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Natural and engineered, nature-based structures offer promise for storm-related disaster risk reduction and flood mitigation, as long as researchers can adequately monitor and study them.

Computationally efficient and accurate quantum mechanical approximations to solve the many-electron Schrödinger equation are crucial for computational materials science. Methods such as coupled cluster theory show potential for widespread adoption if computational cost bottlenecks can be removed. For example, extremely dense k-point grids are required to model long-range electronic correlation effects, particularly for metals. Although these grids can be made more effective by averaging calculations over an offset (or twist angle), the resultant cost in time for coupled cluster theory is prohibitive. We show here that a single special twist angle can be found using the transition structure factor, which provides the same benefit as twist averaging with one or two orders of magnitude reduction in computational time. We demonstrate that this not only works for metal systems but also is applicable to a broader range of materials, including insulators and semiconductors.

We describe a case of hemorrhagic fever with renal syndrome caused by Seoul virus in a woman in Scotland, UK. Whole-genome sequencing showed the virus belonged to a lineage characterized by recent international expansion, probably driven by trade in pet rats.

Background With the spread of the SARS-CoV-2 pandemic in 2020 and the attendant global precautions such as masking, travel restrictions and social distancing, the WHO FluNet data indicated a decline in flu rates. The CDC data for the 2020-2021 season showed the same decline in US flu as well as other respiratory viruses. Two hypotheses to explain the observed phenomenon are the impact of non-pharmaceutical interventions (NPI) to prevent SARS-CoV-2 infection and suppression of other respiratory viruses by SARS-CoV-2 through a form of resource competition. Methods We conducted a study using the EPIC Slicer Dicer analytics tool and the Yale Internal Medicine COVID-19 Database to retrieve data from the Yale New Haven Health System (YNHHS). We tabulated the total number of positive and negative tests for SARS-CoV-2 and a panel of respiratory viruses from September 2, 2018 to April 30, 2022 to cover pre- and peri-pandemic periods. These results were divided into three age groups: ≤12, 13-59, and ≥60. Epidemic curves of each virus with respect to each other, the season, and the introduction of NPIs were constructed to help differentiate between the two hypotheses. Results Pre-pandemic data from 09/2018 to 02/2020 revealed seasonal spikes in influenza A and B with 254 positive weekly influenza A/B tests from 11/2018 to 02/2019 for a positivity rate of 7.97% and 481 positive weekly tests (10.53% positivity rate [PR]) from November 2019 to February 2020. There were only 0.35 positive weekly influenza A/B tests (0.05% PR) from 11/2020 to 02/2021 with 2018 positive weekly tests (6.45% PR) for SARS-CoV-2 over the same period. From 11/2020 to 02/2021, there were 56 positive weekly influenza A/B tests (1.44% PR) and 4347 positive weekly SARS-CoV-2 tests (10.35% PR). From 07/2021 to 11/2021, there was an increased rate of positive RSV tests (82 per week, 15.76% PR) and rhinovirus tests (58 per week, 18.73% PR). There were 803 positive weekly tests (2.53% positivity rate) for SARS-CoV-2 over this same period. Conclusion Since the start of the SARS-CoV-2 pandemic, the number of positive tests for influenza A/B and seasonal respiratory viruses have not reached pre-pandemic levels across the YNHHS. However, rates of influenza and other respiratory viruses have increased since the relaxation of NPIs. Disclosures All Authors: No reported disclosures.

Background: \ud Crimean-Congo Haemorrhagic Fever (CCHF) is an emerging human-health threat causing sporadic outbreaks in livestock farming communities. However, the full extent and the risks associated with exposure of such communities has not previously been well-described.\ud \ud Methods: \ud We collected blood samples from 800 humans, 666 cattle, 549 goats and 32 dogs in districts within and outside Ugandan cattle corridor in a cross-sectional survey, and tested for CCHFV-specific IgG antibodies using Enzyme-Linked Immunosorbent Assays. Sociodemographic and epidemiological data were recorded using structured questionnaire. Ticks were collected to identify circulating nairoviruses by metagenomic sequencing.\ud \ud Results: \ud CCHFV seropositivity was in 221/800 (27·6%) in humans, 612/666 (91·8%) in cattle, 413/549 (75·2%) in goats and 18/32 (56·2%) in dogs. Human seropositivity was associated with livestock farming (AOR=5·68, p50 ticks: AOR=3·52, p=0·004). CCHFV was identified in multiple tick pools of Rhipicephalus appendiculatus.\ud \ud Interpretation: \ud The very high CCHF seropositivity especially among livestock farmers and multiple regional risk factors associated exposures, including collecting/eating engorged ticks previously unrecognised, highlights need for further surveillance and sensitisation and control policies against the disease.

