Use of strips of rapid diagnostic tests as a source of ribonucleic acid for genomic surveillance of viruses: an example of SARS-CoV-2.

BACKGROUND: This study aimed to demonstrate that the genomic material of SARS-CoV-2 can be isolated from strips of COVID-19 rapid diagnostic test cassettes. METHOD: It was a prospective cross-sectional study involving patients admitted to treatment centers and sampling sites in the city of Conakry, Guinea. A total of 121 patients were double sampled, and 9 more patients were tested only for RDT. PCR was conducted according to the protocol of the RunMei kit. Sequencing was performed by using the illumina COVIDSeq protocol. Nine COVID-19 RDTs without nasopharyngeal swabs were in addition tested. RESULT: Among the 130 COVID-19 RDTs, forty-seven were macroscopically positive, whereas seventy-two were positive according to PCR using RDT strip, while among the 121 VTM swabs, sixty-four were positive. Among eighty-three negative COVID-19 RDTs, twenty-seven were positive by PCR using RDT strip with a geometric mean Ct value of 32.49 cycles. Compared to those of PCR using VTM, the sensitivity and specificity of PCR using RDT strip were estimated to be 100% and 85.96%, respectively, with 93.39% test accuracy. Among the fifteen COVID-19 RDT extracts eligible for sequencing, eleven had sequences identical to those obtained via the standard method, with coverage between 75 and 99.6%. CONCLUSION: These results show that COVID-19 RDTs can be used as biological material for the genomic surveillance of SARS-CoV-2.

Genomic analysis of three SARS-CoV-2 waves in west Sumatra: Evolutionary dynamics and variant clustering.

Background: The Severe Acute Respiratory Syndrome Coronavirus 2 virus (SARS-CoV-2) has been undergoing evolutionary changes to improve its ability to thrive within human hosts, leading to the emergence of specific variants associated with subsequent waves of the coronavirus diseases 2019 (COVID-19) pandemic. Indonesia has grappled with the effects of this pandemic and subsequent waves affecting various regions, including West Sumatra. Although located outside Java island epicenter, West Sumatra experienced significant COVID-19 transmission, especially during the third wave in early 2022. Objective: This study aimed to investigate the genetic evolution and epidemiological dynamics of SARS-CoV-2 variants in West Sumatra throughout the three pandemic waves. Methods: We conducted a genotyping study retrospectively using 278 COVID-19 patient samples from 2020 to 2022. The Real-Time Quantitative Reverse Transcription PCR (RT-qPCR) was used for screening, and whole-genome sequence analysis was conducted through the Illumina MiSeq instrument. Result: The analysis revealed distinct patterns in the prevalence of viral lineages across the waves. The initial wave was predominated by clade 20A (77,4 %) especially lineage B.1.466.2 (50 %). The second wave was marked by a significant emergence of the Delta variant (72,5 %), particularly lineage AY.23 (81,1 %), originating from India, with subsequent local evolution leading to the formation of distinct clusters. We found that about 96,7 % of the third wave variant was dominated by Omicron variants, especially the generation of lineages BA.1 and BA.2, demonstrating widespread global dissemination and local variant development. Phylogenetic analysis indicated a close relatedness of West Sumatra variants to those from Malaysia and other parts of Indonesia, highlighting regional transmission dynamics and potential sources of variant introductions. Conclusion: This study has identified unique variant clusters within each wave, suggesting distinct evolutionary pathways and local adaptations. These findings provide valuable insights into the genomic landscape of SARS-CoV-2 in West Sumatra and emphasize the crucial role of ongoing genomic surveillance in tracking viral changes and guiding public health measures.

Carbapenemase-producing Klebsiella quasipneumoniae ST688 (NDM-1) and Klebsiella michiganensis ST40 (KPC-2) in food destined for hospitalized patients.

