Early Transmission Dynamics, Spread, and Genomic Characterization of SARS-CoV-2 in Panama.
Ontology highlight
ABSTRACT:
SUBMITTER: Franco D
PROVIDER: S-EPMC7853578 | biostudies-literature | 2021 Feb
REPOSITORIES: biostudies-literature
Publications
Early Transmission Dynamics, Spread, and Genomic Characterization of SARS-CoV-2 in Panama.
Franco Danilo D Gonzalez Claudia C Abrego Leyda E LE Carrera Jean-Paul JP Diaz Yamilka Y Caicedo Yaset Y Moreno Ambar A Chavarria Oris O Gondola Jessica J Castillo Marlene M Valdespino Elimelec E Gaitán Melissa M Martínez-Mandiche Jose J Hayer Lizbeth L Gonzalez Pablo P Lange Carmen C Molto Yadira Y Mojica Dalis D Ramos Ruben R Mastelari Maria M Cerezo Lizbeth L Moreno Lourdes L Donnelly Christl A CA Pascale Juan Miguel JM Faria Nuno Rodrigues NR Lopez-Verges Sandra S Martinez Alexander A AA
Emerging infectious diseases 20210201 2
We report an epidemiologic analysis of 4,210 cases of infection with severe acute respiratory syndrome coronavirus 2 and genetic analysis of 313 new near-complete virus genomes in Panama during March 9-April 16, 2020. Although containment measures reduced R<sub>0</sub> and R<sub>t</sub>, they did not interrupt virus spread in the country. ...[more]
Similar Datasets
Project description:BackgroundGenomic epidemiology has helped reconstruct the global and regional movement of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there is still a lack of understanding of SARS-CoV-2 spread in some of the world's least developed countries (LDCs).MethodsTo begin to address this disparity, we studied the transmission dynamics of the virus in Bangladesh during the country's first COVID-19 wave by analysing case reports and whole-genome sequences from all eight divisions of the country.ResultsWe detected > 50 virus introductions to the country during the period, including during a period of national lockdown. Additionally, through discrete phylogeographic analyses, we identified that geographical distance and population -density and/or -size influenced virus spatial dispersal in Bangladesh.ConclusionsOverall, this study expands our knowledge of SARS-CoV-2 genomic epidemiology in Bangladesh, shedding light on crucial transmission characteristics within the country, while also acknowledging resemblances and differences to patterns observed in other nations.
| S-EPMC11562509 | biostudies-literature
Project description:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants are a fatal pathogen resulting in substantial morbidity and mortality, and posing a great threat to human health with epidemics and pandemics.MethodsNext-generation sequencing (NGS) was performed to investigate the SARS-CoV-2 genomic characterization. Phylogenetic analysis of SARS-CoV-2 genomes was used to probe the evolutionary. Homology protein structure modelling was done to explore potential effect of the mutations.ResultsThe eighty genome sequences of SARS-CoV-2 obtained from the thirty-nine patients with COVID-19. A novel variant with mutation H625R concomitant with S50L in spike glycoprotein had been identified. Phylogenetic analysis revealed that SARS-CoV-2 variants belong to several distinct lineages. Homology modelling indicated that variant with mutation H625R and S50L increases flexibility of S1 subunit.ConclusionsSARS-CoV-2 genomes are constantly evolving by accumulation of point mutations. The amino acid H625R in combination with S50L may have a significant impact on the interaction between spike glycoprotein and ACE2.
| S-EPMC10731232 | biostudies-literature
Project description:Understanding the effectiveness of infection control methods in reducing and preventing SARS-CoV-2 transmission in healthcare settings is of high importance. We sequenced SARS-CoV-2 genomes for patients and healthcare workers (HCWs) across multiple geographically distinct UK hospitals, obtaining 173 high-quality SARS-CoV-2 genomes. We integrated patient movement and staff location data into the analysis of viral genome data to understand spatial and temporal dynamics of SARS-CoV-2 transmission. We identified eight patient contact clusters (PCC) with significantly increased similarity in genomic variants compared to non-clustered samples. Incorporation of HCW location further increased the number of individuals within PCCs and identified additional links in SARS-CoV-2 transmission pathways. Patients within PCCs carried viruses more genetically identical to HCWs in the same ward location. SARS-CoV-2 genome sequencing integrated with patient and HCW movement data increases identification of outbreak clusters. This dynamic approach can support infection control management strategies within the healthcare setting.
