Contribution of genomic surveillance in the detection and monitoring of SARS variants- CoV-2 during the 6 pandemic waves in the Central African Republic from 2020 to 2023

Contribution of genomic surveillance in the detection and monitoring of SARS variants- CoV-2 during the 6 pandemic waves in the Central African Republic from 2020 to 2023 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Contribution of genomic surveillance in the detection and monitoring of SARS variants- CoV-2 during the 6 pandemic waves in the Central African Republic from 2020 to 2023 Clotaire Donatien RAFAÏ, Ernest Lango-Yaya, Marie Roseline Darnicka Belizaire, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3832420/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: The Covid-19 pandemic has highlighted the need to strengthen diagnosis and genomic surveillance capacities. The Central African Republic was able to manage 5 waves during health monitoring and integrated genomic surveillance as a surveillance tool in 2021. The aim of this study is to report surveillance data from the National Laboratory of Clinical Biology and Public Health and describe the landscape of circulation of SARS-CoV-2 variants. Materials and methods: This is a retrospective, descriptive observational study over a period of 3 years (ranging from April 2020 to November 2023) carried out on a population of consenting volunteers, from throughout the CAR, tested by RT -PCR on nasopharyngeal samples with sufficient information in the LNBCSP databases. Sequencing is largely carried out at the INRB in KINSHASA and from May 2023 at the LNBCSP. Results and discussion: Out of 97,864 RT-PCR tests carried out, 9,764 came back positive, which corresponds to a prevalence of 9.98%. The average age of the patients was 39.97 years ± 13.76 and the sex ratio M/F was 2.12. The positivity of RT-PCR tests was significantly associated with age (p=0.001), sex (p=0.013) and clinical manifestations. Ten variants circulated during the 5 waves recorded. The landscape of circulating variants was dominated by the Omicron (B.1.1.529), Delta (B.1.617.2) variants and especially by B.1.620 and B.640 which marked the second wave in CAR. Conclusion: This retrospective series provides key information for understanding the history of the Covid-19 pandemic in the CAR. Risk factors are identified and the variant circulation landscape described. Strengthening national genomic surveillance capacities would help the country adopt a better response against this pandemic. Biological sciences/Microbiology Biological sciences/Molecular biology SARS-CoV-2 Variants Central African Republic RT-PCR Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 INTRODUCTION Coronaviruses are cold viruses that mainly affect birds and birds. mammals and whose main reservoirs are bats and rodents[1,2]. If the circulating human coronaviruses are responsible for simple seasonal colds, Emerging coronaviruses cause severe acute respiratory syndromes[3]. So the Middle East Respiratory Syndrome Coronavirus, acute respiratory syndrome coronaviruses severe type 1 and 2 (SARS-CoV-1 and SARS-CoV-2) are the three emerging viruses among the 8 coronaviruses responsible for human respiratory infections detected to date[1,2]. Part of Wuhan in December 2019 and declared a pandemic by the WHO on March 11, 2020, the Covid-19 pandemic with its 772,138,818 confirmed cases and 6,985,964 deaths recorded to date of December 6, 2023, is undoubtedly one of the most important since the end of the pandemic Spanish flu in 1918[4–6]. At the height of the pandemic battle, inequalities in access to technology diagnosis and even access to vaccines have negatively impacted response strategies in countries with limited resources [4,6]. But with the continental plan to intensify genomic surveillance launched in Addis Ababa in November 2021, remarkable progress has been made been carried out in the detection and monitoring of SARS-CoV-2 variants in Africa[7]. The Central African Republic is a country located in the heart of Africa, bordered to the north by the Chad, to the south by the Republic of Congo and the Democratic Republic of Congo, to the east by Sudan and South Sudan and to the West by Cameroon[9]. The country has detected its first case of Covid-19 on March 14, 2020 by RT-PCR (in an immigrant patient) and integrated from March 2021 the continental genomic surveillance strategy by initially referring time the samples for sequencing at the National Institute of Biomedical Research (INRB) of Kinshasa before launching national genomic surveillance on March 23, 2023 at the Laboratory National Clinical Biology and Public Health[6,10]. The hypothesis of this study was to know what was the relevant information to extract three years of laboratory surveillance and variant tracking with the aim of better managing the next pandemics. To address these crucial concerns, we have set ourselves the goal principal to study the epidemiological and virological profiles of patients testing positive for Covid-19 at LNBCSP. MATERIAL AND METHODS Study framework The study took place at the National Laboratory of Clinical Biology and Public Health of Bangui. This public non-profit structure, created in 1983, has, among other things, main missions, diagnosis, training, operational research and animation of the National Laboratory Network. Type of study This was a descriptive retrospective study essentially based on the exploitation laboratory survey data. Duration of the study The study covered a period from April 2020 to May 2023. Sampling It is made up of consenting patients who received an RT-PCR test during the period. of study. Inclusion criteria: Patients who benefited from RT-PCR tests and who consented to the procedure were included in this study. filling out the SARS-CoV-2 RT-PCR diagnostic test request form. Non-inclusion criteria: Patients who have benefited from RT-PCR tests and whose sociodemographic information were not recorded in the databases. Laboratory analyses: Withdrawals The samples were collected mainly at the Covid-19 sampling unit of the LNBCSP and at the Covid-19 Patient Screening and Management Center. Others samples were collected in sampling sites in Bangui and the Provinces. Of the samples from mass screening campaigns were also analyzed during this study. Then, the swabs were immersed in virological transport media (MTV) which were then hermetically closed with their cap, after breaking the stems swabs. Transport of samples Samples often collected and placed in double packaging are transported to the container having a biosafety level 2 plus to be inactivated. A recording is made at prior with a coding for the need for subsequent identification. They are then transported to the technical room, always in double packaging. RT-PCR test The National Laboratory uses 3 PCR machines on which the RT-PCR testsSARS-CoV-2 were realized. These are GeneXpert® automatons from CEFEID DIAGNOSTIC (Vira Solelh 81470 Maurens Scopont, France), the ABI FAST from Applied Biosystems (Applied Biosystems, Waltham, MA, United States) and CFX 96 from Biorad ® (Marcy l'Etoile, France). Real-time RT-PCR technique Viral RNA was extracted from nasopharyngeal and oropharyngeal samples using the mini kit QIAamp Viral RNA (Qiagen, Hilden, Germany) according to the instructions of maker. A real-time PCR targeting the ORF_1ab and N genes of SARS-CoV-2 has been carried out using a specific PCR kit (SANSURE Biotech Kit, Changsha, Republic Popular of China) according to the manufacturer's protocol using the 7500 Fast Dx RealTime PCR (Applied Biosystems, Waltham, MA, USA). The technical procedures of this equipment is attached to this document. GeneXpert ® technique This is a fully automated RT-PCR technique consisting of analyzing 300 µl of liquefied sample and included in a specific cartridge. The test is negative if no fluorescence is not detected after 40 cycles. Internal and external controls included in the cartridge allows the manipulation to be validated (See detailed procedure in the appendices). Sequencing Sample selection and sequencing Samples positive for antigen detection and RT-PCR testing (CT value < 30) have were preserved for sequencing. Most of the samples were sent to the Institute National Research Institute of Kinshasa (DRC) for whole genome sequencing by Next Generation Sequencing (NGS). But from April 2023, positive samples responding to the selection criteria, are sequenced locally. NGS sequencing The libraries were prepared according to the construction and sequencing protocol of the Illumina COVID-19 ARTIC v3 V.5 library, using the ARTIC preparation kit NEBNext Ultra II DNA library (New England Biolabs Inc., Ipswich, MA, USA). THE libraries were quantified (Qubit DNA BR, Thermo Scientific, Waltham, MA, USA), normalized and pooled, and sequencing was performed using an Illumina MiSeq 100 (Illumina, San Diego, CA, USA). Assembly The quality of raw reads was checked using the FastQC tool with parameters by default. The playback quality has been improved by trimming the playback using the software fastp, version v0.23.4. The cleaned reads were assembled by mapping guided by reference using the Wuhan-1 reference sequence (accession ID: MN908947) and bowtie2 with default settings. A consensus sequence for the SARS-CoV-2 genome from each sample was obtained using the samtools/bcftool pipeline and then refined by Pilon software, version 1.19. The sequences were annotated by searching for frames of open readings (ORFs) potentially encoding SARS-CoV-2 viral proteins, as annotated in the Uniprot database. Due to the low quality of the regions assembled, ORFs displaying > 