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Intro: The COVID-19 pandemic has triggered global collaborative efforts on response and research to detect SARS-CoV-2 particles not just in the human population but also in wastewater. While the examination of clinical samples from COVID-19 patients links SARS-CoV-2 to specific individuals, the analysis of an amalgam of human feces through environmental surveillance (ES) links SARSCoV-2 to populations and communities served by the wastewater system. Studies on SARS-CoV-2 in the environment were already done in high-resource countries. However, its epidemiology in wastewater bodies in the Philippines is limited. In this study, we used the National ES for Polio and Other Pathogens Network to investigate the molecular epidemiology and transmission dynamics of SARS-CoV-2 at the outset of the pandemic. Method(s): This is a retrospective study of 250 wastewater samples collected from May 2020 to July 2021. Samples were processed using the two-phase concentration technique. Pepper mild mottle virus RNAs were quantified as the internal control. Real-time PCR was used to detect the N-gene of the SARS-CoV-2. Whole genomes were sequenced using the COVID-19 ARTIC v4.0. Phylogenetic and mutation analysis were done and lineage assignments were established using the PANGOLIN software. Finding(s): Forty-two percent (107/250) of the environmental samples detected SARS-CoV-2 particles. Fifty-nine samples with Ct values <=38 were sequenced and the whole genome analysis revealed B.1.1 and B.6. lineages of SARS-CoV-2. When viral load were plotted with the weekly cases in the respective site, we observed that SARS-CoV2 can be detected in wastewater weeks before the spike of cases in the community. Conclusion(s): This is the first report on the detection of B.1.1 and B.6 SARS-CoV-2 particles in waste/surface waters in the Philippines. With the declining incidence of COVID-19 cases, this study provided data regarding the feasibility of establishing environmental surveillance for SARS-CoV-2 as a supplemental tool for human or case monitoring especially in resource-limited settings.Copyright © 2023
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Seven human coronaviruses have been identified so far: four seasonal coronaviruses (HCoV-229E, HCoV-OC43, HCoV-NL63, HCoV-HKU1) and three novel coronaviruses (SARS-CoV, MERS-CoV, SARS-CoV-2). While seasonal coronaviruses cause only mild symptoms, novel coronaviruses cause severe and potentially fatal infections. All known coronaviruses originated in animals. Bats are considered as an origin for the majority of coronaviruses capable of infecting humans;however, rodents are proposed as natural hosts for HCoV-OC43 and HCoV-HKU1. Different animal species could serve as intermediate hosts including alpacas (HCoV-229E), livestock (HCoV-OC43), civet cats (SARS-CoV), camels (MERS-CoV), and pangolins (SARS-CoV-2). In Croatia, SARS-CoV-2 was detected in humans, pet animals, wildlife, and the environment. The COVID-19 pandemic has highlighted the role of the 'One Health' approach in the surveillance of zoonotic diseases.Copyright © 2022, University Hospital of Infectious Diseases. All rights reserved.
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The human pandemic caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that started in December, 2019 is still continuing in various parts of the world. The SARS-CoV-2 has evolved through sporadic mutations and recombination events and the emergence of alternate variants following adaptations in humans and human-to-animal transmission (zooanthraponosis) has raised concerns over the efficacy of vaccines against new variants. The animal reservoir of SARS-CoV-2 is unknown despite reports of SARS-CoV- 2-related viruses in bats and pangolins. A recent report of back-andforth transmission of SARS-CoV-2 between humans and minks on mink farms in the Netherlands has sparked widespread interest in zooanthroponotic transmission of SARS-CoV-2 followed by reemergence to infect human populations. The risk of animal to human transmission depends on virus-host interaction in susceptible species that may be short-term or long term risks. The short term risk might be due to infection to humans during the viremic stage in susceptible animals. The long term risk might be either due to persistence of the virus at population level or latency of infection leading to risk of evolution and re-emergence of the virus. Experimental studies have identified a range of animals that are susceptible and permissive to SARS-CoV-2 infection viz. cats, ferrets, hamsters, mink, non-human primates, tree shrews, raccoon dogs, fruit bats, and rabbits. The health impacts of SARS-CoV-2 infection in animals are unknown and it is likely that other susceptible species have not been discovered yet. Apart from farmed animals, stray cats and rodents have been identified as a potential opportunity for ongoing transmission in intense farming situations. Recognizing animal species that are most susceptible to infection is the first step in preventing ongoing transmission from humans. Minimizing the risk of zooanthraponosis requires multi-sectoral coordination that includes implementation of strict biosecurity measures such as controlled access to farms that house susceptible animals, bio-secure entry and exit protocols, disinfection protocols in farm, down time for animal transport vehicles and daily assessments of human handlers for exposure to SARS-CoV- 2. Hence, active surveillance in animal species that are prioritized based on risk assessment need to be initiated in coordination with health and environment sectors for early identification of emerging and re-emerging variants of SARS-CoV-2 virus in animals.
