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10.1101/2020.10.13.20182949 | sMAdCAM:IL-6 (sMIL Index): A novel signature associated with COVID-19 disease progression and development of anti-SARS-CoV-2 antibodies | Recent studies positing the gut as a sanctuary site for viral persistence in SARS-CoV-2 infection highlight the importance of assimilating profiles of systemic as well as gut inflammatory mediators to understand the pathology of COVID-19. Also, the role of these markers in governing virus specific immunity following infection remains largely unexplored. A cohort (n=84) of SARS-C0V-2 infected individuals included a group of in-patients (n=60) at various stages of disease progression together with convalescent individuals (n=24) recruited between April and June 2020 from Mumbai, India. Follow-up of 35 in-patients at day 7 post diagnosis was carried out. Th1/Th2/Th17 cytokines along with soluble MAdCAM (sMAdCAM) levels in plasma were measured. Also, anti-viral humoral response as measured by rapid antibody test (IgG, IgM), Chemiluminescent Immunoassay (IgG) and antibodies binding to SARS-CoV-2 proteins were measured by Surface Plasmon Resonance (SPR) from plasma.IL-6 and sMAdCAM levels among in-patients inversely correlated with one another. When expressed as a novel integrated marker -sMIL index (sMAdCAM/IL-6 ratio), these levels were incrementally and significantly higher in various disease states with convalescents exhibiting the highest values. Importantly, sMAdCAM levels as well as sMIL index (fold change) correlated with peak association rates of receptor binding domain and fold change in binding to spike respectively as measured by SPR. Our results highlight key systemic and gutassociated parameters that need to be monitored and investigated further to optimally guide therapeutic and prophylactic interventions for COVID-19. | infectious diseases |
10.1101/2020.10.14.20212415 | CoViD-19, learning from the past: A wavelet and cross-correlation analysis of the epidemic dynamics looking to emergency calls and Twitter trends in Italian Lombardy region | The first case of Coronavirus Disease 2019 in Italy was detected on February the 20th in Lombardy region. Since that date, Lombardy has been the most affected Italian region by the epidemic, and its healthcare system underwent a severe overload during the outbreak. From a public health point of view, therefore, it is fundamental to provide healthcare services with tools that can reveal possible new health system stress periods with a certain time anticipation, which is the main aim of the present study. Moreover, the sequence of law decrees to face the epidemic and the large amount of news generated in the population feelings of anxiety and suspicion. Considering this whole complex context, it is easily understandable how people "overcrowded" social media with messages dealing with the pandemic, and emergency numbers were overwhelmed by the calls. Thus, in order to find potential predictors of possible new health system overloads, we analysed data both from Twitter and emergency services comparing them to the daily infected time series at a regional level. Particularly, we performed a wavelet analysis in the time-frequency plane, to finely discriminate over time the anticipation capability of the considered potential predictors. In addition, a cross-correlation analysis has been performed to find a synthetic indicator of the time delay between the predictor and the infected time series. Our results show that Twitter data are more related to social and political dynamics, while the emergency calls trends can be further evaluated as a powerful tool to potentially forecast new stress periods. Since we analysed aggregated regional data, and taking into account also the huge geographical heterogeneity of the epidemic spread, a future perspective would be to conduct the same analysis on a more local basis. | public and global health |
10.1101/2020.10.14.20212415 | CoViD-19, learning from the past: A wavelet and cross-correlation analysis of the epidemic dynamics looking to emergency calls and Twitter trends in Italian Lombardy region | The first case of Coronavirus Disease 2019 in Italy was detected on February the 20th in Lombardy region. Since that date, Lombardy has been the most affected Italian region by the epidemic, and its healthcare system underwent a severe overload during the outbreak. From a public health point of view, therefore, it is fundamental to provide healthcare services with tools that can reveal possible new health system stress periods with a certain time anticipation, which is the main aim of the present study. Moreover, the sequence of law decrees to face the epidemic and the large amount of news generated in the population feelings of anxiety and suspicion. Considering this whole complex context, it is easily understandable how people "overcrowded" social media with messages dealing with the pandemic, and emergency numbers were overwhelmed by the calls. Thus, in order to find potential predictors of possible new health system overloads, we analysed data both from Twitter and emergency services comparing them to the daily infected time series at a regional level. Particularly, we performed a wavelet analysis in the time-frequency plane, to finely discriminate over time the anticipation capability of the considered potential predictors. In addition, a cross-correlation analysis has been performed to find a synthetic indicator of the time delay between the predictor and the infected time series. Our results show that Twitter data are more related to social and political dynamics, while the emergency calls trends can be further evaluated as a powerful tool to potentially forecast new stress periods. Since we analysed aggregated regional data, and taking into account also the huge geographical heterogeneity of the epidemic spread, a future perspective would be to conduct the same analysis on a more local basis. | public and global health |
10.1101/2020.10.14.20212464 | ATTENTIONAL MODULATION OF NEURAL DYNAMICS IN TACTILE PERCEPTION OF COMPLEX REGIONAL PAIN SYNDROME PATIENTS | Body perceptual disturbances are an increasingly acknowledged set of symptoms and possible clinical markers of Complex Regional Pain Syndrome (CRPS), but the neurophysiological and neurocognitive changes that underlie them are still far from being clear. We adopted a multivariate and neurodynamical approach to the analysis of EEG modulations evoked by touch to highlight differences between patients and healthy controls, between affected and unaffected side of the body, and between "passive" (i.e. no task demands and equiprobable digit stimulation) and "active" tactile processing (i.e. where a digit discrimination task was administered and spatial probability manipulated). When correct identifications are considered, an early reduction in cortical decodability (28-56 ms) distinguishes CRPS patients from healthy volunteers. However, when error trials are included in the classifiers training, there is an unexpected increased decodability in the CRPS group compared to healthy volunteers (280-320 ms). These group differences in neural processing seemed to be driven by the affected rather than the unaffected side. We corroborated these findings with several exploratory analyses of neural representation dynamics and behavioural modelling, highlighting the need for single participant analyses. Although several limitations impacted the robustness and generalizability of these comparisons, the proposed analytical approach yielded promising insights (as well as possible biomarkers based on neural dynamics) into the relatively unexplored alterations of tactile decision-making and attentional control mechanisms in chronic CRPS. | rheumatology |
10.1101/2020.10.15.20200600 | The impact of anorexia nervosa and BMI polygenic risk on childhood growth: a 20-year longitudinal population-based study | BackgroundDeviating growth from the norm during childhood has been associated with anorexia nervosa (AN) and obesity later in life. In this study, we examined whether polygenic scores (PGSs) for AN and BMI are associated with growth trajectories spanning the first two decades of life.
MethodsAN-PGS and BMI-PGS were calculated for participants of the Avon Longitudinal Study of Parents and Children (ALSPAC; N=8,654). Using generalized (mixed) linear models, we associated PGSs with trajectories of weight, height, body mass index (BMI), fat mass index (FMI), lean mass index (LMI), and bone mineral density (BMD).
ResultsFemale participants with one SD higher AN-PGS had on average 0.004% slower growth in BMI between the ages 6.5-24 years and a 0.4% slower growth in BMD between the ages 10-24 years. Higher BMI-PGS was associated with faster growth for BMI, FMI, LMI, BMD, and weight trajectories in both sexes throughout childhood. Female participants with both a high AN-PGS and a low BMI-PGS showed slower growth compared to those with both a low AN-PGS and a low BMI-PGS.
ConclusionAN-PGS and BMI-PGS have detectable sex-specific effects on growth trajectories. Female participants with high AN-PGS and low BMI-PGS likely constitute a high-risk group for AN as their growth was slower compared to their peers with high PGS on both traits. Further research is needed to better understand how the AN-PGS and the BMI-PGS co-influence growth during childhood and whether high BMI-PGSs can mitigate the effects of a high AN-PGS. | genetic and genomic medicine |
10.1101/2020.10.14.20212993 | White blood cells and severe COVID-19: a Mendelian randomization study | Increasing evidence shows that white blood cells are associated with the risk of coronavirus disease 2019 (COVID-19), but the direction and causality of this association are not clear. To evaluate the causal associations between various white blood cell traits and the COVID-19 susceptibility and severity, we conducted two-sample bidirectional Mendelian Randomization (MR) analyses with summary statistics from the largest and most recent genome-wide association studies. Our MR results indicated causal protective effects of higher basophil count, basophil percentage of white blood cells, and myeloid white blood cell count on severe COVID-19, with odds ratios (OR) per standard deviation increment of 0.75 (95% CI: 0.60-0.95), 0.70 (95% CI: 0.54-0.92), and 0.85 (95% CI: 0.73-0.98), respectively. Neither COVID-19 severity nor susceptibility was associated with white blood cell traits in our reverse MR results. Genetically predicted high basophil count, basophil percentage of white blood cells, and myeloid white blood cell count are associated with a lower risk of developing severe COVID-19. Individuals with a lower genetic capacity for basophils are likely at risk, while enhancing the production of basophils may be an effective therapeutic strategy. | epidemiology |
10.1101/2020.10.15.20208454 | Modelling SARS-CoV-2 transmission in a UK university setting | Around 40% of school leavers in the UK attend university and individual universities generally host thousands of students each academic year. Bringing together these student communities during the COVID-19 pandemic may require strong interventions to control transmission. Prior modelling analyses of SARS-CoV-2 transmission within universities using compartmental modelling approaches suggest that outbreaks are almost inevitable.
We constructed a network-based model to capture the interactions of a student population in different settings (housing, social and study). For a single academic term of a representative campus-based university, we ran a susceptible-latent-infectious-recovered type epidemic process, parameterised according to available estimates for SARS-CoV-2. We investigated the impact of: adherence to (or effectiveness of) isolation and test and trace measures; room isolation of symptomatic students; and supplementary mass testing.
With all adhering to test, trace and isolation measures, we found that 22% (7% - 41%) of the student population could be infected during the autumn term, compared to 69% (56% - 76%) when assuming zero adherence to such measures. Irrespective of the adherence to isolation measures, on average a higher proportion of students resident on-campus became infected compared to students resident off-campus. Room isolation generated minimal benefits. Regular mass testing, together with high adherence to isolation and test and trace measures, could substantially reduce the proportion infected during the term compared to having no testing.
Our findings suggest SARS-CoV-2 may readily transmit in a university setting if there is limited adherence to nonpharmaceutical interventions and/or there are delays in receiving test results. Following isolation guidance and effective contact tracing curbed transmission and reduced the expected time an adhering student would spend in isolation. | infectious diseases |
10.1101/2020.10.15.20208454 | Modelling SARS-CoV-2 transmission in a UK university setting | Around 40% of school leavers in the UK attend university and individual universities generally host thousands of students each academic year. Bringing together these student communities during the COVID-19 pandemic may require strong interventions to control transmission. Prior modelling analyses of SARS-CoV-2 transmission within universities using compartmental modelling approaches suggest that outbreaks are almost inevitable.
We constructed a network-based model to capture the interactions of a student population in different settings (housing, social and study). For a single academic term of a representative campus-based university, we ran a susceptible-latent-infectious-recovered type epidemic process, parameterised according to available estimates for SARS-CoV-2. We investigated the impact of: adherence to (or effectiveness of) isolation and test and trace measures; room isolation of symptomatic students; and supplementary mass testing.
With all adhering to test, trace and isolation measures, we found that 22% (7% - 41%) of the student population could be infected during the autumn term, compared to 69% (56% - 76%) when assuming zero adherence to such measures. Irrespective of the adherence to isolation measures, on average a higher proportion of students resident on-campus became infected compared to students resident off-campus. Room isolation generated minimal benefits. Regular mass testing, together with high adherence to isolation and test and trace measures, could substantially reduce the proportion infected during the term compared to having no testing.
Our findings suggest SARS-CoV-2 may readily transmit in a university setting if there is limited adherence to nonpharmaceutical interventions and/or there are delays in receiving test results. Following isolation guidance and effective contact tracing curbed transmission and reduced the expected time an adhering student would spend in isolation. | infectious diseases |
10.1101/2020.10.15.20208454 | Modelling SARS-CoV-2 transmission in a UK university setting | Around 40% of school leavers in the UK attend university and individual universities generally host thousands of students each academic year. Bringing together these student communities during the COVID-19 pandemic may require strong interventions to control transmission. Prior modelling analyses of SARS-CoV-2 transmission within universities using compartmental modelling approaches suggest that outbreaks are almost inevitable.
We constructed a network-based model to capture the interactions of a student population in different settings (housing, social and study). For a single academic term of a representative campus-based university, we ran a susceptible-latent-infectious-recovered type epidemic process, parameterised according to available estimates for SARS-CoV-2. We investigated the impact of: adherence to (or effectiveness of) isolation and test and trace measures; room isolation of symptomatic students; and supplementary mass testing.
With all adhering to test, trace and isolation measures, we found that 22% (7% - 41%) of the student population could be infected during the autumn term, compared to 69% (56% - 76%) when assuming zero adherence to such measures. Irrespective of the adherence to isolation measures, on average a higher proportion of students resident on-campus became infected compared to students resident off-campus. Room isolation generated minimal benefits. Regular mass testing, together with high adherence to isolation and test and trace measures, could substantially reduce the proportion infected during the term compared to having no testing.
Our findings suggest SARS-CoV-2 may readily transmit in a university setting if there is limited adherence to nonpharmaceutical interventions and/or there are delays in receiving test results. Following isolation guidance and effective contact tracing curbed transmission and reduced the expected time an adhering student would spend in isolation. | infectious diseases |
10.1101/2020.10.10.20202622 | Clinical, neuroimaging and molecular spectrum of TECPR2-associated hereditary sensory and autonomic neuropathy with intellectual disability | PURPOSEBi-allelic TECPR2 variants have been associated with a complex syndrome with features of both a neurodevelopmental and neurodegenerative disorder. Here, we provide a comprehensive clinical description and variant interpretation framework for this genetic locus.
METHODSThrough an international collaboration, we identified 17 individuals from 15 families with bi-allelic TECPR2-variants. We systemically reviewed clinical and molecular data from this cohort and 11 cases previously reported. Phenotypes were standardized using Human Phenotype Ontology terms.
RESULTSA cross-sectional analysis revealed global developmental delay/intellectual disability, muscular hypotonia, ataxia, hyporeflexia, respiratory infections and central/nocturnal hypopnea as core manifestations. A review of brain MRI scans demonstrated a thin corpus callosum in 52%. We evaluated 17 distinct variants. Missense variants in TECPR2 are predominantly located in the N- and C-terminal regions containing {beta}-propeller repeats. Despite constituting nearly half of disease associated TECPR2 variants, classifying missense variants as (likely) pathogenic according to ACMG criteria remains challenging. We estimate a pathogenic variant carrier frequency of 1/1,221 in the general and 1/155 in the Jewish Ashkenazi populations.
CONCLUSIONBased on clinical, neuroimaging and genetic data, we provide recommendations for variant reporting, clinical assessment, and surveillance/treatment of individuals with TECPR2-associated disorder. This sets the stage for future prospective natural history studies.
CONFLICTS OF INTERESTAll authors involved in the study declare no conflicts of interest relevant to this study. | genetic and genomic medicine |
10.1101/2020.10.15.20212845 | Path-specific population attributable fractions | A population attributable fraction (PAF) represents the relative change in disease prevalence that one might expect if a particular exposure was absent from the population. Often, one might be interested in what percentage of this effect acts through particular pathways. For instance, the effect of excessive alcohol intake on stroke risk may be mediated by blood pressure, body mass index and several other intermediate risk factors. In this situation, attributable fractions for each mediating pathway of interest can be defined as the relative change in disease prevalence from disabling the effect of the exposure through that mediating pathway.
This quantity is related to, but distinct from the recently proposed metrics of direct and indirect PAF by Sjolander. In particular, while differing pathway-specific PAF will each usually be less than total PAF, they may sum over differing mediating pathways to more than total PAF, whereas direct and indirect PAF must sum to total PAF. Here, we present definitions, identifiability conditions and estimation approaches for pathway-specific attributable fractions. We illustrate results, and comparisons to indirect PAF using INTERSTROKE, a case-control study designed to quantify disease burden attributable to a number of known causal risk factors. | epidemiology |
10.1101/2020.10.14.20212613 | Epidemiology and Genetics of Preserved Ratio Impaired SpiroMetry (PRISm): An Analysis of UK Biobank | The authors have withdrawn this manuscript version because the FEV1 percent predicted variable (UK biobank data field 20154) that was used was to determine spirometric pattern was constructed in only "healthy never smokers" or heavy smokers. This means the paper is affected by selection bias and is not generalizable. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author. | respiratory medicine |
10.1101/2020.10.15.20213108 | FebriDx point-of-care test in patients with suspected COVID-19: a systematic review and individual patient data meta-analysis of diagnostic test accuracy studies | BackgroundWe conducted a systematic review and individual patient data (IPD) meta-analysis to evaluate the diagnostic accuracy of a commercial point-of-care test, the FebriDx lateral flow device (LFD), in adult patients with suspected COVID-19. The FebriDx LFD is designed to distinguish between viral and bacterial respiratory infection.
MethodsWe searched MEDLINE, EMBASE, PubMed, Google Scholar, LitCovid, ClinicalTrials.gov and preprint servers on the 13th of January 2021 to identify studies reporting diagnostic accuracy of FebriDx (myxovirus resistance protein A component) versus real time reverse transcriptase polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 in adult patients suspected of COVID-19. IPD were sought from studies meeting the eligibility criteria. Studies were screened for risk of bias using the QUADAS-2 tool. A bivariate linear mixed model was fitted to the data to obtain a pooled estimate of sensitivity and specificity with 95% confidence intervals (95% CIs). A summary receiver operating characteristic (SROC) curve of the model was constructed. A sub-group analysis was performed by meta-regression using the same modelling approach to compare pooled estimates of sensitivity and specificity between patients with a symptom duration of 0 to 7 days and >7 days, and patients aged between 16 to 73 years and >73 years.
ResultsTen studies were screened, and three studies with a total of 1481 patients receiving hospital care were included. FebriDx produced an estimated pooled sensitivity of 0.911 (95% CI: 0.855-0.946) and specificity of 0.868 (95% CI: 0.802-0.915) compared to RT-PCR. There were no significant differences between the sub-groups of 0 to 7 days and >7 days in estimated pooled sensitivity (p = 0.473) or specificity (p = 0.853). There were also no significant differences between the sub-groups of 16 to 73 years of age and >73 years of age in estimated pooled sensitivity (p = 0.946) or specificity (p = 0.486).
