There have been numerous risk tools developed to enable triaging of SARS-CoV-2 positive patients with diverse levels of complexity. Here we presented a simplified risk-tool based on minimal ...parameters and chest X-ray (CXR) image data that predicts the survival of adult SARS-CoV-2 positive patients at hospital admission. We analysed the NCCID database of patient blood variables and CXR images from 19 hospitals across the UK using multivariable logistic regression. The initial dataset was non-randomly split between development and internal validation dataset with 1434 and 310 SARS-CoV-2 positive patients, respectively. External validation of the final model was conducted on 741 Accident and Emergency (A&E) admissions with suspected SARS-CoV-2 infection from a separate NHS Trust. The LUCAS mortality score included five strongest predictors (Lymphocyte count, Urea, C-reactive protein, Age, Sex), which are available at any point of care with rapid turnaround of results. Our simple multivariable logistic model showed high discrimination for fatal outcome with the area under the receiving operating characteristics curve (AUC-ROC) in development cohort 0.765 (95% confidence interval (CI): 0.738-0.790), in internal validation cohort 0.744 (CI: 0.673-0.808), and in external validation cohort 0.752 (CI: 0.713-0.787). The discriminatory power of LUCAS increased slightly when including the CXR image data. LUCAS can be used to obtain valid predictions of mortality in patients within 60 days of SARS-CoV-2 RT-PCR results into low, moderate, high, or very high risk of fatality.
The virus neutralization assay is a principal method to assess the efficacy of antibodies in blocking viral entry. Due to biosafety handling requirements of viruses classified as hazard group 3 or 4, ...pseudotyped viruses can be used as a safer alternative. However, it is often queried how well the results derived from pseudotyped viruses correlate with authentic virus. This systematic review and meta-analysis was designed to comprehensively evaluate the correlation between the two assays.
Using PubMed and Google Scholar, reports that incorporated neutralisation assays with both pseudotyped virus, authentic virus, and the application of a mathematical formula to assess the relationship between the results, were selected for review. Our searches identified 67 reports, of which 22 underwent a three-level meta-analysis.
The three-level meta-analysis revealed a high level of correlation between pseudotyped viruses and authentic viruses when used in an neutralisation assay. Reports that were not included in the meta-analysis also showed a high degree of correlation, with the exception of lentiviral-based pseudotyped Ebola viruses.
Pseudotyped viruses identified in this report can be used as a surrogate for authentic virus, though care must be taken in considering which pseudotype core to use when generating new uncharacterised pseudotyped viruses.
Acute kidney injury (AKI) is a prevalent complication in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive inpatients, which is linked to an increased mortality rate compared to ...patients without AKI. Here we analysed the difference in kidney blood biomarkers in SARS-CoV-2 positive patients with non-fatal or fatal outcome, in order to develop a mortality prediction model for hospitalised SARS-CoV-2 positive patients. A retrospective cohort study including data from suspected SARS-CoV-2 positive patients admitted to a large National Health Service (NHS) Foundation Trust hospital in the Yorkshire and Humber regions, United Kingdom, between 1 March 2020 and 30 August 2020. Hospitalised adult patients (aged ≥ 18 years) with at least one confirmed positive RT-PCR test for SARS-CoV-2 and blood tests of kidney biomarkers within 36 h of the RT-PCR test were included. The main outcome measure was 90-day in-hospital mortality in SARS-CoV-2 infected patients. The logistic regression and random forest (RF) models incorporated six predictors including three routine kidney function tests (sodium, urea; creatinine only in RF), along with age, sex, and ethnicity. The mortality prediction performance of the logistic regression model achieved an area under receiver operating characteristic (AUROC) curve of 0.772 in the test dataset (95% CI: 0.694–0.823), while the RF model attained the AUROC of 0.820 in the same test cohort (95% CI: 0.740–0.870). The resulting validated prediction model is the first to focus on kidney biomarkers specifically on in-hospital mortality over a 90-day period.
Diagnostics for COVID-19 detection are limited in many settings. Syndromic surveillance is often the only means to identify cases but lacks specificity. Rapid antigen testing is inexpensive and ...easy-to-deploy but can lack sensitivity. We examine how combining these approaches can improve surveillance for guiding interventions in low-income communities in Dhaka, Bangladesh. Rapid-antigen-testing with PCR validation was performed on 1172 symptomatically-identified individuals in their homes. Statistical models were fitted to predict PCR-status using rapid-antigen-test results, syndromic data, and their combination. Under contrasting epidemiological scenarios, the models' predictive and classification performance was evaluated. Models combining rapid-antigen-testing and syndromic data yielded equal-to-better performance to rapid-antigen-test-only models across all scenarios with their best performance in the epidemic growth scenario. These results show that drawing on complementary strengths across rapid diagnostics, improves COVID-19 detection, and reduces false-positive and -negative diagnoses to match local requirements; improvements achievable without additional expense, or changes for patients or practitioners.