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SARS-CoV-2 infected cases diagnosis is based on the count of realtime reverse transcription-polymerase chain reaction (RT-PCR). The widely used reverse transcription-polymerase chain reaction (RTPCR) method has some limitations for clinical diagnosis and treatment. However, there are only few reports on the detection of the viral load in the stool and urine samples. While information about other modes of transmission is relatively less, some published literature supporting the possibility of a faecal-oral mode of transmission has been accumulating. Objective(s): The current study's objective was to assess the performance of real-time RT-qPCR assay and a droplet digital RT-PCR (dd RT-PCR) for detecting SARS-CoV-2 in stool and urine specimens. Methodology: One hundred and seven paired samples from 107 COVID-19-confirmed patients were analysed by dd RT-PCR and RTPCR based target gene (N1 and N2). Stool and urine were collected from COVID Care Centers of Pune Region. RNA was isolated using MagMax magnetic beads base procedure for further analysis. Real Time RT-PCR and DD PCR was performed from all the patients. Result(s): In 107 patients, all the stool samples showed 100% positive concordance by both methods, the average of 28.88 cycle threshold (Ct) of RT-PCR was highly correlated with the average copy number of 327.10 copies/mul analyzed in ddPCR. Whereas 27.1% urine samples were tested positive in ddPCR & 1.86% were positive with the average of 36.41 cycle threshold (Ct) in RT-PCR. Using Pangolin COVID-19 Lineage Assigner variants were analyzed and found to be delta prevalent. Conclusion(s): In the context of the COVID-19 pandemic, environmental surveillance for the detection of SARS-CoV-2 has become increasingly important. The findings of this study not only show that SARS-CoV-2 is present in urine and faeces, but they also raise the possibility that low concentrations of the viral target may make it easier to identify positive samples and help resolve situations of inconclusive diagnosis.
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Background: RNA viruses evolve very fast, with a mutation rate of 103 to 105 base sub-stitution per nucleotides per copy. The mutation is a survival strategy for the viruses, which leads them to survive in the new host. Fitness is defined as the replication capacity of the virus in an ex-perimental setup. Generally, the large population passage of the virus leads to fitness gain, but the world data of the coronavirus infection and death shows the flattened curve with time. It is contra-dictory to the principle of fitness gain due to large population passage. The coronavirus is losing its potency but remains infectious as it is passaging into millions that leads to a decline in the death of COVID patients and high recovery rates. Fitness loss of coronaviruses attributed to a high level of mutation in the RNA genome as well as host immune response. The current outbreak of SARS CoV-2 is surfaced in December 2019 in Hubei province of China and considered as bats/pangolin origin, spreading 235 countries of the world, infecting nearly 31,664,104 people, and claimed nearly 972,221 lives as of September 24, 2020 (Death rate approximately 3%). This coronavirus has passaged into 31,664,104 people from the beginning of this pandemic until September 24, 2020. Now the virus is losing potency rather than being monotonous and continuous in producing virus-related complications. The population is still getting infected at the same rate, but the severity of the disease is reduced due to the potency of the virus diminished due to the passage effect as well as fitness loss of the virus due to high mutation rates. The death rate is reduced to 3% as compared to 6% in June 2020, when this paper was first submitted. Objective(s): The purpose of the study is to prove the fact that the coronavirus loses its potency with time but, they remain infective. It becomes more infectious due to mutation of the gene but loses the capacity to kill the host. Method(s): Since the WHO announces the COVID-19 outbreak is an emergency of international con-cern, every country in the world is taking many measures to mitigate the viral load to their popula-tion. Simultaneously, the WHO, CDC USA, CDC Europe, and much other organization is updating the COVID cases and death online daily as reported by the respective country. With the help of the COVID-19 outbreak data published by the European CDC and ourworldindata.org, we correlate the total cases of coronavirus and total death in the top ten affected countries in the world. We also link the trends of total cases vs. total death and total new cases vs. total new death related to COVID-19 in Germany, Spain, the United