OBJECTIVES: Klebsiella spp. are leading causes of nosocomial infections. Their ability to harbour antimicrobial resistance genes makes them an important public health threat. This study aimed to report the genomic background of carbapenemase-producing Klebsiella quasipneumoniae (HV55B) and Klebsiella michiganensis (HV55D) strains isolated from fresh vegetable destined for inpatients. METHODS: Microbiological and molecular methods were used to isolate and identify the strains, which were submitted to the antimicrobial susceptibility test and pH tolerance assays. Whole genome sequencing (WGS) was performed on MiSeq and NextSeq platforms, and online available tools were applied to bioinformatic analysis of clinically relevant information. RESULTS: Both isolates were considered multidrug-resistant and tolerated pH ≥ 4 for 24 h. HV55B belonged to sequence type (ST) ST668, and presented a broad resistome and plasmids from four incompatibility groups. HV55D belonged to ST40. Both strains HV55B and HV55D were genetically close to isolates responsible for human infections around the world, which stands for the plausibility of such bacteria to cause disease in patients of the studied institution. CONCLUSIONS: Our results confirm the presence of carbapenemase-producing Klebsiella spp. in fresh foodstuffs intended for inpatients consumption. The genomes characterized here also provide clinically and genomically relevant information to forthcoming epidemiological surveillance studies.

Bacterial Genomics for National Antimicrobial Resistance Surveillance in Cambodia.

BACKGROUND: Antimicrobial resistance (AMR) surveillance in low- and middle-income countries (LMICs) often relies on poorly resourced laboratory processes. Centralized sequencing was combined with cloud-based, open-source bioinformatics solutions for national AMR surveillance in Cambodia. METHODS: Blood cultures growing gram-negative bacteria were collected at six Cambodian hospitals (January 2021 - October 2022). Isolates were obtained from pure plate growth and shotgun DNA sequencing performed in-country. Using public nucleotide and protein databases, reads were aligned for pathogen identification and AMR gene characterization. Multilocus sequence typing was performed on whole genome assemblies and haplotype clusters compared against published genomes. FINDINGS: Genes associated with acquired resistance to fluoroquinolones were identified in 59%, TMP/SMX in 45%, and aminoglycosides in 52% of 715 isolates. Extended-spectrum beta-lactamase encoding genes were identified in 34% isolates, most commonly blaCTX-M-15, blaCTX-M-27, and blaCTX-M-55 in E. coli sequence types 131 and 1193. Carbapenemase genes were identified in 12% isolates, most commonly blaOXA-23, blaNDM-1, blaOXA-58 and blaOXA-66 in Acinetobacter species. Phylogenetic analysis revealed clonal strains of A. baumannii, representing suspected nosocomial outbreaks, and genetic clusters of quinolone-resistant typhoidal Salmonella and ESBL E. coli cases suggesting community transmission. INTERPRETATION: With accessible sequencing platforms and bioinformatics solutions, bacterial genomics can supplement AMR surveillance in LMICs. FUNDING: Research was supported by the National Institute of Allergy and Infectious Diseases and the Bill and Melinda Gates Foundation [OPP1211806].

A multicenter study on accuracy and reproducibility of nanopore sequencing-based genotyping of bacterial pathogens.

Nanopore sequencing has shown the potential to democratize genomic pathogen surveillance due to its ease of use and low entry cost. However, recent genotyping studies showed discrepant results compared to gold-standard short-read sequencing. Furthermore, although essential for widespread application, the reproducibility of nanopore-only genotyping remains largely unresolved. In our multicenter performance study involving five laboratories, four public health-relevant bacterial species were sequenced with the latest R10.4.1 flow cells and V14 chemistry. Core genome MLST analysis of over 500 data sets revealed highly strain-specific typing errors in all species in each laboratory. Investigation of the methylation-related errors revealed consistent DNA motifs at error-prone sites across participants at read level. Depending on the frequency of incorrect target reads, this either leads to correct or incorrect typing, whereby only minimal frequency deviations can randomly determine the final result. PCR preamplification, recent basecalling model updates and an optimized polishing strategy notably diminished the non-reproducible typing. Our study highlights the potential for new errors to appear with each newly sequenced strain and lays the foundation for computational approaches to reduce such typing errors. In conclusion, our multicenter study shows the necessity for a new validation concept for nanopore sequencing-based, standardized bacterial typing, where single nucleotide accuracy is critical.