ConclusionsBased on the results of three studies, the FebriDx LFD had high diagnostic accuracy for COVID-19 in a hospital setting, however, the pooled estimates of sensitivity and specificity should be interpreted with caution due to the small number of studies included, risk of bias, and inconsistent reference standards. Further research is required to confirm these findings, and determine how FebriDx would perform in different healthcare settings and patient populations.
Trial registrationThis study was conducted at pace as part of the COVID-19 National Diagnostic Research and Evaluation Platform (CONDOR) national test evaluation programme (https://www.condor-platform.org), and as a result, no protocol was developed, and the study was not registered.
Lay summaryTests to diagnose COVID-19 are crucial to help control the spread of the disease and to guide treatment. Over the last few months, tests have been developed to diagnose COVID-19 either by detecting the presence of the virus or by detecting specific markers linked to the virus being active in the body. These tests use complex machines in laboratories accepting samples from large geographical areas. Sometimes it takes days for test results to come back. So, to reduce the wait for results, new portable tests are being developed. These point-of-care (POC) tests are designed to work close to where patients require assessment and care such as hospital emergency departments, GP surgeries or care homes. For these new POC tests to be useful, they should ideally be as good as standard laboratory tests.
In this study we looked at published research into a new test called FebriDx. FebriDx is a POC test that detects the bodys response to infection, and is claimed to be able to detect the presence of any viral infection, including infections due to the SARS-CoV-2 virus which causes COVID-19, as well as bacterial infections which can have similar symptoms. The FebriDx result was compared with standard laboratory tests for COVID-19 performed on the same patients throat and nose swab sample. We were able to analyse data from three studies with a total of 1481 adult patients who were receiving hospital care with symptoms of COVID-19 during the UK pandemic. Approximately one fifth of the patients were diagnosed as positive for SARS-CoV-2 virus using standard laboratory tests for COVID-19.
Our analysis demonstrated that FebriDx correctly identified 91 out of 100 patients who had COVID-19 according to the standard laboratory test. FebriDx also correctly identified 87 out of 100 patients who did not have COVID-19 according to the standard laboratory test. These results have important implications for how these tests could be used. As there were slightly fewer FebriDx false results when the results of the standard laboratory test were positive (9 out of 100) than when the results of the standard laboratory test were negative (13 out of 100), we can have slightly more confidence in a positive test result using FebriDx than a negative FebriDx result.
Overall, we have shown that the FebriDx POC test performed well during the UK COVID-19 pandemic when compared with laboratory tests, especially when COVID-19 was indicated. For the future, this means that the FebriDx POC test might be helpful in making a quick clinical decision on whether to isolate a patient with COVID-19-like symptoms arriving in a busy emergency department. However, our results indicate it would not completely replace the need to conduct a laboratory test in certain cases to confirm COVID-19.
There are limitations to our findings. For example, we do not know if FebriDx will work in a similar way with patients in different settings such as in the community or care homes. Similarly, we do not know whether other viral and bacterial infections which cause similar COVID-19 symptoms, and are more common in the autumn and winter months, could influence the FebriDx test accuracy. Our findings are also only based on three studies. | infectious diseases |
10.1101/2020.10.18.20214767 | Supporting COVID-19 Policy-Making with a Predictive Epidemiological Multi-Model Warning System | In response to the SARS-CoV-2 pandemic, the Austrian governmental crisis unit commissioned a forecast consortium with regularly projections of case numbers and demand for hospital beds. The goal was to assess how likely Austrian ICUs would become overburdened with COVID-19 patients in the upcoming weeks. We consolidated the output of three independent epidemiological models (ranging from agent-based micro simulation to parsimonious compartmental models) and published weekly short-term forecasts for the number of confirmed cases as well as estimates and upper bounds for the required hospital beds. Here, we report on three key contributions by which our forecasting and reporting system has helped shaping Austrias policy to navigate the crisis, namely (i) when and where case numbers and bed occupancy are expected to peak during multiple waves, (ii) whether to ease or strengthen non-pharmaceutical intervention in response to changing incidences, and (iii) how to provide hospital managers guidance to plan health-care capacities. Complex mathematical epidemiological models play an important role in guiding governmental responses during pandemic crises, in particular when they are used as a monitoring system to detect epidemiological change points. | health policy |
10.1101/2020.10.16.20213835 | A Study on the Effects of Containment Policies and Vaccination on the Spread of SARS-CoV-2 | This paper presents a method to predict the spread of the SARS-CoV-2 in a population with a known age-structure, and then, to quantify the effects of various containment policies, including those policies that affect each age-group differently. The model itself is a compartmental model in which each compartment is divided into a number of age-groups. The parameters of the model are estimated using an optimisation scheme and some known results from the theory of monotone systems such that the model output agrees with some collected data on the spread of SARS-CoV-2.
To highlight the strengths of this framework, a few case studies are presented in which different populations are subjected to different containment strategies. They include cases in which the containment policies switch between scenarios with different levels of severity. Then a case study on herd immunity due to vaccination is presented. And then it is shown how we can use this framework to optimally distribute a limited number of vaccine units in a given population to maximise their impact and reduce the total number of infectious individuals.
MSC subclass92C60, 92C50 | epidemiology |
10.1101/2020.10.17.20214304 | A Methodological Checklist for fMRI Drug Cue Reactivity Studies: Development and Expert Consensus | BackgroundCue reactivity is one of the most frequently used paradigms in functional magnetic resonance imaging (fMRI) studies of substance use disorders (SUDs). While there have been promising results elucidating the neurocognitive mechanisms of SUDs and SUD treatments, the interpretability and reproducibility of these studies is limited by incomplete reporting of participant characteristics, task design, craving assessment, scanning preparation and analysis decisions in fMRI drug cue reactivity (FDCR) experiments. This hampers clinical translation, not least because systematic review and meta-analysis of published work is difficult. This consensus paper and Delphi study aims to outline the important methodological aspects of FDCR research, present structured recommendations for more comprehensive methods reporting, and review the FDCR literature to assess the reporting of items that are deemed important.
MethodsFifty-five FDCR scientists from around the world participated in this study. First, an initial checklist of items deemed important in FDCR studies was developed by several members of the Enhanced NeuroImaging Genetics through Meta-Analyses (ENIGMA) Addiction working group based on a systematic review. Using a modified Delphi consensus method, all experts were asked to comment on, revise or add items to the initial checklist, and then to rate the importance of each item in subsequent rounds. The reporting status of items in the final checklist was investigated in 108 recently published FDCR studies identified through a systematic review.
ResultsBy the final round, 38 items reached the consensus threshold and were classified under 7 major categories: "Participant Characteristics", "General fMRI Information", "General Task Information", "Cue Information", "Craving Assessment Inside Scanner", "Craving Assessment Outside Scanner" and "Pre- and Post- Scanning Considerations". The review of the 108 FDCR papers revealed significant gaps in the reporting of the items considered important by the experts. For instance, while items in the "general fMRI reporting" category were reported in 90.5% of the reviewed papers, items in the "pre- and post-scanning considerations" category were reported by only 44.7% of reviewed FDCR studies.
ConclusionConsidering the notable and sometimes unexpected gaps in the reporting of items deemed to be important by experts in any FDCR study, the protocols could benefit from the adoption of reporting standards. This checklist, a living document to be updated as the field and its methods advance, can help improve experimental design, reporting, and the widespread understanding of the FDCR protocols. This checklist can also provide a sample for developing consensus statements for protocols in other areas of task-based fMRI. | psychiatry and clinical psychology |
10.1101/2020.10.17.20214262 | Exact solution of infection dynamics with gamma distribution of generation intervals | Infectious disease outbreaks are expected to grow exponentially in time but their initial dynamics is less known. Here I derive analytical expressions for the infectious disease dynamics with a gamma distribution of generation intervals. Excluding the exponential distribution, the outbreak grows as a power law at short times. At long times the dynamics is exponential with a growth rate determined by the basic reproductive number and the parameters of the generation interval distribution. These analytical expressions can be deployed to do better estimates of infectious disease parameters. | infectious diseases |
10.1101/2020.10.18.20214585 | Exploring surveillance data biases when estimating the reproduction number: with insights into subpopulation transmission of Covid-19 in England | The time-varying reproduction number (Rt: the average number secondary infections caused by each infected person) may be used to assess changes in transmission potential during an epidemic. While new infections are not usually observed directly, they can be estimated from data. However, data may be delayed and potentially biased. We investigated the sensitivity of Rt estimates to different data sources representing Covid-19 in England, and we explored how this sensitivity could track epidemic dynamics in population sub-groups.
We sourced public data on test-positive cases, hospital admissions, and deaths with confirmed Covid-19 in seven regions of England over March through August 2020. We estimated Rt using a model that mapped unobserved infections to each data source. We then compared differences in Rt with the demographic and social context of surveillance data over time.
Our estimates of transmission potential varied for each data source, with the relative inconsistency of estimates varying across regions and over time. Rt estimates based on hospital admissions and deaths were more spatio-temporally synchronous than when compared to estimates from all test-positives. We found these differences may be linked to biased representations of subpopulations in each data source. These included spatially clustered testing, and where outbreaks in hospitals, care homes, and young age groups reflected the link between age and severity of disease.
We highlight that policy makers could better target interventions by considering the source populations of Rt estimates. Further work should clarify the best way to combine and interpret Rt estimates from different data sources based on the desired use. | epidemiology |
10.1101/2020.10.19.20213983 | Sex differences in the genetic regulation of the blood transcriptome response to glucocorticoid receptor activation | Substantial sex differences have been reported in the physiological response to stress at multiple levels, including the release of the stress hormone, cortisol. Here, we explore the genomic variants in 93 females and 196 males regulating the initial transcriptional response to cortisol via glucocorticoid receptor (GR) activation. Gene expression levels in peripheral blood were obtained before and after GR-stimulation with the selective GR agonist dexamethasone to identify differential expression following GR-activation. Sex stratified analyses revealed that while the transcripts responsive to GR-stimulation were mostly overlapping between males and females, the quantitative trait loci (eQTLs) regulation differential transcription to GR-stimulation were distinct. Sex-stratified eQTL SNPs (eSNPs) were located in different functional genomic elements and sex-stratified transcripts were enriched within postmortem brain transcriptional profiles associated with Major Depressive Disorder (MDD) specifically in males and females in the cingulate cortex. Female eSNPs were enriched among SNPs linked to MDD in genome wide association studies. Finally, transcriptional sensitive genetic profile scores derived from sex-stratified eSNPS regulating differential transcription to GR-stimulation were predictive of depression status and depressive symptoms in a sex-concordant manner in a child and adolescent cohort (n = 584). These results suggest potential of eQTLs regulating differential transcription to GR-stimulation as biomarkers of sex-specific biological risk for stress-related psychiatric disorders. | genetic and genomic medicine |
10.1101/2020.10.19.20213975 | Impact on microbiology laboratory turn-around-times following process improvements and total laboratory automation. | IntroductionThe impact of workflow changes and total laboratory automation (TLA) on microbiology culture processing time was evaluated in an academic-affiliated regional hospital.
Materials and MethodsA retrospective analysis of microbiological data in a research database was performed to compare turnaround time (TAT) for organism identification (ID) before and after implementation of TLA (2013 versus 2016, respectively). TAT was compared using the {chi}2 test for categorical variables and log-transformed t-test for continuous variables.
ResultsA total of 9,351 predefined common and clinically important positive mono-bacterial culture results were included in the analysis. Shorter TAT (hours) in 2016 compared to 2013 (p<0.0001) for positive result pathogen ID were observed in specimen types including blood (51.2 vs. 70.6), urine (40.7 vs. 47.1), wound (39.6 vs. 60.2), respiratory (47.7 vs. 67), and all specimen types combined (43.3 vs. 56.8). Although shorter TATs were not observed from all specimen categories for negative result pathogen ID, TAT for all specimen types combined was shorter (p[≤]0.001) in 2016 compared to 2013 (94 vs. 101).
ConclusionsTotal laboratory automation and workflow changes--including process standardization--facilitate shorter organism ID TAT across specimen sources. | health systems and quality improvement |
10.1101/2020.10.19.20215442 | Repeated introductions and intensive community transmission fueled a mumps virus outbreak in Washington State | In 2016/2017, Washington State experienced a mumps outbreak despite high childhood vaccination rates, with cases more frequently detected among school-aged children and members of the Marshallese community. We sequenced 166 mumps virus genomes collected during outbreaks in Washington and other US states, and apply phylodynamic approaches to trace mumps introductions and transmission within Washington. We uncover that mumps was introduced into Washington at least 13 times, primarily from Arkansas, sparking multiple co-circulating transmission chains. Neither vaccination status nor age were strong determinants of transmission. Instead, the outbreak in Washington was overwhelmingly sustained by transmission within the Marshallese community. Our findings underscore the utility of genomic data to clarify epidemiologic factors driving transmission, and pinpoint contact networks as critical determinants of mumps transmission. These results imply that contact structures and historic disparities may leave populations at increased risk for respiratory virus disease even when a vaccine is effective and widely used. | infectious diseases |
10.1101/2020.10.19.20215681 | Discussion of Mental Illness and Mental Health By NBA Players on Twitter | In 2019, the National Basketball Association (NBA) expanded its mental health rules to include mandating that each team have at least one mental health professional on their full-time staff and to retain a licensed psychiatrist to assist when needed. In this work, we investigate the NBA players discussion of mental health using historical data from players public Twitter accounts. All current and former NBA players with Twitter accounts were identified, and each of their last 800 tweets were scraped, yielding 920,000 tweets. A list of search terms derived from the DSM5 diagnoses was then created and used to search all of the nearly one million tweets. In this work, we present the most common search terms used to identify tweets about mental health, present the change in month-by-month tweets about mental health, and identify the impact of players discussing their own mental health struggles on their box score statistics before and after their first tweet discussing their own mental health struggles. | psychiatry and clinical psychology |
10.1101/2020.10.20.20215731 | Effect of park use and landscape structure on COVID-19 transmission rates | The COVID-19 pandemic has had severe impacts on global public health. In England, social distancing measures and a nationwide lockdown were introduced to reduce the spread of the virus. Green space accessibility may have been particularly important during this lockdown, as it could have provided benefits for physical and mental wellbeing. However, the associations between public green space use and the rate of COVID-19 transmission are yet to be quantified, and as the size and accessibility of green spaces vary within Englands local authorities, the risks and benefits to the public of using green space may be context-dependent. To evaluate how green space affected COVID-19 transmission across 299 local authorities (small regions) in England, we calculated a daily case rate metric, based upon a seven-day moving average, for each day within the period June 1st - November 30th 2020 and assessed how baseline health and mobility variables influenced these rates. Next, looking at the residual case rates, we investigated how landscape structure (e.g. area and patchiness of green space) and park use influenced transmission. We first show that reducing mobility is associated with a decline in case rates, especially in areas with high population clustering. After accounting for known mechanisms behind transmission rates, we found that park use (showing a preference for park mobility) was associated with decreased residual case rates, especially when green space was low and contiguous (not patchy). Our results support that a reduction in overall mobility may be a good strategy for reducing case rates, endorsing the success of lockdown measures. However, if mobility is necessary, outdoor park use may be safer than other forms of mobility and associated activities (e.g. shopping or office-based working). | public and global health |
10.1101/2020.10.20.20215731 | Effect of park use and landscape structure on COVID-19 transmission rates | The COVID-19 pandemic has had severe impacts on global public health. In England, social distancing measures and a nationwide lockdown were introduced to reduce the spread of the virus. Green space accessibility may have been particularly important during this lockdown, as it could have provided benefits for physical and mental wellbeing. However, the associations between public green space use and the rate of COVID-19 transmission are yet to be quantified, and as the size and accessibility of green spaces vary within Englands local authorities, the risks and benefits to the public of using green space may be context-dependent. To evaluate how green space affected COVID-19 transmission across 299 local authorities (small regions) in England, we calculated a daily case rate metric, based upon a seven-day moving average, for each day within the period June 1st - November 30th 2020 and assessed how baseline health and mobility variables influenced these rates. Next, looking at the residual case rates, we investigated how landscape structure (e.g. area and patchiness of green space) and park use influenced transmission. We first show that reducing mobility is associated with a decline in case rates, especially in areas with high population clustering. After accounting for known mechanisms behind transmission rates, we found that park use (showing a preference for park mobility) was associated with decreased residual case rates, especially when green space was low and contiguous (not patchy). Our results support that a reduction in overall mobility may be a good strategy for reducing case rates, endorsing the success of lockdown measures. However, if mobility is necessary, outdoor park use may be safer than other forms of mobility and associated activities (e.g. shopping or office-based working). | public and global health |
10.1101/2020.10.20.20215731 | Associations between COVID-19 transmission rates, park use, and landscape structure | The COVID-19 pandemic has had severe impacts on global public health. In England, social distancing measures and a nationwide lockdown were introduced to reduce the spread of the virus. Green space accessibility may have been particularly important during this lockdown, as it could have provided benefits for physical and mental wellbeing. However, the associations between public green space use and the rate of COVID-19 transmission are yet to be quantified, and as the size and accessibility of green spaces vary within Englands local authorities, the risks and benefits to the public of using green space may be context-dependent. To evaluate how green space affected COVID-19 transmission across 299 local authorities (small regions) in England, we calculated a daily case rate metric, based upon a seven-day moving average, for each day within the period June 1st - November 30th 2020 and assessed how baseline health and mobility variables influenced these rates. Next, looking at the residual case rates, we investigated how landscape structure (e.g. area and patchiness of green space) and park use influenced transmission. We first show that reducing mobility is associated with a decline in case rates, especially in areas with high population clustering. After accounting for known mechanisms behind transmission rates, we found that park use (showing a preference for park mobility) was associated with decreased residual case rates, especially when green space was low and contiguous (not patchy). Our results support that a reduction in overall mobility may be a good strategy for reducing case rates, endorsing the success of lockdown measures. However, if mobility is necessary, outdoor park use may be safer than other forms of mobility and associated activities (e.g. shopping or office-based working). | public and global health |
10.1101/2020.10.19.20215483 | Deep learning segmentation model for automated detection of the opacity regions in the chest X-rays of the Covid-19 positive patients and the application for disease severity | PurposeThe pandemic of Covid-19 has caused tremendous losses to lives and economy in the entire world. The machine learning models have been applied to the radiological images of the Covid-19 positive patients for disease prediction and severity assessment. However, a segmentation model for detecting the opacity regions like haziness, ground-glass opacity and lung consolidation from the Covid-19 positive chest X-rays is still lacking.