Background: Statin therapy is effective for the prevention of atherosclerotic cardiovascular disease and is widely prescribed, but there are persisting concerns that statin therapy might frequently cause muscle pain or weakness. We aimed to address these through an individual participant data meta-analysis of all recorded adverse muscle events in large, long-term, randomised, double-blind trials of statin therapy. Methods: Randomised trials of statin therapy were eligible if they aimed to recruit at least 1000 participants with a scheduled treatment duration of at least 2 years, and involved a double-blind comparison of statin versus placebo or of a more intensive versus a less intensive statin regimen. We analysed individual participant data from 19 double-blind trials of statin versus placebo (n=123 940) and four double-blind trials of a more intensive versus a less intensive statin regimen (n=30 724). Standard inverse-variance-weighted meta-analyses of the effects on muscle outcomes were conducted according to a prespecified protocol. Findings: Among 19 placebo-controlled trials (mean age 63 years [SD 8], with 34 533 [27·9%] women, 59 610 [48·1%] participants with previous vascular disease, and 22 925 [18·5%] participants with diabetes), during a weighted average median follow-up of 4·3 years, 16 835 (27·1%) allocated statin versus 16 446 (26·6%) allocated placebo reported muscle pain or weakness (rate ratio [RR] 1·03; 95% CI 1·01–1·06). During year 1, statin therapy produced a 7% relative increase in muscle pain or weakness (1·07; 1·04–1·10), corresponding to an absolute excess rate of 11 (6–16) events per 1000 person-years, which indicates that only one in 15 ([1·07–1·00]/1·07) of these muscle-related reports by participants allocated to statin therapy were actually due to the statin. After year 1, there was no significant excess in first reports of muscle pain or weakness (0·99; 0·96–1·02). For all years combined, more intensive statin regimens (ie, 40–80 mg atorvastatin or 20–40 mg rosuvastatin once per day) yielded a higher RR than less intensive or moderate-intensity regimens (1·08 [1·04–1·13] vs 1·03 [1·00–1·05]) compared with placebo, and a small excess was present (1·05 [0·99–1·12]) for more intensive regimens after year 1. There was no clear evidence that the RR differed for different statins, or in different clinical circumstances. Statin therapy yielded a small, clinically insignificant increase in median creatine kinase values of approximately 0·02 times the upper limit of normal. Interpretation: Statin therapy caused a small excess of mostly mild muscle pain. Most (>90%) of all reports of muscle symptoms by participants allocated statin therapy were not due to the statin. The small risks of muscle symptoms are much lower than the known cardiovascular benefits. There is a need to review the clinical management of muscle symptoms in patients taking a statin. Funding: British Heart Foundation, Medical Research Council, Australian National Health and Medical Research Council.

Mutation—whilst stochastic—is frequently biased toward certain loci. When combined with selection, this results in highly repeatable and predictable evolutionary outcomes. Immotile variants of the bacterium Pseudomonas fluorescens (SBW25) possess a “mutational hotspot” that facilitates repeated occurrences of an identical de novo single nucleotide polymorphism when re-evolving motility, where ≥95% independent lines fix the mutation ntrB A289C. Identifying hotspots of similar potency in other genes and genomic backgrounds would prove valuable for predictive evolutionary models but to do so we must understand the genomic features that enable such a hotspot to form. Here, we reveal that genomic location, local nucleotide sequence, gene strandedness, and presence of mismatch repair proteins operate in combination to facilitate the formation of this mutational hotspot. Our study therefore provides a framework for utilizing genomic features to predict and identify hotspot positions capable of enforcing near-deterministic evolution.

Summary The hepatitis C virus (HCV) is an extremely diverse virus, subtypes of which are distributed variably around the world. Viral genotypes may be divided into epidemic subtypes; those that have become prevalent globally, and endemic subtypes that have a more limited distribution, mainly in Africa and Asia. The high variability of endemic strains reflects evolutionary origins in the locations where they are found. This increased genetic diversity raises the possibility of resistance to pan-genotypic direct-acting antiviral regimens. While many endemic subtypes respond well to direct-acting antiviral therapies, others, for example genotypes 1l, 3b and 4r, do not respond as well as predicted. Many genotypes that are rare in high-income countries but common in other parts of the world have not yet been fully assessed in clinical trials. Further sequencing and clinical studies in sub-Saharan Africa and Asia are indicated to monitor response to treatment and to facilitate the World Health Organization’s 2030 elimination strategy.

BackgroundClinical scores to determine early (6-month) antiretroviral therapy (ART) mortality risk have not been developed for sub-Saharan Africa (SSA), home to 70% of people living with HIV. In the absence of validated scores, WHO eligibility criteria (EC) for ART care intensification are CD4 MethodsWe used Botswana XPRES trial data for adult ART enrollees to develop CD4-independent and CD4-dependent multivariable prognostic models for 6-month mortality. Scores were derived by rescaling coefficients. Scores were developed using the first 50% of XPRES ART enrollees, and their accuracy validated internally and externally using South African TB Fast Track (TBFT) trial data. Predictive accuracy was compared between scores and WHO EC.ResultsAmong 5553 XPRES enrollees, 2838 were included in the derivation dataset; 68% were female and 83 (3%) died by 6 months. Among 1077 TBFT ART enrollees, 55% were female and 6% died by 6 months. Factors predictive of 6-month mortality in the derivation dataset atp 37.5 °C (2 points). The same variables plus CD4 ConclusionsSensitivity of the CD4-independent score was nearly twice that of WHO stage in predicting 6-month mortality and could be used in settings lacking CD4 testing to inform ART care intensification. The CD4-dependent score improved specificity versus WHO EC. Both scores should be considered for scale-up in SSA.