50% coverage were retained. Phylogenetic analyzes and identification of variants/lineages Alignments including low coverage CAR sequences generated for this study as well as CAR and Africa sequences extracted from GISAID and a set of sequences from reference representing all major variants of concern (VoC) in the database GISAID were built using MAFFT v7. A Neighbor Joining Phylogenetic Tree (NJ) CAR genomes was constructed using the MEGA X software, using a model of distance p and applying a pairwise deletion option. A phylogenetic tree maximum likelihood (ML) of African genomes was inferred using the software FastTree, version 2.1.11, which allows the calculation of approximate ML trees for very large alignments, by applying a generalized time-reversible (GTR) model of nucleotides evolution and CAT approximation for different rates of evolution from one site to another. Local support values were calculated with the Shimodaira–Hasegawa test. Trees were visualized and analyzed using FigTree v.1.4.4. For the identification of variants and mutation annotation, sequences were analyzed using Nextclade. Data analyzes Data collection sheets provided by the national coordination of the fight against Covid-19 were used to collect sociodemographic, clinical, biological parameters, including including virological of patients. This data was then entered and analyzed using the epi-info software version 7.2.3.0. The Chi test2Pearson's test and Fisher's exact test were used for categorical variables, with a 95% confidence interval. The differences were considered statistically significant for a p value less than 0.05. Operational definition of waves: The waves correspond to a period of massive, exponential contamination that can be accompanied by a sudden increase in serious cases to the point of exceeding the capacities of healthcare structures as well as high mortality. In the laboratory, wave periods occur result in a high rate of positivity increasing gradually until reaching a peak of positivity of RT-PCR tests before decreasing. RESULTS Sociodemographic characteristics of patients Table I reports the sociodemographic characteristics of the patients, the correlations with RT-PCR test results as well as evolving pandemic trends. The average age of the patients was 39.97 ± 13.90 with extreme ages ranging from 6 months to 92 years. The M/F sex ratio was 2.16. RT-PCR test positivity varied by state clinic of patients, their gender and the pandemic evolution (Table I). Table I: RT-PCR correlation and sociodemographic characteristics of patients Settings Result Total p-value 0.05 Positive % Nagative % Mean age (years ± DS 38.84 ± 13.90 40.10 ± 13.74 39,97 ±13.76 Median age (years) 38.00 40.00 40,00 Age in category (ans) 0.001 0–11 years old 2 0.85 232 99.1 234 1–20 years old 837 11.74 6295 88.26 7132 21–40 years old 5003 11.15 39850 88.85 44853 41–60 years old 3283 08.41 35761 91.59 39044 61–80 years old 601 09.38 5806 90.62 6407 81 years old and over et + 38 19,59 156 80.41 194 TOTAL 9764 9.98 88100 90.02 97864 Gender 4.481 Male 6574 09.69 61251 90.31 67825 Female 3190 10.62 26849 89.38 30039 Sex Ratio M/F = 2,26 TOTAL 9764 09.98 88100 90.02 97864 Patients’condition 0,001 Symptomatic 1511 16.82 7472 83.18 8983 Asymptomatic 8253 9.29 80628 90.71 88881 TOTAL 9764 9.98 88100 90.02 97864 Year 2020 0.079 Male 2223 19.91 8841 80.09 11164 Female 802 18.91 3440 81.09 4242 Sex Ratio M/F = 2,63 TOTAL 3025 19.64 12381 80.36 15406 Year 2021 0.001 Male 2585 11.54 21352 88.46 24137 Female 1671 14.46 9888 85.54 11559 Sex Ratio M/F = 2,07 TOTAL 4456 12.48 32240 87.52 35696 Year 2022 0.051 Male 1516 5.36 26743 94.64 28259 Female 705 5.77 11520 94.23 12225 Sexe Ratio M/F = 2,31 TOTAL 2221 5.49 38263 94.51 40484 Year 2023 0.013 Male 50 1,17 4215 98.83 4265 Female 12 0.60 2001 99.40 2013 Sex Ratio M/F = 2,12 TOTAL 62 0.99 6216 99.01 6278 P = Probability. For a value of P < 0.05, a difference is considered statistically significant. The majority of recruits were male (69%). Women represented 31% of the study population (Fig. 1 ). Pandemic evolution and positivity rate of RT-PCR tests The number of RT-PCR tests carried out increased from 2020 to 2022 before decreasing in 2023. The prevalence of SARS-CoV-2 infection for its part, was 24.43% in 2020, 14.26% in 2021, 5.8% in 2022 and 0.9% in 2023 (Figs. 2 and 3 ). Figure 3 shows a curve infection trends with a peak in the number of cases in 2021 and a trend decreasing since 2022. The succession of waves recorded over the years Over 3 years of pandemic evolution, 6 waves have been recorded. First the first between April and August 2020, then the second between March and June 2021. The third wave broke out between November 2021 and February 2022. The fourth and the fifth wave were recorded between may and july and between September and November 2022. Finally, the sixth wave lasted from January to March 2023 (Fig. 4 ). from 2020 to 2023 The observed mutations are grouped into clades: B.1.640.1, AY.33, AY.122, BA.1.1, BA.2, XBB.1, AY.4, B.1.1, B.1.617.2, BA. 5.1, BA.5.2.6, BE.1.1.1, BQ.1.1, BQ.1.1.1, BQ.1, B.1.620, AY.3, AY.12, BA.5, BA.5.2, BA. 4.1.8, XBB.1.17.1, BQ.1.2.2. A total of 23 different clades identified have been divided according to their size in a bar diagram as presented in Fig. 5 . We note a predominance of the B.1.620 variant, followed by the two Omicron sub-variants represented by B. 1.640.1 and BQ.1.1.1 (Fig. 5 ). A total of 131 sequences with nucleotide coverage greater than or equal to 80% were the subject of this analysis representation between 2021 and 2023(Fig. 5 ). From the sequences determined in our samples, we established a phylogenetic tree of SARS-COV-2 variants and sub-variants. It shows the evolution of mutations originating from infacted hosts depending on the proximity or distance between the strains of the SARS-CoV-2 virus resulting from the COVID-19 pandemic. Figure 6 is the phylogenetic tree of the 23 representative clades, it presents these aspects, in red the Boostrap value indicates the connections and distances between the mutations and the original sequence which circulated during our study period (Fig. 6 ). La Fig. 7 represents the phylodynamics of variants circulating in the Central African territory from South-East Asia and South-West Europe during this study period. This figure comes from the online software Nextsrain. DISCUSSION Prevalence of Covid-19 The prevalence of SARS-CoV-2 infection was 9.9% but much higher (24.43%) in 2020 than in 2023 (0.9%). Trend confirmed by Lango-Yaya et al who reported a prevalence of 24.71% in CAR in 2020[12]. Fairly similar prevalences are reported in the sub-region almost during the same period. Let us remember that the history of the evolution of the pandemic in the Central African Republic was marked by the period before the introduction of the vaccine and that following the vaccination campaign. The last one has corresponded to a reduction in the number of contaminations[6]. Note also that the increase in the number of RT-PCR tests rhymes with the decrease in prevalence for two reasons. First, mass screenings extend to people free of the disease who take steps to preserve their negativity RT-PCR tests, especially for travel purposes[13]. In addition, an increase in capacity screening helps to quickly identify trends and readjust the response with the aim of to stem the pandemic by cutting the chain of transmission. Let us recognize that as such, the RCA, short of RT-PCR tests, had temporarily opted for selective screening of patients symptomatic. This strategy, although economical, had contributed to an increase in contaminations shortly after the detection of the first case on March 14, 2020[6]. But with the support of partners including the African Union, the number of tests carried out has been significantly improved. Those over 80 and those under 20 were the most affected, followed by people aged 20–40 years old. The latter correspond to the active age group who travel a lot more frequently for professional, academic or family reasons. What exposes them at risk of contracting Covid-19. The studies carried out in CAR by Lango-Yaya, Manirakiza and Rafaï corroborate these trends[6],[9],[12]. Other studies carried out in the sub-region report a high prevalence in the active population[14],[15]. In addition, the vulnerability of the elderly has already been reported by MASSAMBA in Senegal and WANG in China[16],[17]. These elderly people who produce insufficiently neutralizing antibodies, also carry numerous comorbidities that can expose to serious forms of Covid-19 as well as high mortality[18]. Sex Positive RT-PCR tests were associated with male gender (sex ratio M/F = 2.26), especially before the introduction of the vaccine in CAR in May 2021 (p = 0.001). The male predisposition to being infected with SARS-CoV-2 is known for hormonal reasons (androgenic)[16],[18]. But with vaccination and immunity acquired after infection over Over the years, trends have changed, alternating between the two sexes[19]. Clinical manifestations The presence of symptoms not only increases the positivity of RT-PCR tests but also that of antigenic tests used on the front line in countries with low RT-PCR testing capacities, such as the CAR which, at a certain point in managing the pandemic reserved RT-PCR for symptomatic patients or even serious cases. Similar trends are reported by Ntagereka in the DRC and by Tegally in a study continental[8],[20]. The succession of waves The CAR experienced 6 waves, the most devastating of which was the second between March and June 2021. The devastation of the second wave was reported by FOKAM in Cameroon, Ntagereka