Global Initiative On Sharing All Influenza Data Research Articles

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in the Middle East and North Africa: Longitudinal Trend Analysis.

This study updates the COVID-19 pandemic surveillance in the Middle East and North Africa (MENA) we first conducted in 2020 with 2 additional years of data for the region. The objective of this study is to determine whether the MENA region meets the criteria for moving from a pandemic to endemic. In doing so, this study considers pandemic trends, dynamic and genomic surveillance methods, and region-specific historical context for the pandemic. These considerations continue through the World Health Organization (WHO) declaration of the end of the public health emergency for the COVID-19 pandemic on May 5, 2023. In addition to updates to traditional surveillance data and dynamic panel estimates from the original study by Post et al, this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a 1-sided t test to determine whether regional weekly speed of COVID-19 spread was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data from September 4, 2020, to May 12, 2023. The speed of COVID-19 spread for the region had remained below the outbreak threshold for 7 continuous months by the time of the WHO declaration. Acceleration and jerk were also low and stable. Although the 1- and 7-day persistence coefficients remained statistically significant and positive, the weekly shift parameters suggested the coefficients had most recently turned negative, meaning the clustering effect of new COVID-19 cases became even smaller in the 2 weeks around the WHO declaration. From December 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t test of the speed of spread equal to 10 became entirely insignificant from October 2022 onward. The COVID-19 pandemic had far-reaching effects on MENA, impacting health care systems, economies, and social well-being. Although COVID-19 continues to circulate in the MENA region, the rate of transmission remained well below the threshold of an outbreak for over 1 year ahead of the WHO declaration. COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. Both standard and enhanced surveillance metrics confirm that the pandemic had transitioned to endemic by the time of the WHO declaration.

Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Latin America and the Caribbean: Longitudinal Trend Analysis.

In May 2020, the World Health Organization (WHO) declared Latin America and the Caribbean (LAC) the epicenter of the COVID-19 pandemic, with over 40% of worldwide COVID-19-related deaths at the time. This high disease burden was a result of the unique circumstances in LAC. This study aimed to (1) measure whether the pandemic was expanding or contracting in LAC when the WHO declared the end of COVID-19 as a public health emergency of international concern on May 5, 2023; (2) use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history; and (3) provide, with a focus on prevention policies, a historical context for the course of the pandemic in the region. In addition to updates of traditional surveillance data and dynamic panel estimates from the original study, we used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern (VOCs). We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Additionally, we conducted a 1-sided t test for whether the regional weekly speed (rate of novel COVID-19 transmission) was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data across the period from August 2020 to May 2023. The speed of pandemic spread for the region had remained below the outbreak threshold for 6 months by the time of the WHO declaration. Acceleration and jerk were also low and stable. Although the 1- and 7-day persistence coefficients remained statistically significant for the 120-day period ending on the week of May 5, 2023, the coefficients were relatively modest in magnitude (0.457 and 0.491, respectively). Furthermore, the shift parameters for either of the 2 most recent weeks around May 5, 2023, did not indicate any change in this clustering effect of cases on future cases. From December 2021 onward, Omicron was the predominant VOC in sequenced viral samples. The rolling t test of speed=10 became entirely insignificant from January 2023 onward. Although COVID-19 continues to circulate in LAC, surveillance data suggest COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. However, the region experienced a high COVID-19 burden in the early stages of the pandemic, and prevention policies should be an immediate focus in future pandemics. Ahead of vaccination development, these policies can include widespread testing of individuals and an epidemiological task force with a contact-tracing system.

Molnupiravir increases SARS-CoV-2 genome diversity and complexity: A case-control cohort study.