MethodsThe recently published collection of the radiological images for a rural population in United States had made the development of such a model a possibility, for the high quality images and consistent clinical measurements. We manually annotated 221 chest X-ray images with the lung fields and the opacity regions and trained a segmentation model for the opacity region using the Unet framework and the Resnet18 backbone. In addition, we applied the percentage of the opacity region over the area of the total lung fields for predicting the severity of patients.
ResultsThe model has a good performance regarding the overlap between the predicted and the manually labelled opacity regions. The performance is comparable for both the testing data set and the validation data set which comes from very diverse sources. However, careful manual examinations by experienced radiologists show mistakes in the predictions, which could be caused by the anatomical complexities. Nevertheless, the percentage of the opacity region can predict the severity of the patients well in regards to the ICU admissions and mortality.
ConclusionIn view of the above, our model is a successful first try in the development of a segmentation model for the opacity regions for the Covid-19 positive chest X-rays. However, additional work is needed before a robust model can be developed for the ultimate goal of the implementations in the clinical setting.
Model and supporting materials can be found in https://github.com/haimingt/opacity_segmentation_covid_chest_X_ray. | radiology and imaging |
10.1101/2020.10.19.20215392 | ANTsX: A dynamic ecosystem for quantitative biological and medical imaging | The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI, both cross-sectionally and longitudinally. These pipelines significantly improve computational efficiency and provide comparable-to-superior accuracy over multiple criteria relative to the existing ANTs workflows and simultaneously illustrate the importance of the comprehensive ANTsX approach as a framework for medical image analysis. | radiology and imaging |
10.1101/2020.10.19.20215392 | ANTsX: A dynamic ecosystem for quantitative biological and medical imaging | The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI, both cross-sectionally and longitudinally. These pipelines significantly improve computational efficiency and provide comparable-to-superior accuracy over multiple criteria relative to the existing ANTs workflows and simultaneously illustrate the importance of the comprehensive ANTsX approach as a framework for medical image analysis. | radiology and imaging |
10.1101/2020.10.19.20215392 | ANTsX: A dynamic ecosystem for quantitative biological and medical imaging | The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI, both cross-sectionally and longitudinally. These pipelines significantly improve computational efficiency and provide comparable-to-superior accuracy over multiple criteria relative to the existing ANTs workflows and simultaneously illustrate the importance of the comprehensive ANTsX approach as a framework for medical image analysis. | radiology and imaging |
10.1101/2020.10.19.20215392 | The ANTsX ecosystem for quantitative biological and medical imaging | The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI, both cross-sectionally and longitudinally. These pipelines significantly improve computational efficiency and provide comparable-to-superior accuracy over multiple criteria relative to the existing ANTs workflows and simultaneously illustrate the importance of the comprehensive ANTsX approach as a framework for medical image analysis. | radiology and imaging |
10.1101/2020.10.18.20214833 | Pre-treatment lactate dehydrogenase levels as predictor of hepatic resection in intermediate stage hepatocellular carcinoma | BackgroundThe selection criterion for hepatic resection(HR) in intermediate-stage(IM) hepatocellular carcinoma(HCC) is still controversial. We used real-world data to evaluate the overall survival (OS) treated with HR or TACE.
MethodsIn all, 942 patients with IM-HCC were categorized in HR and TACE groups. OS was analyzed using the Kaplan-Meier method, log-rank test, Cox proportional hazards models, and propensity score- matched (PSM) analyses. The smooth curve was performed through the generalized additive model. The interaction test was performed to evaluate the HR impact on OS concerning risk factors. Also, we used multiple imputation to deal with the missing data.
ResultsTotally, 23.0% (n=225) of patients received HR. At a median overall survival of 23.7 months, HR was associated with the improved OS on multivariate analysis (hazard ratio, 0.45; 95%CI: 0.35, 0.58; after PSM: 0.56; 95%CI: 0.41, 0.77). Landmark analyses limited to long-term survivors of [≥] 6 months, [≥] 1, and [≥] 2 years demonstrated better OS with HR in all subsets (all P<0.05). After PSM analysis, however, HR increased 20% risk of death (HR, 1.20; 95%CI: 0.67, 2.15) in the subgroup of LDH [≤]192 U/L (P for interaction = 0.037). Furthermore, the significant interaction was robust between the LDH and the HR with respect to 1-, 3-, and 5-year observed survival rate (all P<0.05).
ConclusionHepatic resection was superior to TACE for intermediate-stage HCC in the range of LDH level > 192 U/L. Moreover, TACE might be suitable for patients with LDH level [≤] 192 U/L.
SynopsisO_LIHepatectomy was superior to TACE for BCLC-B HCC.
C_LIO_LIHepatectomy increased 20% risk of death for LDH < 192 U/L after matching.
C_LIO_LIA significant interaction was robust between LDH and with respect to hepatectomy the 1-, 3-, and 5-year observed survival rate.
C_LI | oncology |
10.1101/2020.10.18.20214833 | Hepatic resection versus transarterial chemoembolization for the intermediate stage hepatocellular carcinoma：A cohort study | BackgroundThe selection criterion for hepatic resection(HR) in intermediate-stage(IM) hepatocellular carcinoma(HCC) is still controversial. We used real-world data to evaluate the overall survival (OS) treated with HR or TACE.
MethodsIn all, 942 patients with IM-HCC were categorized in HR and TACE groups. OS was analyzed using the Kaplan-Meier method, log-rank test, Cox proportional hazards models, and propensity score- matched (PSM) analyses. The smooth curve was performed through the generalized additive model. The interaction test was performed to evaluate the HR impact on OS concerning risk factors. Also, we used multiple imputation to deal with the missing data.
ResultsTotally, 23.0% (n=225) of patients received HR. At a median overall survival of 23.7 months, HR was associated with the improved OS on multivariate analysis (hazard ratio, 0.45; 95%CI: 0.35, 0.58; after PSM: 0.56; 95%CI: 0.41, 0.77). Landmark analyses limited to long-term survivors of [≥] 6 months, [≥] 1, and [≥] 2 years demonstrated better OS with HR in all subsets (all P<0.05). After PSM analysis, however, HR increased 20% risk of death (HR, 1.20; 95%CI: 0.67, 2.15) in the subgroup of LDH [≤]192 U/L (P for interaction = 0.037). Furthermore, the significant interaction was robust between the LDH and the HR with respect to 1-, 3-, and 5-year observed survival rate (all P<0.05).
ConclusionHepatic resection was superior to TACE for intermediate-stage HCC in the range of LDH level > 192 U/L. Moreover, TACE might be suitable for patients with LDH level [≤] 192 U/L.
SynopsisO_LIHepatectomy was superior to TACE for BCLC-B HCC.
C_LIO_LIHepatectomy increased 20% risk of death for LDH < 192 U/L after matching.
C_LIO_LIA significant interaction was robust between LDH and with respect to hepatectomy the 1-, 3-, and 5-year observed survival rate.
C_LI | surgery |
10.1101/2020.10.19.20215087 | Evaluation of eye-tracking for a decision support application | Eye-tracking is used widely to investigate attention and cognitive processes while performing tasks in electronic medical record (EMR) systems. We explored a novel application of eye tracking to collect training data for a machine learning-based clinical decision support tool that predicts which patient data are likely to be relevant for a clinical task. Specifically, we investigated in a laboratory setting the accuracy of eye tracking compared to manual annotation for inferring which patient data in the EMR are judged to be relevant by physicians. We evaluated several methods for processing gaze points that were recorded using a low-cost eye tracking device. Our results show that eye-tracking achieves accuracy and precision of 69% and 53% respectively compared to manual annotation and are promising for machine learning. The methods for processing gaze points and scripts that we developed offer a first step in developing novel uses for eye-tracking for clinical decision support.
LAY SUMMARYIn the context of electronic medical record systems, eye-tracking is used extensively to explore attention and cognitive processes. We investigated a novel application of eye tracking to collect training data for machine learning-based clinical decision support. We evaluated several methods for processing gaze points that were recorded using a low-cost eye tracking device. The methods for processing gaze points and scripts that we developed offer a first step in developing novel uses for eye-tracking for clinical decision support. | health informatics |
10.1101/2020.10.21.20215038 | Differences in outcomes following an intensive upper-limb rehabilitation programme for patients with common CNS-acting drug prescriptions. | Difficulty using the upper-limb is a major barrier to independence for many patients post-stroke or brain injury. High dose rehabilitation can result in clinically significant improvements in function even years after the incident, however there is still high variability in patient responsiveness to such interventions that cannot be explained by age, sex or time since stroke.
This retrospective study investigated whether patients prescribed certain classes of CNS-acting drugs - GABA agonists, antiepileptics and antidepressants-differed in their outcomes on the 3 week intensive Queen Square Upper-Limb (QSUL) programme.
For 277 stroke or brain injury patients (167 male, median age 52 years (IQR 21), median time since incident 20 months (IQR 26)) upper-limb impairment and activity was assessed at admission to the programme and at 6 months post-discharge, using the upper limb component of the Fugl-Meyer (FM), Action Research Arm Test (ARAT), and Chedoke Arm and Hand Activity Inventory (CAHAI). Drug prescriptions were obtained from primary care physicians at referral. Specification curve analysis (SCA) was used to protect against selective reporting results and add robustness to the conclusions of this retrospective study.
Patients with GABA agonist prescriptions had significantly worse upper-limb scores at admission but no evidence for a significant difference in programme-induced improvements was found. Additionally, no evidence of significant differences in patients with or without antiepileptic drug prescriptions on either admission to, or improvement on, the programme was found in this study. Whereas, though no evidence was found for differences in admission scores, patients with antidepressant prescriptions experienced reduced improvement in upper-limb function, even when accounting for anxiety and depression scores.
These results demonstrate that, when prescribed typically, there was no evidence that patients prescribed GABA agonists performed worse on this high-intensity rehabilitation programme. Patients prescribed antidepressants, however, performed poorer than expected on the QSUL rehabilitation programme. While the reasons for these differences are unclear, identifying these patients prior to admission may allow for better accommodation of differences in their rehabilitation needs. | neurology |
10.1101/2020.10.21.20216713 | COVID-19 adaptive humoral immunity models: weakly neutralizing versus antibody-disease enhancement scenarios | The interplay between the virus, infected cells and the immune responses to SARS-CoV-2 is still under debate. Extending the basic model of viral dynamics we propose here a formal approach to describe the neutralizing versus weakly (or non-)neutralizing scenarios and compare with the possible effects of antibody-dependent enhancement (ADE). The theoretical model is consistent with data available from the literature; we show that weakly neutralizing antibodies or ADE can both give rise to either final virus clearance or disease progression, but the immuno-dynamic is different in each case. Given that a significant part of the world population is already naturally immunized or vaccinated, we also discuss the implications on secondary infections infections following vaccination or in presence of immune system dysfunctions. | allergy and immunology |
10.1101/2020.10.20.20216358 | Exploiting collider bias to apply two-sample summary data Mendelian randomization methods to one-sample individual level data | Over the last decade the availability of SNP-trait associations from genome-wide association studies data has led to an array of methods for performing Mendelian randomization studies using only summary statistics. A common feature of these methods, besides their intuitive simplicity, is the ability to combine data from several sources, incorporate multiple variants and account for biases due to weak instruments and pleiotropy. With the advent of large and accessible fully-genotyped cohorts such as UK Biobank, there is now increasing interest in understanding how best to apply these well developed summary data methods to individual level data, and to explore the use of more sophisticated causal methods allowing for non-linearity and effect modification.
In this paper we describe a general procedure for optimally applying any two sample summary data method using one sample data. Our procedure first performs a meta-analysis of summary data estimates that are intentionally contaminated by collider bias between the genetic instruments and unmeasured confounders, due to conditioning on the observed exposure. These estimates are then used to correct the standard observational association between an exposure and outcome. Simulations are conducted to demonstrate the methods performance against naive applications of two sample summary data MR. We apply the approach to the UK Biobank cohort to investigate the causal role of sleep disturbance on HbA1c levels, an important determinant of diabetes.
Our approach can be viewed as a generalization of Dudbridge et al. (Nat. Comm. 10: 1561), who developed a technique to adjust for index event bias when uncovering genetic predictors of disease progression based on case-only data. Our work serves to clarify that in any one sample MR analysis, it can be advantageous to estimate causal relationships by artificially inducing and then correcting for collider bias. | epidemiology |
10.1101/2020.10.20.20216457 | Early intervention is the key to success in COVID-19 control | New Zealand responded to the COVID-19 pandemic with a combination of border restrictions and an Alert Level system that included strict stay-at-home orders. These interventions were successful in containing the outbreak and ultimately eliminating community transmission of COVID-19. The timing of interventions is crucial to their success. Delaying interventions may both reduce their effectiveness and mean that they need to be maintained for a longer period. Here, we use a stochastic branching process model of COVID-19 transmission and control to simulate the epidemic trajectory in New Zealand and the effect of its interventions during its COVID-19 outbreak in March-April 2020. We use the model to calculate key measures, including the peak load on the contact tracing system, the total number of reported COVID-19 cases and deaths, and the probability of elimination within a specified time frame. We investigate the sensitivity of these measures to variations in the timing of interventions and show that changing the timing of Alert Level 4 (the strictest level of restrictions) has a far greater impact than the timing of border measures. Delaying Alert Level 4 restrictions results in considerably worse outcomes and implementing border measures alone, without Alert Level 4 restrictions, is insufficient to control the outbreak. We conclude that the rapid response in introducing stay-at-home orders was crucial in reducing the number of cases and deaths and increasing the probability of elimination. | epidemiology |
10.1101/2020.10.21.20214676 | Characterizing the Modern Light Environment and its Influence on Circadian Rhythms | Humans have largely supplanted natural light cycles with a variety of artificial light sources and schedules misaligned with day-night cycles. Circadian disruption has been linked to a number of disease processes, but the extent of circadian disruption among the population is unknown. We measured light exposure and wrist temperature among residents of an urban area for a full week during each of the four seasons, as well as light illuminance in nearby outdoor locations. Daily light exposure was significantly lower for individuals, compared to outdoor light sensors, for all four seasons. There was also little seasonal variation in the realized photoperiod experienced by individuals, with the only significant difference between winter and summer. We tested the hypothesis that differential light exposure impacts circadian phase timing, detected via the wrist temperature rhythm. To determine the influence of light exposure on circadian rhythms, we modeled the impact of morning, afternoon, and nighttime light exposure on the timing of the midline-estimating statistic of rhythm (MESOR). We found that morning light exposure and nighttime light exposure had a significant but opposing impact on MESOR timing. Our results demonstrate that nighttime light can shift/alter circadian rhythms to delay the morning transition from nighttime to daytime physiology, while morning light can lead to earlier onset. Our results demonstrate that circadian shifts and disruptions may be a more regular occurrence in the general population than is currently recognized.
Significance StatementDisruption of circadian rhythms has been linked to various diseases, but the prevalence of circadian disruption among the general population is unknown. Light plays a pivotal role in entraining circadian rhythms to the 24-hour day. Humans have largely supplanted natural light cycles with electrical lighting and through time spent indoors. We have shown that individuals experience a disconnect from natural light cycles, with low daytime light exposure, high levels of light-at-night, and minimal seasonal variation in light exposure. We identified measurable changes in the timing of wrist temperature rhythms as a function of differential light exposure during the morning and nighttime hours. Our findings suggest that circadian shifts, and potentially disruption, may be common in the general population. | public and global health |
10.1101/2020.10.20.20216598 | Phenome-wide screening of GWAS data reveals the complex causal architecture of obesity | ObjectiveIn the present study, we sought to identify causal relationships between obesity and other complex traits and conditions using a data-driven hypothesis-free approach that uses genetic data to infer causal associations.
MethodsWe leveraged available summary-based genetic data from genome-wide association studies on 1,498 phenotypes and applied the latent causal variable method (LCV) between obesity and all traits.
ResultsWe identified 110 traits with significant causal associations with obesity. Notably, obesity influenced 26 phenotypes associated with cardiovascular diseases, 22 anthropometric measurements, nine with the musculoskeletal system, nine with behavioural or lifestyle factors including loneliness or isolation, six with respiratory diseases, five with body bioelectric impedances, four with psychiatric phenotypes, four related to the nervous system, four with disabilities or long-standing illness, three with the gastrointestinal system, three with use of analgesics, two with metabolic diseases, one with inflammatory response and one with the neurodevelopmental disorder ADHD, among others.
ConclusionsOur results indicate that obesity causally affects a wide range of traits and comorbid diseases, thus providing an overview of the metabolic, physiological, and neuropsychiatric impact of obesity on human health. | genetic and genomic medicine |
10.1101/2020.10.21.20216192 | Relaxed peripheral tolerance drives broad de novo autoreactivity in severe COVID-19. | An emerging feature of COVID-19 is the identification of autoreactivity in patients with severe disease that may contribute to disease pathology, however the origin and resolution of these responses remain unclear. Previously, we identified strong extrafollicular B cell activation as a shared immune response feature between both severe COVID-19 and patients with advanced rheumatic disease. In autoimmune settings, this pathway is associated with relaxed peripheral tolerance in the antibody secreting cell compartment and the generation of de novo autoreactive responses. Investigating these responses in COVID-19, we performed single-cell repertoire analysis on 7 patients with severe disease. In these patients, we identify the expansion of a low-mutation IgG1 fraction of the antibody secreting cell compartment that are not memory derived, display low levels of selective pressure, and are enriched for autoreactivity-prone IGHV4-34 expression. Within this compartment, we identify B cell lineages that display specificity to both SARS-CoV-2 and autoantigens, including pathogenic autoantibodies against glomerular basement membrane, and describe progressive, broad, clinically relevant autoreactivity within these patients correlated with disease severity. Importantly, we identify anti-carbamylated protein responses as a common hallmark and candidate biomarker of broken peripheral tolerance in severe COVID-19. Finally, we identify the contraction of this pathway upon recovery, and re-establishment of tolerance standards coupled with a concomitant loss of acute-derived ASCs irrespective of antigen specificity. In total, this study reveals the origins, breadth, and resolution of acute-phase autoreactivity in severe COVID-19, with significant implications in both early interventions and potential treatment of patients with post-COVID sequelae. | infectious diseases |
10.1101/2020.10.21.20216689 | Serological surveillance of SARS-CoV-2: Six-month trends and antibody response in a cohort of public health workers | BackgroundAntibody waning after SARS-CoV-2 infection may result in reduction in long-term immunity following natural infection and vaccination, and is therefore a major public health issue. We undertook prospective serosurveillance in a large cohort of healthy adults from the start of the epidemic in England.