in DRC and Manirakiza in CAR[9,20,21]. It must be recognized that this phase of evolution pandemic corresponds to an evolving trend of variants having undermined strategies initial responses focused on non-vaccination prevention. The variant landscape China's ancestral Wuhan strain gradually replaced by viruses having acquired more power of transmission and replication, mainly thanks to D614G and N501Y mutations which increase the affinity of the spike with the binding domain with ACE, P681H mutations in the furin cleavage domain and responsible for immune escape[21]. We detected 10 variants of interest and a few of concern. The B.1.1.7 or British variants raged during the second wave while the B.1.620 and the B.1.624 dominated the landscape in 2021 before being replaced by the Delta variant. Since the fourth wave, the Omicron variant appeared and established itself as the only variant circulating for two years[6,10]. These landscapes are confirmed by Fokam in Cameroon, Vickos and Rafaï in Central African Republic[6,10,21]. Africa, which was first confronted with cases of importation into start of the pandemic finally saw the emergence of variants of interest, two of which detected on the continent thanks to an expansion of genomic surveillance. This is the variant beta discovered for the first time in a patient from Botswana and the variant Omicron, the first case of which was detected in South Africa. The Central African region has been impacted by the B 1.620 and B1.640 variants [6,10,21]. The first was sequenced for first time in a sample from the Central African Republic and the second circulated there throughout 2021[8]. All these emergences remind us of the need to strengthen national capacities in genomic surveillance with the aim of effectively adjusting the response and even to alert the scientific community as in the case of the detection of the variant B.1.620 made possible by pan-African cooperation. Because the first relative sequences to this variant were detected in samples from the CAR but sequenced in the Democratic Republic of Congo [22]. CONCLUSION This retrospective series, although limited to data from diagnostic test results of laboratory of patients mainly from Bangui, allowed us to better understand to a certain extent the lessons to be learned from the management of the Covid-19 pandemic in the CAR. So, we were able to understand that age, sex and the presence of clinical manifestations were significantly associated with RT-PCR test positivity. We also learned that the CAR went through 6 waves and detected 10 variants including one endemic having circulated during throughout 2021. The persistence of the Omicron variant for almost two years reassures us as for the next waves likely to have very little impact in terms of cases serious and mortality. As the world lives with Covid-19, health monitoring and the intensification of the vaccination could be continued. But with genomic surveillance tools, better epidemiological knowledge is launched. Inequalities in access to tools genomic sequencing, far from being inevitable, should be considered as a challenge to raise. Witness, this sub-regional collaboration initiative before the implementation of the genomic surveillance at the national level last spring. Finally, efforts must be continued to extend sequencing in the provinces of the RCA with the aim of having better information on the genetic diversity of variants and sub-variants in circulation. Declarations Ethical considerations: This study which was part of the national response against Covid-19 was approved by the Institutional Ethical Review Committee of the Ministry of Health and Population of the Central African Republic (CAR). Administrative authorization was obtained from the Minister of Health and Population of the CAR. Voluntary informed consent was obtained from the patients. The study was carried out in strict compliance with the Declaration of Helsinki according to which no intervention likely to alter the dignity, integrity and right to privacy of participants will be implemented. We also received ethical clearance from the Ethics and Scientific Committee of the Faculty of Sciences of Health (N32/FACSS/CES.2020). Human Ethics and Consent to Participate declarations : not applicable. Consent for publication All authors read and approved the manuscript before publication. Availability of data and materials The data that support the findings of this study are available from Public Health Ministry of Central African Republic but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Public Health Minister. Data on GISAID can however be consulted if necessary ( https://www.epicov.org/epi3/frontend#5aa6aa ). Contribution of the authors: Project design: CDR, ELY, MRDB, PS, MMS, BK, JBR Laboratory techniques: CDR, ELY, SN Data analyses: AAOFTG, JAB, OS All authors acknowledge having read the manuscript Recruitment Consent of publication All patients recruited consent and acknowledge having voluntarily participated in the investigation carried out within the framework of public health. Thanks : We thank the entire technical team of the National Laboratory of Clinical Biology and Public health. We also thank the World Health Organization as well as Africa CDC for logistical support. Finally, we thank the INRB Kinshasa and GISAID team who made it possible certain genomic and bioinformatics analyses. Conflict of interest : The authors have no conflicts of interest to declare. References Segondy M. Dossier scientifique Les coronavirus humains. In: RFL Revue francophone des laboratories [Internet]. Elsevier; 2020. p. 32–9. Available from: http://dx.doi.org/10.1016/S1773-035X(20)30311-7 Tang G, Liu Z, Chen D. Human coronaviruses: Origin, host and receptor. J Clin Virol [Internet]. 2022;155(February):105246. Available from: https://doi.org/10.1016/j.jcv.2022.105246 Kin N, Vabret A. Les infections à coronavirus humains. RFL Rev Francoph des Lab [Internet]. 2016;2016(487):25–33. Available from: http://dx.doi.org/10.1016/S1773-035X(16)30369-0 Hantz S. Diagnostic biologique de l’infection à Sars-CoV-2 : stratégies et interprétation des résultats. Rev Francoph des Lab [Internet]. 2020;2020(526):48–56. Available from: http://dx.doi.org/10.1016/S1773-035X(20)30313-0 Surveillance I. COVID-19 Epidemiological Update. 2023;(November):6–8. Rafaï CD, Pierre S, Nambei SW, Lango-yaya E, Belizaire MRD, Ulrich V, et al. Impact of a mass campaign on the evolution of the fourth wave of the Covid-19 pandemic in the Central African Republic. J Virol. 2023; Elie B, Alizon S. Analyses génomiques et phylodynamiques du Sars-CoV-2. Rev Francoph des Lab [Internet]. 2020;2020(526):57–62. Available from: http://dx.doi.org/10.1016/S1773-035X(20)30314-2 Tegally H, San JE, Cotten M, Moir M, Tegomoh B, Mboowa G, et al. The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance. Science (80- ). 2022 Oct 7;378(6615). Manirakiza A, Malaka C, Yambiyo BM, Diemer HS-C, Longo J de D, Namseneï J, et al. Very High Relative Seroprevalence of Anti–SARS-CoV-2 Antibodies Among Communities in Bangui, Central African Republic. SSRN Electron J. 2021;1–10. Vickos U, Camasta M, Grandi N, Scognamiglio S, Schindler T, Roseline M, et al. COVID-19 Genomic Surveillance in Bangui ( Central African Republic ) Reveals a Landscape of Circulating Variants Linked to Validated Antiviral Targets of SARS-CoV-2 Proteome. Viruses. 2023;15(2309). Rafaï CD, Heredeibona LS, Lango-Yaya E, Belizaire RD, Senzongo O, Mbala P, et al. Five successive waves of SARS-CoV-2 infection in the Central African Republic : a prospective observational study from 2020-. Pan Afr Med J. 2023;46(120):1–17. Lango-Yaya E, Béni RD, N’yetobouko S, Koyaweda WG, Rafaï CD. Epidemiological and profile of Covid-19 at the National Laboratory of Clinical Biology and Public Health of Bangui, Central African Republic: cross-Sectionnal Study from April to July 2020. Glob Sci Journals. 2020;8(11):581–90. Pollán M, Pérez-gómez B, Pastor-barriuso R, Oteo J, Hernán MA, Pérez-olmeda M, et al. Articles Prevalence of SARS-CoV-2 in Spain ( ENE-COVID ): a nationwide, population-based seroepidemiological study. 2020;6736(20):1–11. Salem F Ben, Hannachi H, Kalai W, Themlaoui A, Frioui D, Jendoubi N, et al. Profil pidmiologique et clinique de la COVID-19 chez le personnel de sant de lHpital Aziza Othmana, Tunis, Tunisie. Ann françaises d’oto-rhino-laryngologie Pathol cervico-faciale [Internet]. 2023;101818. Available from: https://doi.org/10.1016/j.admp.2023.101818 Iroungou BA, Moussavou PB, Elguero E, Makran J, Bivigou-Mboumba B, Wora E, et al. Trend of expansion of SARS-CoV-2 infection and COVID-19 burden in Gabon (Central Africa) in mid-2021, based on a serological survey. IJID Reg. 2022;5(July):13–7. Massamba B, Assane S, Rokhaya D, Dalahata B, Mamadou C. Infection à Covid-19 en gériatrie au Sénégal. NPG Neurol - Psychiatr - Gériatrie. 2023;(xxxx). Li K, Wang D, Qu H, Rui J, Abudunaibi B, Guo Z, et al. Viral Dynamics of Omicron BA.2.76 Variant of SARS-CoV-2 in a Cohort of COVID-19 Patients. J Infect [Internet]. 2022;(xxxx):2021–3. Available from: http://www.ncbi.nlm.nih.gov/pubmed/36470410 Birato C, Busingo M, Barinjibanjwa N, Bertin B, Muzaliya K, Katabana M, et al. ScienceDirect rielle sur le pro fi l clinique et le pronostic In fl uence de l ’ hypertension art e s pour COVID-19 dans la ville de Bukavu, en des patients hospitalis e publique D e mocratique du Congo : e tude de cohorte prospective R e In fl uence of. 2023;72. Mohamed MS, Moulin TC, Schiöth HB. Sex differences in COVID-19: the role of androgens in disease severity and progression. Endocrine [Internet]. 