Molnupiravir, an oral direct-acting antiviral effective in vitro against SARS-CoV-2, has been largely employed during the COVID-19 pandemic, since December 2021. After marketing and widespread usage, a progressive increase in SARS-CoV-2 lineages characterized by a higher transition/transversion ratio, a characteristic signature of molnupiravir action, appeared in the Global Initiative on Sharing All Influenza Data(GISAID) and International Nucleotide Sequence Database Collaboration(INSDC) databases. Here, we assessed the drug effects by SARS-CoV-2 whole-genome sequencing on 38 molnupiravir-treated persistently positive COVID-19 outpatients tested before and after treatment. Seventeen tixagevimab/cilgavimab-treated outpatients served as controls. Mutational analyses confirmed that SARS-CoV-2 exhibits an increased transition/transversion ratio seven days after initiation of molnupiravir. Moreover we observed an increased G->A ratio compared to controls, which was not related to apolipoprotein B mRNAediting enzyme, catalytic polypeptide-like (APOBEC) activity. In addition, we demonstrated for the first time an increased diversity and complexity of the viral quasispecies.

The global impact of SARS-CoV-2 variant BA.2.86: a comprehensive analysis with the latest developments and transmission trends - an epidemiological study.

The variant BA.2.86 of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is causing concern globally. The virus contains a large number of mutations, and transmission trends are rapidly changing globally. This study investigates the global epidemiological and transmission trends of SARS-CoV-2 new variant BA.2.86 in various continents and countries. The data were recorded using key terms, including SARS-CoV-2, Omicron, BA.2.86, epidemiology, occurrence, incidence, prevalence, and transmission trends. The data on SARS-CoV-2 variant BA.2.86 were searched by the World Health Organization (WHO), Centers for Disease Control and Prevention (CDC), the Global Initiative on Sharing All Influenza Data (GSIAD), PubMed, and Web of Science. Initially, 40 documents were identified, and finally, 8 documents were included for the data analysis and discussion. The analysis of findings on transmission trends was based on the data from August 14, 2023, to February 28, 2024. The SARS-CoV-2, novel variant BA.2.86, crossed the international borders of 6 continents and 89 countries and infected 19,532 people. In Europe, 32 countries are affected and involved 12,667 people (64.85%), North and South America 18 countries with 3,515 cases (17.99%), Asia 27 countries with 2,063 people (10.56%), Oceania 2 countries with 689 cases (3.52%), and Africa 10 countries with 598 (3.06%) cases. The BA.2.86 rapidly spread and mainly affected the people in the United Kingdom 3,228 (16.52%), Sweden 2,380 (12.18%), USA 1,929 (9.87%), Denmark 1,621 (8.29%), Canada 1,516 (7.67%), France 833 (4.26%), Japan 810 (4.14%), Netherlands 725 (3.71%), Germany 681 (3.48%), Spain 665 (3.40%), South Korea 556 (2.84%), and Australia 512 (2.62%). The SARS-CoV-2, novel variant BA.2.86, spread over six continents and 89 countries and affected 19,532 people worldwide. The disease is more prevalent in the United Kingdom, United States of America, and European countries. The detection of the disease in multiple continents and countries suggests some degree of transmissibility. Global health authorities need to rethink their policies and implement strict strategies to eradicate emerging variants and minimize the global disease burden.

Prediction of the effects of the top 10 synonymous mutations from 26645 SARS-CoV-2 genomes

Background The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had led to a global pandemic since December 2019. SARS-CoV-2 is a single-stranded RNA virus, which mutates at a higher rate. Multiple works had been done to study nonsynonymous mutations, which change protein sequences. However, there is little study on the effects of SARS-CoV-2 synonymous mutations, which may affect viral fitness. This study aims to predict the effect of synonymous mutations on the SARS-CoV-2 genome. Methods A total of 26645 SARS-CoV-2 genomic sequences retrieved from Global Initiative on Sharing all Influenza Data (GISAID) database were aligned using MAFFT. Then, the mutations and their respective frequency were identified. Multiple RNA secondary structures prediction tools, namely RNAfold, IPknot++ and MXfold2 were applied to predict the effect of the mutations on RNA secondary structure and their base pair probabilities was estimated using MutaRNA. Relative synonymous codon usage (RSCU) analysis was also performed to measure the codon usage bias (CUB) of SARS-CoV-2. Results A total of 150 synonymous mutations were identified. The synonymous mutation identified with the highest frequency is C3037U mutation in the nsp3 of ORF1a. Of these top 10 highest frequency synonymous mutations, C913U, C3037U, U16176C and C18877U mutants show pronounced changes between wild type and mutant in all 3 RNA secondary structure prediction tools, suggesting these mutations may have some biological impact on viral fitness. These four mutations show changes in base pair probabilities. All mutations except U16176C change the codon to a more preferred codon, which may result in higher translation efficiency. Conclusion Synonymous mutations in SARS-CoV-2 genome may affect RNA secondary structure, changing base pair probabilities and possibly resulting in a higher translation rate. However, lab experiments are required to validate the results obtained from prediction analysis.

