9 research outputs found

    Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

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    Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

    Hospital admission and emergency care attendance risk for SARS-CoV-2 delta (B.1.617.2) compared with alpha (B.1.1.7) variants of concern: a cohort study

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    Background: The SARS-CoV-2 delta (B.1.617.2) variant was first detected in England in March, 2021. It has since rapidly become the predominant lineage, owing to high transmissibility. It is suspected that the delta variant is associated with more severe disease than the previously dominant alpha (B.1.1.7) variant. We aimed to characterise the severity of the delta variant compared with the alpha variant by determining the relative risk of hospital attendance outcomes. Methods: This cohort study was done among all patients with COVID-19 in England between March 29 and May 23, 2021, who were identified as being infected with either the alpha or delta SARS-CoV-2 variant through whole-genome sequencing. Individual-level data on these patients were linked to routine health-care datasets on vaccination, emergency care attendance, hospital admission, and mortality (data from Public Health England's Second Generation Surveillance System and COVID-19-associated deaths dataset; the National Immunisation Management System; and NHS Digital Secondary Uses Services and Emergency Care Data Set). The risk for hospital admission and emergency care attendance were compared between patients with sequencing-confirmed delta and alpha variants for the whole cohort and by vaccination status subgroups. Stratified Cox regression was used to adjust for age, sex, ethnicity, deprivation, recent international travel, area of residence, calendar week, and vaccination status. Findings: Individual-level data on 43 338 COVID-19-positive patients (8682 with the delta variant, 34 656 with the alpha variant; median age 31 years [IQR 17–43]) were included in our analysis. 196 (2·3%) patients with the delta variant versus 764 (2·2%) patients with the alpha variant were admitted to hospital within 14 days after the specimen was taken (adjusted hazard ratio [HR] 2·26 [95% CI 1·32–3·89]). 498 (5·7%) patients with the delta variant versus 1448 (4·2%) patients with the alpha variant were admitted to hospital or attended emergency care within 14 days (adjusted HR 1·45 [1·08–1·95]). Most patients were unvaccinated (32 078 [74·0%] across both groups). The HRs for vaccinated patients with the delta variant versus the alpha variant (adjusted HR for hospital admission 1·94 [95% CI 0·47–8·05] and for hospital admission or emergency care attendance 1·58 [0·69–3·61]) were similar to the HRs for unvaccinated patients (2·32 [1·29–4·16] and 1·43 [1·04–1·97]; p=0·82 for both) but the precision for the vaccinated subgroup was low. Interpretation: This large national study found a higher hospital admission or emergency care attendance risk for patients with COVID-19 infected with the delta variant compared with the alpha variant. Results suggest that outbreaks of the delta variant in unvaccinated populations might lead to a greater burden on health-care services than the alpha variant. Funding: Medical Research Council; UK Research and Innovation; Department of Health and Social Care; and National Institute for Health Research

    Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity

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    Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

    Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study

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    Background The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility. Methods We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, Rt, for the two incidence estimates. Findings From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in reported symptoms or disease duration associated with B.1.1.7. For the same period, possible reinfections were identified in 249 (0·7% [95% CI 0·6–0·8]) of 36 509 app users who reported a positive swab test before Oct 1, 2020, but there was no evidence that the frequency of reinfections was higher for the B.1.1.7 variant than for pre-existing variants. Reinfection occurrences were more positively correlated with the overall regional rise in cases (Spearman correlation 0·56–0·69 for South East, London, and East of England) than with the regional increase in the proportion of infections with the B.1.1.7 variant (Spearman correlation 0·38–0·56 in the same regions), suggesting B.1.1.7 does not substantially alter the risk of reinfection. We found a multiplicative increase in the Rt of B.1.1.7 by a factor of 1·35 (95% CI 1·02–1·69) relative to pre-existing variants. However, Rt fell below 1 during regional and national lockdowns, even in regions with high proportions of infections with the B.1.1.7 variant. Interpretation The lack of change in symptoms identified in this study indicates that existing testing and surveillance infrastructure do not need to change specifically for the B.1.1.7 variant. In addition, given that there was no apparent increase in the reinfection rate, vaccines are likely to remain effective against the B.1.1.7 variant. Funding Zoe Global, Department of Health (UK), Wellcome Trust, Engineering and Physical Sciences Research Council (UK), National Institute for Health Research (UK), Medical Research Council (UK), Alzheimer's Society

    Genomic assessment of quarantine measures to prevent SARS-CoV-2 importation and transmission

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    Mitigation of SARS-CoV-2 transmission from international travel is a priority. We evaluated the effectiveness of travellers being required to quarantine for 14-days on return to England in Summer 2020. We identified 4,207 travel-related SARS-CoV-2 cases and their contacts, and identified 827 associated SARS-CoV-2 genomes. Overall, quarantine was associated with a lower rate of contacts, and the impact of quarantine was greatest in the 16–20 age-group. 186 SARS-CoV-2 genomes were sufficiently unique to identify travel-related clusters. Fewer genomically-linked cases were observed for index cases who returned from countries with quarantine requirement compared to countries with no quarantine requirement. This difference was explained by fewer importation events per identified genome for these cases, as opposed to fewer onward contacts per case. Overall, our study demonstrates that a 14-day quarantine period reduces, but does not completely eliminate, the onward transmission of imported cases, mainly by dissuading travel to countries with a quarantine requirement

    Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

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    AbstractUnderstanding 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.</jats:p

    Complexities of (U-Th)/he zircon thermochronology through the lens of zonation and deep time

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    The zircon (U-Th)/He (zircon-He) system is a dating tool used to date low-temperature geologic events that occur in the upper four kilometers of Earth’s crust. The zircon-He system is defined by the kinetic interactions of radiation damage accumulation and annealing, and He diffusion. The kinetics of the zircon-He system were developed using idealized samples and conditions, which do not always translate well to the complex samples and settings that researchers attempt to date when using the zircon-He system. I seek to better understand how the defining elements of the zircon-He system interact when applied to complex natural samples and deep-time thermal histories. I first explore the role of radiation damage zonation in zircon on annealing kinetics. Annealing is the thermally activated process by which chemical bonds reform after being broken by radiation damage. Radiation damage directly impacts the diffusion of He from the crystal lattice and is a key factor in defining the kinetics of the zircon (U-Th)/He system. Damage accumulates within a crystal as a function of time and U and Th concentration. The total level of radiation damage in a zircon crystal is governed by the thermally-activated, kinetic process of annealing, which in turn influences the interpretation of zircon (U-Th)/He dates for thermal histories. Several annealing models have been defined for the zircon system based on measurements in natural crystals; however, few studies have investigated how multiple levels of radiation damage due to zonation of actinides within a crystal may influence the annealing process. Here I use Raman spectroscopy to map the full-width half maximum (FWHM) of the 3(SiO4) band, a proxy for radiation damage, in zircon crystals from the Lucerne pluton (Maine, USA) with heterogeneous distributions of U and Th. I compare FWHM maps before and after annealing these crystals at laboratory times and temperatures. These maps show that each damage zone within a single zircon acts as an isolated domain that is dictated by an independent set of annealing kinetics. Thermally activated annealing decreases radiation damage in all radiation damage zones; however, the rate of annealing is not consistent across all zones. I identify specific FWHM damage levels present post-annealing regardless of laboratory time temperature conditions: FWHM modes at 2-5 cm-1, 10-15 cm-1, and 25-30 cm-1. I attribute these persistent damage modes to variable annealing kinetics that are partially dependent on the level of pre-annealing damage, combined with the inability of high-damage crystals, or zones within crystals, to fully recover their crystallinity. These findings therefore show that zircon crystals with non-uniform distributions of U and Th can anneal to create long-lived damage zones at specific damage levels, which has implications for treating the zircon (U-Th)/He chronometer as a multi-domain diffusion system. Next, I apply the zircon-He system to the geologically complex deep-time thermal history of the Eastern Grand Canyon. I demonstrate the power of zircon-He thermochronology to