Kingdom, Italy, and New Zealand from January 30, 2020, until September 24, 2020. The reason to select these countries for the study is that these countries updating the COVID cases and deaths regularly and said to achieve the peak of COVID related infections and recovering from the pandemic. Result(s): We have tried to correlate the high mutation rate of the virus that leads to losing its potency to severe infection and death in the human. Viral extinction through high mutation could be considered as the new anti-viral strategies. Conclusion(s): Coronavirus is losing its potency to causing death to the human. The new infection is still being reported from every corner of the world, but the death rate is significantly decreasing.Copyright © 2021 Bentham Science Publishers.
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Background: The Omicron variant B.1.1.529 has led to a new dynamic in the COVID-19 pan-demic, with an increase in cases worldwide. Its rapid propagation favors the emergence of novel sub-lineages, including BA.4 and BA.5. The latter has shown increased transmissibility compared to other Omicron sub-lineages. In Senegal, the emergence of the Omicron variant in December 2021 characterized the triggering of a short and dense epidemiological wave that peaked at the end of February. This wave was followed by a period with a significant drop in the number of COVID-19 cases, but an upsurge in SARS-CoV-2 infection has been noted since mid-June. Objective(s): The purpose of this brief report is to give an update regarding the genomic situation of SARS-CoV-2 in Dakar during this phase of recrudescence of cases. Method(s): We performed amplicon-based SARS-CoV-2 sequencing on nasopharyngeal swab samples from declared COVID-19 patients and outbound travelers that tested positive. Result(s): Ongoing genomic surveillance activities showed that more than half of recent COVID-19 cases were due to the BA.4 and BA.5 sub-lineages that share two critical mutations associated with increased transmissibility and immune response escape. The circulation of recombinants between Omicron sub-lineages was also noted. Conclusion(s): Despite the lack of proven severity of BA.4 and BA.5 sub-lineages, their increased transmis-sibility causes a rapid spread of the virus, hence a surge in the number of cases. This rapid spread consti-tutes a greater risk of exposure for vulnerable patients. To tackle this issue, any increase in the number of cases must be monitored to support public health stakeholders. Therefore, genomic surveillance is an ever-essential element in managing this pandemic.Copyright © 2022 Bentham Science Publishers.
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Background: The new public health emergency of COVID-19 caused by a novel Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), which originated in Wuhan, Hubei province, China in December 2019, evolved into a pandemic in no time and is still in progression. The novel virus mainly targets the lower respiratory system, leading to viral pneumonia, with other associated complications of multi organ failure. Discussion(s): The bats, in particular Rhinolophus affinis, is a natural host of SARS-CoV-2 and the virus is considered to have spread to humans through yet controversial intermediate host pangolins. The incubation period ranges from 2-14 days and mode of person-to-person transmission is primari-ly via the direct contact with the infected person or through the droplets generated by the infected person during coughing or sneezing. The initiation of the infection process by SARS-CoV-2 virus is the invasion of lung type II alveolar cells via a receptor protein called angiotensin-converting enzyme 2 (ACE2) present on the cell membrane with glycosylated spike (S) viral protein that medi-ates host cell invasion. The main diagnostic tools employed are molecular methods based on nucleic acid detection engaging real-time quantitative polymerase chain reaction (RT-qPCR) and a new immunoassays based on antibodies IgM/IgG. Conclusion(s): Due to the lack of specific clinically approved anticovid-19 drugs or vaccines that could be used for its prevention or treatment, the current management approach is essentially sup-portive and symptomatic. The precautionary measures like, social distancing, cleaning hands with soap or sanitizers, using disinfectant solutions to decontaminate the surfaces of things and proper ventilation, wearing masks and other protective gears to curb transmission. The knowledge regard-ing COVID-19 therapies is still evolving and collaborative efforts are being put in to discover definitive therapies on different themes in the form of vaccines, repurposing drugs, RNA interfer-ence, docking studies, etc.Copyright © 2021 Bentham Science Publishers.