Avian H6 Influenza Viruses in Vietnamese Live Bird Markets during 2018-2021.

Avian influenza viruses of the H6 subtype are prevalent in wild ducks and likely play an important role in the ecology of influenza viruses through reassortment with other avian influenza viruses. Yet, only 152 Vietnamese H6 virus sequences were available in GISAID (Global Initiative on Sharing All Influenza Data) prior to this study with the most recent sequences being from 2018. Through surveillance in Vietnamese live bird markets from 2018 to 2021, we identified 287 samples containing one or several H6 viruses and other influenza A virus subtypes, demonstrating a high rate of co-infections among birds in Vietnamese live bird markets. For the 132 H6 samples with unique influenza virus sequences, we conducted phylogenetic and genetic analyses. Most of the H6 viruses were similar to each other and closely related to other H6 viruses; however, signs of reassortment with other avian influenza viruses were evident. At the genetic level, the Vietnamese H6 viruses characterized in our study encode a single basic amino acid at the HA cleavage site, consistent with low pathogenicity in poultry. The Vietnamese H6 viruses analyzed here possess an amino acid motif in HA that confers binding to both avian- and human-type receptors on host cells, consistent with their ability to infect mammals. The frequent detection of H6 viruses in Vietnamese live bird markets, the high rate of co-infections of birds with different influenza viruses, and the dual receptor-binding specificity of these viruses warrant their close monitoring for potential infection and spread among mammals.

Monitoring SARS-CoV-2 genetic variability: A post-market surveillance workflow for combined bioinformatic and laboratory evaluation of commercial RT-PCR assay performance.

The speed at which Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is mutating has made it necessary to frequently assess how these genomic changes impact the performance of diagnostic real-time polymerase chain reaction (RT-PCR) assays. Herein, we describe a generic three-step workflow to assess the effect of genomic mutations on inclusivity and sensitivity of RT-PCR assays. Sequences collected from the Global Initiative on Sharing All Influenza Data (GISAID) were mapped to a SARS-CoV-2 reference genome to evaluate the position and prevalence of mismatches in the oligonucleotide-binding sites of the QIAstat-Dx, an RT-PCR panel designed to detect SARS-CoV-2. The frequency of mutations and their impact on melting temperature were assessed, and sequences flagged by risk-based criteria were examined in vitro. Out of 8,900,393 SARS-CoV-2 genome sequences analyzed, only 173 (0.0019%) genomes contained potentially critical mutations for the QIAstat-Dx; follow-up in-vitro testing confirmed no impact on the assays' performance. The current study demonstrates that SARS-CoV-2 genetic variants do not affect the performance of the QIAstat-Dx device. It is recommended that manufacturers incorporate this workflow into obligatory post-marketing surveillance activities, as this approach could potentially enhance genetic monitoring of their product.