2021;71(1):3–8. Available from: http://dx.doi.org/10.1007/s12020-020-02536-6 World Health Organization. Statement for healthcare professionals _ Regulation of the safety and effectiveness of COVID-19 vaccines. June 16, 2021; https://www.who.int/en/news/item/11-06-2021. Accessed June 23, 2021 Ntagereka PB, Oyola SO, Baenyi SP, Rono GK, Birindwa AB, Shukuru DW, et al. Whole-genome sequencing of SARS-CoV-2 reveals diverse mutations in circulating Alpha and Delta variants during the first, second, and third waves of COVID-19 in South Kivu, east of the Democratic Republic of the Congo. Int J Infect Dis. 2022;122(December 2019):136–43. Fokam J, Essomba RG, Njouom R, Okomo MCA, Eyangoh S, Godwe C, et al. Genomic surveillance of SARS-CoV-2 reveals highest severity and mortality of delta over other variants: evidence from Cameroon. Sci Rep. 2023;13(1):1–10. Lina B. The different phases of molecular and antigenic evolution of SARS-CoV-2 viruses during the 20 months following its emergence. Bull Acad Natl Med. 2022;206(1):87–99. Dudas G, Hong SL, Potter BI, Calvignac-Spencer S, Niatou-Singa FS, Tombolomako TB, et al. Emergence and spread of SARS-CoV-2 lineage B.1.620 with variant of concern-like mutations and deletions. Nat Commun. 2021;12(1):1–12. Additional Declarations No competing interests reported. Supplementary Files SEQUENCEENTRE508020212023.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3832420","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":268397373,"identity":"2bfc3b5a-d265-42de-a611-6754856768ee","order_by":0,"name":"Clotaire Donatien RAFAÏ","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYDACdhBhACIYHzAkVEDZFfi0MDMwNkCUMRswJJyBajlDUAsDVAtjGxFa+JuZjz/4UXBPzrz9MOOHh/MOy5uzNx9gOLgHtxaJw2yJjT0GxcYyZ5KZJRK3HTbc2XMsgeHAM9xaDJh5DBt4DBISZzDkHwBpYdxwI8eA+cMB/Foa/xgk1M/gf8z8I3HOYXuQFoYDBLQ0A21JkJBIZpNIbDicSFALyC+zZQwSDGdIPGazSDiWnrzhzLGEA/i08Lc3H/j45k+CvAR/MvPNHzXWthuONx98gE8LOmgGkyRoYGCoI0XxKBgFo2AUjBAAAHp0VqFc9znKAAAAAElFTkSuQmCC","orcid":"","institution":"National Laboratory of Clinical Biology and Public Health of Bangui","correspondingAuthor":true,"prefix":"","firstName":"Clotaire","middleName":"Donatien","lastName":"RAFAÏ","suffix":""},{"id":268397374,"identity":"0a3ca8c3-c09f-4c95-bf89-a5aec705427e","order_by":1,"name":"Ernest Lango-Yaya","email":"","orcid":"","institution":"National Laboratory of Clinical Biology and Public Health of Bangui","correspondingAuthor":false,"prefix":"","firstName":"Ernest","middleName":"","lastName":"Lango-Yaya","suffix":""},{"id":268397375,"identity":"1268f24a-1115-444e-8d62-8ef9e6e56069","order_by":2,"name":"Marie Roseline Darnicka Belizaire","email":"","orcid":"","institution":"World Health Organization","correspondingAuthor":false,"prefix":"","firstName":"Marie","middleName":"Roseline Darnicka","lastName":"Belizaire","suffix":""},{"id":268397376,"identity":"29303362-25e9-48c3-9680-08b040847ed8","order_by":3,"name":"Maurel Annicet Adonis Ouoko Fa-Ti-Gbia","email":"","orcid":"","institution":"National Laboratory of Clinical Biology and Public Health of Bangui","correspondingAuthor":false,"prefix":"","firstName":"Maurel","middleName":"Annicet Adonis Ouoko","lastName":"Fa-Ti-Gbia","suffix":""},{"id":268397377,"identity":"ea244868-8f20-4884-9dce-51ae1d6fcdf7","order_by":4,"name":"Marcel Mbeko Simaleko","email":"","orcid":"","institution":"Ministry of Health and Population","correspondingAuthor":false,"prefix":"","firstName":"Marcel","middleName":"Mbeko","lastName":"Simaleko","suffix":""},{"id":268397378,"identity":"5e4e220c-2965-474f-adc9-c7e371af0315","order_by":5,"name":"Jean- Baptiste Roungou","email":"","orcid":"","institution":"Ministry of Health and Population","correspondingAuthor":false,"prefix":"","firstName":"Jean-","middleName":"Baptiste","lastName":"Roungou","suffix":""},{"id":268397379,"identity":"767affd7-7ad4-4334-9006-f9ad63750704","order_by":6,"name":"Oscar Senzongo","email":"","orcid":"","institution":"National Laboratory of Clinical Biology and Public Health of Bangui","correspondingAuthor":false,"prefix":"","firstName":"Oscar","middleName":"","lastName":"Senzongo","suffix":""},{"id":268397380,"identity":"811b82a3-2bd7-41a6-8672-1401d8f62673","order_by":7,"name":"Boniface Koffi","email":"","orcid":"","institution":"National Laboratory of Clinical Biology and Public Health of Bangui","correspondingAuthor":false,"prefix":"","firstName":"Boniface","middleName":"","lastName":"Koffi","suffix":""}],"badges":[],"createdAt":"2024-01-03 17:29:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3832420/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3832420/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49956199,"identity":"a0ca70b9-2940-4ca1-b193-204c708f0fd4","added_by":"auto","created_at":"2024-01-22 08:00:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":136081,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of patients by gender\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3832420/v1/26e5ff455f156e2bf47a28c5.png"},{"id":49956198,"identity":"d027bd76-02e7-4dc9-a717-4919227b0830","added_by":"auto","created_at":"2024-01-22 08:00:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":24848,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of patients who performed the RT-PCR Covid-19 test at the LNBCSP, 2020-2023.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3832420/v1/63856e5ee3ab1b1434a80b5f.png"},{"id":49956202,"identity":"3c637f4b-84f8-4fa6-ac31-16d91ef827f9","added_by":"auto","created_at":"2024-01-22 08:00:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":21973,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvolution of RT-PCR Covid-19 test positivities over the years\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3832420/v1/ae059c350faee43a0b69992c.png"},{"id":49956201,"identity":"4565e9bd-b781-405a-92de-e4ff70211129","added_by":"auto","created_at":"2024-01-22 08:00:07","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":64631,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution of SARS-CoV-2 infection in patients tested at the LNBCSP\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003efrom 2020 to 2023\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3832420/v1/1eb8bb534841de3272e40d94.png"},{"id":49956391,"identity":"23a1cd5f-c7c0-4a3c-872b-45141d447e93","added_by":"auto","created_at":"2024-01-22 08:08:07","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":21902,"visible":true,"origin":"","legend":"\u003cp\u003eLandscape of variants detected from 2021 to 2023.\u003c/p\u003e","description":"","filename":"figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-3832420/v1/b369f66cc258e5ba96afcd9d.png"},{"id":49956200,"identity":"e634e4bd-83fd-4d29-be51-9dc47f36d00f","added_by":"auto","created_at":"2024-01-22 08:00:07","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":19879,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree of 23 variants representative of each of the waves and years of their detection.\u003c/p\u003e","description":"","filename":"figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-3832420/v1/5baf12b95826ad60a90a48ea.png"},{"id":49956204,"identity":"8d8db1eb-0ebc-4e94-8a85-9d8e2b6e87aa","added_by":"auto","created_at":"2024-01-22 08:00:07","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":358176,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOrigin and circulation of variants detected from 2020 to 2023\u003c/strong\u003e[11\u003cstrong\u003e]\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-3832420/v1/73824fc0dc709a0afe9465ce.png"},{"id":55707492,"identity":"bdefc289-11d8-4f39-a4f3-3e55b3049053","added_by":"auto","created_at":"2024-05-02 05:18:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2799551,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3832420/v1/51265812-522a-4cc8-95cf-751d92bdf67f.pdf"},{"id":49956205,"identity":"38ebcf66-3707-4c45-9924-d99956e7db42","added_by":"auto","created_at":"2024-01-22 08:00:07","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":947716,"visible":true,"origin":"","legend":"","description":"","filename":"SEQUENCEENTRE508020212023.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3832420/v1/d8d8fee5263daf125981698f.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Contribution of genomic surveillance in the detection and monitoring of SARS variants- CoV-2 during the 6 pandemic waves in the Central African Republic from 2020 to 2023","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCoronaviruses are cold viruses that mainly affect birds and birds. mammals and whose main reservoirs are bats and rodents[1,2]. If the circulating human coronaviruses are responsible for simple seasonal colds,\u003c/p\u003e \u003cp\u003eEmerging coronaviruses cause severe acute respiratory syndromes[3]. So the Middle East Respiratory Syndrome Coronavirus, acute respiratory syndrome coronaviruses severe type 1 and 2 (SARS-CoV-1 and SARS-CoV-2) are the three emerging viruses among the 8 coronaviruses responsible for human respiratory infections detected to date[1,2].\u003c/p\u003e \u003cp\u003ePart of Wuhan in December 2019 and declared a pandemic by the WHO on March 11, 2020, the Covid-19 pandemic with its 772,138,818 confirmed cases and 6,985,964 deaths recorded to date of December 6, 2023, is undoubtedly one of the most important since the end of the pandemic Spanish flu in 1918[4\u0026ndash;6].\u003c/p\u003e \u003cp\u003eAt the height of the pandemic battle, inequalities in access to technology diagnosis and even access to vaccines have negatively impacted response strategies in countries with limited resources [4,6]. But with the continental plan to intensify genomic surveillance launched in Addis Ababa in November 2021, remarkable progress has been made been carried out in the detection and monitoring of SARS-CoV-2 variants in Africa[7].