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10.1101/2020.11.15.20232090 | The effect of body image dissatisfaction on goal-directed decision making in a population marked by negative appearance beliefs and disordered eating | Eating disorders are associated with one of the highest mortality rates among all mental disorders, yet there is very little research about them within the newly emerging and promising field of computational psychiatry. As such, we focus on investigating a previously unexplored, yet a core aspect of eating disorders - body image dissatisfaction. We continue a freshly opened debate about model-based learning and its trade-off against model-free learning - a proxy for goal-directed and habitual behaviour. We perform a behavioural study that utilises a two-step decision-making task and a reinforcement learning model to understand the effect of body image dissatisfaction on model-based learning in a population characterised by high scores of disordered eating and negative appearance beliefs, as recruited using Prolific. We find a significantly reduced model-based contribution in the body image dissatisfaction task condition in the population of interest as compared to a healthy control. | psychiatry and clinical psychology |
10.1101/2020.11.15.20232090 | The effect of body image dissatisfaction on goal-directed decision making in a population marked by negative appearance beliefs and disordered eating | Eating disorders are associated with one of the highest mortality rates among all mental disorders, yet there is very little research about them within the newly emerging and promising field of computational psychiatry. As such, we focus on investigating a previously unexplored, yet a core aspect of eating disorders - body image dissatisfaction. We continue a freshly opened debate about model-based learning and its trade-off against model-free learning - a proxy for goal-directed and habitual behaviour. We perform a behavioural study that utilises a two-step decision-making task and a reinforcement learning model to understand the effect of body image dissatisfaction on model-based learning in a population characterised by high scores of disordered eating and negative appearance beliefs, as recruited using Prolific. We find a significantly reduced model-based contribution in the body image dissatisfaction task condition in the population of interest as compared to a healthy control. | psychiatry and clinical psychology |
10.1101/2020.11.19.20235010 | Unmasking Seasonal Cycles in Human Fertility: How holiday sex and fertility cycles shape birth seasonality | The mechanisms of human birth seasonality have been debated for over 150 years1. In particular, the question of whether sexual activity or fertility variations drive birth seasonality has remained open and challenging to test without large-scale data on sexual activity 2,3. Analyzing data from half-a-million users worldwide collected from the female health tracking app Clue combined with birth records, we inferred that birth seasonality is primarily driven by seasonal fertility, yet increased sexual activity around holidays explains minor peaks in the birth curve. Our data came from locations in the Northern Hemisphere (UK, US, and France) and the Southern Hemisphere (Brazil). We found that fertility peaks between the autumn equinox and winter solstice in the Northern Hemisphere locations and shortly following the winter solstice in the Southern Hemisphere locations. | sexual and reproductive health |
10.1101/2020.11.18.20233874 | Acute nasal dryness in COVID-19 | One of the entry routes of SARS-CoV-2 is the nasal epithelium. Although mounting evidence suggests the presence of olfactory dysfunction, and even anosmia, in patients with COVID-19, it is not clear whether these patients also suffer from other "nasal" symptoms that may influence their olfaction. A group of 35 patients with COVID-19 (and a control group matched in gender and age) were surveyed about the presence of a variety of nasal symptoms that may be associated to drastic perturbations experienced in the nasal cavity (e.g., "excessive dryness" and/or a continual sensation of having had a "nasal douche"). We used a cross-sectional, retrospective survey, targeted at the general population by means of non-quoted, non-random, snowball sampling. Symptoms were assessed with absence/presence responses. The possible association between two continuously distributed latent variables from categorical variables was estimated by means of polychoric correlations. More than 68% of the patients reported at least one "nasal" symptom. The clinical group also experienced "a strange sensation in the nose" and having excessive nasal dryness significantly more often than the control group. Fifty-two percent of the patients (but only 3% of the control group) reported a constant sensation of having had a strong nasal douche. Nasal symptoms predominantly co-occurred with anosmia/hyposmia, and ageusia/hypogeusia, appeared principally before or during the other symptoms of COVID-19, and lasted for twelve days, in average. The presence of these nasal symptoms, and their early occurrence, could potentially facilitate early diagnosis of COVID-19 and initial social distancing efforts. | infectious diseases |