A simple method for estimating time-irreversible nucleotide substitution rates in the SARS-CoV-2 genome

Abstract SARS-CoV-2 is the cause of the current worldwide pandemic of severe acute respiratory syndrome. The change of nucleotide composition of the SARS-CoV-2 genome is crucial for understanding the spread and transmission dynamics of the virus because viral nucleotide sequences are essential in identifying viral strains. Recent studies have shown that cytosine (C) to uracil (U) substitutions are overrepresented in SARS-CoV-2 genome sequences. These asymmetric substitutions between C and U indicate that traditional time-reversible substitution models cannot be applied to the evolution of SARS-CoV-2 sequences. Thus, we develop a new time-irreversible model of nucleotide substitutions to estimate the substitution rates in SARS-CoV-2 genomes. We investigated the number of nucleotide substitutions among the 7862 genomic sequences of SARS-CoV-2 registered in the Global Initiative on Sharing All Influenza Data (GISAID) that have been sampled from all over the world. Using the new method, the substitution rates in SARS-CoV-2 genomes were estimated. The C-to-U substitution rates of SARS-CoV-2 were estimated to be 1.95 × 10−3 ± 4.88 × 10−4 per site per year, compared with 1.48 × 10−4 ± 7.42 × 10−5 per site per year for all other types of substitutions.

Genomic Epidemiology of Severe Acute Respiratory Syndrome Coronavirus 2 in a County Jail.

In the coronavirus disease 2019 (COVID-19) pandemic, correctional facilities are potential hotspots for transmission. We examined the genomic epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) early in the pandemic in one of the country's largest urban jails. Existing SARS-CoV-2 isolates from 131 detainees at the Cook County Jail in Chicago, Illinois, from March 2020 through May 2020 were analyzed by whole-genome sequencing. Contemporaneous isolates from Rush University Medical Center (Chicago, Illinois) and the Global Initiative on Sharing All Influenza Data (GISAID) were used to identify genetic clusters containing only jail isolates. Transmission windows were identified for each pair of detainees using the date of the SARS-CoV-2-positive test and location data to determine if detainees overlapped in the jail, within a specific building, or within particular living units during transmission windows. We identified 29 jail-only clusters that contained 75 of the 132 SARS-CoV-2 isolates from detainees; of these clusters, 17 (58.6%) had individuals who overlapped in the jail during putative transmission windows. Focusing on specific buildings revealed that 2 buildings, a single- and double-cell style of housing. were associated with having detainees infected with similar SARS-CoV-2 genomes during their infectious time period (P < .001). Our findings suggest that there was transmission of SARS-CoV-2 in the jail, in the setting of extensive importation of COVID-19 from the community. Numerous infection control practices at intake and during incarceration were implemented in the jail to limit viral spread. Our study shows the importance of genomic analysis in this type of settings and how it can be utilized within infection control protocols.

Anomaly Detection Models for SARS-CoV-2 Surveillance Based on Genome k-mers.

Since COVID-19 has brought great challenges to global public health governance, developing methods that track the evolution of the virus over the course of an epidemic or pandemic is useful for public health. This paper uses anomaly detection models to analyze SARS-CoV-2 virus genome k-mers to predict possible new critical variants in the collected samples. We used the sample data from Argentina, China and Portugal obtained from the Global Initiative on Sharing All Influenza Data (GISAID) to conduct multiple rounds of evaluation on several anomaly detection models, to verify the feasibility of this virus early warning and surveillance idea and find appropriate anomaly detection models for actual epidemic surveillance. Through multiple rounds of model testing, we found that the LUNAR (learnable unified neighborhood-based anomaly ranking) and LUNAR+LUNAR stacking model performed well in new critical variants detection. The results of simulated dynamic detection validate the feasibility of this approach, which can help efficiently monitor samples in local areas.

Influenza or Immunodeficiency — How did the Categorical Rationale go Wrong?

Albeit it was not fully understood when we were caught off-guard with the first-known outbreak of Severe Acute Respiratory Syndrome (SARS) in 2002 in Guangzhou, People’s Republic of China (PRC), the structural similarity of its Spike 2 (S2) protein to human immunodeficiency virus type 1 (HIV-1) was confirmed two years later [1]. The almost-a-decade inaction since its emergence, seen in Figure 1, is not a single-country phenomenon. Even though the reasons are undetermined yet, global institutional under-reporting of the SARS-CoV deaths is statistically characteristic, where all other countries’ reported data happened to coincide with the regression model from the viral geological emergence origin. Subsequently, SARS-CoV was categorized only in the Global Initiative on Sharing All Influenza Data (GISAID) in 2008, and that was the global institutional basis for the rationales in decisions and operations behind the Coronavirus disease 2019 (COVID-19).