MethodsClinical and non-clinical healthcare workers were recruited across three English regions and tested monthly from March to November 2020 for SARS-CoV-2 spike (S) protein and nucleoprotein (N) antibodies using five different immunoassays. In positive individuals, antibody responses and long-term trends were modelled using mixed effects regression.
FindingsIn total, 2246 individuals attended 12,247 visits and 264 were seropositive in [≥]2 assays. Most seroconversions occurred between March and April 2020. The assays showed >85% agreement for ever-positivity, although this changed markedly over time. Antibodies were detected earlier with Abbott (N) but declined rapidly thereafter. With the EuroImmun (S) and receptor-binding domain (RBD) assays, responses increased for 4 weeks then fell until week 12-16 before stabilising. For Roche (N), responses increased until 8 weeks, stabilised, then declined, but most remained above the positive threshold. For Roche (S), responses continued to climb over the full 24 weeks, with no sero-reversions. Predicted proportions sero-reverting after 52 weeks were 100% for Abbott, 59% (95% credible interval 50-68%) Euroimmun, 41% (30-52%) RBD, 10% (8-14%) Roche (N) <2% Roche (S).
InterpretationTrends in SARS-CoV-2 antibodies following infection are highly dependent on the assay used. Ongoing serosurveillance using multiple assays is critical for monitoring the course and long-term progression of SARS-CoV-2 antibodies. | infectious diseases |
10.1101/2020.10.21.20217042 | SARS-CoV-2 viral dynamics in acute infections | BackgroundSARS-CoV-2 infections are characterized by viral proliferation and clearance phases and can be followed by low-level persistent viral RNA shedding. The dynamics of viral RNA concentration, particularly in the early stages of infection, can inform clinical measures and interventions such as test-based screening.
MethodsWe used prospective longitudinal RT-qPCR testing to measure the viral RNA trajectories for 68 individuals during the resumption of the 2019-20 National Basketball Association season. For 46 individuals with acute infections, we inferred the peak viral concentration and the duration of the viral proliferation and clearance phases.
FindingsAccording to our mathematical model, we found that viral RNA concentrations peaked an average of 3.3 days (95% credible interval [2.5, 4.2]) after first possible detectability at a cycle threshold value of 22.3 [20.5, 23.9]. The viral clearance phase lasted longer for symptomatic individuals (10.9 days [7.9, 14.4]) than for asymptomatic individuals (7.8 days [6.1, 9.7]). A second test within 2 days after an initial positive PCR substantially improves certainty about a patients infection phase. The effective sensitivity of a test intended to identify infectious individuals declines substantially with test turnaround time.
ConclusionsSARS-CoV-2 viral concentrations peak rapidly regardless of symptoms. Sequential tests can help reveal a patients progress through infection stages. Frequent rapid-turnaround testing is needed to effectively screen individuals before they become infectious. | epidemiology |
10.1101/2020.10.21.20216945 | The effect of COVID-19 on critical care research: A prospective longitudinal multinational survey | ImportanceThe COVID-19 pandemic has increased the need for high-quality evidence in critical care, while also increasing the barriers to conducting the research needed to produce such evidence.
ObjectiveTo determine the effect of the first wave of the COVID-19 pandemic on critical care clinical research.
DesignMonthly electronic survey (March 2020 - February 2021).
SettingAdult or pediatric intensive care units (ICUs) from any country participating in at least one research study before the COVID-19 pandemic.
ParticipantsWe recruited one researcher or research coordinator per center, identified via established research networks.
Intervention(s)None
Main Outcome(s) and Measure(s)Primary: Suspending recruitment in clinical research; Secondary: impact of specific factors on research conduct (5-point scales from no effect to very large effect). We assessed the association between research continuity and month, presence of hospitalized patients with COVID-19, and population (pediatric vs. adult ICU) using mixed-effects logistic regression.
Results127 centers (57% pediatric) from 23 countries participated. 95 (75%) of centers suspended recruitment in at least some studies and 37 (29%) suspended recruitment in all studies on at least one month. The proportion of centers reporting recruitment in all studies increased over time (OR per month 1.3, 95% CI 1.2 to 1.4, p < 0.001), controlling for hospitalized patients with COVID-19 and type of ICU (pediatric vs. other). The five factors most frequently identified as having a large or very large effect on clinical research were: local prioritization of COVID-19 specific research (68, 54%), infection control policies limiting access to patients with COVID-19 (61, 49%), infection control policies limiting access to the ICU (52, 41.6%), increased workload of clinical staff (38, 30%), and safety concerns of research staff (36, 29%).
Conclusions and RelevanceDecisions to pause or pursue clinical research varied across centers. Research activity increased over time, despite the presence of hospitalized patients with COVID-19. Guiding principles with local adaptation to safely sustain research during this and future pandemics are urgently needed.
Key PointsO_ST_ABSQuestionC_ST_ABSWhat was the effect of the COVID-19 pandemic on research in 127 adult and pediatric intensive care units (ICUs) between March 2020 and February 2021?
Findings95 (75%) centers suspended recruitment into at least some studies. Active recruitment into studies increased over time (OR per month 1.3, 95% CI 1.2 to 1.4, p < 0.001), controlling for ICU type and the presence of patients with COVID-19.
MeaningResearch activity varied across centers and increased over time, despite the presence of hospitalized patients with COVID-19. Guiding principles to safely sustain research during this and future pandemics are urgently needed. | intensive care and critical care medicine |
10.1101/2020.10.21.20216986 | Simulation and prediction of spread of COVID-19 in The Republic of Serbia by SEIRDS model of disease transmission | As a response to the pandemic caused by SARS-Cov-2 virus, on 15 March, 2020, the Republic of Serbia introduced comprehensive anti-epidemic measures to curb COVID-19. After a slowdown in the epidemic, on 6 May, 2020, the regulatory authorities decided to relax the implemented measures. However, the epidemiological situation soon worsened again. As of 7 February, 2021, a total of 406,352 cases of SARSCov-2 infection have been reported in Serbia, 4,112 deaths caused by COVID-19. In order to better understand the epidemic dynamics and predict possible outcomes, we have developed an adaptive mathematical model SEAIHRDS (S-susceptible, E-exposed, A-asymptomatic, I-infected, H-hospitalized, R-recovered, D-dead due to COVID-19 infection, S-susceptible). The model can be used to simulate various scenarios of the implemented intervention measures and calculate possible epidemic outcomes, including the necessary hospital capacities. Considering promising results regarding the development of a vaccine against COVID-19, the model is extended to simulate vaccination among different population strata. The findings from various simulation scenarios have shown that, with implementation of strict measures of contact reduction, it is possible to control COVID-19 and reduce number of deaths. The findings also show that limiting effective contacts within the most susceptible population strata merits a special attention. However, the findings also show that the disease has a potential to remain in the population for a long time, likely with a seasonal pattern. If a vaccine, with efficacy equal or higher than 65%, becomes available it could help to significantly slow down or completely stop circulation of the virus in human population.
The effects of vaccination depend primarily on: 1. Efficacy of available vaccine(s), 2. Prioritization of the population categories for vaccination, and 3. Overall vaccination coverage of the population, assuming that the vaccine(s) develop solid immunity in vaccinated individuals. With expected basic reproduction number of Ro=2.46 and vaccine efficacy of 68%, an 87% coverage would be sufficient to stop the virus circulation. | epidemiology |
10.1101/2020.10.20.20214718 | Distinguishing non severe cases of dengue from COVID-19 in the context of co-epidemics: a cohort study in a SARS-CoV-2 testing center on Reunion island | BackgroundAs coronavirus 2019 (COVID-19) is spreading globally, several countries are handling dengue epidemics. As both infections are deemed to share similarities at presentation, it would be useful to distinguish COVID-19 from dengue in the context of co-epidemics. Hence, we performed a retrospective cohort study to identify predictors of both infections.
Methodology/Principal FindingsAll the subjects suspected of COVID-19 between March 23 and May 10, 2020, were screened for COVID-19 within the testing center of the University hospital of Saint-Pierre, Reunion island. The screening consisted in a questionnaire surveyed in face-to-face, a nasopharyngeal swab specimen for the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) reverse transcription polymerase chain-reaction and a rapid diagnostic orientation test for dengue. Factors independently associated with COVID-19 or with dengue were sought using multinomial logistic regression models, taking other febrile illnesses (OFIs) as controls. Adjusted Odds ratios (OR) and 95% Confidence Intervals (95%CI) were assessed. Over a two-month study period, we diagnosed 80 COVID-19, 60 non-severe dengue and 872 OFIs cases. Among these, we identified delayed presentation (>3 days) since symptom onset (Odds ratio 1.91, 95% confidence interval 1.07-3.39), contact with a COVID-19 positive case (OR 3.81, 95%CI 2.21-6.55) and anosmia (OR 7.80, 95%CI 4.20-14.49) as independent predictors of COVID-19, body ache (OR 6.17, 95%CI 2.69-14.14), headache (OR 5.03, 95%CI 1.88-13.44) and retro-orbital pain (OR 5.55, 95%CI 2.51-12.28) as independent predictors of dengue, while smoking was less likely observed with COVID-19 (OR 0.27, 95%CI 0.09-0.79) and upper respiratory tract infection symptoms were associated with OFIs.
Conclusions/SignificanceAlthough prone to potential biases, these data suggest that non-severe dengue may be more symptomatic than COVID-19 in a co-epidemic setting with higher dengue attack rates. At clinical presentation, eight basic clinical and epidemiological indicators may help to distinguish COVID-19 or dengue from each other and other febrile illnesses.
Author SummaryAs coronavirus 2019 (COVID-19) is spreading globally, several countries are facing dengue epidemics with the fear the two plagues might overburden their healthcare systems. On Reunion island, southwestern Indian ocean: dengue virus is circulating since 2004 under an endemo-epidemic pattern with yearly outbreaks peaking between March and May since 2015, whereas Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the pathogen responsible of COVID-19, emerged in March 2020, imported from the Bahamas. COVID-19 and dengue are deemed two clinically similar entities, especially within the first two days from symptom onset. In this context, we conducted a cohort study between March 23 and May 10, 2020, within a SARS-CoV-2 testing center, aimed at identifying the factors discriminating both infections. Surprisingly, we found that non-severe dengue was more symptomatic than mild to moderate COVID-19. Indeed, we found body ache, headache and retro-orbital pain to be indicative of dengue, whereas contact with a COVID-19 positive case, anosmia, delayed presentation (>3 days post symptom onset) and absence of active smoking were indicative of COVID-19. These findings highlight the need for accurate diagnostic tools and not to jeopardize dengue control in areas wherever COVID-19 dengue co-epidemics have the potential to wrought havoc to the healthcare system. | infectious diseases |
10.1101/2020.10.21.20210948 | Predicting Dengue Incidence Leveraging Internet-Based Data Sources: A Case Study in 20 cities in Brazil. | The dengue virus affects millions of people every year worldwide, causing large epidemic outbreaks that disrupt peoples lives and severely strain healthcare systems. In the absence of a reliable vaccine against it or an effective treatment to manage the illness in humans, most efforts to combat dengue infections have focused on preventing its vectors, mainly the Aedes aegypti mosquito, from flourishing across the world. These mosquito-control strategies need reliable disease activity surveillance systems to be deployed. Despite significant efforts to estimate dengue incidence using a variety of data sources and methods, little work has been done to understand the relative contribution of the different data sources to improved prediction. Additionally, scholarship on the topic had initially focused on prediction systems at the national- and state-levels, and much remains to be done at the finer spatial resolutions at which health policy interventions often occur. We develop a methodological framework to assess and compare dengue incidence estimates at the city level, and evaluate the performance of a collection of models on 20 different cities in Brazil. The data sources we use towards this end are weekly incidence counts from prior years (seasonal autoregressive terms), weekly-aggregated weather variables, and real-time internet search data. We find that both random forest-based models and LASSO regression-based models effectively leverage these multiple data sources to produce accurate predictions, and that while the performance between them is comparable on average, the former method produces fewer extreme outliers, and can thus be considered more robust. For real-time predictions that assume long delays (6-8 weeks) in the availability of epidemiological data, we find that real-time internet search data are the strongest predictors of dengue incidence, whereas for predictions that assume short delays (1-3 weeks), in which the error rate is halved (as measured by relative RMSE), short-term and seasonal autocorrelation are the dominant predictors. Despite the difficulties inherent to city-level prediction, our framework achieves meaningful and actionable estimates across cities with different demographic, geographic and epidemic characteristics.
Author SummaryAs the incidence of infectious diseases like dengue continues to increase throughout the world, tracking their spread in real time poses a significant challenge to local and national health authorities. Accurate incidence data are often difficult to obtain as outbreaks emerge and unfold, both due the partial reach of serological surveillance (especially in rural areas), and due to delays in reporting, which result in post-hoc adjustments to what should have been real-time data. Thus, a range of nowcasting tools have been developed to estimate disease trends, using different mathematical and statistical methodologies to fill the temporal data gap. Over the past several years, researchers have investigated how to best incorporate internet search data into predictive models, since these can be obtained in real-time. Still, most such models have been regression-based, and have tended to underperform in cases when epidemiological data are only available after long reporting delays. Moreover, in tropical countries, attention has increasingly turned from testing and applying models at the national level to models at higher spatial resolutions, such as states and cities. Here, we develop machine learning models based on both LASSO regression and on random forest ensembles, and proceed to apply and compare them across 20 cities in Brazil. We find that our methodology produces meaningful and actionable disease estimates at the city level with both underlying model classes, and that the two perform comparably across most metrics, although the ensemble method produces fewer outliers. We also compare model performance and the relative contribution of different data sources across diverse geographic, demographic and epidemic conditions. | epidemiology |
10.1101/2020.10.21.20217158 | Cost and social distancing dynamics in a mathematical model of COVID-19 with application to Ontario, Canada | A mathematical model of COVID-19 is presented where the decision to increase or decrease social distancing is modelled dynamically as a function of the measured active and total cases as well as the perceived cost of isolating. Along with the cost of isolation, we define an overburden healthcare cost and a total cost. We explore these costs by adjusting parameters that could change with policy decisions. We observe that two disease prevention practices, namely increasing isolation activity and increasing incentive to isolate do not always lead to optimal health outcomes. We demonstrate that this is due to the fatigue and cost of isolation. We further demonstrate that an increase in the number of lock-downs, each of shorter duration can lead to minimal costs. Our results are compared to case data in Ontario, Canada from March to August 2020 and details of expanding the results to other regions are presented.
Subject Areasmathematical modelling, epidemiology, infectious diseases | epidemiology |
10.1101/2020.10.21.20217265 | An Integrated and Automated Tool for Quantification of Biomechanics in Fetal and Neonatal Echocardiography | BackgroundQuantifying ventricular biomechanics from fetal and neonatal echocardiograms presents unique and significant challenges. A new analysis workflow has been introduced for simultaneous quantification of flow and mechanics of cardiac function using an integrated set of automated, physics-based, echocardiography analysis methods.
MethodsWe used in-house developed analysis algorithms to quantify ventricular biomechanics from four-chamber B-mode and color Doppler routine examination recordings for three hypoplastic left heart (HLHS) patients at 33-weeks gestation and first week post-birth along with age-matched controls. Chamber morphology, tissue motion, atrioventricular valve inflow, and hemodynamic flow parameters were measured.
ResultsPrenatal cardiac output differed between control (LV:157 {+/-} 139 mL/min, RV:257 {+/-} 218 mL/min) and HLHS subjects (410 {+/-} 128 mL/min). This difference persisted for control (LV:233 {+/-} 74 mL/min, RV:242 {+/-} 140 mL/min) and HLHS subjects (637 {+/-} 298 mL/min) after birth. In utero peak early diastolic annulus velocity, e, was elevated in HLHS subjects ({+/-} :1.88 {+/-} 0.97cm/s) compared to controls (LV:1.23 {+/-} 0.81cm/s, RV:1.19 {+/-} 0.57cm/s). After birth e increased in control RVs (1.80 {+/-} 0.73cms) compared to control LVs (1.26 {+/-} 0.50cm/s) and HLHS RVs (1.18 {+/-} 1.12cm/s). Postnatal early filling mitral flow velocity for the control subjects (LV:58.8 {+/-} 17.6 cm/s) and early-filling tricuspid flow of the HLHS subjects (64.8 {+/-} 23.7cm/s) were similar, while the late filling velocity decreased for the control subject LV (33.5 {+/-} 8.1 cm/s) compared to the HLHS subjects (66.9 {+/-} 23.0 cm/s). Importantly, flow energy loss in the fetal HLHS hearts was increased (0.35 {+/-} 0.19 m3/s2) compared to the control subjects (LV:0.09 {+/-} 0.07 m3/s2, RV:0.17 {+/-} 0.12 m3/s2), and further increased postnatally for the HLHS subjects (0.55 {+/-} 0.24 m3/s2) compared to the control subjects (LV:0.23 {+/-} 0.20 m3/s2, RV:0.09 {+/-} 0.06 m3/s2).