We introduce a straightforward Gaussian process regression (GPR) model for the transition structure factor of metal periodic coupled cluster singles and doubles (CCSD) calculations. This is inspired by the method introduced by Liao and Gr\"uneis for interpolating over the transition structure factor to obtain a finite size correction for CCSD [J. Chem. Phys. 145, 141102 (2016)], and by our own prior work using the transition structure factor to efficiently converge CCSD for metals to the thermodynamic limit [Nat. Comput. Sci. 1, 801 (2021)]. In our CCSD-FS-GPR method to correct for finite size errors, we fit the structure factor to a 1D function in the momentum transfer, $G$. We then integrate over this function by projecting it onto a k-point mesh to obtain comparisons with extrapolated results. Results are shown for lithium, sodium, and the uniform electron gas., Comment: 7 pages, 2 figures

Background: \ud 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.\ud \ud Methods: \ud 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.\ud \ud Findings: \ud 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.\ud \ud Interpretation: \ud 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.\ud \ud Funding: \ud Medical Research Council; UK Research and Innovation; Department of Health and Social Care; and National Institute for Health Research.

Access to justice for fraud victims remains an enduring problem in the UK. Law enforcement agencies have limited capacity and capabilities for delivering criminal justice. Civil justice is so expensive that it is only an option for those with deep pockets or lucky enough to find competent professionals who are willing to work under a conditional fee arrangement (no-win-no-fee). This article describes the progress of a fraud case from a victim’s perspective through both the criminal and civil justice systems in the UK. The experiences describe incompetence in law enforcement, dishonesty and incompetence amongst lawyers and other professionals, and fractured, self-centred justice systems that poorly serve the public in England and Wales.

Background Undiagnosed tuberculosis (TB) remains the most common cause of HIV-related mortality. Xpert MTB/RIF (Xpert) is being rolled out globally to improve TB diagnostic capacity. However, previous Xpert impact trials have reported that health system weaknesses blunted impact of this improved diagnostic tool. During phased Xpert rollout in Botswana, we evaluated the impact of a package of interventions comprising (1) additional support for intensified TB case finding (ICF), (2) active tracing for patients missing clinic appointments to support retention, and (3) Xpert replacing sputum-smear microscopy, on early (6-month) antiretroviral therapy (ART) mortality. Methods At 22 clinics, ART enrollees > 12 years old were eligible for inclusion in three phases: a retrospective standard of care (SOC), prospective enhanced care (EC), and prospective EC plus Xpert (EC+X) phase. EC and EC+X phases were implemented as a stepped-wedge trial. Participants in the EC phase received SOC plus components 1 (strengthened ICF) and 2 (active tracing) of the intervention package, and participants in the EC+X phase received SOC plus all three intervention package components. Primary and secondary objectives were to compare all-cause 6-month ART mortality between SOC and EC+X and between EC and EC+X phases, respectively. We used adjusted analyses, appropriate for study design, to control for baseline differences in individual-level factors and intra-facility correlation. Results We enrolled 14,963 eligible patients: 8980 in SOC, 1768 in EC, and 4215 in EC+X phases. Median age of ART enrollees was 35 and 64% were female. Median CD4 cell count was lower in SOC than subsequent phases (184/μL in SOC, 246/μL in EC, and 241/μL in EC+X). By 6 months of ART, 461 (5.3%) of SOC, 54 (3.2%) of EC, and 121 (3.0%) of EC+X enrollees had died. Compared with SOC, 6-month mortality was lower in the EC+X phase (adjusted hazard ratio, 0.77; 95% confidence interval, 0.61–0.97, p = 0.029). Compared with EC enrollees, 6-month mortality was similar among EC+X enrollees. Conclusions Interventions to strengthen ICF and retention were associated with lower early ART mortality. This new evidence highlights the need to strengthen ICF and retention in many similar settings. Similar to other trials, no additional mortality benefit of replacing sputum-smear microscopy with Xpert was observed. Trial registration Retrospectively registered: ClinicalTrials.gov (NCT02538952)

