study adds more knowledge about the Delta variant and sub-variants distribution worldwide by documenting genomic and epidemiological data from Tunisia, a North African region. Such results may be helpful to the understanding of future COVID-19 waves and variants.</p

Data_Sheet_1_The Delta variant wave in Tunisia: Genetic diversity, spatio-temporal distribution and evidence of the spread of a divergent AY.122 sub-lineage.PDF

IntroductionThe Delta variant posed an increased risk to global public health and rapidly replaced the pre-existent variants worldwide. In this study, the genetic diversity and the spatio-temporal dynamics of 662 SARS-CoV2 genomes obtained during the Delta wave across Tunisia were investigated.MethodsViral whole genome and partial S-segment sequencing was performed using Illumina and Sanger platforms, respectively and lineage assignemnt was assessed using Pangolin version 1.2.4 and scorpio version 3.4.X. Phylogenetic and phylogeographic analyses were achieved using IQ-Tree and Beast programs.ResultsThe age distribution of the infected cases showed a large peak between 25 to 50 years. Twelve Delta sub-lineages were detected nation-wide with AY.122 being the predominant variant representing 94.6% of sequences. AY.122 sequences were highly related and shared the amino-acid change ORF1a:A498V, the synonymous mutations 2746T>C, 3037C>T, 8986C>T, 11332A>G in ORF1a and 23683C>T in the S gene with respect to the Wuhan reference genome (NC_045512.2). Spatio-temporal analysis indicates that the larger cities of Nabeul, Tunis and Kairouan constituted epicenters for the AY.122 sub-lineage and subsequent dispersion to the rest of the country.DiscussionThis study adds more knowledge about the Delta variant and sub-variants distribution worldwide by documenting genomic and epidemiological data from Tunisia, a North African region. Such results may be helpful to the understanding of future COVID-19 waves and variants.</p

Data_Sheet_4_The Delta variant wave in Tunisia: Genetic diversity, spatio-temporal distribution and evidence of the spread of a divergent AY.122 sub-lineage.PDF

IntroductionThe Delta variant posed an increased risk to global public health and rapidly replaced the pre-existent variants worldwide. In this study, the genetic diversity and the spatio-temporal dynamics of 662 SARS-CoV2 genomes obtained during the Delta wave across Tunisia were investigated.MethodsViral whole genome and partial S-segment sequencing was performed using Illumina and Sanger platforms, respectively and lineage assignemnt was assessed using Pangolin version 1.2.4 and scorpio version 3.4.X. Phylogenetic and phylogeographic analyses were achieved using IQ-Tree and Beast programs.ResultsThe age distribution of the infected cases showed a large peak between 25 to 50 years. Twelve Delta sub-lineages were detected nation-wide with AY.122 being the predominant variant representing 94.6% of sequences. AY.122 sequences were highly related and shared the amino-acid change ORF1a:A498V, the synonymous mutations 2746T>C, 3037C>T, 8986C>T, 11332A>G in ORF1a and 23683C>T in the S gene with respect to the Wuhan reference genome (NC_045512.2). Spatio-temporal analysis indicates that the larger cities of Nabeul, Tunis and Kairouan constituted epicenters for the AY.122 sub-lineage and subsequent dispersion to the rest of the country.DiscussionThis study adds more knowledge about the Delta variant and sub-variants distribution worldwide by documenting genomic and epidemiological data from Tunisia, a North African region. Such results may be helpful to the understanding of future COVID-19 waves and variants.</p