ConclusionsWe demonstrate the feasibility of integrated quantitative measurements of fetal and neonatal ventricular hemodynamics and biomechanics using only four-chamber B-mode and color Doppler recordings. | cardiovascular medicine |
10.1101/2020.10.21.20217331 | Requirements for the containment of COVID-19 disease outbreaks through periodic testing, isolation, and quarantine | We employ individual-based Monte Carlo computer simulations of a stochastic SEIR model variant on a two-dimensional Newman-Watts small-world network to investigate the control of epidemic outbreaks through periodic testing and isolation of infectious individuals, and subsequent quarantine of their immediate contacts. Using disease parameters informed by the COVID-19 pandemic, we investigate the effects of various crucial mitigation features on the epidemic spreading: fraction of the infectious population that is identifiable through the tests; testing frequency; time delay between testing and isolation of positively tested individuals; and the further time delay until quarantining their contacts as well as the quarantine duration. We thus determine the required ranges for these intervention parameters to yield effective control of the disease through both considerable delaying the epidemic peak and massively reducing the total number of sustained infections. | epidemiology |
10.1101/2020.10.21.20217331 | Requirements for the containment of COVID-19 disease outbreaks through periodic testing, isolation, and quarantine | We employ individual-based Monte Carlo computer simulations of a stochastic SEIR model variant on a two-dimensional Newman-Watts small-world network to investigate the control of epidemic outbreaks through periodic testing and isolation of infectious individuals, and subsequent quarantine of their immediate contacts. Using disease parameters informed by the COVID-19 pandemic, we investigate the effects of various crucial mitigation features on the epidemic spreading: fraction of the infectious population that is identifiable through the tests; testing frequency; time delay between testing and isolation of positively tested individuals; and the further time delay until quarantining their contacts as well as the quarantine duration. We thus determine the required ranges for these intervention parameters to yield effective control of the disease through both considerable delaying the epidemic peak and massively reducing the total number of sustained infections. | epidemiology |
10.1101/2020.10.22.20216481 | Hardness of Herd Immunity and Success Probability of Quarantine Measures: A Branching Process Approach | Herd immunity refers to the collective resistance of a population against the spreading of an infection as an epidemic. Understanding the dependencies of herd immunity on various epidemiological parameters is of immense importance for strategizing control measures against an infection in a population. Using an age-dependent branching process model of infection propagation, we obtain interesting functional dependencies of herd immunity on the incubation period of the contagion, contact rate, and the probability of disease transmission from an infected to a susceptible individual. We show that herd immunity is difficult to achieve in case of a high incubation period of the contagion. We derive a method to quantify the success probabilities of quarantine measures to mitigate infection from a population, before achieving herd immunity. We provide a mechanistic derivation of the distribution of generation time from basic principles, which is of central importance to estimate the reproduction number R0, but has been assumed in an ad hoc manner in epidemiological studies, by far. This derivation of the generation time distribution has the generality to be applied in the study of many other age-dependent branching processes, such as the growth of bacterial colonies, various problems in evolutionary and population biology etc. | infectious diseases |
10.1101/2020.10.22.20213876 | The characteristics of oxygen concentration and the role of correction factor in real-time GI Breath Test | A high quality end-expiratory breath sample is required for a reliable GI breath test result. Oxygen (O2) concentration in the breath sample can be used as a quality marker. This study investigated the characteristics of oxygen concentration in breath sample and the issues with using a correction factor in real-time breath test. The results indicated 95.4% of 564 patients were able to achieve an O2 concentration below 14% in their end-expiratory breath. A further 293 samples were studied and revealed that the distribution of O2 concentration was between 16.5% and 9.5%. Applying a correction factor to predict the end-expiratory H2 and CH4 values led to an average error of -36.4% and -12.8% respectively. The correction factor algorithm based on limiting O2 at 14% would have resulted in false negative result for 50% of the positive cases. This study has also indicated the continuous O2 measurement is essential to ensure breath sample quality by preventing secondary breathing during real-time breath collection. | gastroenterology |
10.1101/2020.10.23.20213652 | A global atlas of genetic associations of 220 deep phenotypes | Current genome-wide association studies (GWASs) do not yet capture sufficient diversity in populations and scope of phenotypes. To expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype GWASs (diseases, biomarkers, and medication usage) in BioBank Japan (n=179,000), by incorporating past medical history and text-mining of electronic medical records. Meta-analyses with the UK Biobank and FinnGen (ntotal=628,000) identified [~]5,000 novel loci, which improved the resolution of genomic map of human traits. This atlas elucidated landscape of pleiotropy as represented by MHC locus, where we conducted HLA fine-mapping. Finally, we performed statistical decomposition of matrices of phenome-wide summary statistics, and identified latent genetic components, which pinpointed responsible variants and biological mechanisms underlying current disease classifications across populations. The decomposed components enabled genetically-informed subtyping of similar diseases (e.g., allergic diseases). Our study suggests a potential avenue for hypothesis-free re-investigation of human diseases through genetics. | genetic and genomic medicine |
10.1101/2020.10.23.20218198 | Development and validation of multivariable machine learning algorithms to predict risk of cancer in symptomatic patients referred urgently from primary care | BackgroundUrgent Suspected Cancer (Two Week Wait, 2WW) referrals have improved early cancer detection but are increasingly a major burden on NHS services. This has been exacerbated by the COVID-19 pandemic.
MethodWe developed and validated tests to assess the risk of any cancer for 2WW patients. The tests use routine blood measurements (FBC, U&E, LFTs, tumour markers), combining them using machine learning and statistical modelling. Algorithms were developed and validated for nine 2WW pathways using retrospective data from 371,799 referrals to Leeds Teaching Hospitals Trust (development set 224,669 referrals, validation set 147,130 referrals). A minimum set of blood measurements were required for inclusion, and missing data were modelled internally by the algorithms.
ResultsWe present results for two clinical use-cases. In use-case 1, the algorithms identify 20% of patients who do not have cancer and may not need an urgent 2WW referral. In use-case 2, they identify 90% of cancer cases with a high probability of cancer that could be prioritised for review.
ConclusionsCombining a panel of widely available blood markers produces effective blood tests for cancer for NHS 2WW patients. The tests are affordable, can be deployed rapidly to any NHS pathology laboratory with no additional hardware requirements. | health informatics |
10.1101/2020.10.23.20218586 | Mitochondrial genome copy number measured by DNA sequencing in human blood is strongly associated with metabolic traits via cell-type composition differences | Mitochondrial genome copy number (MT-CN) varies among humans and across tissues and is highly heritable, but its causes and consequences are not well understood. When measured by bulk DNA sequencing in blood, MT-CN may reflect a combination of the number of mitochondria per cell and cell type composition. Here, we studied MT-CN variation in blood-derived DNA from 19,184 Finnish individuals using a combination of genome (N = 4,163) and exome sequencing (N = 19,034) data as well as imputed genotypes (N = 17,718). We identified two loci significantly associated with MT-CN variation: a common variant at the MYB-HBS1L locus (P = 1.6x10-8), which has previously been associated with numerous hematological parameters; and a burden of rare variants in the TMBIM1 gene (P = 3.0x10-8), which has been reported to protect against non-alcoholic fatty liver disease. We also found that MT-CN is strongly associated with insulin levels (P = 2.0x10-21) and other metabolic syndrome (metS) related traits. Using a Mendelian randomization framework, we show evidence that MT-CN measured in blood is causally related to insulin levels. We then applied an MT-CN polygenic risk score (PRS) derived from Finnish data to the UK Biobank, where the association between the PRS and metS traits was replicated. Adjusting for cell counts largely eliminated these signals, suggesting that MT-CN affects metS via cell type composition. These results suggest that measurements of MT-CN in blood-derived DNA partially reflect differences in cell-type composition and that these differences are causally linked to insulin and related traits. | genetic and genomic medicine |
10.1101/2020.10.23.20218511 | Large-scale population analysis of SARS-CoV-2 whole genome sequences reveals host-mediated viral evolution with emergence of mutations in the viral Spike protein associated with elevated mortality rates | BackgroundWe aimed to further characterize and analyze in depth intra-host variation and founder variants of SARS-CoV-2 worldwide up until August 2020, by examining in excess of 94,000 SARS-CoV-2 viral sequences in order to understand SARS-CoV-2 variant evolution, how these variants arose and identify any increased mortality associated with these variants.
Methods and FindingsWe combined worldwide sequencing data from GISAID and Sequence Read Archive (SRA) repositories and discovered SARS-CoV-2 hypermutation occurring in less than 2% of COVID19 patients, likely caused by host mechanisms involved APOBEC3G complexes and intra-host microdiversity. Most of this intra-host variation occurring in SARS-CoV-2 are predicted to change viral proteins with defined variant signatures, demonstrating that SARS-CoV-2 can be actively shaped by the host immune system to varying degrees. At the global population level, several SARS-CoV-2 proteins such as Nsp2, 3C-like proteinase, ORF3a and ORF8 are under active evolution, as evidenced by their increased {pi}N/ {pi}S ratios per geographical region. Importantly, two emergent variants: V1176F in co-occurrence with D614G mutation in the viral Spike protein, and S477N, located in the Receptor Binding Domain (RBD) of the Spike protein, are associated with high fatality rates and are increasingly spreading throughout the world. The S477N variant arose quickly in Australia and experimental data support that this variant increases Spike protein fitness and its binding to ACE2.
ConclusionsSARS-CoV-2 is evolving non-randomly, and human hosts shape emergent variants with positive fitness that can easily spread into the population. We propose that V1776F and S477N variants occurring in the Spike protein are two novel mutations occurring in SARS-CoV-2 and may pose significant public health concerns in the future.
Author SummaryWe have developed an efficient bioinformatics pipeline that has allowed us obtain the most complete picture to date of how the SARS-CoV-2 virus has changed during the last eight month global pandemic and will continue to change in the near future. We characterized the importance of the host immune response in shaping viral variants at different degrees, evidenced by hypermutation responses on SARS-CoV-2 in less than 2% of infections and positive selection of several viral proteins by geographical region. We underscore how human hosts are shaping emergent variants with positive fitness that can easily spread into the population, evidenced by variants V1176F and S477N, located in the stalk and receptor binding domains of the Spike protein, respectively. Variant V1176 is associated with increased mortality rates in Brazil and variant S477N is associated with increased mortality rates over the world. In addition, it has been experimentally demonstrated that S477N variant increase fitness of Spike protein and its binding with ACE2, thus predicting to increase virulence of SARS-CoV-2. This limits the concept of herd immunity proposals and re-emphasize the need to limit the spread of the virus to avoid emergence of more virulent forms of SARS-CoV-2 that can spread worldwide. | infectious diseases |
10.1101/2020.10.24.20218701 | Clinical and spatial characteristics of Severe Acute Respiratory Syndrome by COVID-19 in Indigenous of Brazil | The new coronavirus (SARS-CoV-2) emerged in Wuhan in China in December 2019, causing severe pneumonias and deaths, soon in March 2020 it reached pandemic level, affecting several countries including Brazil. The disease was named COVID-19, with characteristics of most infected having mild and moderate symptoms and a part severe symptom. The disease has already reached 158 ethnic groups, which have high vulnerability and limited access to health services. The objective is to investigate the clinical and spatial characteristics of Severe Acute Respiratory Syndrome of COVID-19 in the indigenous peoples of Brazil. It is an epidemiological, cross-sectional, analytical ecological study, based on data from the OpenDataSUS platform from 01/01/2020 to 31/08/2020. Profile variables, signs and symptoms and risk factors/comorbidities. The data were analyzed by Bioestat 5.3. There were 1,207 cases and 470 deaths. Profile: male gender (59.48%) means age 53 years. Signs and symptoms: fever (74.23%), cough (77.71%), sore throat (35.62%), dyspnea (69.34%), respiratory discomfort (62.80%), O2 saturation <95% (56.42%); and associated with mortality: dyspnea (80.0%) and O2 saturation <95% (69.36%). Risk factors and comorbidities (45.89%) were associated with deaths (54.04%). Comorbidities: Chronic Cardiovascular Disease (18.97%) and Diabetes Mellitus (18.97%), and associated with deaths: Chronic Cardiovascular Disease (24.46%). Being admitted to the ICU has a risk of death in (OR-3.96-<0.0001-CI-2,913/5,383) followed by not being vaccinated against influenza (OR-1.85-<0.0001-CI-1,358/2,528). The public and health policies of Brazil should be directed to control the dissemination of COVID-19 in this population, that COVID-19 evolves in the same intensity, however, the indigenous have vulnerabilities that can increase the impact of the pan-demic in this population. | epidemiology |
10.1101/2020.10.23.20218479 | COVID -19: could green tea catechins reduce the risks? | PurposeSeveral lines of emerging pharmacological and epidemiological evidence imply that overall risks related to COVID-19 may be reduced by green tea catechins. Therefore, it may be expected that countries with higher per/capita green tea consumption would be less affected by COVID-19. The aim of this study was to assess this possibility.
MethodsAmong countries with at least 3 million population (n=134), countries with relatively high (above 150 g) per/capita green tea consumption have been identified (n=21); (ii) normalized to population values of COVID-19 cases (morbidity) and deaths (mortality) for groups of countries with high and low per/capita green tea consumption were compared.
ResultsStriking differences in COVID-19 morbidity and mortality between groups of countries with high and low green tea consumption were found. The differences were still observed after the adjustment for the onset of the disease. An analysis using multiple linear regression approach suggests that the associations are present at the level of individual countries.
ConclusionEvidence supporting the idea that green tea constituents could reduce overall risks related to COVID-19 has been obtained. The results are promising and are in line with emerging evidence from other studies including pharmacological ones. Nevertheless, because of limitations of this study the idea still should be considered as a hypothesis requiring further assessment. Several vaccines are currently validated for COVID-19 prevention and mass vaccination has already been started in many countries. Still, it is likely that the development of an efficient drug therapy that reduces COVID-19 severity/mortality would be important for rather prolonged time. In this context, the results obtained in this study may have significant implications. | epidemiology |
10.1101/2020.10.24.20215061 | MEGA: Machine Learning-Enhanced Graph Analytics for COVID-19 Infodemic Control | The authors have withdrawn their manuscript whilst they perform additional experiments to test some of their conclusions further. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author. | health informatics |
10.1101/2020.10.25.20219048 | Ct threshold values, a proxy for viral load in community SARS-CoV-2 cases, demonstrate wide variation across populations and over time | Information on SARS-CoV-2 in representative community surveillance is limited, particularly cycle threshold (Ct) values (a proxy for viral load). Of 3,312,159 nose and throat swabs taken 26-April-2020 to 13-March-2021 in the UKs national COVID-19 Infection Survey, 27,902(0.83%) were RT-PCR-positive, 10,317(37%), 11,012(40%) and 6,550(23%) for 3, 2 or 1 of the N, S and ORF1ab genes respectively, with median Ct=29.2 ([~]215 copies/ml; IQR Ct=21.9-32.8, 14-56,400 copies/ml). Independent predictors of lower Cts (i.e. higher viral load) included self-reported symptoms and more genes detected, with at most small effects of sex, ethnicity and age. Single-gene positives almost invariably had Ct>30, but Cts varied widely in triple-gene positives, including without symptoms. Population-level Cts changed over time, with declining Ct preceding increasing SARS-CoV-2 positivity. Of 6,189 participants with IgG S-antibody tests post-first RT-PCR-positive, 4,808(78%) were ever antibody-positive; Cts were significantly higher in those remaining antibody-negative. Community SARS-CoV-2 Ct values could be a useful epidemiological early-warning indicator.
IMPACT STATEMENTCt values from SARS-CoV-2 RT-PCR tests vary widely and over calendar time. They have the potential to be used more broadly in public testing programmes as an "early-warning" system for shifts in infectious load and hence transmission. | infectious diseases |
10.1101/2020.10.25.20200675 | Impact of COVID-19 on diagnoses, monitoring and mortality in people with type 2 diabetes: a UK-wide cohort study involving 14 million people in primary care | AIMSTo compare trends in diagnoses, monitoring and mortality in patients with type 2 diabetes, before and after the first COVID-19 peak.
METHODSWe constructed a cohort of 25 million patients using electronic health records from 1831 UK general practices registered with the Clinical Practice Research Datalink (CPRD), including 14 million patients followed between March and December 2020. We compared trends using regression models and 10-year historical data. We extrapolated the number of missed/delayed diagnoses using UK Office for National Statistics data.
RESULTSIn England, rates of new type 2 diabetes diagnoses were reduced by 70% (95% CI 68%-71%) in April 2020, with similar reductions in Northern Ireland, Scotland and Wales. Between March and December, we estimate that there were approximately 60,000 missed/delayed diagnoses across the UK. In April, rates of HbA1c testing were greatly reduced in England (reduction: 77% (95% CI 76%-78%)) with more marked reductions in the other UK nations (83% (83-84%)). Reduced rates of diagnosing and monitoring were particularly evident in older people, in males, and in those from deprived areas. In April, the mortality rate in England was more than 2-fold higher (112%) compared to prior trends, but was only 65% higher in Northern Ireland, Scotland and Wales.
CONCLUSIONSAs engagement increases, healthcare services will need to manage the backlog and anticipate greater deterioration of glucose control due to delayed diagnoses and reduced monitoring in those with pre-existing diabetes. Older people, men, and those from deprived backgrounds will be groups to target for early intervention.
RESEARCH IN CONTEXTO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIThe higher COVID-related death rate in people with diabetes has been well-documented
C_LIO_LIA study involving the residents of Salford, UK showed 135 fewer diagnoses of type 2 diabetes than expected between March and May 2020, which amounted to a 49% reduction in activity
C_LIO_LIThere is limited data on the impact of the COVID-19 pandemic on the diagnosis and monitoring of type 2 diabetes
C_LI
What is the key question?O_LIWhat has been the impact of the COVID-19 pandemic on the diagnosis and monitoring of type 2 diabetes across the UK?
C_LI
What are the new findings?O_LIAcross the UK, the rate of new type 2 diabetes diagnoses was reduced by up to 70% in April 2020 compared to 10-year historical trends
C_LIO_LIBetween March and December 2020, it is estimated that 60,000 people have had a missed or delayed diagnosis
C_LIO_LIThe frequency of HbA1c monitoring in type 2 diabetes was reduced by 77-83% in April 2020 and by 31-37% overall between March and December 2020
C_LI
How might this impact on clinical practice in the foreseeable future?O_LIDuring this pandemic and associated lockdowns, effective public communications should ensure that patients remain engaged with diabetes services including HbA1c screening and monitoring
C_LI | endocrinology |
10.1101/2020.10.26.20219774 | Collecting genetic samples and linked mental health data from adolescents in schools: Protocol co-production and a mixed-methods pilot of feasibility and acceptability | ObjectivesTo co-produce a school-based protocol and examine acceptability and feasibility of collecting saliva samples for genetic studies from secondary/high school students for the purpose of mental health research.
DesignProtocol co-production and mixed-methods feasibility pilot.
SettingSecondary schools in Wales, UK.