\u003c/p\u003e \u003cp\u003eThe Central African Republic is a country located in the heart of Africa, bordered to the north by the\u003c/p\u003e \u003cp\u003eChad, to the south by the Republic of Congo and the Democratic Republic of Congo, to the east by Sudan and South Sudan and to the West by Cameroon[9]. The country has detected its first case of Covid-19 on March 14, 2020 by RT-PCR (in an immigrant patient) and integrated from March 2021 the continental genomic surveillance strategy by initially referring time the samples for sequencing at the National Institute of Biomedical Research (INRB) of Kinshasa before launching national genomic surveillance on March 23, 2023 at the Laboratory National Clinical Biology and Public Health[6,10].\u003c/p\u003e \u003cp\u003eThe hypothesis of this study was to know what was the relevant information to extract three years of laboratory surveillance and variant tracking with the aim of better managing the next pandemics.\u003c/p\u003e \u003cp\u003eTo address these crucial concerns, we have set ourselves the goal principal to study the epidemiological and virological profiles of patients testing positive for Covid-19 at LNBCSP.\u003c/p\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy framework\u003c/h2\u003e \u003cp\u003eThe study took place at the National Laboratory of Clinical Biology and Public Health of Bangui. This public non-profit structure, created in 1983, has, among other things, main missions, diagnosis, training, operational research and animation of the National Laboratory Network.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eType of study\u003c/h2\u003e \u003cp\u003eThis was a descriptive retrospective study essentially based on the exploitation laboratory survey data.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDuration of the study\u003c/h2\u003e \u003cp\u003eThe study covered a period from April 2020 to May 2023.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSampling\u003c/h2\u003e \u003cp\u003eIt is made up of consenting patients who received an RT-PCR test during the period.\u003c/p\u003e \u003cp\u003eof study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eInclusion criteria:\u003c/h2\u003e \u003cp\u003ePatients who benefited from RT-PCR tests and who consented to the procedure were included in this study. filling out the SARS-CoV-2 RT-PCR diagnostic test request form.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eNon-inclusion criteria:\u003c/h2\u003e \u003cp\u003ePatients who have benefited from RT-PCR tests and whose sociodemographic information were not recorded in the databases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eLaboratory analyses:\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eWithdrawals\u003c/h2\u003e \u003cp\u003eThe samples were collected mainly at the Covid-19 sampling unit of the LNBCSP and at the Covid-19 Patient Screening and Management Center. Others samples were collected in sampling sites in Bangui and the Provinces. Of the samples from mass screening campaigns were also analyzed during\u003c/p\u003e \u003cp\u003ethis study.\u003c/p\u003e \u003cp\u003eThen, the swabs were immersed in virological transport media (MTV) which were then hermetically closed with their cap, after breaking the stems swabs.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTransport of samples\u003c/h2\u003e \u003cp\u003eSamples often collected and placed in double packaging are transported to the container having a biosafety level 2 plus to be inactivated. A recording is made at prior with a coding for the need for subsequent identification. They are then transported to the technical room, always in double packaging.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eRT-PCR test\u003c/h2\u003e \u003cp\u003eThe National Laboratory uses 3 PCR machines on which the RT-PCR testsSARS-CoV-2 were realized. These are GeneXpert\u0026reg; automatons from CEFEID DIAGNOSTIC (Vira Solelh 81470 Maurens Scopont, France), the ABI FAST from Applied Biosystems (Applied Biosystems,\u003c/p\u003e \u003cp\u003eWaltham, MA, United States) and CFX 96 from Biorad \u0026reg; (Marcy l'Etoile, France).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eReal-time RT-PCR technique\u003c/h2\u003e \u003cp\u003eViral RNA was extracted from nasopharyngeal and oropharyngeal samples using the mini kit QIAamp Viral RNA (Qiagen, Hilden, Germany) according to the instructions of maker. A real-time PCR targeting the ORF_1ab and N genes of SARS-CoV-2 has \u003csub\u003ebeen\u003c/sub\u003e carried out using a specific PCR kit (SANSURE Biotech Kit, Changsha, Republic Popular of China) according to the manufacturer's protocol using the 7500 Fast Dx RealTime PCR (Applied Biosystems, Waltham, MA, USA). The technical procedures of this equipment is attached to this document.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eGeneXpert \u0026reg; technique\u003c/h2\u003e \u003cp\u003eThis is a fully automated RT-PCR technique consisting of analyzing 300 \u0026micro;l of liquefied sample and included in a specific cartridge. The test is negative if no fluorescence is not detected after 40 cycles. Internal and external controls included in the cartridge allows the manipulation to be validated (See detailed procedure in the appendices).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eSequencing Sample selection and sequencing\u003c/h2\u003e \u003cp\u003eSamples positive for antigen detection and RT-PCR testing (CT value\u0026thinsp;\u0026lt;\u0026thinsp;30) have were preserved for sequencing. Most of the samples were sent to the Institute National Research Institute of Kinshasa (DRC) for whole genome sequencing by Next Generation Sequencing (NGS). But from April 2023, positive samples responding to the selection criteria, are sequenced locally.\u003c/p\u003e \u003cp\u003eNGS sequencing\u003c/p\u003e \u003cp\u003eThe libraries were prepared according to the construction and sequencing protocol of the Illumina COVID-19 ARTIC v3 V.5 library, using the ARTIC preparation kit NEBNext Ultra II DNA library (New England Biolabs Inc., Ipswich, MA, USA). THE libraries were quantified (Qubit DNA BR, Thermo Scientific, Waltham, MA, USA), normalized and pooled, and sequencing was performed using an Illumina MiSeq 100 (Illumina, San Diego, CA, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eAssembly\u003c/h2\u003e \u003cp\u003eThe quality of raw reads was checked using the FastQC tool with parameters by default. The playback quality has been improved by trimming the playback using the software fastp, version v0.23.4. The cleaned reads were assembled by mapping guided by reference using the Wuhan-1 reference sequence (accession ID: MN908947) and bowtie2 with default settings. A consensus sequence for the SARS-CoV-2 genome from each sample was obtained using the samtools/bcftool pipeline and then refined by Pilon software, version 1.19. The sequences were annotated by searching for frames of open readings (ORFs) potentially encoding SARS-CoV-2 viral proteins, as annotated in the Uniprot database. Due to the low quality of the regions assembled, ORFs displaying\u0026thinsp;\u0026gt;\u0026thinsp;50% coverage were retained.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePhylogenetic analyzes and identification of variants/lineages\u003c/h2\u003e \u003cp\u003eAlignments including low coverage CAR sequences generated for this study as well as CAR and Africa sequences extracted from GISAID and a set of sequences from reference representing all major variants of concern (VoC) in the database GISAID were built using MAFFT v7. A Neighbor Joining Phylogenetic Tree (NJ) CAR genomes was constructed using the MEGA X software, using a model of distance p and applying a pairwise deletion option. A phylogenetic tree maximum likelihood (ML) of African genomes was inferred using the software FastTree, version 2.1.11, which allows the calculation of approximate ML trees for very large alignments, by applying a generalized time-reversible (GTR) model of nucleotides evolution and CAT approximation for different rates of evolution from one site to another.\u003c/p\u003e \u003cp\u003eLocal support values were calculated with the Shimodaira\u0026ndash;Hasegawa test. Trees were visualized and analyzed using FigTree v.1.4.4. For the identification of variants and mutation annotation, sequences were analyzed using Nextclade.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eData analyzes\u003c/h2\u003e \u003cp\u003eData collection sheets provided by the national coordination of the fight against Covid-19 were used to collect sociodemographic, clinical, biological parameters, including including virological of patients. This data was then entered and analyzed using the epi-info software version 7.2.3.0. The Chi test2Pearson's test and Fisher's exact test were used for categorical variables, with a 95% confidence interval. The differences were considered statistically significant for a p value less than 0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eOperational definition of waves:\u003c/h2\u003e \u003cp\u003eThe waves correspond to a period of massive, exponential contamination that can be accompanied by a sudden increase in serious cases to the point of exceeding the capacities of healthcare structures as well as high mortality. In the laboratory, wave periods occur result in a high rate of positivity increasing gradually until reaching a peak of positivity of RT-PCR tests before decreasing.