10.1101/2020.11.18.20234039 | The detection and stability of the SARS-CoV-2 RNA biomarkers in wastewater influent in Helsinki, Finland | Wastewater-based surveillance of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is used to monitor the population-level prevalence of the COVID-19 disease. In many cases, due to lockdowns or analytical delays, the analysis of wastewater samples might only be possible after prolonged storage. In this study, the effect of storage conditions on the RNA copy numbers of the SARS-CoV-2 virus in wastewater influent was studied and compared to the persistence of norovirus over time at 4{degrees}C, -20{degrees}C, and -75{degrees}C using the reverse-transcription quantitative PCR (RT-qPCR) assays E-Sarbeco, N2, and norovirus GII. For the first time in Finland, the presence of SARS-CoV-2 RNA was tested in 24 h composite influent wastewater samples collected from Viikinmaki wastewater treatment plant, Helsinki, Finland. The detected and quantified SARS-CoV-2 RNA copy numbers of the wastewater sample aliquots taken during 19-20 April 2020 and stored for 29, 64, and 84 days remained surprisingly stable. In the stored samples, the SARS betacoronavirus and SARS-CoV-2 copy numbers, but not the norovirus GII copy numbers, seemed slightly higher when analyzed from the pre-centrifuged pellet--that is, the particulate matter of the influent--as compared with the supernatant (i.e., water fraction) used for ultrafiltration, although the difference was not statistically significant. Furthermore, when wastewater was spiked with SARS-CoV-2, linear decay at 4{degrees}C was observed on the first 28 days, while no decay was visible within 58 days at -20{degrees}C or -75{degrees}C. In conclusion, freezing temperatures should be used for storage when immediate SARS-CoV-2 RNA analysis from the wastewater influent is not possible. Analysis of the particulate matter of the sample, in addition to the water fraction, can improve the detection frequency. | public and global health |
10.1101/2020.11.18.20230649 | A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2 | BackgroundAs part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being changed, ultimately altering the dynamics of disease spread. These modifications could be specific to the type of business being operated.
MethodsWe use a data-driven approach to parameterise an individual-based network model for transmission of SARS-CoV-2 amongst the working population, stratified into work sectors. The network is comprised of layered contacts to consider the risk of spread in multiple encounter settings (workplaces, households, social and other). We analyse several interventions targeted towards working practices: mandating a fraction of the population to work from home; using temporally asynchronous work patterns; and introducing measures to create COVID-secure workplaces. We also assess the general role of adherence to (or effectiveness of) isolation and test and trace measures and demonstrate the impact of all these interventions across a variety of relevant metrics.
ResultsThe progress of the epidemic can be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, if required to be present at the workplace, asynchronous work patterns can help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. When assessing COVID-secure workplace measures, we found that smaller work teams and a greater reduction in transmission risk reduced the probability of large, prolonged outbreaks. Finally, following isolation guidance and engaging with contact tracing without other measures is an effective tool to curb transmission, but is highly sensitive to adherence levels.
ConclusionsIn the absence of sufficient adherence to non-pharmaceutical interventions, our results indicate a high likelihood of SARS-CoV-2 spreading widely throughout a worker population. Given the heterogeneity of demographic attributes across worker roles, in addition to the individual nature of controls such as contact tracing, we demonstrate the utility of a network model approach to investigate workplace-targeted intervention strategies and the role of test, trace and isolation in tackling disease spread. | infectious diseases |
10.1101/2020.11.18.20230649 | A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2 | BackgroundAs part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being changed, ultimately altering the dynamics of disease spread. These modifications could be specific to the type of business being operated.
MethodsWe use a data-driven approach to parameterise an individual-based network model for transmission of SARS-CoV-2 amongst the working population, stratified into work sectors. The network is comprised of layered contacts to consider the risk of spread in multiple encounter settings (workplaces, households, social and other). We analyse several interventions targeted towards working practices: mandating a fraction of the population to work from home; using temporally asynchronous work patterns; and introducing measures to create COVID-secure workplaces. We also assess the general role of adherence to (or effectiveness of) isolation and test and trace measures and demonstrate the impact of all these interventions across a variety of relevant metrics.