ParticipantsStudents aged 11-13 years.
Primary and secondary outcome measuresCo-produced research protocol including an interactive science workshop delivered in schools; school, parental and student recruitment rates; adherence to protocol and adverse events; ability to extract and genotype saliva samples; student enjoyment of the science workshop; and qualitative analysis of teacher focus groups on acceptability and feasibility.
ResultsFive secondary schools participated in the co-production phase, and three of these took part in the research study (eligible sample n=868 students). Four further schools were subsequently approached, but none participated. Parental opt-in consent was received from 98 parents (11.3% eligible sample), three parents (0.3%) actively refused and responses were not received for 767 (88.4%) parents. We obtained saliva samples plus consent for data linkage for 79 students. Only one sample was of insufficient quality to be genotyped. The science workshop received positive feedback from students. Feedback from teachers showed that undertaking research like this in schools is viewed as acceptable in principle, potentially feasible, but that there are important procedural barriers to be overcome. Key recommendations include establishing close working relationships between the research team and school classroom staff, together with improved methods for communicating with and engaging parents.
ConclusionsThere are major challenges to undertaking large scale genetic mental health research in secondary schools. Such research may be acceptable in principle, and in practice DNA collected from saliva in classrooms is of sufficient quality. However, key challenges that must be overcome include ensuring representative recruitment of schools and sufficient parental engagement where opt-in parental consent is required.
Article SummaryO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIThis is the first study to test the feasibility and acceptability of collecting genetic samples in secondary schools and obtaining consent for linkage to questionnaire and record-based mental health data.
C_LIO_LIA key strength is co-production of the research protocol with stakeholders (young people, parents/guardians, schools).
C_LIO_LIWe used a mixed-methods approach to assess the feasibility and acceptability of carrying out genetic research studies of mental health in schools.
C_LIO_LIThis pilot study was conducted in three mainstream secondary schools in Wales, UK so it is unclear whether findings are transferrable to a wider section of schools in Wales and other countries, education systems and age groups.
C_LIO_LIIt was not possible to collect data on the reasons for return or non-return of parental consent.
C_LI | psychiatry and clinical psychology |
10.1101/2020.10.26.20219774 | Collecting genetic samples and linked mental health data from adolescents in schools: Protocol co-production and a mixed-methods pilot of feasibility and acceptability | ObjectivesTo co-produce a school-based protocol and examine acceptability and feasibility of collecting saliva samples for genetic studies from secondary/high school students for the purpose of mental health research.
DesignProtocol co-production and mixed-methods feasibility pilot.
SettingSecondary schools in Wales, UK.
ParticipantsStudents aged 11-13 years.
Primary and secondary outcome measuresCo-produced research protocol including an interactive science workshop delivered in schools; school, parental and student recruitment rates; adherence to protocol and adverse events; ability to extract and genotype saliva samples; student enjoyment of the science workshop; and qualitative analysis of teacher focus groups on acceptability and feasibility.
ResultsFive secondary schools participated in the co-production phase, and three of these took part in the research study (eligible sample n=868 students). Four further schools were subsequently approached, but none participated. Parental opt-in consent was received from 98 parents (11.3% eligible sample), three parents (0.3%) actively refused and responses were not received for 767 (88.4%) parents. We obtained saliva samples plus consent for data linkage for 79 students. Only one sample was of insufficient quality to be genotyped. The science workshop received positive feedback from students. Feedback from teachers showed that undertaking research like this in schools is viewed as acceptable in principle, potentially feasible, but that there are important procedural barriers to be overcome. Key recommendations include establishing close working relationships between the research team and school classroom staff, together with improved methods for communicating with and engaging parents.
ConclusionsThere are major challenges to undertaking large scale genetic mental health research in secondary schools. Such research may be acceptable in principle, and in practice DNA collected from saliva in classrooms is of sufficient quality. However, key challenges that must be overcome include ensuring representative recruitment of schools and sufficient parental engagement where opt-in parental consent is required.
Article SummaryO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIThis is the first study to test the feasibility and acceptability of collecting genetic samples in secondary schools and obtaining consent for linkage to questionnaire and record-based mental health data.
C_LIO_LIA key strength is co-production of the research protocol with stakeholders (young people, parents/guardians, schools).
C_LIO_LIWe used a mixed-methods approach to assess the feasibility and acceptability of carrying out genetic research studies of mental health in schools.
C_LIO_LIThis pilot study was conducted in three mainstream secondary schools in Wales, UK so it is unclear whether findings are transferrable to a wider section of schools in Wales and other countries, education systems and age groups.
C_LIO_LIIt was not possible to collect data on the reasons for return or non-return of parental consent.
C_LI | psychiatry and clinical psychology |
10.1101/2020.10.26.20218206 | Neural adaptation of cingulate and insular activity during delayed fear extinction: A replicable pattern across assessment sites and repeated measurements | Adapting threat-related memories towards changing environments is a fundamental ability of organisms. One central process of fear reduction is suggested to be extinction learning, experimentally modeled by extinction training that is repeated exposure to a previously conditioned stimulus (CS) without providing the expected negative consequence (unconditioned stimulus, US). Although extinction training is well investigated, evidence regarding process-related changes in neural activation over time is still missing. Using optimized delayed extinction training in a multicentric trial we tested whether: 1) extinction training elicited decreasing CS-specific neural activation and subjective ratings, 2) extinguished conditioned fear would return after presentation of the US (reinstatement), and 3) results are comparable across different assessment sites and repeated measures. We included 100 healthy subjects (measured twice, 13-week-interval) from six sites. 24h after fear acquisition training, extinction training, including a reinstatement test, was applied during fMRI. Alongside, participants had to rate subjective US-expectancy, arousal and valence. In the course of the extinction training, we found decreasing neural activation in the insula and cingulate cortex as well as decreasing US-expectancy, arousal and negative valence towards CS+. Re-exposure to the US after extinction training was associated with a temporary increase in neural activation in the anterior cingulate cortex (exploratory analysis) and changes in US-expectancy and arousal ratings. While ICCs-values were low, findings from small groups suggest highly consistent effects across time-points and sites. Therefore, this delayed extinction fMRI-paradigm provides a solid basis for the investigation of differences in neural fear-related mechanisms as a function of anxiety-pathology and exposure-based treatment.
Clinical Trials RegistrationRegistry names: Deutsches Register Klinischer Studien (DRKS) - German Clinical Trails Register
ClinicalTrials.gov
Registration ID-numbers: DRKS00008743
DRKS00009687
ClinicalTrials.gov Identifier: NCT02605668
URLs: https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00008743
https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00009687
https://clinicaltrials.gov/ct2/show/NCT02605668 | psychiatry and clinical psychology |
10.1101/2020.10.26.20215897 | Comparison of Japanese nurse practitioner-led care and physician trainees-led care on patients' length of stay in a secondary emergency department: A retrospective study | ObjectivesWe compared nurse practitioner-led care and physician trainees-led care on patients length of stay in a secondary emergency department in Japan.
MethodsThis observational research utilized a secondary data analysis of medical records. Participants (N = 1,419; mean age = 63.9 {+/-} 23.4 years; 52.3% men) were patients who were transferred to the emergency department by an ambulance between April 2016 and March 2018 in western Tokyo. Multiple linear regression analyses were performed with the length of stay as the dependent variable and the factors related to the length of stay, including medical care leaders, as the independent variable to compare Japanese nurse practitioner-led care and physician trainees-led care on patients length of stay.
ResultsApproximately half of the patients (n = 763; 53.8%) received Japanese nurse practitioner-led care. Patients length of stay was significantly shorter by six minutes in the Japanese nurse practitioner-led care group than the physician trainees-led care group.
ConclusionPatients length of stay was significantly shorter by six minutes in the Japanese nurse practitioner group than the physician trainees group. This time difference suggests that the medical care led by Japanese nurse practitioners is more efficient. In the future, the cost-effectiveness of Japanese nurse practitioner medical care, safety, and patient satisfaction should be examined in a multi-institutional joint study. | public and global health |
10.1101/2020.10.26.20213231 | Understanding the impact of high-risk human papillomavirus on oropharyngeal squamous cell carcinomas in Taiwan: A retrospective cohort study | Background and ObjectivesHuman papillomavirus (HPV)-driven oropharyngeal squamous cell carcinoma (OPSCC) is increasing globally. In Taiwan, HPV-positive OPSCC is obscured by tobacco, alcohol, and betel quid use. We investigated the role of high-risk HPV (hrHPV) in a large retrospective Taiwan OPSCC cohort.
Methods and ResultsThe cohort of 541 OPSCCs treated at Chang Gung Memorial Hospital from 1998-2016 consisted of 507 men (94%) and 34 women (6%). Most used tobacco (81%), alcohol (51%), and betel quid (65%). Formalin-fixed, paraffin-embedded tissue was used for p16 staining (a surrogate marker for HPV) and testing for HPV DNA presence and type by Multiplex HPV PCR-MassArray. HPV DNA and/or p16 staining (HPV-positive) was found in 28.4% (150/528) tumors. p16 and HPV DNA were strongly correlated (F < 0.0001). HPV16 was present in 82.8%, and HPV58 in 7.5% of HPV-positive tumors. HPV was associated with higher age (55.5 vs. 52.7 years, p = 0.004), lower T-stage (p = 0.008) better overall survival (OS) (hazard ratio [HR] 0.58 [95% CI 0.42-0.81], p = 0.001), and disease-free survival (DFS) (HR 0.54 [95% CI 0.40-0.73], p < 0.0001). Alcohol was strongly associated with recurrence and death (OS: HR 2.06 [95% CI 1.54-2.74], p < 0.0001; DFS: HR 1.72 [95% CI 1.33-2.24], p < 0.0001). OS and DFS in HPV-positive cases decreased for alcohol users (p < 0.0001). Obscured by the strong alcohol effect, predictive associations were not found for tobacco or betel quid.
ConclusionsAs with HPV-positive OPSCC globally, HPV is an increasingly important etiological factor in Taiwanese OPSCC. HPV-positive OPSCC has considerable survival benefit, but that is reduced by alcohol, tobacco, and betel quid use. hrHPV is a cancer risk factor in males and females. Vaccinating both sexes with a multivalent vaccine including HPV58, combined with alcohol and tobacco cessation policies will be effective cancer-prevention public health strategies in Taiwan. | otolaryngology |
10.1101/2020.10.26.20219899 | Phenome-wide HLA association landscape of 235,000 Finnish biobank participants | The human leukocyte antigen (HLA) system is the single most important genetic susceptibility factor for many autoimmune diseases and immunological traits. However, in a range of clinical phenotypes the impact of HLA alleles or their combinations on the disease risk are not comprehensively understood.
For systematic population-level analysis of HLA-phenotype associations we imputed the alleles of classical HLA genes in a discovery cohort of 146,630 and replication cohort of 89,340 Finns of whom SNP genotype data and 3,355 disease phenotypes were available as part of the FinnGen project.
The results suggest HLA associations in phenotypes not reported previously and highlight interactions between HLA genes and alleles in autoimmune diseases. Furthermore, shared HLA alleles in autoimmune and infectious diseases support a genetic link between these diseases. | allergy and immunology |
10.1101/2020.10.26.20219550 | Detecting behavioural changes in human movement to inform the spatial scale of interventions against COVID-19 | BackgroundIn 2020, the UK enacted an intensive, nationwide lockdown on March 23 to mitigate transmission of COVID-19. As restrictions began to ease, resurgences in transmission were targeted by geographically-limited interventions of various stringencies. Understanding the spatial scale of networks of human interaction, and how these networks change over time, is critical to inform interventions targeted at the most at-risk areas without unnecessarily restricting areas at low risk of resurgence.
MethodsWe use detailed human mobility data aggregated from Facebook users to determine how the spatially-explicit network of movements changed before and during the lockdown period, in response to the easing of restrictions, and to the introduction of locally-targeted interventions. We also apply community detection techniques to the weighted, directed network of movements to identify geographically-explicit movement communities and measure the evolution of these community structures through time.
FindingsWe found that the mobility network became more sparse and the number of mobility communities decreased under the national lockdown, a change that disproportionately affected long distance journeys central to the mobility network. We also found that the community structure of areas in which locally-targeted interventions were implemented following epidemic resurgence did not show reorganization of community structure but did show small decreases in indicators of travel outside of local areas.
InterpretationWe propose that communities detected using Facebook or other mobility data be used to assess the impact of spatially-targeted restrictions and may inform policymakers about the spatial extent of human movement patterns in the UK. These data are available in near real-time, allowing quantification of changes in the distribution of the population across the UK, as well as changes in travel patterns to inform our understanding of the impact of geographically-targeted interventions.
Putting Research Into ContextO_ST_ABSEvidence before this studyC_ST_ABSLarge-scale intensive interventions in response to the COVID-19 pandemic have been implemented globally, significantly affecting human movement patterns. Mobility data show spatially-explicit network structure, but it is not clear how that structure changed in response to national or locally-targeted interventions.
Added value of this studyWe used daily mobility data aggregated from Facebook users to quantify changes in the travel network in the UK during the national lockdown, and in response to local interventions. We identified changes in human behaviour in response to interventions and identified the community structure inherent in these networks. This approach to understanding changes in the travel network can help quantify the extent of strongly connected communities of interaction and their relationship to the extent of spatially-explicit interventions.
Implications of all the available evidenceWe show that spatial mobility data available in near real-time can give information on connectivity that can be used to understand the impact of geographically-targeted interventions and in the future, to inform spatially-targeted intervention strategies.