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Introduction/ Background: Genomic surveillance of SARS-CoV-2 is crucial for monitoring the spread of the disease and guiding public health decisions but the capacity for SARSCoV- 2 sequencing in Africa remains low. This research aims to increase the genomic contribution from the Africa and gain insights of the SARS-CoV-2 infections in Ghana and Africa. Methods: We utilised samples from two sources;firstly, community surveillance undertaken using the Ghana Influenza Surveillance Network and secondly imported cases of SARS-CoV-2 detected in travellers. A total of 457 patients from Ghana, collected from 1st April 2020 to 31st August 2021, were sequenced using Oxford Nanopore Technology sequencing and the ARTIC tiled amplicon method. The sequence lineages were typed using Pangolin and the phylogenetic analysis was carried out using IQtree and TreeTime. Results: We detected three waves of SARS-CoV-2 infections in Ghana. The first wave of infection was mainly contained in the Greater Accra, later spreading to other regions in the second and third wave. B.1 and B.1.1. were the most prevalent lineages in wave one, while the B.1.1.7/alpha variant is responsible for the second wave. An investigation into the lineages detected in Ghana led us to discover that B.1.1.318 (which contains the E484K mutation shown to impact antibody recognition) has a high cumulative prevalence rate in a number of neighbouring West African countries, suggesting that there might be a regional circulation. Impact: The high-quality sequences produced from this study were submitted to the largest open-access SARSCoV- 2 sequence database, increasing the genomic contribution from Africa. By sequencing both community samples and imported cases in Ghana, the study revealed an insight into the SARS-CoV-2 epidemiology in Ghana and West Africa. Conclusion: This study not only informed us of the epidemiological characteristics of the SARS-CoV-2 outbreaks in Ghana, but also shed light on the epidemiological trends of neighbouring countries that may have less sequencing capacity, highlighting the important role of pathogen genomic sequencing in cross-border and regional disease surveillance.
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Introduction/ Background: The COVID-19 pandemic has caused significant mortality and multiple variants of SARS-CoV-2 have been documented. Delta is the predominant variant around the world. Genomic surveillance can help country to overcome the pandemic by informing/prevention strategies. We aim to determine the dynamic of SARS-CoV-2 in Brazzaville, ROC, between December 2020-July 2021. Methods: Between December 2020 and July 2021, oropharyngeal swabs from symptomatic individuals (n=600) were screened for COVID-19 from different districts of Brazzaville, ROC. RNA was extracted from swabs using the QIAamp Viral RNA Mini Kit (Qiagen, Hilden, Germany) and subjected to RealStar® SARS-CoV-2 real-time PCR targeting the S gene of SARS-CoV-2 (Altona Diagnostics, Hamburg, Germany) was performed in LightCycler® 480 Instrument II (Roche diagnostics, Mannheim, Germany). Found 317 individuals tested positive for COVID-19 and 182 samples that were having Ct <30 were subjected to Next- Generation Sequencing (NGS). Results: The characteristics of the study population from 171 genomes sequenced are as following, the median age of the subjects was 34 years (IQR: 25 to 47) and 67% (115/171) were males. The genomes were assigned to different pangolin lineages. A total of 15 variants were found circulating during the study period. For phylogenetic analysis, variants B.1.544 and B.1 were clustered into a single, and four sister lineages, B.1.214, B.1.214.1, B.214.2 and B.1.214.3, were clustered into a single clade. The B.1.214.2 was the predominant lineage. The VOC lineages B.1.1.7 and B.1.627.2 now have been finding in circulation in the ROC. Impact: The results from the present study indicate that many SARS-COV-2 variants are circulating in the ROC, and the detection of B.1.1.7 and B.1.617.2 variants for the first time in the country is the raised alarm to the health authorities. Conclusion: Many SARS-COV-2 variants are circulating in the ROC, and the detection of B.1.1.7 and B.1.617.2 variants for the first time in the country is the raised alarm to the health authorities. Thus, the spatiotemporal genomic surveillance of SARS-CoV-2 variants contributes to our understanding of viral dynamics.
