ABSTRACT
ABSTRACT Background: SARS-CoV-2 has evolved rapidly, resulting in emergence of lineages with competitive advantage over one another. Co-infections with different SARS-CoV-2 lineages can give rise to recombinant lineages. To date, XBB lineage is the most widespread recombinant lineage worldwide, with the recently named XBB.1.16 lineage causing a surge in the number of COVID-19 cases in India. Methodology: The present study involved retrieval of SARS-CoV-2 genome sequences from India (between 1st December 2022 and 8th April 2023) through GISAID; sequences were curated, followed by lineage and phylogenetic analysis. Demographic and clinical data from Maharashtra, India were collected telephonically, recorded in Microsoft (R) Excel, and analysed using IBM (R) SPSS statistics, version 29.0.0.0 (241). Results: A total of 2,944 sequences were downloaded from the GISAID database, of which 2,856 were included in the study following data curation. The sequences from India were dominated by the XBB.1.16* lineage (36.17%) followed by XBB.2.3* (12.11%) and XBB.1.5* (10.36%). Of the 2,856 cases, 693 were from Maharashtra; 386 of these were included in the clinical study. The clinical features of COVID-19 cases with XBB.1.16* infection (XBB.1.16* cases, 276 in number) showed that 92% of those had a symptomatic disease, with fever (67%), cough (42%), rhinorrhoea (33.7%), body ache (14.5%) and fatigue (14.1%) being the most common symptoms. Presence of comorbidity was found in 17.7% of the XBB.1.16* cases. Among the XBB.1.16* cases, 91.7% were vaccinated with at least one dose of vaccine against COVID-19. While 74.3% of XBB.1.16* cases were home-isolated; 25.7% needed hospitalization/institutional quarantine, of these, 33.8% needed oxygen therapy. Out of 276 XBB.1.16* cases, seven (2.5%) cases succumbed to the disease. Majority of XBB.1.16* cases who died belonged to an elderly age group (60 years and above), had underlying comorbid condition/s, and needed supplemental oxygen therapy. The clinical features of COVID-19 cases infected with other co-circulating Omicron variants were similar to XBB.1.16* cases. Conclusion: The study reveals that XBB.1.16* lineage has become the most predominant SARS-CoV-2 lineage in India. The study also shows that the clinical features and outcome of XBB.1.16* cases were similar to those of other co-circulating Omicron lineage infected cases in Maharashtra, India. Keywords: XBB.1.16, XBB.1.16.1, XBB.1.16*, XBB, Omicron variant, COVID-19, SARS-CoV-2, Clinical features
Subject(s)
Coinfection , Pain , Fever , Cough , COVID-19 , FatigueABSTRACT
The COVID-19 pandemic has emphasized the urgency for rapid public health surveillance methods in early detection and monitoring of the transmission of infectious diseases. The wastewater-based epidemiology (WBE) has emerged as a promising tool to analyze and enumerate the prevalence of infectious pathogens in a population ahead of time. In the present study, real time quantitative polymerase chain reaction (RT-qPCR) and Illumina sequencing was performed to determine the SARS-CoV-2 load trend and dynamics of variants over a longitudinal scale in 442 wastewater (WW) samples collected from 10 sewage treatment plants (STPs) of Pune city, India, during November 2021 to April-2022. In total 426 distinct lineages representing 17 highly transmissible variants of SARS-CoV-2 were identified. The SARS-CoV-2 Omicron variant fragments were detected in WW samples prior to its detection in clinical cases. Moreover, highly contagious sub-lineages of Omicron, such as BA.2.12 (0.8-0.25%), BA.2.38 (0.8-1.0%), BA.2.75 (0.01-0.02%), BA.3 (0.09-6.3%), BA.4 (0.24-0.29%), and XBB (0.01-13.7%) fragments were significantly detected. The longitudinal analysis also suggested the presence of the BA.5 lineage in November 2021, which was not reported in the clinical settings throughout the duration of this study, indicative of silent variant persistence. Overall, the present study demonstrated the practicality of WBE in early detection of SARS CoV-2 variants, which could be useful in tracking future outbreaks of SARS-CoV-2. Such approaches could be implicated in the monitoring of the infectious agents before they appear in clinical cases.