Purpose The purpose of this paper is to explore the impact of media coverage on offenders convicted of occupational fraud and corruption in the UK. It examines the extent of media coverage and provides insights into the experiences of offenders. Design/methodology/approach The study is based upon interviews with 17 convicted offenders, and on a content analysis of one national and two regional newspapers in the UK. Findings The findings suggest that offenders convicted of occupational crime and corruption are more likely to experience media coverage than previously assumed and that personal digital criminal legacies create long-term labels which lead to economic strains and social fractures that hinder productive reintegration into society. Research limitations/implications The research is limited by a small sample frame in the UK. Nevertheless, the findings suggest further research is required as they have important implications for privacy and rehabilitation. Practical implications In particular, offenders and their families need support in dealing with their personal digital criminal legacies, accessing their privacy rights and coping with the strains created by online stigmatisation. From a policy perspective, the existing regulatory framework that supports rehabilitation in the UK, especially the increasingly archaic Rehabilitation of Offenders Act 1974, requires close examination and debate to ensure it is fit for the digital era. The findings also suggest that policies, practices and responsibilities of the public sector in employing offenders need to be examined. Originality/value It is a rare study of white-collar offenders after their release from prison. The findings are of relevance to criminal justice policy makers, rehabilitation services and academics.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections were rising during early summer 2021 in many countries as a result of the Delta variant. We assessed reverse transcription polymerase chain reaction swab positivity in the Real-time Assessment of Community Transmission–1 (REACT-1) study in England. During June and July 2021, we observed sustained exponential growth with an average doubling time of 25 days, driven by complete replacement of the Alpha variant by Delta and by high prevalence at younger, less-vaccinated ages. Prevalence among unvaccinated people [1.21% (95% credible interval 1.03%, 1.41%)] was three times that among double-vaccinated people [0.40% (95% credible interval 0.34%, 0.48%)]. However, after adjusting for age and other variables, vaccine effectiveness for double-vaccinated people was estimated at between ~50% and ~60% during this period in England. Increased social mixing in the presence of Delta had the potential to generate sustained growth in infections, even at high levels of vaccination.

Background The B.1.1.7 (Alpha) SARS-CoV-2 variant of concern was associated with increased transmission relative to other variants present at the time of its emergence and several studies have shown an association between the B.1.1.7 lineage infection and increased 28-day mortality. However, to date none have addressed the impact of infection on severity of illness or the need for oxygen or ventilation. Methods In this prospective clinical cohort sub-study of the COG-UK consortium, 1475 samples from hospitalised and community cases collected between the 1st November 2020 and 30th January 2021 were collected. These samples were sequenced in local laboratories and analysed for the presence of B.1.1.7-defining mutations. We prospectively matched sequence data to clinical outcomes as the lineage became dominant in Scotland and modelled the association between B.1.1.7 infection and severe disease using a 4-point scale of maximum severity by 28 days: 1. no support, 2. oxygen, 3. ventilation and 4. death. Additionally, we calculated an estimate of the growth rate of B.1.1.7-associated infections following introduction into Scotland using phylogenetic data. Results B.1.1.7 was responsible for a third wave of SARS-CoV-2 in Scotland, and rapidly replaced the previously dominant second wave lineage B.1.177) due to a significantly higher transmission rate (∼5 fold). Of 1475 patients, 364 were infected with B.1.1.7, 1030 with B.1.177 and 81 with other lineages. Our cumulative generalised linear mixed model analyses found evidence (cumulative odds ratio: 1.40, 95% CI: 1.02, 1.93) of a positive association between increased clinical severity and lineage (B.1.1.7 versus non-B.1.1.7). Viral load was higher in B.1.1.7 samples than in non-B.1.1.7 samples as measured by cycle threshold (Ct) value (mean Ct change: -2.46, 95% CI: -4.22, -0.70). Conclusions The B.1.1.7 lineage was associated with more severe clinical disease in Scottish patients than co-circulating lineages. Funding COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institute. Funding was also provided by UKRI through the JUNIPER consortium (grant number MR/V038613/1). Sequencing and bioinformatics support was funded by the Medical Research Council (MRC) core award (MC UU 1201412).

This article explores white collar criminals’ experience of imprisonment in England and Wales. Based upon interviews with 13 convicted offenders after they had completed their imprisonment, it is the first study to date of this kind in England and Wales (all others have been based in prison). It offers a unique impartial insight of prisoners’ experience, beyond the influence of the prison walls. The paper explores the experience around the largely American ‘special sensitivity’ debate, over whether such offenders are more sensitive to prison. The research uncovers both positive experiences, labelled ‘good’, but also negative, labelled ‘bad’ (non-violent experiences) and ‘ugly’ (violent experiences). Overall the findings reveal it is difficult to apply the special sensitivity hypothesis universally to this group of offenders.

ObjectivesPatients requiring haemodialysis are at increased risk of serious illness with SARS-CoV-2 infection. To improve the understanding of transmission risks in six Scottish renal dialysis units, we utilised the rapid whole-genome sequencing data generated by the COG-UK consortium.MethodsWe combined geographical, temporal and genomic sequence data from the community and hospital to estimate the probability of infection originating from within the dialysis unit, the hospital or the community using Bayesian statistical modelling and compared these results to the details of epidemiological investigations.ResultsOf 671 patients, 60 (8.9%) became infected with SARS-CoV-2, of whom 16 (27%) died. Within-unit and community transmission were both evident and an instance of transmission from the wider hospital setting was also demonstrated.ConclusionsNear-real-time SARS-CoV-2 sequencing data can facilitate tailored infection prevention and control measures, which can be targeted at reducing risk in these settings.