Development of a Framework for Establishing 'Gold Standard' Outbreak Data from Submitted SARS-CoV-2 Genome Samples.

Submitted genomic data for respiratory viruses reflect the emergence and spread of new variants. Although delays in submission limit the utility of these data for prospective surveillance, they may be useful for evaluating other surveillance sources. However, few studies have investigated the use of these data for evaluating aberration detection in surveillance systems. Our study used a Bayesian online change point detection algorithm (BOCP) to detect increases in the number of submitted genome samples as a means of establishing 'gold standard' dates of outbreak onset in multiple countries. We compared models using different data transformations and parameter values. BOCP detected change points that were not sensitive to different parameter settings. We also found data transformations were essential prior to change point detection. Our study presents a framework for using global genomic submission data to develop 'gold standard' dates about the onset of outbreaks due to new viral variants.

Metaviromic reveals the dynamics and diversity of the virosphere in wastewater samples from Natal, Brazil.

The COVID-19 pandemic underscored the significance of omics technology and Wastewater-Based Epidemiology for epidemic preparedness. This study investigates the virosphere in wastewater samples from Natal (Brazil), aiming to understand its structure, relationships, and potential. Metaviromic analysis was used on DNA and RNA from weekly samples collected over a year (June/2021 to May/2022) from three wastewater treatment plants. The virosphere showed stability, particularly in viruses infecting microorganisms and plants. However, an alternation of representatives of viruses that infect animals has been observed. Among the most abundant viruses infecting microorganisms are genera associated with the bacterial genera Escherichia, Pseudomonas, and Caulobacte. Regarding the viruses infecting plants, Sobemovirus and Tobamovirus are the most abundant genera. Odontoglossum ringspot virus was identified as a possible RNA virus biomarker. Among DNA viruses infecting animals, genera Bocaparvovirus and Mastadenovirus are the most prevalent. Intriguingly, some Poxviridae family members were observed in the samples. Co-occurrence network analysis identified potential biomarkers like Volepox virus, Anatid herpesvirus 1, and Caviid herpesvirus 2. Among RNA viruses affecting animals, Mamastrovirus, Rotavirus, and Norovirus genera were the most abundant pathogens. Furthermore, members of the Coronaviridae family exhibited a high degree of centrality values in the co-occurrence network, even connecting with unclassified viruses. The study emphasizes the importance of research in understanding the roles of unclassified viruses. In addition, we observed an association between Coronaviridae reads, rainfall, and the number of reported COVID-19 cases. Our study highlights the diversity and complexity of the viral community in wastewater and the need for research to understand better the ecological roles unclassified viruses play. Such advances will significantly contribute to our preparedness and response to future viral threats. Furthermore, our study contributes to knowledge of virosphere dynamics, offering insights that can contribute to the direction of future public health policies and interventions.

Long-term surveillance of SARS-CoV-2 in the school community from Campo Grande, Brazil.

BACKGROUND: The COVID-19 pandemic has significantly impacted education systems worldwide, with Brazil being one of the countries with the longest school closures. Over a million children and teenagers have been affected, leading to increased hunger and nutritional deficiencies. This study aimed to implement long-term surveillance of SARS-CoV-2 infections in public and private schools in Campo Grande, Brazil, after returning to in-person classes. METHODS: The study involved testing and genomic surveillance at 23 public and private schools in Campo Grande, Mato Grosso do Sul, Brazil, from October 18, 2021 to November 21, 2022. The participants eligible for enrollment were students aged 6-17 years and staff members from school institutions. At the time of collection, participants were asked if they had symptoms in the last two weeks. Whole-genome sequencing of SARS-CoV-2 was conducted to identify circulating variants and to compare them with those detected in the municipality. The demographic data and clinical history of the participants were described, and a logistic regression model was used to understand how the RT-qPCR results could be related to different characteristics. RESULTS: The study included 999 participants, most of whom were women. A total of 85 tests were positive, with an overall positivity rate of 3.2%. The dynamics of case frequency were consistent with those observed in the municipality during the study period. The most common symptoms reported were cough, rhinorrhea, headache, and sore throat. Symptoms were significantly associated with SARS-CoV-2 infection. Eleven lineages were identified in school community samples, with a frequency of occurrence per period similar to that found in the sequences available for the municipality. The most prevalent lineages within the sampling period were BA.2 (59.3%) and BA.5 (29.6%). CONCLUSIONS: Our findings demonstrate that schools can play a crucial role in epidemiological surveillance, helping trigger rapid responses to pathogens such as SARS-CoV-2. Long-term surveillance can be used to track outbreaks and assess the role of children and adults in transmission. It can also contribute to pandemic preparedness, enabling a rapid response to emergencies, such as COVID-19.