ResultsThe progress of the epidemic can be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, if required to be present at the workplace, asynchronous work patterns can help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. When assessing COVID-secure workplace measures, we found that smaller work teams and a greater reduction in transmission risk reduced the probability of large, prolonged outbreaks. Finally, following isolation guidance and engaging with contact tracing without other measures is an effective tool to curb transmission, but is highly sensitive to adherence levels.
ConclusionsIn the absence of sufficient adherence to non-pharmaceutical interventions, our results indicate a high likelihood of SARS-CoV-2 spreading widely throughout a worker population. Given the heterogeneity of demographic attributes across worker roles, in addition to the individual nature of controls such as contact tracing, we demonstrate the utility of a network model approach to investigate workplace-targeted intervention strategies and the role of test, trace and isolation in tackling disease spread. | infectious diseases |
10.1101/2020.11.18.20230649 | A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2 | BackgroundAs part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being changed, ultimately altering the dynamics of disease spread. These modifications could be specific to the type of business being operated.
MethodsWe use a data-driven approach to parameterise an individual-based network model for transmission of SARS-CoV-2 amongst the working population, stratified into work sectors. The network is comprised of layered contacts to consider the risk of spread in multiple encounter settings (workplaces, households, social and other). We analyse several interventions targeted towards working practices: mandating a fraction of the population to work from home; using temporally asynchronous work patterns; and introducing measures to create COVID-secure workplaces. We also assess the general role of adherence to (or effectiveness of) isolation and test and trace measures and demonstrate the impact of all these interventions across a variety of relevant metrics.
ResultsThe progress of the epidemic can be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, if required to be present at the workplace, asynchronous work patterns can help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. When assessing COVID-secure workplace measures, we found that smaller work teams and a greater reduction in transmission risk reduced the probability of large, prolonged outbreaks. Finally, following isolation guidance and engaging with contact tracing without other measures is an effective tool to curb transmission, but is highly sensitive to adherence levels.
ConclusionsIn the absence of sufficient adherence to non-pharmaceutical interventions, our results indicate a high likelihood of SARS-CoV-2 spreading widely throughout a worker population. Given the heterogeneity of demographic attributes across worker roles, in addition to the individual nature of controls such as contact tracing, we demonstrate the utility of a network model approach to investigate workplace-targeted intervention strategies and the role of test, trace and isolation in tackling disease spread. | infectious diseases |
10.1101/2020.11.18.20230649 | A network modelling approach to assess non-pharmaceutical disease controls in a worker population: An application to SARS-CoV-2 | BackgroundAs part of a concerted pandemic response to protect public health, businesses can enact non-pharmaceutical controls to minimise exposure to pathogens in workplaces and premises open to the public. Amendments to working practices can lead to the amount, duration and/or proximity of interactions being changed, ultimately altering the dynamics of disease spread. These modifications could be specific to the type of business being operated.
MethodsWe use a data-driven approach to parameterise an individual-based network model for transmission of SARS-CoV-2 amongst the working population, stratified into work sectors. The network is comprised of layered contacts to consider the risk of spread in multiple encounter settings (workplaces, households, social and other). We analyse several interventions targeted towards working practices: mandating a fraction of the population to work from home; using temporally asynchronous work patterns; and introducing measures to create COVID-secure workplaces. We also assess the general role of adherence to (or effectiveness of) isolation and test and trace measures and demonstrate the impact of all these interventions across a variety of relevant metrics.
ResultsThe progress of the epidemic can be significantly hindered by instructing a significant proportion of the workforce to work from home. Furthermore, if required to be present at the workplace, asynchronous work patterns can help to reduce infections when compared with scenarios where all workers work on the same days, particularly for longer working weeks. When assessing COVID-secure workplace measures, we found that smaller work teams and a greater reduction in transmission risk reduced the probability of large, prolonged outbreaks. Finally, following isolation guidance and engaging with contact tracing without other measures is an effective tool to curb transmission, but is highly sensitive to adherence levels.