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic characteristics of patients\u003c/h2\u003e \u003cp\u003eTable I reports the sociodemographic characteristics of the patients, the correlations with RT-PCR test results as well as evolving pandemic trends.\u003c/p\u003e \u003cp\u003eThe average age of the patients was 39.97\u0026thinsp;\u0026plusmn;\u0026thinsp;13.90 with extreme ages ranging from 6 months to 92 years. The M/F sex ratio was 2.16. RT-PCR test positivity varied by state clinic of patients, their gender and the pandemic evolution (Table I).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable I: RT-PCR correlation and sociodemographic characteristics of patients\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSettings\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eResult\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePositive\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eNagative\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMean age (years\u0026thinsp;\u0026plusmn;\u0026thinsp;DS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.84\u0026thinsp;\u0026plusmn;\u0026thinsp;13.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.10 \u0026plusmn; 13.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39,97 \u0026plusmn;13.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian age (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40,00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge in category (ans)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u0026ndash;11 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e234\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;20 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7132\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u0026ndash;40 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39850\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44853\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e41\u0026ndash;60 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e08.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e91.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e61\u0026ndash;80 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e09.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6407\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e81 years old and over et +\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19,59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e194\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97864\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e4.481\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e09.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e67825\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e89.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30039\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex Ratio M/F\u0026thinsp;=\u0026thinsp;2,26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e09.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97864\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePatients\u0026rsquo;condition\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0,001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSymptomatic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e83.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8983\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsymptomatic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80628\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88881\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e90.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97864\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYear 2020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11164\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3440\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e81.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4242\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex Ratio M/F\u0026thinsp;=\u0026thinsp;2,63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15406\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYear 2021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2585\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24137\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11559\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex Ratio M/F\u0026thinsp;=\u0026thinsp;2,07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e87.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35696\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYear 2022\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26743\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28259\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12225\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSexe Ratio M/F\u0026thinsp;=\u0026thinsp;2,31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e94.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40484\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYear 2023\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e98.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4265\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex Ratio M/F\u0026thinsp;=\u0026thinsp;2,12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTOTAL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e99.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6278\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;Probability. For a value of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05, a difference is considered statistically significant.\u003c/p\u003e \u003cp\u003eThe majority of recruits were male (69%). Women represented 31% of the study population (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePandemic evolution and positivity rate of RT-PCR tests\u003c/p\u003e \u003cp\u003eThe number of RT-PCR tests carried out increased from 2020 to 2022 before decreasing in 2023.\u003c/p\u003e \u003cp\u003eThe prevalence of SARS-CoV-2 infection for its part, was 24.43% in 2020, 14.26% in 2021, 5.8% in 2022 and 0.9% in 2023 (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows a curve infection trends with a peak in the number of cases in 2021 and a trend decreasing since 2022.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eThe succession of waves recorded over the years\u003c/h2\u003e \u003cp\u003eOver 3 years of pandemic evolution, 6 waves have been recorded. First the first between April and August 2020, then the second between March and June 2021. The third wave broke out between November 2021 and February 2022. The fourth and the fifth wave were recorded between may and july and between September and November 2022. Finally, the sixth wave lasted from January to March 2023 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003efrom 2020 to 2023\u003c/h2\u003e \u003cp\u003eThe observed mutations are grouped into clades: B.1.640.1, AY.33, AY.122, BA.1.1, BA.2, XBB.1, AY.4, B.1.1, B.1.617.2, BA. 5.1, BA.5.2.6, BE.1.1.1, BQ.1.1, BQ.1.1.1, BQ.1, B.1.620, AY.3, AY.12, BA.5, BA.5.2, BA. 4.1.8, XBB.1.17.1, BQ.1.2.2. A total of 23 different clades identified have been divided according to their size in a bar diagram as presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. We note a predominance of the B.1.620 variant, followed by the two Omicron sub-variants represented by B. 1.640.1 and BQ.1.1.1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA total of 131 sequences with nucleotide coverage greater than or equal to 80% were the subject of this analysis representation between 2021 and 2023(Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFrom the sequences determined in our samples, we established a phylogenetic tree of SARS-COV-2 variants and sub-variants. It shows the evolution of mutations originating from infacted hosts depending on the proximity or distance between the strains of the SARS-CoV-2 virus resulting from the COVID-19 pandemic. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e is the phylogenetic tree of the 23 representative clades, it presents these aspects, in red the Boostrap value indicates the connections and distances between the mutations and the original sequence which circulated during our study period (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eLa Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e represents the phylodynamics of variants circulating in the Central African territory from South-East Asia and South-West Europe during this study period. This figure comes from the online software Nextsrain.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of Covid-19\u003c/h2\u003e \u003cp\u003eThe prevalence of SARS-CoV-2 infection was 9.9% but much higher (24.43%) in 2020 than in 2023 (0.9%). Trend confirmed by Lango-Yaya et al who reported a prevalence of 24.71% in CAR in 2020[12]. Fairly similar prevalences are reported in the sub-region almost during the same period. Let us remember that the history of the evolution of the pandemic in the Central African Republic was marked by the period before the introduction of the vaccine and that following the vaccination campaign. The last one has corresponded to a reduction in the number of contaminations[6].\u003c/p\u003e \u003cp\u003eNote also that the increase in the number of RT-PCR tests rhymes with the decrease in prevalence for two reasons. First, mass screenings extend to people free of the disease who take steps to preserve their negativity RT-PCR tests, especially for travel purposes[13]. In addition, an increase in capacity screening helps to quickly identify trends and readjust the response with the aim of to stem the pandemic by cutting the chain of transmission. Let us recognize that as such, the RCA, short of RT-PCR tests, had temporarily opted for selective screening of patients symptomatic. This strategy, although economical, had contributed to an increase in contaminations shortly after the detection of the first case on March 14, 2020[6]. But with the support of partners including the African Union, the number of tests carried out has been significantly improved.