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Introduction/ Background: In this cross-sectional study, we conducted genomic surveillance of SARS-CoV-2 with the aim of identifying emerging variants and tracking the genomic evolution of the virus. Furthermore, we analyzed the trends of SARS-CoV-2 lineages over time in Uganda. Methods: We performed SARS-CoV-2 whole-genome deep sequencing on samples collected between June- August 2021 from 107 patients (RT-PCR Ct values < 26) from 10 Districts in central (Kampala, Wakiso, Mpigi, Kalungu, Kalangala, Kassanda and Mityana) and northern (Dokolo, Amudat, Moroto) Uganda. Sequencing was done using the Illumina Miseq and Oxford Nanopore MinION next generation sequencing platforms. Deep sequence reads were assembled using Genome Detective and Nanopolish/Medaka (ARTIC). Quality control of the sequences was done using Nextclade and Geneious followed by lineage analysis using PANGOLIN (Phylogenetic Assignment of Named Global Outbreak LINeages). Results: 102 (95.3%) of 107 genomes were of the Delta variant (B.1.617.2). Delta AY sub-lineages detected at low prevalence included AY.1, AY.4, AY.16, AY.33 and AY.39. One AY.1 (delta plus) and 2 AY.16 sub-lineages were identified. Additionally, 1 Kappa B.1.617.1 variant was detected. Other minority lineages included A, B and Eta (B.1.525). By 20th September 2021, 712 SARSCoV- 2 sequences from Uganda had been deposited in GISAID (https://www.gisaid.org) and between December 2020 to January 2021, the A.23.1 variant dominated. The first Delta variant (B.1.617.1) sample was collected in March 2021 and by June 2021, Delta accounted for >90% of all detected variants. Impact: This study provides valuable information on the circulating variants and lineages in Uganda and contributes towards the national SARS-CoV-2 genomic surveillance. However, a major limitation of the study is the suboptimal sampling as a result of funding challenges. Conclusion: In Uganda, Delta has largely replaced other variants and is the dominant circulating SARS-CoV-2 variant. Study findings suggest that continued SARS-CoV-2 genomic surveillance from recently collected samples is critical to keep track of the circulating and emerging variants.
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Background: The rapid spread of COVID-19 has resulted in an urgent need for effective diagnostic and therapeutic strategies against SARS-CoV-2. Next-generation sequencing (NGS) is a powerful tool in the identification and characterization of this pathogen and genomic information may aid in understanding the mechanisms of therapeutic resistance, vaccine escape, virulence, and pathogenicity. The Ion AmpliSeq SARS-CoV-2 Research Panel is a targeted NGS solution that facilitates sequence analysis of the SARS-CoV-2 genome. Paired with a bioinformatics assembly and variant calling pipelines, this assay allows for accurate characterization of the dominant SARS-CoV-2 variant. This assay's performance was analytically validated for the detection of mutations (substitutions, insertions, and deletions) in RNA derived from nasopharyngeal (NP) swabs. Method: The Ion AmpliSeq SARS-CoV-2 Research panel consists of two primer pair pools generating 237 amplicons specific to the SARS-CoV-2 virus. Reverse transcription of the RNA was performed using the SuperScript VILO cDNA Synthesis kit. Library preparation was then completed using the Ion AmpliSeq Library Kit Plus kit. The final library was quantified, normalized, pooled, and sequenced. Raw sequencing data was aligned to the AmpliSeq SARS-CoV-2 Research panel, using the MN908947.3 reference genome. Variants were called using the Torrent Variant Caller and annotated using the COVID19AnnotateSnpEff plugin. The reference-guided iterative assembler IRMA was used to produce a single consensus sequence consisting of the reference genome sequence modified to include sequence variations supported by the reads. The Pangolin COVID-19 lineage assigner software tool was used to assign SARS-CoV-2 lineage. Analytical validation was completed using controls (Twist Biosciences, BEI Resources, ATCC) and RNA derived from NP swabs. Accuracy and specificity were examined by evaluating the correctness of calling true negative variants compared to false positive and all other variant calls, respectively. Precision and limit of detection (LoD) were examined by evaluating the concordance of variants across replicate samples. Limit of Blank (LoB) was calculated as the 95th percentile of reads per amplicon in the negative samples. Results: Accuracy of base calling, specificity, and precision were 100% for SNVs, insertions, and deletions above 25% allele frequency. LoD was determined to be 576 viral copies/mL. LoB was determined to be 202 reads per amplicon. Pangolin lineage assignment was 100% for all samples. Conclusions: This panel accurately characterizes SARS-CoV-2 variants, allowing for accurate consensus sequence generation, mutation annotation, and lineage assignment.