ConclusionsIn the absence of sufficient adherence to non-pharmaceutical interventions, our results indicate a high likelihood of SARS-CoV-2 spreading widely throughout a worker population. Given the heterogeneity of demographic attributes across worker roles, in addition to the individual nature of controls such as contact tracing, we demonstrate the utility of a network model approach to investigate workplace-targeted intervention strategies and the role of test, trace and isolation in tackling disease spread. | infectious diseases |
10.1101/2020.11.18.20230540 | Genetic and environmental regulation of caudate nucleus transcriptome: insight into schizophrenia risk and the dopamine system | Increased dopamine (DA) signaling in the striatum has been a cornerstone hypothesis about psychosis for over 50 years. Increased dopamine release results in psychotic symptoms, while D2 dopamine receptor (DRD2) antagonists are antipsychotic. Recent schizophrenia GWAS identified risk-associated common variants near the DRD2 gene, but the risk mechanism has been unclear. To gain novel insight into risk mechanisms underlying schizophrenia, we performed a comprehensive analysis of the genetic and transcriptional landscape of schizophrenia in postmortem caudate nucleus from a cohort of 444 individuals. Integrating expression quantitative trait loci (eQTL) analysis, transcriptome wide association study (TWAS), and differential expression analysis, we found many new genes associated with schizophrenia through genetic modulation of gene expression. Using a new approach based on deep neural networks, we construct caudate nucleus gene expression networks that highlight interactions involving schizophrenia risk. Interestingly, we found that genetic risk for schizophrenia is associated with decreased expression of the short isoform of DRD2, which encodes the presynaptic autoreceptor, and not with the long isoform, which encodes the postsynaptic receptor. This association suggests that decreased control of presynaptic DA release is a potential genetic mechanism of schizophrenia risk. Altogether, these analyses provide a new resource for the study of schizophrenia that can bring insight into risk mechanisms and potential novel therapeutic targets. | psychiatry and clinical psychology |
10.1101/2020.11.20.20235291 | Isolation thresholds for curbing SARS-CoV-2 resurgence | Self-instigated isolation is heavily relied on to curb SARS-CoV-2 transmission. Accounting for uncertainty in the latent and prepatent periods, as well as the proportion of infections that remain asymptomatic, the limits of this intervention at different phases of infection resurgence are estimated. We show that by October 2020, SARS-CoV-2 transmission rates in England had already begun exceeding levels that could be interrupted using this intervention alone, lending support to the second national lockdown on November 5th 2020. | epidemiology |
10.1101/2020.11.19.20235101 | A framework to model global, regional, and national estimates of intimate partner violence | AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSAccurate and reliable estimates of violence against women statistics form the backbone of monitoring efforts to eliminate these human right violations and public health concerns. Estimating the prevalence of intimate partner violence (IPV) is challenging due to variations in case definition and recall period, surveyed populations, partner definition, level of age disaggregation, and survey representativeness, among others. In this paper, we aim to develop a sound and flexible statistical modeling framework for global, regional, and national IPV statistics.
MethodsWe modeled IPV within a Bayesian multilevel modeling framework, accounting for heterogeneity of age groups using age-standardization, and age patterns and time trends using splines functions. Survey comparability is achieved using adjustment factors which are estimated using exact matching and their uncertainty accounted for. Both in-sample and out-of-sample comparisons are used for model validation, including posterior predictive checks. Post-processing of models outputs is performed to aggregate estimates at different geographic levels and age groups.
ResultsA total of 307 unique studies conducted between 2000-2018, from 154 countries/territories/areas, and totaling nearly 1.8 million unique women responses informed lifetime IPV. Past year IPV had similar number of studies (n=332), countries represented (n=159), and individual responses (n=1.8 million). Roughly half of IPV observations required some adjustments. Posterior predictive checks suggest good model fit to data and out-of-sample comparisons provided reassuring results with small median prediction errors and appropriate coverage of predictions intervals.