Understanding the Transmission Dynamics of the Chikungunya Virus in Africa.

The Chikungunya virus (CHIKV) poses a significant global public health concern, especially in Africa. Since its first isolation in Tanzania in 1953, CHIKV has caused recurrent outbreaks, challenging healthcare systems in low-resource settings. Recent outbreaks in Africa highlight the dynamic nature of CHIKV transmission and the challenges of underreporting and underdiagnosis. Here, we review the literature and analyse publicly available cases, outbreaks, and genomic data, providing insights into the epidemiology, genetic diversity, and transmission dynamics of CHIKV in Africa. Our analyses reveal the circulation of geographically distinct CHIKV genotypes, with certain regions experiencing a disproportionate burden of disease. Phylogenetic analysis of sporadic outbreaks in West Africa suggests repeated emergence of the virus through enzootic spillover, which is markedly different from inferred transmission dynamics in East Africa, where the virus is often introduced from Asian outbreaks, including the recent reintroduction of the Indian Ocean lineage from the Indian subcontinent to East Africa. Furthermore, there is limited evidence of viral movement between these two regions. Understanding the history and transmission dynamics of outbreaks is crucial for effective public health planning. Despite advances in surveillance and research, diagnostic and surveillance challenges persist. This review and secondary analysis highlight the importance of ongoing surveillance, research, and collaboration to mitigate the burden of CHIKV in Africa and improve public health outcomes.

In field use of water samples for genomic surveillance of infectious spleen and kidney necrosis virus (ISKNV) infecting tilapia fish in Lake Volta, Ghana.

Viral outbreaks are a constant threat to aquaculture, limiting production for better global food security. A lack of diagnostic testing and monitoring in resource-limited areas hinders the capacity to respond rapidly to disease outbreaks and to prevent viral pathogens becoming endemic in fisheries productive waters. Recent developments in diagnostic testing for emerging viruses, however, offers a solution for rapid in situ monitoring of viral outbreaks. Genomic epidemiology has furthermore proven highly effective in detecting viral mutations involved in pathogenesis and assisting in resolving chains of transmission. Here, we demonstrate the application of an in-field epidemiological tool kit to track viral outbreaks in aquaculture on farms with reduced access to diagnostic labs, and with non-destructive sampling. Inspired by the "lab in a suitcase" approach used for genomic surveillance of human viral pathogens and wastewater monitoring of COVID19, we evaluated the feasibility of real-time genome sequencing surveillance of the fish pathogen, Infectious spleen and kidney necrosis virus (ISKNV) in Lake Volta. Viral fractions from water samples collected from cages holding Nile tilapia (Oreochromis niloticus) with suspected ongoing ISKNV infections were concentrated and used as a template for whole genome sequencing, using a previously developed tiled PCR method for ISKNV. Mutations in ISKNV in samples collected from the water surrounding the cages matched those collected from infected caged fish, illustrating that water samples can be used for detecting predominant ISKNV variants in an ongoing outbreak. This approach allows for the detection of ISKNV and tracking of the dynamics of variant frequencies, and may thus assist in guiding control measures for the rapid isolation and quarantine of infected farms and facilities.

Tracking the phylogenetic profile of HEV in swine and wild boar in Europe.