We report the facile production of ArCF2X and ArCX3 from ArCF3 using catalytic iron(III)halides, which constitutes the first iron-catalyzed halogen exchange for non-aromatic CF bonds. Theoretical calculations suggest direct activation of C–F bonds by iron coordination. ArCX3 and ArCF2X products of the reaction are synthetically valuable due to their diversification potential. In particular, bromo-, chloro-, and iododifluoromethyl arenes (ArCF2Br, ArCF2Cl, ArCF2I, respectively) provide access to a myriad of difluoromethyl arene derivatives (ArCF2R). To optimize for mono-halogen exchange, a statistical method called Design of Experiments was used. Optimized parameters were successfully applied to electron rich and electron deficient aromatic substrates, and to the late stage diversification of flufenoxuron, a commercial insecticide.

The second SARS virus, SARS-CoV-2, emerged in December 2019, and within a month was globally distributed. It was first introduced into Scotland in February 2020 associated with returning travellers and visitors. By March it was circulating in communities across the UK, and to control COVID-19 cases, and prevent overwhelming of the National Health Service (NHS), a ‘lockdown’ was introduced on 23rd March 2020 with a restriction of people’s movements. To augment the public health efforts a large-scale genome epidemiology effort (as part of the COVID-19 Genomics UK (COG-UK) consortium) resulted in the sequencing of over 5000 SARS-CoV-2 genomes by 18th August 2020 from Scottish cases, about a quarter of the estimated number of cases at that time. Here we quantify the geographical origins of the first wave introductions into Scotland from abroad and other UK regions, the spread of these SARS-CoV-2 lineages to different regions within Scotland (defined at the level of NHS Health Board) and the effect of lockdown on virus ‘success’. We estimate that approximately 300 introductions seeded lineages in Scotland, with around 25% of these lineages composed of more than five viruses, but by June circulating lineages were reduced to low levels, in line with low numbers of recorded positive cases. Lockdown was, thus, associated with a dramatic reduction in infection numbers and the extinguishing of most virus lineages. Unfortunately since the summer cases have been rising in Scotland in a second wave, with >1000 people testing positive on a daily basis, and hospitalisation of COVID-19 cases on the rise again. Examining the available Scottish genome data from the second wave, and comparing it to the first wave, we find that while some UK lineages have persisted through the summer, the majority of lineages responsible for the second wave are new introductions from outside of Scotland and many from outside of the UK. This indicates that, while lockdown in Scotland is directly linked with the first wave case numbers being brought under control, travel-associated imports (mostly from Europe or other parts of the UK) following the easing of lockdown are responsible for seeding the current epidemic population. This demonstrates that the impact of stringent public health measures can be compromised if following this, movements from regions of high to low prevalence are not minimised.

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., Graphical Abstract, Highlights • Increasing frequency of SARS-CoV-2 D614G is consistent with a selective advantage • Phylodynamic analyses do not show significantly different growth of D614G clusters • There is no association of D614G replacement with greater severity of infection • The D614G replacement is associated with higher viral loads and younger patient age, Analysis of the spread and frequency of SARS-CoV-2 D614G in the United Kingdom suggests a selective advantage for this strain that is associated with higher viral loads in younger patients but not higher COVID-19 clinical severity or mortality.

The technological changes of the last 30 years have facilitated a substantial increase in cybercrimes. The impact of these crimes on victims has not been the subject of extensive research. This paper based upon a British Home Office funded study draws upon the experience of 52 victims of computer misuse crime, which can be broadly grouped under hacking and computer virus related crimes. Drawing upon the interviews with these victims the researchers identified a continuum of three components founded upon the seriousness of the incident and the impact on the victim. These three categories included: incidents of inconvenience, crimes of inconvenience and serious crimes of personal violation or significant financial loss or fear of. The paper provides depth accounts of 15 of the 52 victims interviewed to illustrate this continuum.

While changes in SARS-CoV-2 viral load over time have been documented, detailed information on the impact of remdesivir and how it might alter intra-host viral evolution is limited. Sequential viral loads and deep sequencing of SARS-CoV-2 recovered from the upper respiratory tract of hospitalised children revealed that remdesivir treatment suppressed viral RNA levels in one patient but not in a second infected with an identical strain. Evidence of drug resistance to explain this difference was not found. Reduced levels of subgenomic (sg) RNA during treatment of the second patient, suggest an additional effect of remdesivir on viral replication that is independent of viral RNA levels. Haplotype reconstruction uncovered persistent SARS-CoV-2 variant genotypes in four patients. We conclude that these are likely to have arisen from within-host evolution, and not co-transmission, although superinfection cannot be excluded in one case. Sample-to-sample heterogeneity in the abundances of variant genotypes is best explained by the presence of discrete viral populations in the lung with incomplete population sampling in diagnostic swabs. Such compartmentalisation is well described in serious lung infections caused by influenza and Mycobacterium tuberculosis and has been associated with poor drug penetration, suboptimal treatment and drug resistance. Our data provide evidence that remdesivir is able to suppress SARS-CoV-2 replication in vivo but that its efficacy may be compromised by factors reducing penetration into the lung. Based on data from influenza and Mycobacterium tuberculosis lung infections we conclude that early use of remdesivir combined with other agents should now be evaluated.Summary SentenceDeep sequencing of longitudinal samples from SARS-CoV-2 infected paediatric patients identifies evidence of remdesivir-associated inhibition of viral replication in vivo and uncovers evidence of within host evolution of distinct viral genotypes.