ConclusionsThe proposed modeling framework can pool both national and sub-national surveys, account for heterogeneous age groups and age trends, accommodate different surveyed population, adjust for differences in survey instruments, and efficiently propagate uncertainty to model outputs. By describing this model to reproducible levels of details, the accurate interpretation and responsible use of estimates for global monitoring of violence against women elimination efforts are supported, as part of the Sustainable Development Goals. | public and global health |
10.1101/2020.11.19.20234963 | The effectiveness of early diagnostic tools for neural lesions in leprosy. An observational cohort study | Cegana LHV, Nardi SMT, Pascoeto L, Paschoal VDA. The effectiveness of early diagnostic tools for neural lesions in leprosy. 37p. MANUSCRIPT, 2020. https://doi.org/10.1101/2020.11.19.20234963
IntroductionLeprosy can cause different lesions in peripheral nerves and inervatory structures.
ObjectivesTo analyse the effectiveness of evaluation protocols used to identify neural lesions in leprosy such as Degree of Physical Disability (DPD), Simplified Neurological Assessment (SNA) and propose to use Neurodynamic Assessment (NDA).
MethodDescriptive analytical study, associative, with 27 individuals treated in two outpatient leprosy clinics in Sao Paulo State, between 2017 and 2019, and 27 individuals from the paired control group. The Mann-Whitney, Multivariate Linear Regression and association between variables and P<0.05 values were used.
ResultsThe test that most captured the neurological alterations was the SNA, with 22 (81.5%) in the upper limbs (ULs) and 25 (92.6%) in the lower limbs (LLs), followed by the NDA, with 20 (74.1%) in the ULs and 11 (40.7%) in the LLs. The DPD showed handicap in the hands of 16 (59.2%) individuals and in the feet of 17 (62.9%) individuals, and they have expressed sensitivity. DPD showed agreement with SNA in 21 (77.8%) of the cases in ULs (p=0.010) and 19 (70,4%) of the cases in LLs (p=0.060). DPD and NDA showed that in 19 (70.4%) of the patients evaluated there was concordance of results in ULs (p=0.143); 9 (33.3%) in LLs (p=0.125). SNA and the NDA in the ULs found agreement in 21 (77.8%); 11 (40.7%) (p=0.786) in the LLs.
ConclusionThe three assessment instruments are specific and will hardly produce false positive tests. DPD can produce more false negatives than SNA. If there is an instrument to be chosen, it should be the SNA, since it is more sensitive, more accurate and has a less negative likelihood ratio. Neurodynamic tests were positive in 7.4% of individuals while there were still no changes in the SNA; afterwards, these changes appeared.
DescriptorsNeural mobilization; Leprosy; Peripheral nerves; Disability; Pain; Physical therapy. | rehabilitation medicine and physical therapy |
10.1101/2020.11.19.20235077 | Comparing COVID-19 and influenza presentation and trajectory | BackgroundCOVID-19 is a newly recognized illness with a predominantly respiratory presentation. It is important to characterize the differences in disease presentation and trajectory between COVID-19 patients and other patients with common respiratory illnesses. These differences can enhance knowledge of pathogenesis and help in guiding treatment.
MethodsData from electronic medical records were obtained from individuals admitted with respiratory illnesses to Rambam Health Care Campus, Haifa, Israel, between October 1st, 2014 and October 1st, 2020. Four groups of patients were defined: COVID-19 (693), influenza (1,612), severe acute respiratory infection (SARI) (2,292) and Others (4,054). The variable analyzed include demographics (7), vital signs (8), lab tests (38),and comorbidities (15) from a total of 8,651 hospitalized adult patients. Statistical analysis was performed on biomarkers measured at admission and for their disease trajectory in the first 48 hours of hospitalization, and on comorobidity prevalence.
ResultsCOVID-19 patients were overall younger in age and had higher body mass index, compared to influenza and SARI. Comorbidity burden was lower in the COVID-19 group compared to influenza and SARI. Severely- and moderately-ill COVID-19 patients older than 65 years of age suffered higher rate of in-hospital mortality compared to hospitalized influenza patients. At admission, white blood cells and neutrophils were lower among COVID-19 patients compared to influenza and SARI patients, while pulse rate and lymphoctye percentage were higher. