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1.
Clin Infect Dis ; 75(2): 305-313, 2022 08 25.
Article in English | MEDLINE | ID: covidwho-1708892

ABSTRACT

BACKGROUND: Post-vaccination infections challenge the control of the coronavirus disease 2019 (COVID-19) pandemic. METHODS: We matched 119 cases of post-vaccination severe acute respiratory syndrome coronavirus 2 infection with BNT162b2 mRNA or ChAdOx1 nCOV-19 to 476 unvaccinated patients with COVID-19 (September 2020-March 2021) according to age and sex. Differences in 60-day all-cause mortality, hospital admission, and hospital length of stay were evaluated. Phylogenetic, single-nucleotide polymorphism (SNP), and minority variant allele (MVA) full-genome sequencing analysis was performed. RESULTS: Overall, 116 of 119 cases developed COVID-19 post-first vaccination dose (median, 14 days). Thirteen of 119 (10.9%) cases and 158 of 476 (33.2%) controls died (P < .001), corresponding to the 4.5 number needed to treat (NNT). Multivariably, vaccination was associated with a 69.3% (95% confidence interval [CI]: 45.8 to 82.6) relative risk (RR) reduction in mortality. Similar results were seen in subgroup analysis for patients with infection onset ≥14 days after first vaccination and across vaccine subgroups. Hospital admissions (odds ratio, 0.80; 95% CI: .51 to 1.28) and length of stay (-1.89 days; 95% CI: -4.57 to 0.78) were lower for cases, while cycle threshold values were higher (30.8 vs 28.8, P = .053). B.1.1.7 was the predominant lineage in cases (100 of 108, 92.6%) and controls (341 of 446, 76.5%). Genomic analysis identified 1 post-vaccination case that harbored the E484K vaccine-escape mutation (B.1.525 lineage). CONCLUSIONS: Previous vaccination reduces mortality when B.1.1.7 is the predominant lineage. No significant lineage-specific genomic changes during phylogenetic, SNP, and MVA analysis were detected.


Subject(s)
COVID-19 , SARS-CoV-2 , BNT162 Vaccine , Case-Control Studies , ChAdOx1 nCoV-19 , Genomics , Humans , Phylogeny , SARS-CoV-2/genetics , Vaccination
2.
J Med Virol ; 94(1): 161-172, 2022 01.
Article in English | MEDLINE | ID: covidwho-1544335

ABSTRACT

Detailed information on intrahost viral evolution in SARS-CoV-2 with and without treatment is limited. Sequential viral loads and deep sequencing of SARS-CoV-2 from the upper respiratory tract of nine hospitalized children, three of whom were treated with remdesivir, revealed that remdesivir treatment suppressed viral load in one patient but not in a second infected with an identical strain without any evidence of drug resistance found. Reduced levels of subgenomic RNA during treatment of the second patient, suggest an additional effect of remdesivir on viral replication. Haplotype reconstruction uncovered persistent SARS-CoV-2 variant genotypes in four patients. These likely arose from within-host evolution, although superinfection cannot be excluded in one case. Although our dataset is small, observed sample-to-sample heterogeneity in variant frequencies across four of nine patients suggests the presence of discrete viral populations in the lung with incomplete population sampling in diagnostic swabs. Such compartmentalization could compromise the penetration of remdesivir into the lung, limiting the drugs in vivo efficacy, as has been observed in other lung infections.


Subject(s)
Adenosine Monophosphate/analogs & derivatives , Alanine/analogs & derivatives , Antiviral Agents/therapeutic use , COVID-19 Drug Treatment , COVID-19/virology , Evolution, Molecular , SARS-CoV-2/genetics , Adenosine Monophosphate/therapeutic use , Adolescent , Alanine/therapeutic use , Child , Child, Preschool , Drug Resistance, Viral , Female , Haplotypes , Humans , Infant , Lung/virology , Male , Phylogeny , RNA, Viral/analysis , RNA, Viral/genetics , SARS-CoV-2/isolation & purification , SARS-CoV-2/physiology , Viral Load , Virus Replication/drug effects
3.
J Infect ; 83(6): 693-700, 2021 12.
Article in English | MEDLINE | ID: covidwho-1446866

ABSTRACT

OBJECTIVES: Recently emerging SARS-CoV-2 variants have been associated with an increased rate of transmission within the community. We sought to determine whether this also resulted in increased transmission within hospitals. METHODS: We collected viral sequences and epidemiological data of patients with community and healthcare associated SARS-CoV-2 infections, sampled from 16th November 2020 to 10th January 2021, from nine hospitals participating in the COG-UK HOCI study. Outbreaks were identified using ward information, lineage and pairwise genetic differences between viral sequences. RESULTS: Mixed effects logistic regression analysis of 4184 sequences showed healthcare-acquired infections were no more likely to be identified as the Alpha variant than community acquired infections. Nosocomial outbreaks were investigated based on overlapping ward stay and SARS-CoV-2 genome sequence similarity. There was no significant difference in the number of patients involved in outbreaks caused by the Alpha variant compared to outbreaks caused by other lineages. CONCLUSIONS: We find no evidence to support it causing more nosocomial transmission than previous lineages. This suggests that the stringent infection prevention measures already in place in UK hospitals contained the spread of the Alpha variant as effectively as other less transmissible lineages, providing reassurance of their efficacy against emerging variants of concern.