Aim
Species rarity is often used as a measure to assess the risk of extinction of species, and thus, different methods have been developed to describe the composition of rare species in biological ...communities. These methods usually depend on species attributes that are not always available and very often ignore imperfect species detection. In this work, we developed a new method to characterize species rarity in a community when species are detected imperfectly. Our modelling framework is based on Bayesian occupancy models to estimate species distributions under imperfect detection using presence‐nondetection data.
Innovation
We propose a finite mixture occupancy model to identify rare species based on their occupancy and class‐membership probabilities. Here, we explored a two‐class finite mixture model to distinguish between rare and common species classes and presented the general modelling framework for a problem with more than two classes. By using simulations, we were able to compare our model results under different scenarios obtaining a high‐classification performance across all of them. Additionally, we applied our model to a data set of Odonata occurrence records that were partially observed due to imperfect detection and quantified the proportion of rare species on a national scale across waterbodies in the United Kingdom.
Main conclusions
Nowadays, biodiversity conservation involves monitoring programmes that target multiple species within a community where individual species responses may vary widely. This high variability makes the task of identifying the ecological processes that drive distributions of rare species difficult. Thus, our method represents a new approach to characterize the composition of a community in terms of species rarity while correcting for detectability bias. Our modelling framework also suggests lines of research and future developments for the understanding of how species rarity can be measured in a wide range of scenarios.
Understanding the spatiotemporal dynamics of river water chemistry from its source to sinks is critical for constraining the origin, transformation, and “hotspots” of contaminants in a river basin. ...To provide new spatiotemporal constraints on river chemistry, dissolved trace element concentrations were measured at 17 targeted locations across the Ramganga River catchment. River water samples were collected across three seasons: pre-monsoon, monsoon, and post-monsoon between 2019 and 2021. To remove the dependency of trace element concentrations on discharge, we used molar ratios, as discharge data on Indian transboundary rivers are not publicly available. The dataset reveals significant spatiotemporal variability in dissolved trace element concentrations of the Ramganga River. Samples collected upstream of Moradabad, a major industrial city in western Uttar Pradesh, are characterized by ~ 1.2–2.5 times higher average concentrations of most of the trace elements except Sc, V, Cr, Rb, and Pb, likely due to intense water–rock interactions in the headwaters. Such kind of enrichment in trace metal concentrations was also observed at sites downstream of large cities and industrial centers. However, such enrichment was not enough to bring a major change in the River Ganga chemistry, as the signals got diluted downstream of the Ramganga-Ganga confluence. The average river water composition of the Ramganga River was comparable to worldwide river water composition, albeit a few sites were characterized by very high concentrations of dissolved trace elements. Finally, we provide an outlook that calls for an assessment of stable non-traditional isotopes that are ideally suited to track the origin and transformation of elements such as Li, Mg, Ca, Ti, V, Cr, Fe, Ni, Cu, Zn, Sr, Ag, Cd, Sn, Pt, and Hg in Indian rivers.
To determine how the intrinsic severity of successively dominant SARS-CoV-2 variants changed over the course of the pandemic.
A retrospective cohort analysis in the NHS Greater Glasgow and Clyde (NHS ...GGC) Health Board. All sequenced non-nosocomial adult COVID-19 cases in NHS GGC with relevant SARS-CoV-2 lineages (B.1.177/Alpha, Alpha/Delta, AY.4.2 Delta/non-AY.4.2 Delta, non-AY.4.2 Delta/Omicron, and BA.1 Omicron/BA.2 Omicron) during analysis periods were included. Outcome measures were hospital admission, ICU admission, or death within 28 days of positive COVID-19 test. We report the cumulative odds ratio; the ratio of the odds that an individual experiences a severity event of a given level vs all lower severity levels for the resident and the replacement variant after adjustment.
After adjustment for covariates, the cumulative odds ratio was 1.51 (95% CI: 1.08–2.11) for Alpha versus B.1.177, 2.09 (95% CI: 1.42–3.08) for Delta versus Alpha, 0.99 (95% CI: 0.76–1.27) for AY.4.2 Delta versus non-AY.4.2 Delta, 0.49 (95% CI: 0.22–1.06) for Omicron versus non-AY.4.2 Delta, and 0.86 (95% CI: 0.68–1.09) for BA.2 Omicron versus BA.1 Omicron.
The direction of change in intrinsic severity between successively emerging SARS-CoV-2 variants was inconsistent, reminding us that the intrinsic severity of future SARS-CoV-2 variants remains uncertain.
