SPEAR: Systematic ProtEin AnnotatoR

Summary We present SPEAR, a lightweight and rapid SARS-CoV-2 variant annotation and scoring tool, for identifying mutations contributing to potential immune escape and transmissibility (ACE2 binding) at point of sequencing. SPEAR can be used in the field to evaluate genomic surveillance results in real-time and features a powerful interactive data visualisation report. Availability and implementation SPEAR and documentation are freely available on GitHub: https://github.com/m-crown/SPEAR and is implemented in Python and installable via Conda environment. Supplemental Supplementary data are available at Bioinformatics online

A Revisit of Rainfall Simulator as a Potential Tool for Hydrological Research

Different means of hydrological data collection have developed and used. However, they are constraint in one way or other. This paper therefore revisited the rainfall simulator as potential tool for hydrological research. The research disclosed that there are three different types of rainfall simulators; drop former simulator, pressure nozzle simulator and hybrid simulator. It can further be classified as indoor model and outdoor. The research also showed that precipitation is the driving force in hydrological studies. Consequently, in the design of rainfall simulator, the following should be taken into consideration: nozzle spacing, pump size, nozzle size, nozzle type, nozzle spacing, plot size and pressure. Meanwhile, intensity, distribution uniformity, kinetic energy, rainfall drop size and rainfall terminal velocity should be noted in its evaluation. Factoring-in the aforementioned design considerations, data collection is made easy without necessarily waiting for the natural rainfall. Since the rainfall can be controlled, the erratic and unpredictable changeability of natural rainfall is eliminated. Emanating from the findings, pressurized rainfall simulator produces rainfall characteristics similar to natural rainfall, which is therefore recommended for laboratory use if natural rainfall-like characteristics is the main target

Is metal theft committed by organized crime groups, and why does it matter?

Using the example of metal theft in the United Kingdom, this study used mixed methods to evaluate the accuracy of police estimates of the involvement of organised crime groups (OCGs) in crime. Police estimate that 20-30% of metal theft is committed by OCGs, but this study found that only 0.5% of metal thieves had previous convictions for offences related to OCGs, that only 1.3% were linked to OCGs by intelligence information, that metal thieves typically offended close to their homes and that almost no metal thefts involved sophisticated offence methods. It appears that police may over-estimate the involvement of OCGs in some types of crime. The reasons for and consequences of this over-estimation are discussed

Lineage replacement and evolution captured by 3 years of the United Kingdom Coronavirus (COVID-19) Infection Survey

The Office for National Statistics Coronavirus (COVID-19) Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors, although this was also accompanied by a gradual fall in average viral burdens from June 2021 to March 2023. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non-SGTF over time. Evolution was characterized by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens

Factors affecting turnaround time of SARS-CoV-2 sequencing for inpatient infection prevention and control decision making: Analysis of data from the COG-UK HOCI study

Background Barriers to rapid return of sequencing results can affect the utility of sequence data for infection prevention and control decisions. Aim To undertake a mixed-methods analysis to identify challenges sites faced in achieving a rapid turnaround time (TAT) in the COG-UK Hospital-Onset COVID-19 Infection (COG-UK HOCI) study. Methods For the quantitative analysis, timepoints relating to different stages of the sequencing process were extracted from both the COG-UK HOCI dataset and surveys of study sites. Qualitative data relating to the barriers and facilitators to achieving rapid TAT were included from thematic analysis. Findings The overall TAT, from sample collection to receipt of sequence report by infection control teams, varied between sites (median 5.1 days, range 3.0 – 29.0 days). Most variation was seen between reporting of a positive COVID-19 PCR result to sequence report generation (median 4.0 days, range 2.3 – 27.0 days). On deeper analysis, most of this variability was accounted for by differences in the delay between the COVID-19 PCR result and arrival of the sample at the sequencing laboratory (median 20.8 hours, 16.0 – 88.7 hours). Qualitative analyses suggest closer proximity of sequencing labs to diagnostic labs, increased staff flexibility and regular transport times facilitated a shorter TAT. Conclusion Integration of pathogen sequencing into diagnostic laboratories may help improve sequencing TAT to allow sequence data to be of tangible value to infection control practice. Adding a quality control step upstream to increase capacity further down the workflow may also optimise TAT if lower quality samples are removed earlier on

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Outcomes of SARS-CoV-2 omicron infection in residents of long-term care facilities in England (VIVALDI): a prospective, cohort study