Subject(s)
Communicable Diseases , COVID-19ABSTRACT
Background: The SARS-CoV-2 has evolved to produce new variants causing successive waves of infection. Currently, six variants are being monitored by the World Health Organization that are replacing BA.5. These include BQ.1*, BA.5 with one or several of five mutations (R346X, K444X, V445X, N450D, N460X), BA.2.75*, XBB*, BA.4.6*, and BA.2.30.2*. BQ.1 and XBB variants are more immune evasive and have spread quickly throughout the world. With the concern of the potential severity of infections caused by these variants, the present study describes the clinical characteristics and outcomes of these major variants in Maharashtra. Material and Methods: A total of 1039 Reverse Transcriptase-Polymerase Chain Reaction (RT-PCR) positive SARS-CoV-2 samples, with a cycle threshold value (Ct) less than 25, were processed for SARS-CoV-2 whole genome sequencing between 10th July 2022 and 10th December 2022. All corresponding demographic and clinical data were recorded and analyzed using MicrosoftTM ExcelTM and Epi InfoTM. Results: Out of 1039 samples sequenced, 829 (79.79%) were assigned Pango lineages, of which BA.2.75 (67.31%) was the predominant Omicron variant, followed by the XBB* (17.13%), BA.2.38* (5.43%), BA.2.10* (3.62%) and BA.5* (3.50%). A total of 494 cases were contacted telephonically, of which 455 (92.11%) were symptomatic with mild symptoms. Fever (78.46%) was the most common symptom, followed by rhinorrhoea (46.37%), cough (42.20%), myalgia (19.56%) and fatigue (18.24%). Of the 494 cases, 379 (76.72%) cases recovered at home, and 115 (23.28%) were institutionally quarantined/ hospitalized. Among the home-isolated and hospitalized cases, 378 (99.74%) and 101 (87.83%) recovered with symptomatic treatment, whereas 01 (0.26%) and 14 (12.17%) succumbed to the disease, respectively. Of the 494 cases, 449 (90.89%) were vaccinated with at least one dose of the COVID-19 vaccine, 40 (8.10%) were unvaccinated, and for 05 (1.01%) cases, vaccine data was not available. Conclusion: The current study indicates that the XBB* variant is causing mild disease in India. However, as XBB* possess both immune-escape and infectivity-enhancing mutations, it has the potential to spread to other parts of the world rapidly.
Subject(s)
Fever , Myalgia , COVID-19 , FatigueABSTRACT
The modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Genomic surveillance has come to the forefront during the coronavirus disease 2019 (COVID-19) pandemic at both local and global scales to identify variants of concern. Tracking variants of concern (VOC) is integral to understanding the evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in space and time. Combining phylogenetics with epidemiological data like case incidence, spatial spread, and transmission dynamics generates actionable information. Here we discuss the genome surveillance done in Pune, India, through sequencing 10,496 samples from infected individuals and integrating them with multiple heterogeneous outbreak data. The rise and fall of VOCs along with shifting transmission dynamics in the time interval of December 2020 to March 2022 was identified. Population-based estimates of the proportion of circulating variants indicated the second and third peak of infection in Pune to be driven by VOCs Kappa (B.1.617.1), Delta (B.1.617.2), and Omicron (B.1.1.529) respectively. Integrating single nucleotide polymorphism changes across all sequenced genomes identified C (Cytosine) > T (Thymine) and G (Guanine) > T (Thymine) substitutions to dominate with higher rates of adaptive evolution in Spike (S), RNA-dependent RNA polymerase (RdRp), and Nucleocapsid (N) genes. Spike Protein mutational profiling during and pre-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified specific recombinant X lineages, XZ, XQ, and XM. BA.1 from Pune was found to be highly divergent by global sequence alignment and hierarchical clustering. Our ''band of five'' outbreak data analytics which includes the integration of five heterogeneous data types indicates that a strong surveillance system with comprehensive high-quality metadata was critical to understand the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. We anticipate the use of such integrated workflows to be critical for pandemic preparedness in the future.
Subject(s)
Coronavirus Infections , COVID-19ABSTRACT
Background: The SARS-CoV-2 Delta variant (B.1.617.2) was first detected in India in late 2020 and soon became the predominant lineage owing to its high transmissibility. Over time, the virus has acquired mutations and has evolved into many new sub-lineages. AY.4 is one such sub-lineage that grew in frequency globally. Therefore, we aimed to compare the severity of infection due to Delta sub-lineages to Delta infections in Pune, Maharashtra, India. Material and Methods: Whole-genome sequencing and analysis of 255 SARS-CoV-2 positive samples, collected between 1st August to 1st September 2021, by BJ Government Medical College, Pune, was carried out at the Indian Institute of Science Education and Research (IISER), Pune and the Council of Scientific and Industrial Research-Institute of Genomics and Integrative Biology (CSIR-IGIB), New Delhi. Individual-level data on these patients were collected from ICMR COVID-19 Data Portal. Additional information regarding the presence of any symptoms, comorbidities, hospitalization, international travel history within 14 days and vaccination status was collected by telephonic interview with each patient by the BJGMC Sequencing Team.