Hepatitis E virus (HEV) infection is prevalent among domestic pigs and wild boar in Europe. This study focused on the genetic diversity of HEV subtypes 3c, 3e and 3f among swine and wild boar in Europe as well as their circulation. Phylogenetic analysis and Bayesian phylogenetic inference were applied on the selected ORF2 capsid HEV sequences to co-estimate the viral circulation, the mean evolutionary rates and the dated trees. The estimated mean values of the HEV ORF2 capsid gene evolutionary rate were 8.29 x 10-3, 5.96 x 10-3, and 1.107 x 10-2 substitutions/site/year, respectively for 3c, 3e and 3f. The majority of the HEV 3c and 3e supported clusters did not show intermixing between swine and wild boar. Thus, although the intermixing observed in a minority of HEV 3c and 3e supported clusters suggests that transmission/circulation of these subtypes between swine and wild boar can potentially occur, 3c and 3e European wild boar HEV populations remained mainly segregated. In contrast, one half of the HEV 3f supported clusters showed intermixing between swine and wild boar, providing evidence for transfer/circulation to swine. The data suggest that continued virologic surveillance in swine and wild boar is necessary, together with targeted measures to reduce the chance of HEV transmission to humans.

Easing genomic surveillance: A comprehensive performance evaluation of long-read assemblers across multi-strain mixture data of HIV-1 and Other pathogenic viruses for constructing a user-friendly bioinformatic pipeline.

Background: Determining the appropriate computational requirements and software performance is essential for efficient genomic surveillance. The lack of standardized benchmarking complicates software selection, especially with limited resources. Methods: We developed a containerized benchmarking pipeline to evaluate seven long-read assemblers-Canu, GoldRush, MetaFlye, Strainline, HaploDMF, iGDA, and RVHaplo-for viral haplotype reconstruction, using both simulated and experimental Oxford Nanopore sequencing data of HIV-1 and other viruses. Benchmarking was conducted on three computational systems to assess each assembler's performance, utilizing QUAST and BLASTN for quality assessment. Results: Our findings show that assembler choice significantly impacts assembly time, with CPU and memory usage having minimal effect. Assembler selection also influences the size of the contigs, with a minimum read length of 2,000 nucleotides required for quality assembly. A 4,000-nucleotide read length improves quality further. Canu was efficient among de novo assemblers but not suitable for multi-strain mixtures, while GoldRush produced only consensus assemblies. Strainline and MetaFlye were suitable for metagenomic sequencing data, with Strainline requiring high memory and MetaFlye operable on low-specification machines. Among reference-based assemblers, iGDA had high error rates, RVHaplo showed the best runtime and accuracy but became ineffective with similar sequences, and HaploDMF, utilizing machine learning, had fewer errors with a slightly longer runtime. Conclusions: The HIV-64148 pipeline, containerized using Docker, facilitates easy deployment and offers flexibility to select from a range of assemblers to match computational systems or study requirements. This tool aids in genome assembly and provides valuable information on HIV-1 sequences, enhancing viral evolution monitoring and understanding.

Reduced Likelihood of Hospitalization with the JN.1 or HV.1 SARS-CoV-2 Variants Compared to the EG.5 Variant.

Within a multi-state viral genomic surveillance program, we evaluated whether proportions of SARS-CoV-2 infections attributed to the JN.1 variant and to XBB-lineage variants (including HV.1 and EG.5) differed between inpatient and outpatient care settings during periods of cocirculation. Both JN.1 and HV.1 were less likely than EG.5 to account for infections among inpatients versus outpatients (aOR=0.60 [95% CI: 0.43-0.84; p=0.003] and aOR=0.35 [95% CI: 0.21-0.58; p<0.001], respectively). JN.1 and HV.1 variants may be associated with a lower risk of severe illness. The severity of COVID-19 may have attenuated as predominant circulating SARS-CoV-2 lineages shifted from EG.5 to HV.1 to JN.1.

Gut colonization by extended-spectrum ß-lactamase-producing Escherichia coli in dairy herd in Brazil: successful dissemination of a One Health clone.