\u003c/p\u003e \u003cp\u003eThose over 80 and those under 20 were the most affected, followed by people aged 20\u0026ndash;40 years old. The latter correspond to the active age group who travel a lot more frequently for professional, academic or family reasons. What exposes them at risk of contracting Covid-19. The studies carried out in CAR by Lango-Yaya, Manirakiza and Rafa\u0026iuml; corroborate these trends[6],[9],[12]. Other studies carried out in the sub-region report a high prevalence in the active population[14],[15].\u003c/p\u003e \u003cp\u003eIn addition, the vulnerability of the elderly has already been reported by MASSAMBA in Senegal and WANG in China[16],[17]. These elderly people who produce insufficiently neutralizing antibodies, also carry numerous comorbidities that can expose to serious forms of Covid-19 as well as high mortality[18].\u003c/p\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eSex\u003c/h2\u003e \u003cp\u003ePositive RT-PCR tests were associated with male gender (sex ratio M/F\u0026thinsp;=\u0026thinsp;2.26), especially before the introduction of the vaccine in CAR in May 2021 (p\u0026thinsp;=\u0026thinsp;0.001). The male predisposition to\u003c/p\u003e \u003cp\u003ebeing infected with SARS-CoV-2 is known for hormonal reasons\u003c/p\u003e \u003cp\u003e(androgenic)[16],[18]. But with vaccination and immunity acquired after infection over Over the years, trends have changed, alternating between the two sexes[19].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eClinical manifestations\u003c/h2\u003e \u003cp\u003eThe presence of symptoms not only increases the positivity of RT-PCR tests but also that of antigenic tests used on the front line in countries with low RT-PCR testing capacities, such as the CAR which, at a certain point in managing the pandemic reserved RT-PCR for symptomatic patients or even serious cases. Similar trends are reported by Ntagereka in the DRC and by Tegally in a study continental[8],[20].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eThe succession of waves\u003c/h2\u003e \u003cp\u003eThe CAR experienced 6 waves, the most devastating of which was the second between March and June 2021.\u003c/p\u003e \u003cp\u003eThe devastation of the second wave was reported by FOKAM in Cameroon, Ntagereka in DRC and Manirakiza in CAR[9,20,21]. It must be recognized that this phase of evolution pandemic corresponds to an evolving trend of variants having undermined strategies initial responses focused on non-vaccination prevention.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003eThe variant landscape\u003c/h2\u003e \u003cp\u003eChina's ancestral Wuhan strain gradually replaced by viruses\u003c/p\u003e \u003cp\u003ehaving acquired more power of transmission and replication, mainly thanks to\u003c/p\u003e \u003cp\u003eD614G and N501Y mutations which increase the affinity of the spike with the binding domain with ACE, P681H mutations in the furin cleavage domain and responsible for immune escape[21].\u003c/p\u003e \u003cp\u003eWe detected 10 variants of interest and a few of concern.\u003c/p\u003e \u003cp\u003eThe B.1.1.7 or British variants raged during the second wave while the B.1.620 and the\u003c/p\u003e \u003cp\u003eB.1.624 dominated the landscape in 2021 before being replaced by the Delta variant. Since the fourth wave, the Omicron variant appeared and established itself as the only variant circulating for two years[6,10].\u003c/p\u003e \u003cp\u003eThese landscapes are confirmed by Fokam in Cameroon, Vickos and Rafa\u0026iuml; in Central African Republic[6,10,21]. Africa, which was first confronted with cases of importation into start of the pandemic finally saw the emergence of variants of interest, two of which detected on the continent thanks to an expansion of genomic surveillance. This is the variant beta discovered for the first time in a patient from Botswana and the variant Omicron, the first case of which was detected in South Africa. The Central African region has been impacted by the B 1.620 and B1.640 variants [6,10,21]. The first was sequenced for first time in a sample from the Central African Republic and the second circulated there throughout 2021[8]. All these emergences remind us of the need to strengthen national capacities in genomic surveillance with the aim of effectively adjusting the response and even to alert the scientific community as in the case of the detection of the variant\u003c/p\u003e \u003cp\u003eB.1.620 made possible by pan-African cooperation. Because the first relative sequences to this variant were detected in samples from the CAR but sequenced in the Democratic Republic of Congo [22].\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis retrospective series, although limited to data from diagnostic test results of laboratory of patients mainly from Bangui, allowed us to better understand to a certain extent the lessons to be learned from the management of the Covid-19 pandemic in the CAR. So, we were able to understand that age, sex and the presence of clinical manifestations were significantly associated with RT-PCR test positivity. We also learned that the CAR went through 6 waves and detected 10 variants including one endemic having circulated during throughout 2021. The persistence of the Omicron variant for almost two years reassures us as for the next waves likely to have very little impact in terms of cases serious and mortality.\u003c/p\u003e \u003cp\u003eAs the world lives with Covid-19, health monitoring and the intensification of the vaccination could be continued. But with genomic surveillance tools, better epidemiological knowledge is launched. Inequalities in access to tools genomic sequencing, far from being inevitable, should be considered as a challenge to raise. Witness, this sub-regional collaboration initiative before the implementation of the genomic surveillance at the national level last spring.\u003c/p\u003e \u003cp\u003eFinally, efforts must be continued to extend sequencing in the provinces of the RCA with the aim of having better information on the genetic diversity of variants and sub-variants in circulation.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical considerations:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study which was part of the national response against Covid-19 was approved by the Institutional Ethical Review Committee of the Ministry of Health and Population of the Central African Republic (CAR). Administrative authorization was obtained from\u0026nbsp;the Minister of Health and Population of the CAR. Voluntary informed consent was obtained from the patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study was carried out in strict compliance with the Declaration of Helsinki according to which no intervention likely to alter the dignity, integrity and right to privacy of participants will be implemented.\u0026nbsp;We also received ethical clearance from the Ethics and Scientific Committee of the Faculty of Sciences of Health (N32/FACSS/CES.2020).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations\u003c/strong\u003e: not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the manuscript before publication.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from Public Health Ministry of Central African Republic but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of Public Health Minister.\u003c/p\u003e\n\u003cp\u003eData on GISAID can however be consulted if necessary\u003cstrong\u003e(\u003cstrong\u003ehttps://www.epicov.org/epi3/frontend#5aa6aa\u003c/strong\u003e\u003c/a\u003e\u003cstrong\u003e).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContribution of the authors:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProject design: CDR, ELY, MRDB, PS, MMS, BK, JBR\u003c/p\u003e\n\u003cp\u003eLaboratory techniques: CDR, ELY, SN\u003c/p\u003e\n\u003cp\u003eData analyses: AAOFTG, JAB, OS\u003c/p\u003e\n\u003cp\u003eAll authors acknowledge having read the manuscript\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRecruitment Consent of publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll patients recruited consent and acknowledge having voluntarily participated in\u003c/p\u003e\n\u003cp\u003ethe investigation carried out within the framework of public health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThanks :\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the entire technical team of the National Laboratory of Clinical Biology and Public health. We also thank the World Health Organization as well as Africa CDC for logistical support.\u003c/p\u003e\n\u003cp\u003eFinally, we thank the INRB Kinshasa and GISAID team who made it possible certain genomic and bioinformatics analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest :\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e Segondy M. Dossier scientifique Les coronavirus humains. In: RFL Revue francophone des laboratories [Internet]. Elsevier; 2020. p. 32\u0026ndash;9. Available from: http://dx.doi.org/10.1016/S1773-035X(20)30311-7\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Tang G, Liu Z, Chen D. Human coronaviruses: Origin, host and receptor. J Clin Virol [Internet]. 