Sub-Saharan Africa Surveillance Metrics and History of the COVID-19 Pandemic: Updated Epidemiological Assessment.

This study updates the COVID-19 pandemic surveillance in Sub-Saharan Africa (SSA) we first conducted in 2020 by providing two additional years of data for the region. First, we aim to measure whether there was an expansion or contraction in the pandemic in SSA when the World Health Organization (WHO) declared the end of the public health emergency for the COVID-19 pandemic on May 5, 2023. Second, we use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history. Third, we aim to provide historical context for the course of the pandemic in SSA. In addition to updates of traditional surveillance data and dynamic panel estimates from the original study by Post et al. (2021), this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a one-sided t-test for whether regional weekly speed was greater than an outbreak threshold of ten. We ran the test iteratively with a rolling, six month-window of data across the sample period. Speed for the region remained well below the outbreak threshold before and after the WHO declaration. Acceleration and jerk were also low and stable. The 7-day persistence coefficient remained somewhat large (1.11) and statistically significant. However, both shift parameters for the weeks around the WHO declaration were negative, meaning the clustering effect of new COVID-19 cases had become recently smaller. From November 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t-test of speed equal to ten was insignificant for the entire sample period. While COVID-19 continues to circulate in SSA, the region never reached outbreak status, and the weekly transmission rate had remained below one case per 100,000 population for well over one year ahead of the WHO declaration. COVID-19 is endemic in the region and no longer reaches the threshold of a pandemic definition. Both standard and enhanced surveillance metrics confirm that the pandemic had ended in SSA by the time of the WHO declaration.

Delineating the Structure-Dynamics-Binding Differences among BA.1, BA.4/5, and BF.7 SARS-CoV-2 Variants through Atomistic Simulations: Correlation with Structural and Epidemiological Features.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an RNA virus possessing a spike (S) protein that facilitates the entry of the virus into human cells. The emergence of highly transmissible and fit SARS-CoV-2 variants has been driven by the positive selection of mutations within the S-protein. Notable among these variants are alpha, beta, gamma, delta, and omicron (BA.1), with the latter contributing to significant global health challenges and impacting populations worldwide. Recently, a novel subvariant of BA.1, named BF.7, has surfaced, purportedly exhibiting elevated transmissibility and infectivity rates. In order to comprehend and compare the transmissibility and disease progression characteristics of distinct SARS-CoV-2 variants, we performed an extensive comparative analysis utilizing all-atom molecular dynamics (MD) simulations (in triplicate) to investigate the structural, dynamic, and binding features of BA.1, BA.4/5, and BF.7. Our simulation findings, energetic analysis, and assessment of physicochemical properties collectively illuminate the dominance of the BA.1 variant over the others, a trend that is further substantiated by the sustained global prevalence of BA.1 relative to BA.4/5 and BF.7. Additionally, our simulation results align well with the reported cryoelectron microscopy (cryo-EM) structural data and epidemiological characteristics obtained from the Global Initiative on Sharing All Influenza Data (GISAID). This study presents a comprehensive comparative elucidation of the critical structural, dynamic, and binding attributes of these variants, providing insights into the predominance of BA.1 and its propensity to continuously generate numerous novel subvariants.

South Asia's COVID-19 History and Surveillance: Updated Epidemiological Assessment.