The overuse of antimicrobials in livestock has contributed to the emergence and selection of clinically relevant multidrug-resistant bacteria. In Brazil, there is no conclusive information on the occurrence of Escherichia coli producing extended-spectrum ß-lactamase (ESßL) in cattle breeding, which is an important sector of agribusiness in this country. Herein, we investigated the presence of ESßL-positive E. coli strains in dairy cattle from a commercial farm with routine practice of therapeutic cephalosporins. Ninety-five rectal swab samples were collected from healthy dairy calves and cows under treatment with ceftiofur. Samples were screened for the presence of ESßL producers, and positive isolates were identified by MALDI-TOF, with subsequent screening for genes encoding ESßL variants by PCR and sequencing. The presence of ESßL (CTX-M-15)-producing E. coli was confirmed in calves, and lactating and dry cows. Most ESßL strains with genetic homologies ≥ 90% were grouped into two major PFGE clusters, confirming the suscessful expansion of clonally related lineages in animals from different lactating cycles, on the same property. Four representatives CTX-M-15-positive E. coli strains had their genomes sequenced, belonging to the clonal complex (CC) 23 and sequence type (ST) 90. A phylogeographical landscape of ST90 was performed revealing a global One Health linkage. Our results highlight the intestinal microbiota of dairy cattle as a hotspot for the spread of critical priority ESßL-producing E. coli and demonstrate that ST90 is an international clone genomically adapted to human and animal hosts, which deserve additional investigation to determine its zoonotic potential and impact in food chain.

Detection of Multiple Human Viruses, including Mpox, Using a Wastewater Surveillance Approach in Brazil.

Sewage surveillance can be used as an effective complementary tool for detecting pathogens in local communities, providing insights into emerging threats and aiding in the monitoring of outbreaks. In this study using qPCR and whole genomic sewage surveillance, we detected the Mpox virus along with other viruses, in municipal and hospital wastewaters in Belo Horizonte, Brazil over a 9-month period (from July 2022 until March 2023). MPXV DNA detection rates varied in our study, with 19.6% (11 out of 56 samples) detected through the hybrid capture method of whole-genome sequencing and 20% (12 out of 60 samples) through qPCR. In hospital wastewaters, the detection rate was higher, at 40% (12 out of 30 samples) compared to 13.3% (4 out of 30 samples) in municipal wastewaters. This variation could be attributed to the relatively low number of MPXV cases reported in the city, which ranged from 106 to 341 cases during the study period, and the dilution effects, given that each of the two wastewater treatment plants (WWTP) investigated serves approximately 1.1 million inhabitants. Additionally, nine other virus families were identified in both hospitals and municipal wastewaters, including Adenoviridade, Astroviridae, Caliciviridae, Picornaviridade, Polyomaviridae, Coronaviridae (which includes SARS-CoV-2), Herspesviridae, Papillomaviridae and Flaviviridae (notably including Dengue). These findings underscore the potential of genomic sewage surveillance as a robust public health tool for monitoring a wide range of viruses circulating in both community and hospitals environments, including MPXV.

Highly sensitive wastewater surveillance of SARS-CoV-2 variants by targeted next-generation amplicon sequencing provides early warning of incursion in Victoria, Australia.

The future of the COVID pandemic and its public health and societal impact will be determined by the profile and spread of emerging variants and the timely identification and response to them. Wastewater surveillance of SARS-CoV-2 has been widely adopted in many countries across the globe and has played an important role in tracking infection levels and providing useful epidemiological information that cannot be adequately captured by clinical testing alone. However, novel variants can emerge rapidly, spread globally, and markedly alter the trajectory of the pandemic, as exemplified by the Delta and Omicron variants. Most mutations linked to the emergence of new SARS-CoV-2 variants are found within variable regions of the SARS-CoV-2 Spike protein. We have developed a duplex hemi-nested PCR method that, coupled with short amplicon sequencing, allows simultaneous typing of two of the most highly variable and informative regions of the Spike gene: the N-terminal domain and the receptor binding motif. Using this method in an operationalized public health program, we identified the first known incursion of Omicron BA.1 into Victoria, Australia and demonstrated how sensitive amplicon sequencing methods can be combined with wastewater surveillance as a relatively low-cost solution for early warning of variant incursion and spread.IMPORTANCEThis study offers a rapid, cost-effective, and sensitive approach for monitoring SARS-CoV-2 variants in wastewater. The method's flexibility permits timely modifications, enabling the integration of emerging variants and adaptations to evolving SARS-CoV-2 genetics. Of particular significance for low- and middle-income regions with limited surveillance capabilities, this technique can potentially be utilized to study a range of pathogens or viruses that possess diverse genetic sequences, similar to influenza.