Data SharingData used in this study are available from the Facebook Data for Good Partner Program by application. Code and supplementary information for this paper are available online (https://github.com/hamishgibbs/facebook_mobility_uk), alongside publication. | epidemiology |
10.1101/2020.10.26.20219642 | A2B-COVID: A method for evaluating potential SARS-CoV-2 transmission events | Identifying linked cases of infection is a key part of the public health response to viral infectious disease. Viral genome sequence data is of great value in this task, but requires careful analysis, and may need to be complemented by additional types of data. The Covid-19 pandemic has highlighted the urgent need for analytical methods which bring together sources of data to inform epidemiological investigations. We here describe A2B-COVID, an approach for the rapid identification of linked cases of coronavirus infection. Our method combines knowledge about infection dynamics, data describing the movements of individuals, and novel approaches to genome sequence data to assess whether or not cases of infection are consistent or inconsistent with linkage via transmission. We apply our method to analyse and compare data collected from two wards at Cambridge University Hospitals, showing qualitatively different patterns of linkage between cases on designated Covid-19 and non-Covid-19 wards. Our method is suitable for the rapid analysis of data from clinical or other potential outbreak settings. | epidemiology |
10.1101/2020.10.26.20218495 | Speech cortical activation and connectivity in typically developing children and those with listening difficulties | Listening difficulties (LiD) in people who have normal audiometry (LiD) are a widespread but poorly understood form of hearing impairment. Recent research suggests that childhood LiD are cognitive rather than auditory in origin. We assessed that hypothesis using behavioral testing and fMRI with 43 typically developing children and 42 age matched (6-13 years old) children with LiD, categorized by caregiver report (ECLiPS). The children with LiD had clinically normal hearing. For sentence listening tasks, we found no group differences in fMRI brain cortical activation by increasingly complex speech, from phonology to intelligibility to semantics. Using resting state fMRI, we examined the temporal connectivity of cortical auditory and related speech perception networks. Significant group differences were found only in cortical connections engaged by more complex speech processing. The strength of the affected connections was related to the childrens performance on tests of dichotic listening, speech-in-noise, attention, memory and verbal vocabulary. Together, these results support the hypothesis that childhood LiD reflects cognitive and language rather than auditory deficits. | neurology |
10.1101/2020.10.27.20220202 | The mass balance model of obesity explains the weight loss advantage of a low-carbohydrate diet over a isocaloric low-fat diet | Differential weight and fat losses under isocaloric diets of distinct macronutrient composition are well-documented findings in obesity research.1-6 Such data are considered a result of inadequate methodology as it disagree with the energy balance theory.7 A recent mathematical analysis of this paradigm has found, however, serious analytical contradictions in its foundations.8 As an alternative, a mass balance model was proposed to explain the aforesaid body composition alterations. Here, we expand on this observation by contrasting both models. We show that mass balance explains a wide range of fending experiments including those concurring with the energy balance principle. The latter, however, is less flexible and results in poor forecasts in settings consistent with mass balance. The energy balance theory is thus an unsatisfactory model of body composition changes. Consequently, by shifting to a mass balance paradigm of obesity a much deeper understanding of this disease may follow in the near future. | nutrition |
10.1101/2020.10.27.20220202 | The mass balance model of obesity explains the weight loss advantage of a low-carbohydrate diet over a isocaloric low-fat diet | Differential weight and fat losses under isocaloric diets of distinct macronutrient composition are well-documented findings in obesity research.1-6 Such data are considered a result of inadequate methodology as it disagree with the energy balance theory.7 A recent mathematical analysis of this paradigm has found, however, serious analytical contradictions in its foundations.8 As an alternative, a mass balance model was proposed to explain the aforesaid body composition alterations. Here, we expand on this observation by contrasting both models. We show that mass balance explains a wide range of fending experiments including those concurring with the energy balance principle. The latter, however, is less flexible and results in poor forecasts in settings consistent with mass balance. The energy balance theory is thus an unsatisfactory model of body composition changes. Consequently, by shifting to a mass balance paradigm of obesity a much deeper understanding of this disease may follow in the near future. | nutrition |
10.1101/2020.10.27.20220202 | Macronutrient mass intake explains deferential weight and fat loss in isocaloric diets | Differential weight and fat losses under isocaloric diets of distinct macronutrient composition are well-documented findings in obesity research.1-6 Such data are considered a result of inadequate methodology as it disagree with the energy balance theory.7 A recent mathematical analysis of this paradigm has found, however, serious analytical contradictions in its foundations.8 As an alternative, a mass balance model was proposed to explain the aforesaid body composition alterations. Here, we expand on this observation by contrasting both models. We show that mass balance explains a wide range of fending experiments including those concurring with the energy balance principle. The latter, however, is less flexible and results in poor forecasts in settings consistent with mass balance. The energy balance theory is thus an unsatisfactory model of body composition changes. Consequently, by shifting to a mass balance paradigm of obesity a much deeper understanding of this disease may follow in the near future. | nutrition |
10.1101/2020.10.27.20220202 | Macronutrient mass intake explains deferential weight and fat loss in isocaloric diets | Differential weight and fat losses under isocaloric diets of distinct macronutrient composition are well-documented findings in obesity research.1-6 Such data are considered a result of inadequate methodology as it disagree with the energy balance theory.7 A recent mathematical analysis of this paradigm has found, however, serious analytical contradictions in its foundations.8 As an alternative, a mass balance model was proposed to explain the aforesaid body composition alterations. Here, we expand on this observation by contrasting both models. We show that mass balance explains a wide range of fending experiments including those concurring with the energy balance principle. The latter, however, is less flexible and results in poor forecasts in settings consistent with mass balance. The energy balance theory is thus an unsatisfactory model of body composition changes. Consequently, by shifting to a mass balance paradigm of obesity a much deeper understanding of this disease may follow in the near future. | nutrition |
10.1101/2020.10.27.20220202 | Macronutrient mass intake explains deferential weight and fat loss in isocaloric diets | Differential weight and fat losses under isocaloric diets of distinct macronutrient composition are well-documented findings in obesity research.1-6 Such data are considered a result of inadequate methodology as it disagree with the energy balance theory.7 A recent mathematical analysis of this paradigm has found, however, serious analytical contradictions in its foundations.8 As an alternative, a mass balance model was proposed to explain the aforesaid body composition alterations. Here, we expand on this observation by contrasting both models. We show that mass balance explains a wide range of fending experiments including those concurring with the energy balance principle. The latter, however, is less flexible and results in poor forecasts in settings consistent with mass balance. The energy balance theory is thus an unsatisfactory model of body composition changes. Consequently, by shifting to a mass balance paradigm of obesity a much deeper understanding of this disease may follow in the near future. | nutrition |
10.1101/2020.10.27.20220202 | Macronutrient mass intake explains deferential weight and fat loss in isocaloric diets | Differential weight and fat losses under isocaloric diets of distinct macronutrient composition are well-documented findings in obesity research.1-6 Such data are considered a result of inadequate methodology as it disagree with the energy balance theory.7 A recent mathematical analysis of this paradigm has found, however, serious analytical contradictions in its foundations.8 As an alternative, a mass balance model was proposed to explain the aforesaid body composition alterations. Here, we expand on this observation by contrasting both models. We show that mass balance explains a wide range of fending experiments including those concurring with the energy balance principle. The latter, however, is less flexible and results in poor forecasts in settings consistent with mass balance. The energy balance theory is thus an unsatisfactory model of body composition changes. Consequently, by shifting to a mass balance paradigm of obesity a much deeper understanding of this disease may follow in the near future. | nutrition |
10.1101/2020.10.27.20220202 | Macronutrient mass intake explains deferential weight and fat loss in isocaloric diets | Differential weight and fat losses under isocaloric diets of distinct macronutrient composition are well-documented findings in obesity research.1-6 Such data are considered a result of inadequate methodology as it disagree with the energy balance theory.7 A recent mathematical analysis of this paradigm has found, however, serious analytical contradictions in its foundations.8 As an alternative, a mass balance model was proposed to explain the aforesaid body composition alterations. Here, we expand on this observation by contrasting both models. We show that mass balance explains a wide range of fending experiments including those concurring with the energy balance principle. The latter, however, is less flexible and results in poor forecasts in settings consistent with mass balance. The energy balance theory is thus an unsatisfactory model of body composition changes. Consequently, by shifting to a mass balance paradigm of obesity a much deeper understanding of this disease may follow in the near future. | nutrition |
10.1101/2020.10.27.20220202 | The energy balance theory: an unsatisfactory model of body composition fluctuations | Differential weight and fat losses under isocaloric diets of distinct macronutrient composition are well-documented findings in obesity research.1-6 Such data are considered a result of inadequate methodology as it disagree with the energy balance theory.7 A recent mathematical analysis of this paradigm has found, however, serious analytical contradictions in its foundations.8 As an alternative, a mass balance model was proposed to explain the aforesaid body composition alterations. Here, we expand on this observation by contrasting both models. We show that mass balance explains a wide range of fending experiments including those concurring with the energy balance principle. The latter, however, is less flexible and results in poor forecasts in settings consistent with mass balance. The energy balance theory is thus an unsatisfactory model of body composition changes. Consequently, by shifting to a mass balance paradigm of obesity a much deeper understanding of this disease may follow in the near future. | nutrition |
10.1101/2020.10.25.20219063 | Emergence and spread of a SARS-CoV-2 variant through Europe in the summer of 2020 | Following its emergence in late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic resulting in unprecedented efforts to reduce transmission and develop therapies and vaccines (WHO Emergency Committee, 2020; Zhu et al., 2020). Rapidly generated viral genome sequences have allowed the spread of the virus to be tracked via phylogenetic analysis (Worobey et al., 2020; Hadfield et al., 2018; Pybus et al., 2020). While the virus spread globally in early 2020 before borders closed, intercontinental travel has since been greatly reduced, allowing continent-specific variants to emerge. However, within Europe travel resumed in the summer of 2020, and the impact of this travel on the epidemic is not well understood. Here we report on a novel SARS-CoV-2 variant, 20E (EU1), that emerged in Spain in early summer, and subsequently spread to multiple locations in Europe. We find no evidence of increased transmissibility of this variant, but instead demonstrate how rising incidence in Spain, resumption of travel across Europe, and lack of effective screening and containment may explain the variants success. Despite travel restrictions and quarantine requirements, we estimate 20E (EU1) was introduced hundreds of times to countries across Europe by summertime travellers, likely undermining local efforts to keep SARS-CoV-2 cases low. Our results demonstrate how a variant can rapidly become dominant even in absence of a substantial transmission advantage in favorable epidemiological settings. Genomic surveillance is critical to understanding how travel can impact SARS-CoV-2 transmission, and thus for informing future containment strategies as travel resumes.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the first pandemic where the spread of a viral pathogen has been globally tracked in near real-time using phylogenetic analysis of viral genome sequences (Worobey et al., 2020; Hadfield et al., 2018; Pybus et al., 2020). SARS-CoV-2 genomes continue to be generated at a rate far greater than for any other pathogen and more than 500,000 full genomes are available on GISAID as of February 2020 (Shu and McCauley, 2017).
In addition to tracking the viral spread, these genome sequences have been used to monitor mutations which might change the transmission, pathogenesis, or anti-genic properties of the virus. One mutation in particular, D614G in the spike protein, has received much attention. This variant (Nextstrain clade 20A) seeded large outbreaks in Europe in early 2020 and subsequently dominated the outbreaks in the Americas, thereby largely replacing previously circulating lineages. This rapid rise led to the suggestion that this variant is more transmissible, which has since been corroborated by phylogenetic (Korber et al., 2020; Volz et al., 2020) and experimental evidence (Plante et al., 2020; Yurkovetskiy et al., 2020).
Following the global dissemination of SARS-CoV-2 in early 2020 (Worobey et al., 2020), intercontinental travel dropped dramatically. Within Europe, however, travel and in particular holiday travel resumed in summer (though at lower levels than in previous years) with largely uncharacterized effects on the pandemic. Here we report on a novel SARS-CoV-2 variant 20E (EU1) (S:A222V) that emerged in early summer 2020, presumably in Spain, and subsequently spread to multiple locations in Europe. Over the summer, it rose in frequency in parallel in multiple countries. As we report here, this variant, 20E (EU1), and a second variant 20A.EU2 with mutation S477N in the spike protein accounted for the majority of sequences in Europe in the autumn of 2020. | epidemiology |
10.1101/2020.10.27.20220434 | Knowledge, attitudes, and perceptions of long-acting reversible contraceptive (LARC) methods among healthcare workers in sub-Saharan Africa: a systematic review and meta-analysis | ObjectiveTo assess the knowledge, attitudes, and perceptions (KAP) of long-acting reversible contraceptive (LARC) methods among healthcare workers (HCWs) in sub-Saharan Africa (SSA).
MethodsA systematic review and meta-analysis were conducted following the PRISMA methodology. Two authors independently searched three electronic databases for studies published between 2000 and January 2020 reporting on the KAP of LARC methods among HCWs in SSA. Titles and abstracts were screened against eligibility criteria, data were extracted and the included studies were assessed for risk of bias. A meta-analysis of proportions for 11 pre-determined questions relating to LARC KAP was performed. Heterogeneity was explored using the I2-statistic and publication bias investigated using funnel plots and Eggers tests.
ResultsTwenty-two studies comprising of 11 272 HCWs from 11 SSA countries were included. Forty-one percent (95% CI: 20%, 61%) of HCWs had received intrauterine contraceptive device (IUCD) insertion training while 63% (95% CI: 44%, 81%) expressed a desire for training. Only 27% (95% CI: 18%, 36%) deemed IUCD appropriate for HIV-infected women. Restrictions for IUCD and injectables based on a minimum age were imposed by 56% (95% CI: 33%, 78%) and 60% (95% CI: 36%, 84%), respectively. Minimum parity restrictions were observed among 29% (95% CI: 9%, 50%) of HCWs for IUCDs and 36% (95% CI: 16%, 56%) for injectable contraceptives. Heterogeneity was high and publication bias was present in two of the 11 questions.
ConclusionThe systematic review and meta-analysis indicate that unnecessary provider-imposed restrictions may hinder the uptake of LARC methods by women in SSA.
Conflicts of InterestNone.
Ethics approvalEthical approval was received from the Faculty of Health Sciences Research Ethics Committee (REC) at the University of Pretoria, School of Health Systems and Public Health. Reference Number: 640/2019
Authors ContributionsAll authors contributed to the design of the study and the preparation of the manuscript. LR, ST and AM contributed toward the statistical analysis. All authors read and approved the content of the manuscript. | sexual and reproductive health |
10.1101/2020.10.26.20220111 | Life Expectancy and Voting Patterns in 2020 US Presidential Election | IntroductionIn the 2016 U.S. Presidential election, voters in communities with recent stagnation or decline in life expectancy were more likely to vote for the Republican candidate than in prior Presidential elections. We aimed to assess the association between change in life expectancy and voting patterns in the 2020 Presidential election.
MethodsWith data on county-level life expectancy from the Institute for Health Metrics and Evaluation and voting data from GitHub, we used weighted multivariable linear regression to estimate the association between the change in life expectancy from 1980 to 2014 and the proportion of votes for the Republican candidate in the 2020 Presidential election.
ResultsAmong 3,110 U.S counties and Washington, D.C., change in life expectancy at the county level was negatively associated with Republican share of the vote in the 2020 Presidential election (parameter estimate -7.2, 95% confidence interval, -7.8 to -6.6). With the inclusion of state, sociodemographic, and economic variables in the model, the association was attenuated (parameter estimate -0.8; 95% CI, -1.5 to -0.2).
ConclusionCounties with a less positive trajectory in life expectancy were more likely to vote for Republican candidates in the 2020 U.S. Presidential election, but the association was mediated by demographic, social and economic factors. | health policy |
10.1101/2020.10.29.20222265 | Analysis of the early Covid-19 epidemic curve in Germany by regression models with change points | We analyze the Covid-19 epidemic curve from March to end of April 2020 in Germany. We use statistical models to estimate the number of cases with disease onset on a given day and use back-projection techniques to obtain the number of new infections per day. The respective time series are analyzed by a trend regression model with change points. The change points are estimated directly from the data. We carry out the analysis for the whole of Germany and the federal state of Bavaria, where we have more detailed data. Both analyses show a major change between March 9th and 13th for the time series of infections: from a strong increase to a decrease. Another change was found between March 25th and March 29th, where the decline intensified. Furthermore, we perform an analysis stratified by age. A main result is a delayed course of the epidemic for the age group 80+ resulting in a turning point at the end of March.
Our results differ from those by other authors as we take into account the reporting delay, which turned out to be time dependent and therefore changes the structure of the epidemic curve compared to the curve of newly reported cases. | epidemiology |
10.1101/2020.10.27.20220897 | The effect of eviction moratoria on the transmission of SARS-CoV-2 | Massive unemployment during the COVID-19 pandemic could result in an eviction crisis in US cities. Here we model the effect of evictions on SARS-CoV-2 epidemics, simulating viral transmission within and among households in a theoretical metropolitan area. We recreate a range of urban epidemic trajectories and project the course of the epidemic under two counterfactual scenarios, one in which a strict moratorium on evictions is in place and enforced, and another in which evictions are allowed to resume at baseline or increased rates. We find, across scenarios, that evictions lead to significant increases in infections. Applying our model to Philadelphia using locally-specific parameters shows that the increase is especially profound in models that consider realistically heterogenous cities in which both evictions and contacts occur more frequently in poorer neighborhoods. Our results provide a basis to assess municipal eviction moratoria and show that policies to stem evictions are a warranted and important component of COVID-19 control. | epidemiology |
10.1101/2020.10.28.20220657 | High performances of a novel antigen detection test on nasopharyngeal specimens for SARS-CoV-2 infection diagnosis: a prospective study | IntroductionThe SARS-CoV-2 pandemic has become a major public health issue worldwide. Developing and evaluating rapid and easy-to-perform diagnostic tests is an absolute priority. The current study was designed to assess diagnostic performances of an antigen-based rapid detection test (COVID-VIRO(R)) in a real-life setting.
MethodsTwo nasopharyngeal specimens of symptomatic or asymptomatic adult patients hospitalized in the Infectious Diseases Department or voluntarily accessing the COVID-19 Screening Department of the Regional Hospital of Orleans, France, were concurrently collected. COVID VIRO(R) diagnostic specificity and sensitivity were assessed in comparison to real-time reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) results. A subset of patients underwent an additional oropharyngeal and/or a saliva swab for rapid testing.
Results121 patients already having a confirmed infection and 127 patients having no evidence of recent or ongoing infection were enrolled, for a total of 248 couple of nasopharyngeal swab specimens. Overall COVID-VIRO(R) sensitivity was 96.7% (IC: 93.5%-99.9%). In asymptomatic patients, symptomatic patients having symptoms for more than 4 days and those having a RT-qPCR Cycle threshold value [≥]32, sensitivity was of 100%, 95.8% and 91.9% respectively. The concordance between RT-qPCR and COVID VIRO(R) rapid test was 100% for the 127 patients with no SARS-CoV-2 infection.
ConclusionCOVID-VIRO(R) test had 100% specificity and above 95% sensitivity, better than WHO recommendations (specificity [≥]97-100%, sensitivity [≥]80%). These rapid tests are particularly interesting for large-scale screening in Emergency Department, low resource settings and airports. | infectious diseases |
10.1101/2020.10.29.20217059 | Fine mapping of the HLA locus in Parkinson's disease in Europeans | ObjectiveTo fine map the association between human leukocyte antigen (HLA) genes and Parkinsons disease (PD) that was discovered using genome-wide association studies (GWASs).
MethodsWe performed a thorough analysis of the HLA locus in 13,770 PD patients, 20,214 proxy-cases and 490,861 controls of European origin. We used GWAS data to impute HLA types and performed multiple regression models to examine the association of specific HLA types, different haplotypes and specific amino acid changes. We further performed conditional analyzes to identify specific alleles or genetic variants that drive the association with PD.
ResultsFour HLA types were associated with PD after correction for multiple comparisons, HLA-DQA1*03:01, HLA-DQB1*03:02, HLA-DRB1*04:01 and HLA-DRB1*04:04. Haplotype analyzes followed by amino-acid analysis and conditional analyzes suggested that the association is protective and primarily driven by three specific amino acid polymorphisms present in most HLA-DRB1*04 subtypes - 11V, 13H and 33H (OR=0.87 95%CI=0.83-0.90, p<8.23x10-9 for all three variants). No other effects were present after adjustment for these amino acids.
ConclusionsOur results suggest that specific variants in the HLA-DRB1 gene are associated with reduced risk of PD, providing additional evidence for the role of the immune system in PD. Although effect size is small and has no diagnostic significance, understanding the mechanism underlying this association may lead to identification of new targets for therapeutics development. | genetic and genomic medicine |
10.1101/2020.10.28.20221986 | Causal Impacts of Teaching Modality on U.S. COVID-19 Spread in Fall 2020 Semester | We study the impact of college reopening in Fall 2020 on county-level COVID-19 cases and deaths using the information of 1,076 U.S. colleges. We match college and county characteristics using several methods and calculate the average treatment effects of three teaching modalities: in-person, online, and hybrid on COVID-19 outcomes up to two months after college reopening. In pairwise comparison, colleges reopened with in-person teaching mode were found to have about 36% point more cases within 15 days of reopening, compared to those reopened online, and the gap widens over time at a decreasing rate. Death rates follow the pattern with a time lag. However, colleges with hybrid mode catch the pattern of in-person mode after some time. We also find that greater endowment and student population, and fewer republican votes in the county are major predictors of choosing remote teaching modes over in-person.
JEL codesA23, I18, I23. | health policy |
10.1101/2020.10.28.20221986 | Impacts of Teaching Modality on U.S. COVID-19 Spread in Fall 2020 Semester | We study the impact of college reopening in Fall 2020 on county-level COVID-19 cases and deaths using the information of 1,076 U.S. colleges. We match college and county characteristics using several methods and calculate the average treatment effects of three teaching modalities: in-person, online, and hybrid on COVID-19 outcomes up to two months after college reopening. In pairwise comparison, colleges reopened with in-person teaching mode were found to have about 36% point more cases within 15 days of reopening, compared to those reopened online, and the gap widens over time at a decreasing rate. Death rates follow the pattern with a time lag. However, colleges with hybrid mode catch the pattern of in-person mode after some time. We also find that greater endowment and student population, and fewer republican votes in the county are major predictors of choosing remote teaching modes over in-person.
JEL codesA23, I18, I23. | health policy |
10.1101/2020.10.29.20222208 | Method development and characterization of the low molecular weight peptidome of human wound fluids | Wound infections are significant challenges globally, and there is an unmet need for better diagnosis of wound healing status and infection. The wound healing process is characterized by proteolytic events that are the result of basic physiological processes, but also dysfunctional activations by endogenous and bacterial proteases. Peptides, downstream reporters of these proteolytic actions, could therefore serve as a promising tool for diagnosis of wounds.