This study updates the COVID-19 pandemic surveillance in South Asia we first conducted in 2020 with two additional years of data for the region. We assess whether COVID-19 had transitioned from pandemic to endemic at the point the World Health Organization (WHO) ended the publication health emergency status for COVID-19 on May 5, 2023. First, we aim to measure whether there was an expansion or contraction in the pandemic in South Asia around the WHO declaration. Second, we use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history. Third, we aim to provide historical context for the course of the pandemic in South Asia. In addition to updates of traditional surveillance data and dynamic panel estimates from the original study Welch et al. (2021), this study used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern. We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Finally, we conducted a one-sided t-test for whether regional weekly speed or transmission rate per 100,000 population was greater than an outbreak threshold of ten. We ran the test iteratively with six months of data across the sample period. Speed for the region remained below the outbreak threshold for over a year by the time of the WHO declaration. Acceleration and jerk were also low and stable. While the 1-day persistence coefficients remained statistically significant and positive (1.168), the 7-day persistence coefficient was negative (-0.185), suggesting limited cluster effects in which cases on a given day predict cases seven days forward. Furthermore, the shift parameters for either of the two most recent weeks around May 5, 2023, did not indicate any overall change in the persistence measure around the time of WHO declaration. From December of 2021 onward, Omicron was the predominant variant of concern in sequenced viral samples. The rolling t-test of speed equal to ten was statistically insignificant across the entire pandemic. While COVID-19 continues to circulate in South Asia, the rate of transmission had remained below the outbreak threshold for well over a year ahead of the WHO declaration. COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. Both standard and enhanced surveillance metrics confirm that the pandemic had ended by the time of the WHO declaration. Prevention policies should be a focus ahead of future pandemics. On that point, policy should emphasize an epidemiological task force with widespread testing and a contact-tracing system.

Omicron new variant BA.2.86 (Pirola): Epidemiological, biological, and clinical characteristics - a global data-based analysis.

Since December 2019, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused a threatening situation worldwide. The new variant of SARS-CoV-2, BA.2.86, also known as Pirola, is an Omicron subvariant that causes great concern because it has been found to contain a large number of mutations. This study aims to investigate and identify the biological and clinical characteristics of this threatening new variant of SARS-CoV-2, which is BA.2.86. This observational study was performed in the Department of Physiology, College of Medicine, King Saud University, Riyadh, Saudi Arabia. The literature was searched using the key terms including "SARS-CoV-2, Omicron, BA.2.86, Pirola, epidemiology, clinical characteristics". The data on Omicron BA.2.86 were obtained from the World Health Organization (WHO), Centers for Disease Control and Prevention (CDC), the Global Initiative on Sharing All Influenza Data (GSIAD), PubMed, Web of Science, regional ministries, research institutes, and international print media. Initially, 26 documents were identified and 10 documents were included for the data analysis. The information on the prevalence and the biological characteristics of the new variant of SARS-CoV-2, Omicron BA.2.86, was recorded and synthesized for analysis. The Omicron BA.2.86 has been identified in 23 countries with 264 confirmed cases as of September 28, 2023. The number and distribution of these cases encompass the United Kingdom 66 (25.0%), USA 34 (12.87%), Denmark 31 (11.74%), Sweden 25 (9.46%), South Africa 20 (7.57%), Spain 20 (7.57%), France 15 (5.68%), Portugal 7 (2.65%), Japan 6 (2.27%), Canada 5 (1.89%), Thailand 5 (1.89%), Israel 5 (1.89%), Greece 5 (1.89%), Germany 3 (1.13%), Belgium 3 (1.13%), Luxembourg 3 (1.13%), Netherlands 3 (1.13%), South Korea 3 (1.13%). However, one case in each country has been reported in Australia, Italy, Iceland, Switzerland, and China. The disease has been reported more frequently in females (71.0%) than males (29.0%). To date, no deaths have been reported. The novel variant has spread more swiftly than other variants of SARS-CoV-2 and has crossed many international borders. The new Omicron variant BA.2.86 has affected 264 people in 23 countries. The disease is more common in females than males and mainly affects old age people (over 60 years of age). However, no deaths have been reported. The variant is spreading swiftly and transmitted more rapidly. The clinical manifestations in patients with Omicron BA.2.86 variant are not well documented and may be similar to earlier strains of COVID-19 by presenting with mild infectious symptoms, including headache, body ache, cough, fever, generalized myalgia, and severe fatigue. The global health authorities must take preventive measures to stop the outbreak of this emerging variant across the globe to minimize the disease burden.