•Dominant SARS-CoV-2 variants showed higher and lower severity than their precursors.•Conclusions are unchanged when a more stringent severity classifications are used.•The historical trend suggests more intrinsically severe variants arising is plausible.
The SARS-CoV-2 Alpha variant was associated with increased transmission relative to other variants present at the time of its emergence and several studies have shown an association between Alpha ...variant infection and increased hospitalisation and 28-day mortality. However, none have addressed the impact on maximum severity of illness in the general population classified by the level of respiratory support required, or death. We aimed to do this.
In this retrospective multi-centre clinical cohort sub-study of the COG-UK consortium, 1475 samples from Scottish hospitalised and community cases collected between 1st November 2020 and 30th January 2021 were sequenced. We matched sequence data to clinical outcomes as the Alpha variant became dominant in Scotland and modelled the association between Alpha variant infection and severe disease using a 4-point scale of maximum severity by 28 days: 1. no respiratory support, 2. supplemental oxygen, 3. ventilation and 4. death.
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 (Alpha variant versus pre-Alpha variants).
The Alpha variant was associated with more severe clinical disease in the Scottish population than co-circulating lineages.
10 million people are chronically infected with the hepatitis C virus (HCV) in sub-Saharan Africa. The assessment of viral genotypes and treatment response in this region is necessary to achieve the ...WHO target of worldwide elimination of viral hepatitis by 2030. We aimed to investigate the prevalence of HCV genotypes and outcomes of treatment with direct-acting antiviral agents in Benin, a country with a national HCV seroprevalence of 4%.
This prospective cohort study was conducted at two referral hospitals in Benin. Individuals were eligible for inclusion if they were seropositive for HCV and willing to consent to participation in the study; exclusion criteria were an inability to give consent or incarceration. Viraemia was confirmed by PCR. The primary outcomes were to identify HCV genotypes and measure sustained virological response rates 12 weeks after completion of treatment (SVR12) with a 12-week course of sofosbuvir–velpatasvir or sofosbuvir–ledipasvir, with or without ribavirin. We conducted phylogenetic and resistance analyses after the next-generation sequencing of samples with a cycle threshold (Ct) value of 30 or fewer cycles. The in-vitro efficacy of NS5A inhibitors was tested using a subgenomic replicon assay.
Between June 2, 2019, and Dec 30, 2020, 148 individuals were screened for eligibility, of whom 100 were recruited prospectively to the study. Plasma samples from 79 (79%) of the 100 participants were positive for HCV by PCR. At the time of the study, 52 (66%) of 79 patients had completed treatment, with an SVR12 rate of 94% (49 of 52). 57 (72%) of 79 samples had a Ct value of 30 or fewer cycles and were suitable for whole-genome sequencing, from which we characterised 29 (51%) samples as genotype 1 and 28 (49%) as genotype 2. Three new genotype 1 subtypes (1q, 1r, and 1s) and one new genotype 2 subtype (2xa) were identified. The most commonly detected subtype was 2d (12 21% of 57 samples), followed by 1s (eight 14%), 1r (five 9%), 1b (four 7%), 1q (three 5%), 2xa (three 5%), and 2b (two 3%). 20 samples (11 genotype 2 and nine genotype 1) were unassigned new singleton lineages. 53 (93%) of 57 sequenced samples had at least two resistance-associated substitutions within the NS5A gene. Subtype 2d was associated with a lower-than-expected SVR12 rate (eight 80% of ten patients). For one patient, with subtype 2b, treatment was not successful.
This study revealed a high SVR rate in Benin among individuals treated for HCV with sofosbuvir–velpatasvir, including those with highly diverse viral genotypes. Further studies of treatment effectiveness in genotypes 2d and 2b are indicated.
Medical Research Council, Wellcome, Global Challenges Research Fund, Academy of Medical Sciences, and PHARMBIOTRAC.
Objectives The SARS-CoV-2 Alpha variant was associated with increased transmission relative to other variants present at the time of its emergence and several studies have shown an association ...between Alpha variant infection and increased hospitalisation and 28-day mortality. However, none have addressed the impact on maximum severity of illness in the general population classified by the level of respiratory support required, or death. We aimed to do this. Methods In this retrospective multi-centre clinical cohort sub-study of the COG-UK consortium, 1475 samples from Scottish hospitalised and community cases collected between 1st November 2020 and 30th January 2021 were sequenced. We matched sequence data to clinical outcomes as the Alpha variant became dominant in Scotland and modelled the association between Alpha variant infection and severe disease using a 4-point scale of maximum severity by 28 days: 1. no respiratory support, 2. supplemental oxygen, 3. ventilation and 4. death. Results 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 (Alpha variant versus pre-Alpha variants). Conclusions The Alpha variant was associated with more severe clinical disease in the Scottish population than co-circulating lineages.
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