Subject(s)
COVID-19 , Cross Infection , Cross Infection/epidemiology , Hospitals , Humans , SARS-CoV-2 , United Kingdom/epidemiology
4.
Clin Pharmacol Ther ; 110(2): 321-333, 2021 08.
Article in English | MEDLINE | ID: covidwho-1103289

ABSTRACT

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) viral loads change rapidly following symptom onset, so to assess antivirals it is important to understand the natural history and patient factors influencing this. We undertook an individual patient-level meta-analysis of SARS-CoV-2 viral dynamics in humans to describe viral dynamics and estimate the effects of antivirals used to date. This systematic review identified case reports, case series, and clinical trial data from publications between January 1, 2020, and May 31, 2020, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A multivariable Cox proportional hazards (Cox-PH) regression model of time to viral clearance was fitted to respiratory and stool samples. A simplified four parameter nonlinear mixed-effects (NLME) model was fitted to viral load trajectories in all sampling sites and covariate modeling of respiratory viral dynamics was performed to quantify time-dependent drug effects. Patient-level data from 645 individuals (age 1 month to 100 years) with 6,316 viral loads were extracted. Model-based simulations of viral load trajectories in samples from the upper and lower respiratory tract, stool, blood, urine, ocular secretions, and breast milk were generated. Cox-PH modeling showed longer time to viral clearance in older patients, men, and those with more severe disease. Remdesivir was associated with faster viral clearance (adjusted hazard ratio (AHR) = 9.19, P < 0.001), as well as interferon, particularly when combined with ribavirin (AHR = 2.2, P = 0.015; AHR = 6.04, P = 0.006). Combination therapy should be further investigated. A viral dynamic dataset and NLME model for designing and analyzing antiviral trials has been established.


Subject(s)
Antiviral Agents/pharmacology , COVID-19 Drug Treatment , COVID-19/virology , Viral Load/drug effects , Adenosine Monophosphate/analogs & derivatives , Adenosine Monophosphate/pharmacology , Adult , Alanine/analogs & derivatives , Alanine/pharmacology , Clinical Trials as Topic , Drug Therapy, Combination , Female , Humans , Interferons/pharmacology , Male , Middle Aged , Proportional Hazards Models , SARS-CoV-2/pathogenicity , Virus Shedding/drug effects
6.
Infect Genet Evol ; 83: 104351, 2020 09.
Article in English | MEDLINE | ID: covidwho-175956

ABSTRACT

SARS-CoV-2 is a SARS-like coronavirus of likely zoonotic origin first identified in December 2019 in Wuhan, the capital of China's Hubei province. The virus has since spread globally, resulting in the currently ongoing COVID-19 pandemic. The first whole genome sequence was published on January 5 2020, and thousands of genomes have been sequenced since this date. This resource allows unprecedented insights into the past demography of SARS-CoV-2 but also monitoring of how the virus is adapting to its novel human host, providing information to direct drug and vaccine design. We curated a dataset of 7666 public genome assemblies and analysed the emergence of genomic diversity over time. Our results are in line with previous estimates and point to all sequences sharing a common ancestor towards the end of 2019, supporting this as the period when SARS-CoV-2 jumped into its human host. Due to extensive transmission, the genetic diversity of the virus in several countries recapitulates a large fraction of its worldwide genetic diversity. We identify regions of the SARS-CoV-2 genome that have remained largely invariant to date, and others that have already accumulated diversity. By focusing on mutations which have emerged independently multiple times (homoplasies), we identify 198 filtered recurrent mutations in the SARS-CoV-2 genome. Nearly 80% of the recurrent mutations produced non-synonymous changes at the protein level, suggesting possible ongoing adaptation of SARS-CoV-2. Three sites in Orf1ab in the regions encoding Nsp6, Nsp11, Nsp13, and one in the Spike protein are characterised by a particularly large number of recurrent mutations (>15 events) which may signpost convergent evolution and are of particular interest in the context of adaptation of SARS-CoV-2 to the human host. We additionally provide an interactive user-friendly web-application to query the alignment of the 7666 SARS-CoV-2 genomes.


Subject(s)
Betacoronavirus/genetics , Coronavirus Infections/virology , Genetic Variation , Genome, Viral , Pneumonia, Viral/virology , Adaptation, Physiological/genetics , Antiviral Agents , COVID-19 , COVID-19 Vaccines , Coronavirus Infections/prevention & control , Humans , Likelihood Functions , Mutation , Pandemics , Phylogeny , SARS-CoV-2 , Viral Vaccines
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