The southern beech (genus Fuscospora and Lophozonia) forest in New Zealand periodically has “mast” years, during which very large volumes of seeds are produced. This excessive seed production results in a population explosion of rodents and mustelids, which then puts pressure on native birds. To protect the birds, extra pest controls, costing in the order of NZD 20 million, are required in masting areas. To plan pest control and keep it cost-effective, it would be helpful to have a map of the masting areas. In this study, we developed a remote sensing method for the creation of a national beech flowering map. It used a temporal sequence of Sentinel-2 satellite imagery to determine areas in which a yellow index, which was based on red and green reflectance (red-green)/(red + green), was higher than normal in spring. The method was used to produce national maps of heavy beech flowering for the years 2017 to 2021. In 2018, which was a major beech masting year, of the 4.1 million ha of beech forest in New Zealand, 27.6% was observed to flower heavily. The overall classification accuracy of the map was 90.8%. The method is fully automated and could be used to help to identify areas of potentially excessive seed fall across the whole of New Zealand, several months in advance of when pest control would be required.

We have developed periscope, a tool for the detection and quantification of sub-genomic RNA (sgRNA) in SARS-CoV-2 genomic sequence data. The translation of the SARS-CoV-2 RNA genome for most open reading frames (ORFs) occurs via RNA intermediates termed “sub-genomic RNAs”. sgRNAs are produced through discontinuous transcription which relies on homology between transcription regulatory sequences (TRS-B) upstream of the ORF start codons and that of the TRS-L which is located in the 5’ UTR. TRS-L is immediately preceded by a leader sequence. This leader sequence is therefore found at the 5’ end of all sgRNA. We applied periscope to 1,155 SARS-CoV-2 genomes from Sheffield, UK and validated our findings using orthogonal datasets and in vitro cell systems. Using a simple local alignment to detect reads which contain the leader sequence we were able to identify and quantify reads arising from canonical and non-canonical sgRNA. We were able to detect all canonical sgRNAs at expected abundances, with the exception of ORF10. A number of recurrent non-canonical sgRNAs are detected. We show that the results are reproducible using technical replicates and determine the optimum number of reads for sgRNA analysis. In VeroE6 ACE2+/− cell lines, periscope can detect the changes in the kinetics of sgRNA in orthogonal sequencing datasets. Finally, variants found in genomic RNA are transmitted to sgRNAs with high fidelity in most cases. This tool can be applied to all sequenced COVID-19 samples worldwide to provide comprehensive analysis of SARS-CoV-2 sgRNA.

SARS-CoV-2, the causative agent of COVID-19, emerged in Wuhan, China in December 2019 and spread rapidly throughout the world. Understanding the introductions of this new coronavirus in different settings may assist control efforts and the establishment of frameworks to support rapid response in future infectious disease outbreaks.We investigated the first four weeks of emergence of the SARS-CoV-2 virus in Scotland after the first case reported on the 1st March 2020. We obtained full genome sequences from 452 individuals with a laboratory-confirmed diagnosis of COVID-19, representing 20% of all cases until 1st April 2020 (n=2310). This permitted a genomic epidemiology approach to study the introductions and spread of the SARS-2 virus in Scotland.From combined phylogenetic and epidemiological analysis, we estimated at least 113 introductions of SARS-CoV-2 into Scotland during this period. Clusters containing multiple sequences suggestive of onward transmission occurred in 48/86 (56%). 42/86 (51%) clusters had no known international travel history indicating undetected introductions.The majority of viral sequences were most closely related to those circulating in other European countries, including Italy, Austria and Spain. Travel-associated introductions of SARS-CoV-2 into Scotland predated travel restrictions in the UK and other European countries. The first local transmission occurred three days after the first case. A shift from travel-associated to sustained community transmission was apparent after only 11 days. Undetected introductions occurred prior to the first known case of COVID-19. Earlier travel restrictions and quarantine measures might have resulted in fewer introductions into Scotland, thereby reducing the number of cases and the subsequent burden on health services. The high number of introductions and transmission rates were likely to have impacted on national contact tracing efforts. Our results also demonstrate that local real-time genomic epidemiology can be used to monitor transmission clusters and facilitate control efforts to restrict the spread of COVID-19.FundingMRC (MC UU 1201412), UKRI/Wellcome (COG-UK), Wellcome Trust Collaborator Award (206298/Z/17/Z – ARTIC Network; TCW Wellcome Trust Award 204802/Z/16/ZResearch in contextEvidence before this studyCoronavirus disease-2019 (COVID-19) was first diagnosed in Scotland on the 1st of March 2020 following the emergence of the causative severe acute respiratory system coronavirus 2 (SARS-CoV-2) virus in China in December 2019. During the first month of the outbreak in Scotland, 2310 positive cases of COVID-19 were detected, associated with 1832 hospital admissions, 207 intensive care admissions and 126 deaths. The number of introductions into Scotland and the source of those introductions was not known prior to this study.Added value of this studyUsing a combined phylogenetic and epidemiological approach following real-time next generation sequencing of 452 SARS-CoV-2 samples, it was estimated that the virus was introduced to Scotland on at least 113 occasions, mostly from other European countries, including Italy, Austria and Spain. Localised outbreaks occurred in the community across multiple Scottish health boards, within healthcare facilities and an international conference and community transmission was established rapidly, before local and international lockdown measures were introduced.