2022;155(February):105246. Available from: https://doi.org/10.1016/j.jcv.2022.105246\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Kin N, Vabret A. Les infections \u0026agrave; coronavirus humains. RFL Rev Francoph des Lab [Internet]. 2016;2016(487):25\u0026ndash;33. Available from: http://dx.doi.org/10.1016/S1773-035X(16)30369-0\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Hantz S. Diagnostic biologique de l\u0026rsquo;infection \u0026agrave; Sars-CoV-2 : strat\u0026eacute;gies et interpr\u0026eacute;tation des r\u0026eacute;sultats. Rev Francoph des Lab [Internet]. 2020;2020(526):48\u0026ndash;56. Available from: http://dx.doi.org/10.1016/S1773-035X(20)30313-0\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Surveillance I. COVID-19 Epidemiological Update. 2023;(November):6\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Rafa\u0026iuml; CD, Pierre S, Nambei SW, Lango-yaya E, Belizaire MRD, Ulrich V, et al. Impact of a mass campaign on the evolution of the fourth wave of the Covid-19 pandemic in the Central African Republic. J Virol. 2023;\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Elie B, Alizon S. Analyses g\u0026eacute;nomiques et phylodynamiques du Sars-CoV-2. Rev Francoph des Lab [Internet]. 2020;2020(526):57\u0026ndash;62. Available from: http://dx.doi.org/10.1016/S1773-035X(20)30314-2\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Tegally H, San JE, Cotten M, Moir M, Tegomoh B, Mboowa G, et al. The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance. Science (80- ). 2022 Oct 7;378(6615).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Manirakiza A, Malaka C, Yambiyo BM, Diemer HS-C, Longo J de D, Namsene\u0026iuml; J, et al. Very High Relative Seroprevalence of Anti\u0026ndash;SARS-CoV-2 Antibodies Among Communities in Bangui, Central African Republic. SSRN Electron J. 2021;1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Vickos U, Camasta M, Grandi N, Scognamiglio S, Schindler T, Roseline M, et al. COVID-19 Genomic Surveillance in Bangui ( Central African Republic ) Reveals a Landscape of Circulating Variants Linked to Validated Antiviral Targets of SARS-CoV-2 Proteome. Viruses. 2023;15(2309).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Rafa\u0026iuml; CD, Heredeibona LS, Lango-Yaya E, Belizaire RD, Senzongo O, Mbala P, et al. Five successive waves of SARS-CoV-2 infection in the Central African Republic : a prospective observational study from 2020-. Pan Afr Med J. 2023;46(120):1\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Lango-Yaya E, B\u0026eacute;ni RD, N\u0026rsquo;yetobouko S, Koyaweda WG, Rafa\u0026iuml; CD. Epidemiological and profile of Covid-19 at the National Laboratory of Clinical Biology and Public Health of Bangui, Central African Republic: cross-Sectionnal Study from April to July 2020. Glob Sci Journals. 2020;8(11):581\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Poll\u0026aacute;n M, P\u0026eacute;rez-g\u0026oacute;mez B, Pastor-barriuso R, Oteo J, Hern\u0026aacute;n MA, P\u0026eacute;rez-olmeda M, et al. Articles Prevalence of SARS-CoV-2 in Spain ( ENE-COVID ): a nationwide, population-based seroepidemiological study. 2020;6736(20):1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Salem F Ben, Hannachi H, Kalai W, Themlaoui A, Frioui D, Jendoubi N, et al. Profil pidmiologique et clinique de la COVID-19 chez le personnel de sant de lHpital Aziza Othmana, Tunis, Tunisie. Ann fran\u0026ccedil;aises d\u0026#146;oto-rhino-laryngologie Pathol cervico-faciale [Internet]. 2023;101818. Available from: https://doi.org/10.1016/j.admp.2023.101818\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Iroungou BA, Moussavou PB, Elguero E, Makran J, Bivigou-Mboumba B, Wora E, et al. Trend of expansion of SARS-CoV-2 infection and COVID-19 burden in Gabon (Central Africa) in mid-2021, based on a serological survey. IJID Reg. 2022;5(July):13\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Massamba B, Assane S, Rokhaya D, Dalahata B, Mamadou C. Infection \u0026agrave; Covid-19 en g\u0026eacute;riatrie au S\u0026eacute;n\u0026eacute;gal. NPG Neurol - Psychiatr - G\u0026eacute;riatrie. 2023;(xxxx).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Li K, Wang D, Qu H, Rui J, Abudunaibi B, Guo Z, et al. Viral Dynamics of Omicron BA.2.76 Variant of SARS-CoV-2 in a Cohort of COVID-19 Patients. J Infect [Internet]. 2022;(xxxx):2021\u0026ndash;3. Available from: http://www.ncbi.nlm.nih.gov/pubmed/36470410\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Birato C, Busingo M, Barinjibanjwa N, Bertin B, Muzaliya K, Katabana M, et al. ScienceDirect rielle sur le pro fi l clinique et le pronostic In fl uence de l \u0026rsquo; hypertension art e s pour COVID-19 dans la ville de Bukavu, en des patients hospitalis e publique D e mocratique du Congo : e tude de cohorte prospective R e In fl uence of. 2023;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Mohamed MS, Moulin TC, Schi\u0026ouml;th HB. Sex differences in COVID-19: the role of androgens in disease severity and progression. Endocrine [Internet]. 2021;71(1):3\u0026ndash;8. Available from: http://dx.doi.org/10.1007/s12020-020-02536-6\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e World Health Organization. Statement for healthcare professionals _ Regulation of the safety and effectiveness of COVID-19 vaccines. June 16, 2021; https://www.who.int/en/news/item/11-06-2021. Accessed June 23, 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Ntagereka PB, Oyola SO, Baenyi SP, Rono GK, Birindwa AB, Shukuru DW, et al. Whole-genome sequencing of SARS-CoV-2 reveals diverse mutations in circulating Alpha and Delta variants during the first, second, and third waves of COVID-19 in South Kivu, east of the Democratic Republic of the Congo. Int J Infect Dis. 2022;122(December 2019):136\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Fokam J, Essomba RG, Njouom R, Okomo MCA, Eyangoh S, Godwe C, et al. Genomic surveillance of SARS-CoV-2 reveals highest severity and mortality of delta over other variants: evidence from Cameroon. Sci Rep. 2023;13(1):1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Lina B. The different phases of molecular and antigenic evolution of SARS-CoV-2 viruses during the 20 months following its emergence. Bull Acad Natl Med. 2022;206(1):87\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Dudas G, Hong SL, Potter BI, Calvignac-Spencer S, Niatou-Singa FS, Tombolomako TB, et al. Emergence and spread of SARS-CoV-2 lineage B.1.620 with variant of concern-like mutations and deletions. Nat Commun. 2021;12(1):1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"SARS-CoV-2, Variants, Central African Republic, RT-PCR","lastPublishedDoi":"10.21203/rs.3.rs-3832420/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3832420/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eThe Covid-19 pandemic has highlighted the need to strengthen diagnosis and genomic surveillance capacities. The Central African Republic was able to manage 5 waves during health monitoring and integrated genomic surveillance as a surveillance tool in 2021.\u003c/p\u003e\n\u003cp\u003eThe aim of this study is to report surveillance data from the National Laboratory of Clinical\u003c/p\u003e\n\u003cp\u003eBiology and Public Health and describe the landscape of circulation of SARS-CoV-2 variants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and methods: \u003c/strong\u003eThis is a retrospective, descriptive observational study over a period of 3 years (ranging from April 2020 to November 2023) carried out on a population of consenting volunteers, from throughout the CAR, tested by RT -PCR on nasopharyngeal samples with sufficient information in the LNBCSP databases. Sequencing is largely carried out at the INRB in KINSHASA and from May 2023 at the LNBCSP.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults and discussion:\u003c/strong\u003e Out of 97,864 RT-PCR tests carried out, 9,764 came back positive, which corresponds to a prevalence of 9.98%. The average age of the patients was 39.97 years ± 13.76 and the sex ratio M/F was 2.12. The positivity of RT-PCR tests was significantly associated with age (p=0.001), sex (p=0.013) and clinical manifestations. Ten variants circulated during the 5 waves recorded. The landscape of circulating variants was dominated by the Omicron (B.1.1.529), Delta (B.1.617.2) variants and especially by B.1.620 and B.640 which marked the second wave in CAR.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThis retrospective series provides key information for understanding the history of the Covid-19 pandemic in the CAR. Risk factors are identified and the variant circulation landscape described. Strengthening national genomic surveillance capacities would help the country adopt a better response against this pandemic.\u003c/p\u003e","manuscriptTitle":"Contribution of genomic surveillance in the detection and monitoring of SARS variants- CoV-2 during the 6 pandemic waves in the Central African Republic from 2020 to 2023","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-22 08:00:02","doi":"10.21203/rs.3.rs-3832420/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"32c145bf-8025-49f0-a5eb-7d97e0b1d62a","owner":[],"postedDate":"January 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":28270217,"name":"Biological sciences/Microbiology"},{"id":28270218,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2024-05-02T05:10:45+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-22 08:00:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3832420","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3832420","identity":"rs-3832420","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}