ABSTRACT
The mutational landscape of SARS-CoV-2 varies at both the dominant viral genome sequence and minor genomic variant population. An early change associated with transmissibility was the D614G substitution in the spike protein. This appeared to be accompanied by a P323L substitution in the viral polymerase (NSP12), but this latter change was not under strong selective pressure. Investigation of P323L/D614G changes in the human population showed rapid emergence during the containment phase and early surge phase of wave 1 in the UK. This rapid substitution was from minor genomic variants to become part of the dominant viral genome sequence. A rapid emergence of 323L but not 614G was observed in a non-human primate model of COVID-19 using a starting virus with P323 and D614 in the dominant genome sequence and 323L and 614G in the minor variant population. In cell culture, a recombinant virus with 323L in NSP12 had a larger plaque size than the same recombinant virus with P323. These data suggest that it may be possible to predict the emergence of a new variant based on tracking the distribution and frequency of minor variant genomes at a population level, rather than just focusing on providing information on the dominant viral genome sequence e.g., consensus level reporting. The ability to predict an emerging variant of SARS-CoV-2 in the global landscape may aid in the evaluation of medical countermeasures and non-pharmaceutical interventions.
Subject(s)
COVID-19ABSTRACT
The number of occupants in a space influences the risk of far-field airborne transmission of SARS-CoV-2 because the likelihood of having infectious and susceptible people both correlate with the number of occupants. This paper explores the relationship between occupancy and the probability of infection, and how this affects an individual person and a population of people. Mass-balance and dose-response models determine far-field transmission risks for an individual person and a population of people after sub-dividing a large reference space into 10 identical comparator spaces. For a single infected person, the dose received by an individual person in the comparator space is 10-times higher because the equivalent ventilation rate per infected person is lower when the per capita ventilation rate is preserved. However, accounting for population dispersion, such as the community prevalence of the virus, the probability of an infected person being present and uncertainty in their viral load, shows the transmission probability increases with occupancy and the reference space has a higher transmission risk. Also, far-field transmission is likely to be a rare event that requires a high emission rate, and there are a set of Goldilocks conditions that are just right when ventilation is effective at mitigating against transmission. These conditions depend on the viral load, because when they are very high or low, ventilation has little effect on transmission risk. Nevertheless, resilient buildings should deliver the equivalent ventilation rate required by standards as minimum.
ABSTRACT
Background: The Randomised Evaluation of COVID-19 Therapy (RECOVERY) trial is aimed at addressing the urgent need to find effective treatments for patients hospitalised with suspected or confirmed COVID-19. The trial has had many successes, including discovering that dexamethasone is effective at reducing COVID-19 mortality, the first treatment to reach this milestone in a randomised controlled trial. Despite this, it continues to use standard or `fixed’ randomization (FR) to allocate patients to treatments. We assessed the impact of implementing response adaptive randomization (RAR) within RECOVERY using an array of performance measures, to learn if it could be beneficial going forward. This design feature has recently been implemented within the REMAP-CAP trial. Methods: Trial data was simulated to closely match the data for patients allocated to either standard care or dexamethasone in the RECOVERY trial from March-June 2020, representing two out of five arms tested throughout this period. Two forms of FR and two forms of RAR were tested. Randomization strategies were performed at the whole trial level as well as within three pre-specified patient subgroups defined by patients’ respiratory support level. Results: RAR strategies led to more patients being given dexamethasone and a lower mortality rate in the trial. Subgroup specific RAR reduced mortality rates even further. RAR did not induce any meaningful bias in treatment effect estimates, but reduced statistical power compared to FR, with subgroup level adaptive randomizations exhibiting the largest power reduction. Conclusions: Using RAR within RECOVERY could have resulted in fewer deaths in the trial. However, a larger trial would have been needed to attain the same study power. This could potentially have prolonged the time to full approval of the drug, unless RAR itself led to an increased recruitment rate. Deciding how to balance the needs of patients within a trial and future patients who have yet to fall ill is an important ethical question of our time. RAR deserves to be considered as a design feature in future trials of COVID-19 and other diseases.
Subject(s)
COVID-19ABSTRACT
New variants of SARS-CoV-2 are continuing to emerge and dominate the regional and global sequence landscapes. Several variants have been labelled as Variants of Concern (VOCs) because of perceptions or evidence that these may have a transmission advantage, increased risk of morbidly and/or mortality or immune evasion in the context of prior infection or vaccination. Placing the VOCs in context and also the underlying variability of SARS-CoV-2 is essential in understanding virus evolution and selection pressures. Sequences of SARS-CoV-2 in nasopharyngeal swabs from hospitalised patients in the UK were determined and virus isolated. The data indicated the virus existed as a population with a consensus level and non-synonymous changes at a minor variant. For example, viruses containing the nsp12 P323L variation from the Wuhan reference sequence, contained minor variants at the position including P and F and other amino acids. These populations were generally preserved when isolates were amplified in cell culture. In order to place VOCs B.1.1.7 (the UK Kent variant) and B.1.351 (the South African variant) in context their growth was compared to a spread of other clinical isolates. The data indicated that the growth in cell culture of the B.1.1.7 VOC was no different from other variants, suggesting that its apparent transmission advantage was not down to replicating more quickly. Growth of B.1.351 was towards the higher end of the variants. Overall, the study suggested that studying the biology of SARS-CoV-2 is complicated by population dynamics and that these need to be considered with new variants.
Subject(s)
COVID-19 , InfectionsABSTRACT
Middle East Respiratory Syndrome coronavirus (MERS-CoV) is a zoonotic infection that emerged in the Middle East in 2012. Symptoms range from mild to severe and include both respiratory and gastrointestinal illnesses. The virus is mainly present in camel populations with occasional spill overs into humans. The severity of infection in humans is influenced by numerous factors and similar to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) underlying health complications can play a major role. Currently, MERS-CoV and SARS-CoV-2 are co-incident in the Middle East and a rapid way is required of sequencing MERS-CoV to derive genotype information for molecular epidemiology. Additionally, complicating factors in MERS-CoV infections are co-infections that require clinical management. The ability to rapidly characterise these infections would be advantageous. To rapidly sequence MERS-CoV, we developed an amplicon-based approach coupled to Oxford Nanopore long read length sequencing. The advantage of this approach is that insertions and deletions can be identified – which are the major drivers of genotype change in coronaviruses. This and a metagenomic approach were evaluated on clinical samples from patients with MERS. The data illustrated that whole genome or near whole genome information on MERS-CoV could be rapidly obtained. This approach provided data on both consensus genomes and the presence of minor variants including deletion mutants. Whereas, the metagenomic analysis provided information of the background microbiome.