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Objective To analyze the molecular epidemiological characteristics of the Corona virus disease 2019 (COVID‑19) cases in Shijiazhuang, which can reveal the origin of the outbreak and provide a scientific basis for COVID‑19 prevention and control. Methods From January 2 to January 8, 2021, a total of 404 samples from 170 COVID‑19 cases were collected from the Shijiazhuang Fifth Hospital. The consensus sequence of 2019 novel Coronavirus(2019‑nCoV) was obtained through multiplex polymerase chain reaction‑based sequencing. The sequences of 170 COVID‑19 cases were analyzed by the PANGOLIN, and the data were statistically analyzed by T‑test. Results Among the 404 COVID‑19 samples, a total of 356 samples obtained high quality genome sequences (>95%, 100×sequencing depth). The whole genome sequences of 170 COVID‑19 cases were obtained by eliminating repeated samples. All 170 sequences were recognized as lineage B1.1 using PANGOLIN. The number of single nucleotide polymorphism arrange from 18-22 and most of the single nucleotide polymorphism were synonymous variants. All of 170 genomes could be classified into 48 sub‑groups and most of the genomes were classified into 2 sub‑groups (66 and 31, respectively). Conclusions All cases in this study are likely originated from one imported case. The viruses have spread in the community for a long time and have mutated during the community transmission.
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The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), responsible for the COVID-19 pandemic, has become one of the most studied viruses since its emergence. Two years after its outbreak, SARSCoV- 2 still represents a major public health priority as it keeps spreading at an alarming rate through the rise of many pathogenic variants. These latter can be a serious threat the more their genomic sequence diverge from the original strain, the less efficient the vaccine will remain. Therefore, it is critical for medical services to be able to determine straight out the strain they are dealing with, also as the location of the occurred genomic mutations and identify which viral protein has evolved. In this context, our main goal is to understand the nuances behind the mutations observed simultaneously in the genome and the proteome. To do so, we developed a user-friendly web-service software (Viral Instant Mutation Viewer or VIMVer) which allows an instant identification of new mutations and displayed them in both the nucleotide and protein sequences in comparison to a reference sequence (wuhan-1). Given a SARS-CoV-2 nucleotide sequence (as a newly sequenced genome), our software will instantly extract, analyse and visualize mutations on the genome and the proteome with the proper numbering and positioning. Additionally, the output is linked to Phylogenetic Assignment of Named Global Outbreak LINeages (Pangolin COVID-19) (2), which will thus allow an automatic identification of the Lineage or its position in relation to known lineage. We believe this tool will help many in their daily process to analyse their data. The source code is released under public licence and can be adapted for further development.