Üçüncü Basamak Üniversite Hastanesinde Takip Edilen Altı SARS-CoV-2 Pozitif Hastanın Tüm Genom Dizi Analizi

Aims: In this study, we aimed to determine mutations in the gene sequence of this virus, by performing whole genome sequence analysis from patient samples found positive by actual RT-PCR (PCR) for SARS-CoV-2.&#x0D; Methods: The study included six adult patient samples with different clinical manifestations with positive PCR tests for SARS-CoV-2, between June 01, 2020, and March 12, 2021. Sequence knowledge of all samples/testers has been loaded into the GISEAD (Global Initiative on Sharing All Influenza Data) data system. Clade Analysis, Genome Analysis, Variant Analysis, and Phylogenetic Tree Analysis were conducted.&#x0D; Results: 3 of the patients were women (female), and three were men(male), with the mean age of 42.5 years old (between 20 - 61). Totally 71 mutations were specified in 6 adult patients. By the Pangolin lineage, three of the patients were B.1.177, two were B.1, one was of B1.36 lineage. By the Pango lineage, two of the patients were B.1.609, one was B.177, one was B.1.36. By the Nexstrain Clade, four of the patients were 20A and two were of 19A lineage. No D614G mutation was detected in any of the patients. While five patients recovered, one patient with metastatic lung adenocarcinoma died.&#x0D; Conclusion; The patients were detected in the commonly found 'Non-VOC' group. Therefore, variants could not be associated with the clinical status and prognosis of the patients. However, it is thought that the data obtained contribute to both global and national SARS-CoV-2 data.

Effect of the SARS-CoV-2 Delta-associated G15U mutation on the s2m element dimerization and its interactions with miR-1307-3p.

The s2m, a highly conserved 41-nt hairpin structure in the SARS-CoV-2 genome, serves as an attractive therapeutic target that may have important roles in the virus life cycle or interactions with the host. However, the conserved s2m in Delta SARS-CoV-2, a previously dominant variant characterized by high infectivity and disease severity, has received relatively less attention than that of the original SARS-CoV-2 virus. The focus of this work is to identify and define the s2m changes between Delta and SARS-CoV-2 and the subsequent impact of those changes upon the s2m dimerization and interactions with the host microRNA miR-1307-3p. Bioinformatics analysis of the GISAID database targeting the s2m element reveals a >99% correlation of a single nucleotide mutation at the 15th position (G15U) in Delta SARS-CoV-2. Based on 1H NMR spectroscopy assignments comparing the imino proton resonance region of s2m and the s2m G15U at 19°C, we show that the U15-A29 base pair closes, resulting in a stabilization of the upper stem without overall secondary structure deviation. Increased stability of the upper stem did not affect the chaperone activity of the viral N protein, as it was still able to convert the kissing dimers formed by s2m G15U into a stable duplex conformation, consistent with the s2m reference. However, we show that the s2m G15U mutation drastically impacts the binding of host miR-1307-3p. These findings demonstrate that the observed G15U mutation alters the secondary structure of s2m with subsequent impact on viral binding of host miR-1307-3p, with potential consequences on immune responses.