Here, we demonstrate a method for the characterisation of the peptidome of wound fluids. We compare acute non-infected wound fluids obtained post-surgery with plasma samples and find significantly higher protein and peptide numbers in wound fluids, which typically were also smaller in size as compared to plasma-derived peptides. Furthermore, we analyse wound fluids collected from dressings after facial skin graft surgery and compare three uninfected, healing wounds with three inflamed Staphylococcus aureus infected wounds. The results identify unique peptide patterns of various proteins, including coagulation and complement factors, proteases and antiproteinases.
Together, the work defines a workflow for analysis of peptides derived from wound fluids and demonstrate a proof-of-concept that such fluids can be used for analysis of qualitative differences of peptide patterns from larger patient cohorts, providing potential biomarkers for wound healing and infection. | dermatology |
10.1101/2020.10.28.20221721 | A Time-dependent mathematical model for COVID-19 transmission dynamics and analysis of critical and hospitalized cases with bed requirements | A time-dependent SEAIHCRD model is the extension of the SEIR model, which includes some new compartment that is asymptomatic infectious people, hospitalized people, critical people, and dead compartments. In this article, we analyzed six countries, namely the United States, Brazil, India, South Africa, Russia, and Mexico. A time-dependent SEAIHCRD model calculates the magnitude of peaks for exposed people, asymptomatic infectious people, symptomatic infectious people, hospitalized people, the number of people admitted to ICUs, and the number of COVID-19 deaths over time. It also computes the spread scenario and endpoints of disease. The proposed model also involves asymptomatic infectious individuals. To estimate the various parameters, we first collect the data and fit that using the Lavenberg-Marquardt model for death cases. Then we calculate infection rate, recovery rate, case fatality rate, and the basic reproduction number over time. We calculate two types of case fatality rates: one is the daily case fatality rate, and the other is the total case fatality rate. The proposed model includes the social distance parameter, various age classes, hospital beds for severe cases, and ICU beds or ventilators for critical cases. This model will be useful to determine various essential parameters such as daily hospitalization rate, daily death rates, including the requirement of normal and ICU beds during peak days of infection. | epidemiology |
10.1101/2020.10.28.20221770 | The association between socioeconomic status and mobility reductions in the early stage of England's COVID-19 epidemic | This study uses mobile phone data to examine how socioeconomic status was associated with the extent of mobility reduction during the spring 2020 lockdown in England in a manner that considers both potentially confounding effects and spatial dependency and heterogeneity. It shows that socioeconomic status as approximated through income and occupation was strongly correlated with the extent of mobility reduction. It also demonstrates that the specific nature of the association of socioeconomic status with mobility reduction varied markedly across England. Finally, the analysis suggests that the ability to restrict everyday mobility in response to a national lockdown is distributed in a spatially uneven manner, and may need to be considered a luxury or, failing that, a tactic of survival for specific social groups. | epidemiology |
10.1101/2020.10.29.20222091 | Clinical validation of Whole Genome Sequencing for cancer diagnostics | Whole genome sequencing (WGS) using fresh frozen tissue and matched blood samples from cancer patients is becoming in reach as the most complete genetic tumor test. With a trend towards the availability of small biopsies and the need to screen an increasing number of (complex) biomarkers, the use of a single all-inclusive test is preferred over multiple consecutive assays. To meet high-quality diagnostics standards, we optimized and clinically validated WGS sample and data processing procedures resulting in a technical success rate of 95.6% for fresh-frozen samples with sufficient ([≥]20%) tumor content.
Independent validation of identified biomarkers against commonly used diagnostic assays showed a high sensitivity (recall) (98.5%) and precision (positive predictive value) (97.8%) for detection of somatic SNV and indels (across 22 genes), and high concordance for detection of gene amplification (97.0%, EGRF and MET) as well as somatic complete loss (100%, CDKN2A/p16). Gene fusion analysis showed a concordance of 91.3% between DNA-based WGS and an orthogonal RNA-based gene fusion assay. Microsatellite (in)stability assessment showed a sensitivity of 100% with a precision of 94%, and virus detection (HPV) an accuracy of 100% compared to standard testing.
In conclusion, whole genome sequencing has a >95% sensitivity and precision compared to routinely used DNA techniques in diagnostics and all relevant mutation types can be detected reliably in a single assay. | genetic and genomic medicine |
10.1101/2020.10.28.20221804 | A catalog of associations between rare coding variants and COVID-19 outcomes | Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-19 (COVID-19), a respiratory illness that can result in hospitalization or death. We investigated associations between rare genetic variants and seven COVID-19 outcomes in 543,213 individuals, including 8,248 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 14 interferon pathway genes in which rare deleterious variants have been reported in severe COVID-19 patients; (ii) 167 genes located in COVID-19 GWAS risk loci; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, with results publicly browsable at https://rgc-covid19.regeneron.com. | infectious diseases |
10.1101/2020.10.29.20220426 | Occupational risk of COVID-19 in the 1st vs 2nd wave of infection | AimTo study whether employees in occupations that typically imply close contact with other people are tested more and at higher risk of confirmed SARS-CoV-2 infection (COVID-19) and related hospitalization, in the 1st and 2nd wave of infection in Norway.
MethodsIn all 3 559 694 residents of Norway on January 1st 2020 aged 20-70 (with mean [SD] age 44.1 [14.3] years and 51% men), we studied COVID-19 testing patterns sorted by occupation (using Standard Classification of Occupations [ISCO-08]). We also studied whether selected occupations had a higher risk of 1) confirmed COVID-19 and 2) hospitalization with COVID-19, compared to everyone else aged 20-70 years using logistic regression adjusted for age, sex, testing behavior, and own and maternal country of birth.
ResultsOccupations with high frequency of testing (e.g. health personnel and teachers) had a low frequency of positive tests. Nurses, physicians, dentists, physiotherapists, bus/tram and taxi drivers had 1.1-4 times the odds of COVID-19 during the 1st wave, whereas bartenders, waiters, transport conductors and travel stewards had 1.1-3 times the odds of COVID-19 during the 2nd wave (when compared to everyone else). Teachers had moderately increased odds of COVID-19. Occupation may be of limited relevance for hospitalization with the disease.
ConclusionStudying the entire Norwegian population using international standardized codes of occupations, our findings may be of relevance to national and regional authorities in handling the pandemic. Also, our findings provide a knowledge foundation for the more targeted future studies of lockdown, testing strategies and disease control measures. | infectious diseases |
10.1101/2020.10.30.20220855 | Prevalence of missing data in the National Cancer Database and association with overall survival | ImportanceCancer registries are important real-world data (RWD) sources that rely on data abstraction from the medical record, however, patients with unknown or missing data are under-represented in studies that use such data sources.
ObjectiveTo determine the prevalence of missing data and its associated overall survival among cancer patients
Design, Setting, and ParticipantsIn this retrospective cohort study, all variables within the National Cancer Database (NCDB) were reviewed for missing or unknown values for the three most common cancers in the United States diagnosed from 2006 to 2015. Prevalence of patient records with missing data and their associated overall survival were determined. Data analysis was performed from February to August 2020.
ExposuresAny missing data field within a patient record among 63 variables of interest, from over 130 variables total in the NCDB.
Main Outcome and MeasurePrevalence of cancer patient records with missing data and associated two-year overall survival
ResultsA total of 1,198,749 non-small cell lung cancer (NSCLC) patients (mean [SD] age, 68.5 [10.9] years; 569,938 [47.5%] women), 2,120,775 breast cancer patients (mean [SD] age, 61.0 [13.3] years; 2,101,758 [99.1%] women), and 1,158,635 prostate cancer patients (mean [SD] age, 65.2 [9.0] years; 0 [0%] women) were included for analysis. For NSCLC, there were 851,295 (71.0%) patients with missing data in variables of interest; 2-year overall survival was 33.2% for patients with missing data and 51.6% for patients with complete data (p<0.001). For breast cancer, there were 1,161,096 (54.7%) patients with missing data; 2-year overall survival was 93.2% for patients with missing data and 93.9% for patients with complete data (p<0.001). For prostate cancer, there were 460,167 (39.7%) patients with missing data; 2-year overall survival was 91.0% for patients with missing data and 95.6% for patients with complete data (p<0.001).
Conclusions and RelevanceWithin a large cancer registry-based RWD source, missing data that was unable to be ascertained from the medical record was highly prevalent. Missing data among cancer patients was associated with heterogeneous differences in overall survival. Improving documentation and data quality are needed to best leverage RWD for clinical advancements. | oncology |
10.1101/2020.10.29.20222455 | A tipping point in cancer-immune dynamics leads to divergent immunotherapy responses and hampers biomarker discovery | BackgroundPredicting treatment response or survival of cancer patients remains challenging in immuno-oncology. Efforts to overcome these challenges focus, among others, on the discovery of new biomarkers. Despite advances in cellular and molecular approaches, only a limited number of candidate biomarkers eventually enter clinical practice.
MethodsA computational modeling approach based on ordinary differential equations was used to simulate the fundamental mechanisms that dictate tumor-immune dynamics and to investigate its implications on responses to immune checkpoint inhibition (ICI) and patient survival. Using in silico biomarker discovery trials, we revealed fundamental principles that explain the diverging success rates of biomarker discovery programs.
ResultsOur model shows that a tipping point - a sharp state transition between immune control and immune evasion - induces a strongly non-linear relationship between patient survival and both immunological and tumor-related parameters. In patients close to the tipping point, ICI therapy may lead to long-lasting survival benefits, whereas patients far from the tipping point may fail to benefit from these potent treatments.
ConclusionThese findings have two important implications for clinical oncology. First, the apparent conundrum that ICI induces substantial benefits in some patients yet completely fails in others could be, to a large extent, explained by the presence of a tipping point. Second, predictive biomarkers for immunotherapy should ideally combine both immunological and tumor-related markers, as a patients distance from the tipping point can typically not be reliably determined from solely one of these. The notion of a tipping point in cancer-immune dynamics helps to devise more accurate strategies to select appropriate treatments for cancer patients. | oncology |
10.1101/2020.11.02.20222869 | Outbreak investigation of Visceral Leishmaniasis in Borena Zone, Oromia Region, Ethiopia, November 2019: Case Control study | BackgroundVisceral Leishmaniasis (VL) caused by Leishmania parasites, infects mammals transmitted by Phlebotomine sand-flies and mostly affects the poorest. VL distributed worldwide and prevalent in Ethiopia. Knowing occurrence of disease and risk factor is a remedy for controlling. The aim of study was to identify factors associated with VL.
MethodsCase control study was carried out during October-November 2019 in Borena. A 1:2 Cases and controls were identified by case definition and 33 cases were included in the study. Participants >18years interviewed and caregivers of <18 were questioned for legal issue. Epi-info and SPSS were used for data entry and analysis. Primarily predictors were identified using chi-square at significant level P<0.05 with 95%CI, then candidate predictors were analysed using bivariate and multivariate analysis to identify associated factors.
ResultAmong 153 suspected cases, 9 suspected deaths reported; 33 (22%) cases and 3 deaths were verified for VL. Among 33 verified cases 15(45.5%) were in July 2019, in comparison of 4years data, there is surge cases in July-August 2019, 26(79%) of cases were from Dire, Attack Rate (AR) = 15/100,000, CFR=9.1%. Among all, 15-64year were highly affected with AR=19.3. A case control engaged 99(100%) respondents and among all 93(93.9%) were male, 68(68.8%) were 15-64years. Adult education Adjusted Odds Ratio (AOR) = 30.438(2.378, 389.602), bed-net AOR=9.024 (1.763, 46.205) and walling AOR=0.052(0.004, 0.739) were associated factors with VL at 95%CI with p-value<0.05.
ConclusionMale 15-64years were highly susceptible. Level of education, ITNs and walling were associated factors with VL. Formulating policies and guidelines for male 15-64 years related vector control and awareness creation regarding feeding habit of sand fly, prevention and control were recommended. Awareness of community on prevention method; using repellents, ITNs utilization, and safe sleeping mechanisms are mandatory. Further investigation on the issue is best remedy to overcome future VL outbreak occurrence. | epidemiology |
10.1101/2020.11.01.20217497 | Encephalopathies associated with severe COVID-19 present specific neurovascular unit alterations without evidence of strong neuroinflammation | ObjectiveCoronavirus disease (COVID-19) has been associated with a large variety of neurological disorders. However the mechanisms underlying these neurological complications remain elusive. In this study we aimed at determining whether neurological symptoms were caused by SARS-CoV-2 direct infection or by either systemic or local pro-inflammatory mediators.
MethodsWe checked for SARS-CoV-2 RNA by RT-qPCR, SARS-CoV-2-specific antibodies and for 49 cytokines/chemokines/growth factors (by Luminex) in the cerebrospinal fluids (CSF) +/-sera of a cohort of 22 COVID-19 patients with neurological presentation and 55 neurological control patients (inflammatory [IND], non-inflammatory [NIND], multiple sclerosis [MS]).
ResultsWe detected SARS-CoV-2 RNA and virus-specific antibodies in the CSF of 0/22 and 10/21 COVID-19 patients, respectively. Of the four categories of tested patients, the CSF of IND exhibited the highest level of cytokines, chemokines and growth factors. In contrast, COVID-19 patients did not present overall upregulation of inflammatory mediators in the CSF. However, the CSF of patients with severe COVID-19 (ICU patients) exhibited higher concentrations of CCL2, CXCL8, and VEGF-A in the CSF than patients with a milder form of COVID-19. In addition, we could show that intrathecal CXCL8 synthesis was linked to an elevated barrier index and correlated to the increase of peripheral inflammation (serum HGF and CXCL10).
ConclusionOur results point at an absence of massive SARS-CoV-2 infection or inflammation of the central nervous system, but highlight a specific impairment of the neurovascular unit linked to intrathecal production of CXCL8. | neurology |
10.1101/2020.11.02.20224568 | Effectiveness of quarantine and testing to prevent COVID-19 transmission from arriving travelers | ObjectiveTo assess the efficacy of policies designed to reduce the risk of international travelers importing SARS-CoV-2 into a country.
MethodWe developed a simulation model and compared mandatory quarantine, testing, and combined quarantine and testing. We assessed the sensitivity of policy effectiveness to the timing of testing, compliance with quarantine and isolation, and other factors.
ResultsIn the base scenario, a 2-day quarantine reduced more risk than testing alone. The effectiveness of a 5-day quarantine requirement with perfect compliance was similar to a 14-day quarantine with moderate compliance. Testing 72h before arrival reduced less than 10% of in-country transmission risk across all scenarios. The addition of testing to quarantine added value for shorter quarantine lengths, when testing compliance was enforced, and when testing was performed near the end of quarantine.
ConclusionsQuarantine is more effective at preventing SARS-CoV-2 transmission from arriving travelers than testing alone, but testing combined with quarantine can add value if longer quarantine requirements are infeasible. Enforcing compliance with quarantine and isolation is critical. Requiring a negative test up to 72h before arrival may have limited effectiveness. | health policy |
10.1101/2020.11.02.20222778 | SARS-CoV-2 responsive T cell numbers are associated with protection from COVID-19: A prospective cohort study in keyworkers | Immune correlates of protection from COVID-19 are incompletely understood. 2,826 keyworkers had T-SPOT(R) Discovery SARS-CoV-2 tests (measuring interferon-{gamma} secreting, SARS-CoV-2 responsive T cells, Oxford Immunotec Ltd), and anti-Spike S1 domain IgG antibody levels (EuroImmun AG) performed on recruitment into a cohort study. 285/2,826 (10.1%) of participants had positive SARS-CoV-2 RT-PCR tests, predominantly associated with symptomatic illness, during 200 days followup. T cell responses to Spike, Nucleoprotein and Matrix proteins (SNM responses) were detected in some participants at recruitment, as were anti-Spike S1 IgG antibodies; higher levels of both were associated with protection from subsequent SARS-CoV-2 test positivity. In volunteers with moderate antibody responses, who represented 39% (252/654) of those with detectable anti-Spike IgG, protection was partial, and higher with higher circulating T cell SNM responses. SARS-CoV-2 responsive T cell numbers predict protection in individuals with low anti-Spike IgG responses; serology alone underestimates the proportion of the population protected after infection. | infectious diseases |
10.1101/2020.11.03.20225144 | Characteristics of those most vulnerable to employment changes during the COVID-19 pandemic: a nationally representative cross-sectional study in Wales | BackgroundThe public health response to the SARS-CoV-2 (COVID-19) pandemic has had a detrimental impact on employment and there are concerns the impact may be greatest amongst the most vulnerable. We examined the characteristics of those who experienced changes in employment status during the early months of the pandemic.
MethodsData was collected from a cross-sectional, nationally representative household survey of the working age population (18-64 years) in Wales in May/June 2020 (N=1,379). We looked at changes in employment and being placed on furlough since February 2020 across demographics, contract type, job skill level, health status and household factors. Chi-squared or Fishers tests and multinomial logistic regression models examined associations between demographics, subgroups and employment outcomes.
ResultsOf our respondents 91.0% remained in the same job in May/June 2020 as they were in February 2020, 5.7% were now in a new job, and 3.3% experienced unemployment. In addition, 24% of our respondents reported being placed on furlough. Non-permanent contract types, individuals who reported low mental wellbeing and household financial difficulties were all significant factors in experiencing unemployment. Being placed on furlough was more likely in younger (18-29 years) and older (60-64 years) workers, those in lower skilled jobs and from households with less financial security.
ConclusionA number of vulnerable population groups were observed to experience detrimental employment outcomes during the initial stage of the COVID-19 pandemic. Targeted support is needed to mitigate against both the direct impacts on employment, and indirect impacts on financial insecurity and health.
What is already known on this subject?O_LIThe response to the current global pandemic caused by SARS-CoV-2 (COVID-19) is already having a significant impact on peoples ability to work and employment status.
C_LIO_LIEmerging UK employment data has raised concerns about the disproportionate impact on specific demographic groups.
C_LI
What this study adds?O_LIGroups that reported higher proportions of being placed on furlough included younger (18-29 years) and older (50-64 years) workers, people from more deprived areas, in lower skilled jobs, and those from households with less financial security.
C_LIO_LIJob insecurity in the early months of the COVID-19 pandemic was experienced more by those self-employed or employed on atypical or fixed term contract arrangements compared to those holding permanent contracts.
C_LIO_LITo ensure that health and wealth inequalities are not exacerbated by COVID-19 or the economic response to the pandemic, interventions should include the promotion of secure employment and target the groups identified as most susceptible to the emerging harms of the pandemic.
C_LI | public and global health |