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Background: Spain has been one of the main epicenters for Covid-19 in Europe. The country is divided into 17 Autonomous Communities (AC) and two Autonomous Cities (ACi). This study aims to describe the epidemiology of SARS-CoV-2 in Spain across 3 study periods established from the beginning of the pandemic to the third epidemiologic wave, after analyzing genomes from all AC/ACi from February 2020 to March 2021. Methods: All 14,256 available partial and complete Spanish SARS-CoV-2 human genomic sequences deposited in the GISAID repository (https://www. gisaid.org/) until 21 March 2021 were downloaded in nucleotides and classified according to the AC/ACi and to the epidemiological week by collection date. The sequences were assigned to the genetic lineages according to Pangolin COVID-19 Lineage Assigner (https://pangolin.cog-uk.io/). Epiweeks were grouped into three main periods adjusted to the Spanish epidemic curve, as informed in the National Epidemiological Surveillance Network (RENAVE, https://cnecovid.isciii. es). The first period comprised from the beginning of the pandemic to the end of the first state of emergency (June 2020). The second period included the second epidemic wave (June-December 2020), and the third period covered the third wave (December 2020-March 2021). Only AC with at least 10 sequences for each period were described in the results. The two ACi were considered together. Results: Before the national lockdown (14 March 2020), 11 SARS-CoV-2 lineages were circulating in Spain with A.2 lineage predominance. During the lockdown the SARS-CoV-2 variant diversity increased, decreasing during the confinement. During this period, B.1 was the main circulating variant. During summer 2020, B.1.177 became the main circulating variant. The third wave was characterized by the introduction and fast spread of the B.1.1.7 or Alpha Variant of Concern. Conclusion: The reduction of diversity during the lockdown suggests this measure was effective in reducing the import of SARS-CoV-2 lineages. After the opening of borders within Europe during summer 2020, the variant diversity increased again and B.1.177 became the predominant variant, suggesting that despite the efforts to avoid SARS-CoV-2 spread between countries, travel restrictions during summer 2020 were not sufficient to control viral spreading. The variant distribution was heterogeneous among the AC and periods, reflecting different incidence and sequencing capacities across AC.
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Background. The consequences of SARS-CoV2 reinfections for patients, healthcare workers and society are unclear. We reviewed the clinical, laboratory, and epidemiological characteristics of patients re-infected with genetically distinct strains of SARS-CoV2 identified by Whole Virus Genome Sequencing (WvGS). Methods. Cases were selected based on a positive SARS-CoV-2 Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) test, clinical resolution, a negative interim test and a subsequent positive nasopharyngeal swab. Positive samples were prepared for sequencing by cDNA synthesis, tiled-PCR following the ARTIC protocol and amplicon sequencing using Illumina MiSeq platform. Raw reads were mapped to the reference sequence using bowtie and Samtools was used for variants calling and to generate the consensus sequences. Comparative sequence analysis was conducted by phylogenetic inference maximum likelihood method with RAxML using the multiple sequence aligned by MAFFT. Clades and variants were assigned respectively using Nextstrain and Pangolin COVID-19 lineage assigner (Figure 1). The clinical, radiological and laboratory data were collected from patient medical notes and laboratory information system. Results. Two cases of SARS-CoV-2 reinfection were detected by RT-PCR (patient 1 and 2). CT values and strain variants are presented in Table 1. The time between detection of the first and second infection was 67 and 270 days respectively. WvGS confirmed that the second episodes were due to a genetically distinct strain of SARS CoV2. These reflected the dominant contemporaneous variants in circulation. Both patients were immunocompromised from co-morbidities and medications. First and subsequent infections were minimally symptomatic. Both cases were associated with known hospital outbreaks. They passed away within 2 weeks of the second infection of unrelated causes. Conclusion. Two patients in this study were diagnosed with a SARS-CoV-2 reinfection confirmed by WvGS. A common factor in these cases was immunocompromise. Where a previously infected patient test shows a new positive or an unexpected reduction in CT value is observed, we recommend individual risk assessment to determine the timing of discontinuation of isolation and infection control precautions.