SARS-CoV-2 genomic characterization and evolution in China

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) affected global health worldwide due to its high contagiousness. During the viral spread, many mutations occurred within the virus genome. China has adopted nonpharmaceutical intervention (NPI) to contain COVID-19 outbreaks. In order to understand the evolution and genomic variation of SARS-CoV-2 in China under this policy, a total of 524 sequences downloaded from Global Initiative on Sharing All Influenza Data (GISAID) between 2019 and 2022 were included in this study. The time-scaled evolutionary analysis showed that these sequences clustered in three groups (Group A-C). Group B and C accounted for the majority of the sequences whose divergence times were around 2020 and distributed in multiple regions. Group A was mainly composed of G variants, which were mainly isolated from several regions. Moreover, we found that 191 sites had mutations with no less than 3 times, including 30 amino acids that were deleted. Finally, we found that spike and nucleocapsid genes underwent positive selection evolution, indicating that the mutations within spike and nucleocapsid genes increased the SARS-CoV-2 contagiousness. Hence, this study preliminarily elucidates the evolutionary characteristics and genomic mutations of SARS-CoV-2 under the implementation of the NPI policy in China, providing scientific basis for further understanding the control effect of the NPI policy on the epidemic.

Genetic Variation of Structural and Functional Genes of SARS-CoV-2 Isolates Circulating in Banyumas (Indonesia)

Scientists are performing various measurements to overcome the COVID-19 pandemic. The genomic mutations of SARS-CoV-2 can change their pathogenicity, infectivity, transmission, and antigenicity. This present study aimed to know a) the genetic variation of structural and functional genes of SARS-CoV-2 circulating in Banyumas and b) the potential of the Cilacap’s Harbour as a human mobility portal on the genetic variations of SARS-CoV-2 circulating in Banyumas, Central Java (Indonesia). Genomic sequence of SARS-CoV-2 isolates were taken from the Global Initiative on Sharing All Influenza Data (GISAID) and the National Center for Biotechnology Information (NCBI) online platforms. A gene cut was carried out from Wuhan reference isolate, fifteen isolates from Banyumas, and two isolates from Cilacap (Central Java) using Unipro UGENE v. 33.0 software, considering the annotation of the Wuhan-1 isolate. Genetic variations were detected among SARS-CoV-2 isolates circulating in Banyumas. The structural protein (envelope, membrane, nucleocapsid) encoding gene and the RdRp gene were highly conserved to Wuhan reference genome (Wuhan-Hu-1). Meanwhile, the ORF and the spike-encoding genes were less identical to the Wuhan reference genome. This study also proposed that human mobility from outside Central Java through Cilacap’s Harbour did not affect the genetic variation of SARS-CoV-2 isolates circulating in Banyumas (Central Java).

Genomic Surveillance of SARS-CoV-2 Variants in the Dominican Republic and Emergence of a Local Lineage.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an RNA virus that evolves over time, leading to new variants. In the current study, we assessed the genomic epidemiology of SARS-CoV-2 in the Dominican Republic. A total of 1149 SARS-CoV-2 complete genome nucleotide sequences from samples collected between March 2020 and mid-February 2022 in the Dominican Republic were obtained from the Global Initiative on Sharing All Influenza Data (GISAID) database. Phylogenetic relationships and evolution rates were analyzed using the maximum likelihood method and the Bayesian Markov chain Monte Carlo (MCMC) approach. The genotyping details (lineages) were obtained using the Pangolin web application. In addition, the web tools Coronapp, and Genome Detective Viral Tools, among others, were used to monitor epidemiological characteristics. Our results show that the most frequent non-synonymous mutation over the study period was D614G. Of the 1149 samples, 870 (75.74%) were classified into 8 relevant variants according to Pangolin/Scorpio. The first Variants Being Monitored (VBM) were detected in December 2020. Meanwhile, in 2021, the variants of concern Delta and Omicron were identified. The mean mutation rate was estimated to be 1.5523 × 10-3 (95% HPD: 1.2358 × 10-3, 1.8635 × 10-3) nucleotide substitutions per site. We also report the emergence of an autochthonous SARS-CoV-2 lineage, B.1.575.2, that circulated from October 2021 to January 2022, in co-circulation with the variants of concern Delta and Omicron. The impact of B.1.575.2 in the Dominican Republic was minimal, but it then expanded rapidly in Spain. A better understanding of viral evolution and genomic surveillance data will help to inform strategies to mitigate the impact on public health.