The claim of the open government data (OGD) movement is that it would add considerable value to the political, economic and social development of nations. Thus, during the past few years, governments around the world have been under increasing pressure to release data to encourage citizen participation in government. In the UK, the government publishes its data on the data.gov.uk website for the public to find, view, download and interrogate. 1 In this paper, we evaluate the extent of openness of OGD in the UK – a recognised global leader in the OGD movement – by examining a sample of 400 datasets listed on this website. The examination uses an ‘ordinary citizen’ test, which is developed based on the original eight Sebastopol principles of open data. Our examination discovers that existing prevalent measures of openness of data are inadequate. Our findings demonstrate that the majority of the published government resources on the website are informational rather than granular data. In fact, only a small minority of these advertised as open data are actually open, which severely limits their open government utilities.

The endemic New Zealand kauri trees (Agathis australis) are of major importance for the forests in the northern part of New Zealand. The mapping of kauri locations is required for the monitoring of the deadly kauri dieback disease (Phytophthora agathidicida (PTA)). In this study, we developed a method to identify kauri trees by optical remote sensing that can be applied in an area-wide campaign. Dead and dying trees were separated in one class and the remaining trees with no to medium stress symptoms were defined in the two classes “kauri” and “other”. The reference dataset covers a representative selection of 3165 precisely located crowns of kauri and 21 other canopy species in the Waitakere Ranges west of Auckland. The analysis is based on an airborne hyperspectral AISA Fenix image (437–2337 nm, 1 m2 pixel resolution). The kauri spectra show characteristically steep reflectance and absorption features in the near-infrared (NIR) region with a distinct long descent at 1215 nm, which can be parameterised with a modified Normalised Water Index (mNDWI-Hyp). With a Jeffries–Matusita separability over 1.9, the kauri spectra can be well separated from 21 other canopy vegetation spectra. The Random Forest classifier performed slightly better than Support Vector Machine. A combination of the mNDWI-Hyp index with four additional spectral indices with three red to NIR bands resulted in an overall pixel-based accuracy (OA) of 91.7% for crowns larger 3 m diameter. While the user’s and producer’s accuracies for the class “kauri” with 94.6% and 94.8% are suitable for management purposes, the separation of “dead/dying trees” from “other” canopy vegetation poses the main challenge. The OA can be improved to 93.8% by combining “kauri” and “dead/dying” trees in one class, separate classifications for low and high forest stands and a binning to 10 nm bandwidths. Additional wavelengths and their respective indices only improved the OA up to 0.6%. The method developed in this study allows an accurate location of kauri trees for an area-wide mapping with a five-band multispectral sensor in a representative selection of forest ecosystems.

This paper explores the rarely researched areas of co-offending and bribery. Based upon interviews with six persons convicted of bribery-related offences and other cases in the public domain, the paper explores how previously ‘clean’ persons are recruited to corrupt schemes. In doing so, the paper draws on Reason’s resident pathogen theory on safety and uniquely applies it to bribery. The paper also identifies common recruitment techniques used by corruptors and proposes pathogen network analysis as a novel method for enhancing bribery prevention.

The resilience of some high-profile white-collar criminals in the media gaze after prison may lead some to conclude, particularly as some research also supports this notion, that this group of offenders generally manages well after conviction. Research in this area is, however, small and largely American. The authors seek to add to this small body of research by offering findings on the impact of conviction on 17 UK convicted white-collar criminals after completion of their sentence. It provides a unique insight into the consequences of conviction, showing that although there were some offenders who did experience limited impact and coped well, there was also a significant group who suffered a decline in status, financial losses, negative media coverage, and relationship and mental health problems, to name some. The authors argue more research is needed on this group and their needs as they are often neglected by the criminal justice system.