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Background. A COVID-19 vaccine breakthrough infection is defined as SARSCoV-2 RNA or antigen detected ≥ 14 days after completion of a final vaccine dose. CDC's May 25 MMWR report of 10,262 vaccine breakthrough infections in the U.S. is likely an underestimate. Herein, we report Veterans Health Administration (VHA) breakthrough cases, focusing on hospitalizations and deaths. Methods. We extracted COVID-19 vaccine breakthrough infections tested between 1/19/2021 and 4/30/2021 from the VHA Corporate Data Warehouse (including screening tests). We reviewed medical records of cases who died and/or were hospitalized within 14 days of SARS-CoV-2 positive test for clinician documentation of conditions deemed high risk for COVID-19 and to confirm hospitalization or death was related to COVID-19. SARS-CoV-2 whole genome sequencing (Clear Labs platform) and antigen testing (Abbott BinaxNOW) from available patient samples were performed and Pangolin lineage determined. Results. 1,142 COVID-19 vaccine breakthrough infections were identified. 357/1,142 (31.3%) were hospitalized and/or died. 1,085 (95%) were male (Table 1), and median age was 72.5 years (74 years for hospitalized/deceased patients). COVID-19 infection contributed to hospitalization and/or death in 139 (38.9%) cases. The remaining 218 (61.1%) were hospitalized or died of causes apparently unrelated to COVID-19. Smoking and heart conditions were seen most frequently among hospitalized/ deceased breakthrough cases (Table 2). Variant B.1.1.7 was predominant, present in 17/27 (63%) total samples sequenced, and 13/21 (61.9%) hospitalized/deceased. (Table 3). Of 21 sequenced hospitalized/deceased cases, SARS-CoV-2 antigen positivity was present in 11 (52.4%). Conclusion. Compared to CDC reported breakthrough infections, VHA cases were more male, older, and hospitalized/died at higher frequency. Further study is needed to determine the contribution of specific underlying conditions, COVID-19 vaccine formulations and variants on hospitalization and death among COVID-19 vaccine breakthrough infections. Sequencing efforts for breakthrough cases should be intensified, particularly for those presenting with more severe infections.
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Background. The coronavirus disease (COVID-19) pandemic has affected residents in long-term care facilities (LTCF) significantly. Understanding transmission dynamics in this setting is crucial to control the spread of COVID-19 in this population. Using whole genome sequencing (WGS) of SARS-CoV-2, we aimed to delineate the points of introduction and transmission pathways in a large LTCF in Quebec, Canada. Methods. Between 2020-10-28 and 2021-01-09, COVID-19 cases occurred in 102 residents and 111 HCW at a 387-bed LTCF;cases were distributed in 11 units on 6 floors. As part of outbreak analysis, SARS-CoV-2 isolates underwent WGS using the Oxford Nanopore Minion and the Artic V3 protocol. Lineage attribution and sequence types (ST, within 3 mutations) were assigned based on Pangolin classification and variant analysis. Epidemiologic data including date of positive PCR test, resident room number and HCW work location were collected. Self-reported high-risk exposures were collected by HCW questionnaire via phone interview after consent. Cases and their ST, geo-temporal relations and HCW-reported exposures were examined via network plots and geography-based epidemic curves to infer points of introduction and paths of transmission. Results. Of 170 isolates available from 100/102 residents and 70/111 HCW, 130 (76.4%) were successfully sequenced. Phylogenetic analysis revealed 7 separate introductions to the LTCF. Grouping of ST by units was observed, with temporal appearance of ST supporting HCW introduction in 7/11 units. Proportion of phone interview completion was low at 35% (26/70). Few HCW recalled specific high-risk exposures. Recalled exposures supported by genetic linkage revealed potential between-unit introductions from HCW-to-HCW transmission at work and outside the workplace (e.g. carpooling). On one unit, a wandering resident was identified as a likely source of transmission to other residents (Figure 1). Network plot of cases clustered by geographic unit, colour-coded by sequence type. Circles represent residents;addition signs represent healthcare workers. Blue lines represent identified high-risk exposures. Node labels represent floor and unit identifiers;2 units per floor. Conclusion. We demonstrate the complex genomic epidemiology of a multi-unit LTCF outbreak, putting into evidence the importance of a multi-faceted approach to limit transmission. This analysis highlights the utility of using WGS to uncover unsuspected transmission routes, such as HCW contact outside work, which can prompt new infection control measures.