Rapid identification and subsequent contextualization of an outbreak of methicillin-resistant Staphylococcus aureus in a neonatal intensive care unit using nanopore sequencing.

Outbreaks of methicillin-resistant Staphylococcus aureus (MRSA) are well described in the neonatal intensive care unit (NICU) setting. Genomics has revolutionized the investigation of such outbreaks; however, to date, this has largely been completed retrospectively and has typically relied on short-read platforms. In 2022, our laboratory established a prospective genomic surveillance system using Oxford Nanopore Technologies sequencing for rapid outbreak detection. Herein, using this system, we describe the detection and control of an outbreak of sequence-type (ST)97 MRSA in our NICU. The outbreak was identified 13 days after the first MRSA-positive culture and at a point where there were only two known cases. Ward screening rapidly defined the extent of the outbreak, with six other infants found to be colonized. There was minimal transmission once the outbreak had been detected and appropriate infection control measures had been instituted; only two further ST97 cases were detected, along with three unrelated non-ST97 MRSA cases. To contextualize the outbreak, core-genome single-nucleotide variants were identified for phylogenetic analysis after de novo assembly of nanopore data. Comparisons with global (n=45) and national surveillance (n=35) ST97 genomes revealed the stepwise evolution of methicillin resistance within this ST97 subset. A distinct cluster comprising nine of the ten ST97-IVa genomes from the NICU was identified, with strains from 2020 to 2022 national surveillance serving as outgroups to this cluster. One ST97-IVa genome presumed to be part of the outbreak formed an outgroup and was retrospectively excluded. A second phylogeny was created using Illumina sequencing, which considerably reduced the branch lengths of the NICU isolates on the phylogenetic tree. However, the overall tree topology and conclusions were unchanged, with the exception of the NICU outbreak cluster, where differences in branch lengths were observed. This analysis demonstrated the ability of a nanopore-only prospective genomic surveillance system to rapidly identify and contextualize an outbreak of MRSA in a NICU.

Mathematical modeling of SARS-CoV-2 variant substitutions in European countries: transmission dynamics and epidemiological insights.

Background: Countries across Europe have faced similar evolutions of SARS-CoV-2 variants of concern, including the Alpha, Delta, and Omicron variants. Materials and methods: We used data from GISAID and applied a robust, automated mathematical substitution model to study the dynamics of COVID-19 variants in Europe over a period of more than 2 years, from late 2020 to early 2023. This model identifies variant substitution patterns and distinguishes between residual and dominant behavior. We used weekly sequencing data from 19 European countries to estimate the increase in transmissibility ( Δ ß ) between consecutive SARS-CoV-2 variants. In addition, we focused on large countries with separate regional outbreaks and complex scenarios of multiple competing variants. Results: Our model accurately reproduced the observed substitution patterns between the Alpha, Delta, and Omicron major variants. We estimated the daily variant prevalence and calculated Δ ß between variants, revealing that: ( i ) Δ ß increased progressively from the Alpha to the Omicron variant; ( i i ) Δ ß showed a high degree of variability within Omicron variants; ( i i i ) a higher Δ ß was associated with a later emergence of the variant within a country; ( i v ) a higher degree of immunization of the population against previous variants was associated with a higher Δ ß for the Delta variant; ( v ) larger countries exhibited smaller Δ ß , suggesting regionally diverse outbreaks within the same country; and finally ( v i ) the model reliably captures the dynamics of competing variants, even in complex scenarios. Conclusion: The use of mathematical models allows for precise and reliable estimation of daily cases of each variant. By quantifying Δ ß , we have tracked the spread of the different variants across Europe, highlighting a robust increase in transmissibility trend from Alpha to Omicron. Additionally, we have shown that the geographical characteristics of a country, as well as the timing of new variant entrances, can explain some of the observed differences in variant substitution dynamics across countries.