Background Among people living with HIV (PLHIV), more flexible and sensitive tuberculosis (TB) screening tools capable of detecting both symptomatic and subclinical active TB are needed to (1) reduce morbidity and mortality from undiagnosed TB; (2) facilitate scale-up of tuberculosis preventive therapy (TPT) while reducing inappropriate prescription of TPT to PLHIV with subclinical active TB; and (3) allow for differentiated HIV–TB care. Methods and findings We used Botswana XPRES trial data for adult HIV clinic enrollees collected during 2012 to 2015 to develop a parsimonious multivariable prognostic model for active prevalent TB using both logistic regression and random forest machine learning approaches. A clinical score was derived by rescaling final model coefficients. The clinical score was developed using southern Botswana XPRES data and its accuracy validated internally, using northern Botswana data, and externally using 3 diverse cohorts of antiretroviral therapy (ART)-naive and ART-experienced PLHIV enrolled in XPHACTOR, TB Fast Track (TBFT), and Gugulethu studies from South Africa (SA). Predictive accuracy of the clinical score was compared with the World Health Organization (WHO) 4-symptom TB screen. Among 5,418 XPRES enrollees, 2,771 were included in the derivation dataset; 67% were female, median age was 34 years, median CD4 was 240 cells/μL, 189 (7%) had undiagnosed prevalent TB, and characteristics were similar between internal derivation and validation datasets. Among XPHACTOR, TBFT, and Gugulethu cohorts, median CD4 was 400, 73, and 167 cells/μL, and prevalence of TB was 5%, 10%, and 18%, respectively. Factors predictive of TB in the derivation dataset and selected for the clinical score included male sex (1 point), ≥1 WHO TB symptom (7 points), smoking history (1 point), temperature >37.5°C (6 points), body mass index (BMI) 10) yielded TB prevalence of 1%, 1%, 2%, and 6% in the lowest risk group and 33%, 22%, 26%, and 32% in the highest risk group for XPRES, XPHACTOR, TBFT, and Gugulethu cohorts, respectively. At clinical score ≥2, the number needed to screen (NNS) ranged from 5.0 in Gugulethu to 11.0 in XPHACTOR. Limitations include that the risk score has not been validated in resource-rich settings and needs further evaluation and validation in contemporary cohorts in Africa and other resource-constrained settings. Conclusions The simple and feasible clinical score allowed for prioritization of sensitivity and NPV, which could facilitate reductions in mortality from undiagnosed TB and safer administration of TPT during proposed global scale-up efforts. Differentiation of risk by clinical score cutoff allows flexibility in designing differentiated HIV–TB care to maximize impact of available resources., Andrew Auld and colleagues evaluate a clinical score for active tuberculosis in persons with HIV infection., Author summary Why was this study done? Tuberculosis (TB) remains the most common cause of death among people living with HIV (PLHIV) and is often undiagnosed at time of death. Rapid scale-up of tuberculosis preventive therapy (TPT) to 13 million PLHIV in low- and middle-income countries (LMICs) has been proposed for 2021; however, active TB is commonly asymptomatic and therefore missed by current WHO-recommended 4-symptom TB screening rules. Therefore, more sensitive TB screening tools are needed to better facilitate early TB diagnosis and safer scale-up of TPT to PLHIV by avoiding TPT prescription to clients with asymptomatic active TB, who need TB treatment. What did the researchers do and find? We derived a TB risk score for PLHIV from XPRES trial data and validated the score on 3 external datasets. We prioritized high sensitivity and ability to correctly rule out TB (i.e., high negative predictive value (NPV)) at key time points in care such as HIV clinic enrollment and before TPT prescription. Both logistic regression and random forest machine learning approaches were used to identify the 6 most important predictors, commonly available in LMIC clinic settings. In the external datasets, TB risk score ≥2 had higher sensitivity (87% to 97%) than WHO 4-symptom screening rule and increased NPV by 0.3% to 1.7%. Three risk groups were identified by the score, with active TB prevalence in external datasets ranging from 1% to 6% in the lowest to 22% to 32% in the highest risk groups. What do these findings mean? Following further validation, this clinical score could improve early detection of active TB to reduce morbidity and mortality from undiagnosed TB. Use of the clinical score cutoff of ≥2 during the proposed TPT scale-up for 13 million PLHIV could potentially avoid many thousands of PLHIV with active TB being inappropriately prescribed TPT. By differentiating 3 risk groups, the score also allows for the development of differentiated service delivery models suitable for LMIC.

Mycobacterium tuberculosis complex (MTBC) is divided into several major phylogenetic lineages, with differential distribution globally. Using population-based data collected over a three year period, we performed 24-locus Mycobacterial Interspersed Repeat Unit – Variable Number Tandem Repeat (MIRU-VNTR) genotyping on all culture isolates from two districts of the country that differ in tuberculosis (TB) incidence (Gaborone, the capital, and Ghanzi in the Western Kalahari). The study objective was to characterize the molecular epidemiology of TB in these districts. Overall phylogenetic diversity mirrored that reported from neighboring Republic of South Africa, but differences in the two districts were marked. All four major lineages of M. tuberculosis were found in Gaborone, but only three of the four major lineages were found in Ghanzi. Strain diversity was lower in Ghanzi, with a large proportion (38%) of all isolates having an identical MIRU-VNTR result, compared to 6% of all isolates in Gaborone with the same MIRU-VNTR result. This study demonstrates localized differences in strain diversity by two districts in Botswana, and contributes to a growing characterization of MTBC diversity globally.