| S-EPMC8009659 | biostudies-literature
Project description:From February to April 2020, Lombardy (Italy) reported the highest numbers of SARS-CoV-2 cases worldwide. By analyzing 346 whole SARS-CoV-2 genomes, we demonstrate the presence of seven viral lineages in Lombardy, frequently sustained by local transmission chains and at least two likely to have originated in Italy. Six single nucleotide polymorphisms (five of them non-synonymous) characterized the SARS-CoV-2 sequences, none of them affecting N-glycosylation sites. The seven lineages, and the presence of local transmission clusters within three of them, revealed that sustained community transmission was underway before the first COVID-19 case had been detected in Lombardy.
| S-EPMC7815831 | biostudies-literature
Project description:The highly pathogenic virus SARS-CoV-2 has shattered the healthcare system of the world causing the COVID-19 pandemic since first detected in Wuhan, China. Therefore, scrutinizing the genome structure and tracing the transmission of the virus has gained enormous interest in designing appropriate intervention strategies to control the pandemic. In this report, we examined 4,622 sequences from Bangladesh and found that they belonged to thirty-five major PANGO lineages, while Delta alone accounted for 39%, and 78% were from just four primary lineages. Our research has also shown Dhaka to be the hub of viral transmission and observed the virus spreading back and forth across the country at different times by building a transmission network. The analysis resulted in 7,659 unique mutations, with an average of 24.61 missense mutations per sequence. Moreover, our analysis of genetic diversity and mutation patterns revealed that eight genes were under negative selection pressure to purify deleterious mutations, while three genes were under positive selection pressure. Together with an ongoing genomic surveillance program, these data will contribute to a better understanding of SARS-CoV-2, as well as its evolution pattern and pandemic characteristics in Bangladesh.
| S-EPMC9548531 | biostudies-literature
Project description:The coronavirus disease 2019 (COVID-19) pandemic has greatly damaged human society, but the origins and early transmission patterns of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogen remain unclear. Here, we reconstructed the transmission networks of SARS-CoV-2 during the first three and six months since its first report based on ancestor-offspring relationships using BANAL-52-referenced mutations. We explored the position (i.e., root, middle, or tip) of early detected samples in the evolutionary tree of SARS-CoV-2. In total, 6 799 transmission chains and 1 766 transmission networks were reconstructed, with chain lengths ranging from 1-9 nodes. The root node samples of the 1 766 transmission networks were from 58 countries or regions and showed no common ancestor, indicating the occurrence of many independent or parallel transmissions of SARS-CoV-2 when first detected (i.e., all samples were located at the tip position of the evolutionary tree). No root node sample was found in any sample ( n=31, all from the Chinese mainland) collected in the first 15 days from 24 December 2019. Results using six-month data or RaTG13-referenced mutation data were similar. The reconstruction method was verified using a simulation approach. Our results suggest that SARS-CoV-2 may have already been spreading independently worldwide before the outbreak of COVID-19 in Wuhan, China. Thus, a comprehensive global survey of human and animal samples is essential to explore the origins of SARS-CoV-2 and its natural reservoirs and hosts.
| S-EPMC10236306 | biostudies-literature
Project description:Understanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.