Genomic surveillance of SARS-CoV-2 and emergence of XBB.1.16 variant in Rajasthan.

PURPOSE: Genomic surveillance of positive SARS-CoV-2 samples is important to monitor the genetic changes occurring in virus, this was enhanced after the WHO designation of XBB.1.16 as a variant under monitoring in March 2023. From 5th February till May 6, 2023 all positive SARS-CoV-2 samples were monitored for genetic changes. METHODS: A total of 1757 samples having Ct value <25 (for E and ORF gene) from different districts of Rajasthan were processed for Next Generation Sequencing (NGS). The FASTA files obtained on sequencing were used for lineage determination using Nextclade and phylogenetic tree construction. RESULTS AND CONCLUSIONS: Sequencing and lineage identification was done in 1624 samples. XBB.1.16 was the predominant lineage in 1413 (87.0%) cases while rest was other XBB (207, 12.74%) and other lineages (4, 0.2%). Of the 1413 XBB.1.16 cases, 57.47% were males and 42.53% were females. Majority (66.53%) belonged to 19-59 year age. 84.15% of XBB.1.16 cases were infected for the first time. Hospitalization was required in only 2.2% cases and death was reported in 5 (0.35%) patients. Most of the cases were symptomatic and the commonest symptoms were fever, cough and rhinorrhea. Co-morbidities were present in 414 (29.3%) cases. Enhanced genomic surveillance helped to rapidly identify the spread of XBB variant in Rajasthan. This in turn helped to take control measures to prevent spread of virus and estimate public health risks of the new variant relative to the previously circulating lineages. XBB variant was found to spread rapidly but produced milder disease.

Genomic surveillance during the first two years of the COVID-19 pandemic - country experience and lessons learned from Türkiye.

Background: Türkiye confirmed its first case of SARS-CoV-2 on March 11, 2020, coinciding with the declaration of the global COVID-19 pandemic. Subsequently, Türkiye swiftly increased testing capacity and implemented genomic sequencing in 2020. This paper describes Türkiye's journey of establishing genomic surveillance as a middle-income country with limited prior sequencing capacity and analyses sequencing data from the first two years of the pandemic. We highlight the achievements and challenges experienced and distill globally relevant lessons. Methods: We tracked the evolution of the COVID-19 pandemic in Türkiye from December 2020 to February 2022 through a timeline and analysed epidemiological, vaccination, and testing data. To investigate the phylodynamic and phylogeographic aspects of SARS-CoV-2, we used Nextstrain to analyze 31,629 high-quality genomes sampled from seven regions nationwide. Results: Türkiye's epidemiological curve, mirroring global trends, featured four distinct waves, each coinciding with the emergence and spread of variants of concern (VOCs). Utilizing locally manufactured kits to expand testing capacity and introducing variant-specific quantitative reverse transcription polymerase chain reaction (RT-qPCR) tests developed in partnership with a private company was a strategic advantage in Türkiye, given the scarcity and fragmented global supply chain early in the pandemic. Türkiye contributed more than 86,000 genomic sequences to global databases by February 2022, ensuring that Turkish data was reflected globally. The synergy of variant-specific RT-qPCR kits and genomic sequencing enabled cost-effective monitoring of VOCs. However, data analysis was constrained by a weak sequencing sampling strategy and fragmented data management systems, limiting the application of sequencing data to guide the public health response. Phylodynamic analysis indicated that Türkiye's geographical position as an international travel hub influenced both national and global transmission of each VOC despite travel restrictions. Conclusion: This paper provides valuable insights into the testing and genomic surveillance systems adopted by Türkiye during the COVID-19 pandemic, proposing important lessons for countries developing national systems. The findings underscore the need for robust testing and sampling strategies, streamlined sample referral, and integrated data management with metadata linkage and data quality crucial for impactful epidemiological analysis. We recommend developing national genomic surveillance strategies to guide sustainable and integrated expansion of capacities built for COVID-19 and to optimize the effective utilization of sequencing data for public health action.