Background: The SARS-CoV-2 omicron variant (B.1.1.529) is highly transmissible, but disease severity appears to be reduced compared with previous variants such as alpha and delta. We investigated the risk of severe outcomes following infection in residents of long-term care facilities. Methods: We did a prospective cohort study in residents of long-term care facilities in England who were tested regularly for SARS-CoV-2 between Sept 1, 2021, and Feb 1, 2022, and who were participants of the VIVALDI study. Residents were eligible for inclusion if they had a positive PCR or lateral flow device test during the study period, which could be linked to a National Health Service (NHS) number, enabling linkage to hospital admissions and mortality datasets. PCR or lateral flow device test results were linked to national hospital admission and mortality records using the NHS-number-based pseudo-identifier. We compared the risk of hospital admission (within 14 days following a positive SARS-CoV-2 test) or death (within 28 days) in residents who had tested positive for SARS-CoV-2 in the period shortly before omicron emerged (delta-dominant) and in the omicron-dominant period, adjusting for age, sex, primary vaccine course, past infection, and booster vaccination. Variants were confirmed by sequencing or spike-gene status in a subset of samples. Results: 795 233 tests were done in 333 long-term care facilities, of which 159 084 (20·0%) could not be linked to a pseudo-identifier and 138 012 (17·4%) were done in residents. Eight residents had two episodes of infection (>28 days apart) and in these cases the second episode was excluded from the analysis. 2264 residents in 259 long-term care facilities (median age 84·5 years, IQR 77·9–90·0) were diagnosed with SARS-CoV-2, of whom 253 (11·2%) had a previous infection and 1468 (64·8%) had received a booster vaccination. About a third of participants were male. Risk of hospital admissions was markedly lower in the 1864 residents infected in the omicron-period (4·51%, 95% CI 3·65–5·55) than in the 400 residents infected in the pre-omicron period (10·50%, 7·87–13·94), as was risk of death (5·48% [4·52–6·64] vs 10·75% [8·09–14·22]). Adjusted hazard ratios (aHR) also indicated a reduction in hospital admissions (0·64, 95% CI 0·41–1·00; p=0·051) and mortality (aHR 0·68, 0·44–1·04; p=0·076) in the omicron versus the pre-omicron period. Findings were similar in residents with a confirmed variant. Interpretation: Observed reduced severity of the omicron variant compared with previous variants suggests that the wave of omicron infections is unlikely to lead to a major surge in severe disease in long-term care facility populations with high levels of vaccine coverage or natural immunity. Continued surveillance in this vulnerable population is important to protect residents from infection and monitor the public health effect of emerging variants. Funding: UK Department of Health and Social Care

Multiple pathways of SARS-CoV-2 nosocomial transmission uncovered by integrated genomic and epidemiological analyses during the second wave of the COVID-19 pandemic in the UK

INTRODUCTION: Throughout the global COVID-19 pandemic, nosocomial transmission has represented a major concern for healthcare settings and has accounted for many infections diagnosed within hospitals. As restrictions ease and novel variants continue to spread, it is important to uncover the specific pathways by which nosocomial outbreaks occur to understand the most suitable transmission control strategies for the future. METHODS: In this investigation, SARS-CoV-2 genome sequences obtained from 694 healthcare workers and 1,181 patients were analyzed at a large acute NHS hospital in the UK between September 2020 and May 2021. These viral genomic data were combined with epidemiological data to uncover transmission routes within the hospital. We also investigated the effects of the introduction of the highly transmissible variant of concern (VOC), Alpha, over this period, as well as the effects of the national vaccination program on SARS-CoV-2 infection in the hospital. RESULTS: Our results show that infections of all variants within the hospital increased as community prevalence of Alpha increased, resulting in several outbreaks and super-spreader events. Nosocomial infections were enriched amongst older and more vulnerable patients more likely to be in hospital for longer periods but had no impact on disease severity. Infections appeared to be transmitted most regularly from patient to patient and from patients to HCWs. In contrast, infections from HCWs to patients appeared rare, highlighting the benefits of PPE in infection control. The introduction of the vaccine at this time also reduced infections amongst HCWs by over four-times. DISCUSSION: These analyses have highlighted the importance of control measures such as regular testing, rapid lateral flow testing alongside polymerase chain reaction (PCR) testing, isolation of positive patients in the emergency department (where possible), and physical distancing of patient beds on hospital wards to minimize nosocomial transmission of infectious diseases such as COVID-19

SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2

Background: Since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Genomic surveillance in regions of high immunity is crucial in detecting emerging variants that can more successfully navigate the immune landscape. Methods: We present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. During round 14 (9 September–27 September 2021) and 15 (19 October–5 November 2021) lineages were determined for 1322 positive individuals, with 27.1% of those which reported their symptom status reporting no symptoms in the previous month. Results: We identified 44 unique lineages, all of which were Delta or Delta sub-lineages, and found a reduction in their mutation rate over the study period. The proportion of the Delta sub-lineage AY.4.2 was increasing, with a reproduction number 15% (95% CI 8–23%) greater than the most prevalent lineage, AY.4. Further, AY.4.2 was less associated with the most predictive COVID-19 symptoms (p = 0.029) and had a reduced mutation rate (p = 0.050). Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England. Conclusions: As SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals

Genomics-informed outbreak investigations of SARS-CoV-2 using civet

The scale of data produced during the SARS-CoV-2 pandemic has been unprecedented, with more than 13 million sequences shared publicly at the time of writing. This wealth of sequence data provides important context for interpreting local outbreaks. However, placing sequences of interest into national and international context is difficult given the size of the global dataset. Often outbreak investigations and genomic surveillance efforts require running similar analyses again and again on the latest dataset and producing reports. We developed civet (cluster investigation and virus epidemiology tool) to aid these routine analyses and facilitate virus outbreak investigation and surveillance. Civet can place sequences of interest in the local context of background diversity, resolving the query into different ’catchments’ and presenting the phylogenetic results alongside metadata in an interactive, distributable report. Civet can be used on a fine scale for clinical outbreak investigation, for local surveillance and cluster discovery, and to routinely summarise the virus diversity circulating on a national level. Civet reports have helped researchers and public health bodies feedback genomic information in the appropriate context within a timeframe that is useful for public health