| S-EPMC8826310 | biostudies-literature
Project description:With the progression of the global SARS-CoV-2 pandemic, the new variants have become more infectious and continue spreading at a higher rate than pre-existing ones. Thus, we conducted a study to explore the epidemiology of emerging variants of SARS-CoV-2 that circulated in Bangladesh from December 2020 to September 2021, representing the 2nd and 3rd waves. We collected new cases and deaths per million daily data with the reproduction rate. We retrieved 928 SARS-CoV-2 sequences from GISAID and performed phylogenetic tree construction and mutation analysis. Case counts were lower initially at the end of 2020, during January-February and April-May 2021, whereas the death toll reached the highest value of 1.587 per million on the first week of August and then started to decline. All the variants (α, β, δ, η) were prevalent in the capital city, Dhaka, with dispersion to large cities, such as Sylhet and Chattogram. The B.1.1.25 lineage was prevalent during December 2020, but the B.1.617.2/δ variant was later followed by the B.1.351/β variant. The phylogeny revealed that the various strains found in Bangladesh could be from numerous countries. The intra-cluster and inter-cluster communication began in Bangladesh soon after the virus arrived. The prominent amino acid substitution was D614G from December 2020 to July 2021 (93.5 to 100%). From February-April, one of the VOC's important mutations, N501Y substitution, was also estimated at 51.8%, 76.1%, and 65.1% for the α, β and γ variants, respectively. The γ variant's unique mutation K417T was detected only at 1.8% in February. Another frequent mutation was P681R, a salient feature of the δ variant, detected in June (88.2%) and July (100%). Furthermore, only one γ variant was detected during the entire second and third wave, whereas no η variant was observed in this period. This rapid growth in the number of variants identified across Bangladesh shows virus adaptation and a lack of strict quarantine, prompting periodic genomic surveillance to foresee the spread of new variants, if any, and to take preventive measures as soon as possible.
| S-EPMC9414541 | biostudies-literature
Project description:Since the emergence of COVID-19, a series of non-pharmaceutical interventions (NPIs) has been implemented by governments and public health authorities world-wide to control and curb the ongoing pandemic spread. From that perspective, Belarus is one of a few countries with a relatively modern healthcare system, where much narrower NPIs have been put in place. Given the uniqueness of this Belarusian experience, the understanding its COVID-19 epidemiological dynamics is essential not only for the local assessment, but also for a better insight into the impact of different NPI strategies globally. In this work, we integrate genomic epidemiology and surveillance methods to investigate the emergence and spread of SARS-CoV-2 in the country. The observed Belarusian SARS-CoV-2 genetic diversity originated from at least eighteen separate introductions, at least five of which resulted in on-going domestic transmissions. The introduction sources represent a wide variety of regions, although the proportion of regional virus introductions and exports from/to geographical neighbors appears to be higher than for other European countries. Phylodynamic analysis indicates a moderate reduction in the effective reproductive number ℛ e after the introduction of limited NPIs, with the reduction magnitude generally being lower than for countries with large-scale NPIs. On the other hand, the estimate of the Belarusian ℛ e at the early epidemic stage is comparable with this number for the neighboring ex-USSR country of Ukraine, where much broader NPIs have been implemented. The actual number of cases by the end of May, 2020 was predicted to be 2-9 times higher than the detected number of cases.
| S-EPMC8077579 | biostudies-literature
Project description:The spread of SARS-CoV-2 has been geographically uneven. To understand the drivers of this spatial variation in SARS-CoV-2 transmission, in particular the role of stochasticity, we used the early stages of the SARS-CoV-2 invasion in Washington state as a case study. We analysed spatially-resolved COVID-19 epidemiological data using two distinct statistical analyses. The first analysis involved using hierarchical clustering on the matrix of correlations between county-level case report time series to identify geographical patterns in the spread of SARS-CoV-2 across the state. In the second analysis, we used a stochastic transmission model to perform likelihood-based inference on hospitalised cases from five counties in the Puget Sound region. Our clustering analysis identifies five distinct clusters and clear spatial patterning. Four of the clusters correspond to different geographical regions, with the final cluster spanning the state. Our inferential analysis suggests that a high degree of connectivity across the region is necessary for the model to explain the rapid inter-county spread observed early in the pandemic. In addition, our approach allows us to quantify the impact of stochastic events in determining the subsequent epidemic. We find that atypically rapid transmission during January and February 2020 is necessary to explain the observed epidemic trajectories in King and Snohomish counties, demonstrating a persisting impact of stochastic events. Our results highlight the limited utility of epidemiological measures calculated over broad spatial scales. Furthermore, our results make clear the challenges with predicting epidemic spread within spatially extensive metropolitan areas, and indicate the need for high-resolution mobility and epidemiological data.
| S-EPMC10335681 | biostudies-literature