resolve cooling events of Precambrian basement exposures below the Great Unconformity surface in the Grand Canyon. I combine new zircon-He data with previous 40Ar/39Ar mica and K-spar results to model the 1 Ga, thermal history of these basement rocks. Forward and inverse models of zircon-He date-effective uranium (eU) concentration, a proxy for radiation damage, suggest that the main phase of Precambrian cooling to <200 °C was between 1350 and 1250 Ma, after the Yavapai orogeny. This result agrees with K-spar 40Ar/39Ar thermochronology showing rapid post-1400 Ma cooling and both are consistent with the 1255 Ma depositional age for the Unkar Group. The data and models are highly sensitive to late-stage reheating due to burial beneath ~ 3-4 km of Phanerozoic strata prior to the Laramide orogeny; models that best match observed date-eU correlations show maximum temperatures of 140-160 °C, in agreement with apatite (U-Th)/He and fission-track data. Forward and inverse models also test for the age of carving of Grand Canyon; they support a multi-stage cooling model involving 25-15 Ma cooling from 100 to 50 °C during partial carving of Eastern Grand Canyon, with post- 6 Ma rapid cooling indicated by 3 to 7 Ma zircon-He dates over a wide range of high eU. The zircon-He data capture basement exhumation below the Great Unconformity during the Mesoproterozoic (1300-1250 Ma), and “young” (20-0 Ma) carving of Grand Canyon. Finally, I assess the role of zonation in creating secondary dispersion in zircon-He data. High-levels of secondary dispersion can be seen in the zircon-He data collected from the Eastern Grand Canyon. Dispersion in zircon-He data can lead to greater levels of uncertainty in modeled thermal histories. Dispersive datapoints were determined as those datapoints that deviate from the average date-eU trendline of the binned data by more than 2 standard deviations. All dispersive datapoints were targeted as potentially having severe zonation, which can create unaccounted for complexities in the kinetics applied to the zircon-He system. CL images were collected for zircon separates from the Eastern Grand Canyon and showed a range of zonation patterns from no zonation and concentric zonation to chaotic, non-concentric zonation. I ran two inverse models to see if the addition of zonation information increases the probability of various thermal events in the Eastern Grand Canyon thermal history. One inverse model used data without any zonation information and the other used data with zonation information based on anonymous zonation styles identified in CL image. I also created forward models to see if the level of secondary dispersion could be modeled by artificially creating zircon-He data with zoned eU information data. I found that the addition of zonation information to my inverse models does not increase the probability of known thermal events but creates a less complex thermal history. The artificially zoned data does not fully explain the level of secondary dispersion seen in the measured zircon-He data. Of the seven dispersive datapoints identified in the zircon-He data, only three datapoints were captured by the artificially zoned data, leaving the two oldest and two youngest dispersive datapoints unexplained. I attribute the decrease in complexity of the zoned thermal history, and the inability of artificially zoned data to account for all secondary dispersion, to an overly simplified morphology of zonation in both my inverse and forward models. I suggest that He diffusion kinetics should include the option for the use of a multi-domain diffusion (MDD) model where domains are separated by fast-pathways of diffusion. The introduction of a non-nested MDD would allow for zonation information from chaotic zones to be better modeled and could ultimately reduce dispersion in zircon-He data. The collective results of this dissertation show both the utility of zircon-He thermochronology and areas where the method can be expanded and improved upon. Proper kinetic models for describing radiation damage annealing and He diffusion in zircon with heterogeneous uranium and thorium distribution would allow for zircon-He users to better understand the complexities and dispersion found in their zircon-He data. The potential for zoned zircon to produce additional dates and thermal history information using the zircon-He method, particularly in deep-time settings, makes improving the communal understanding and application of the underlying kinetics of the zircon-He methods all the more imperative.U of I OnlyAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD syste

    Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity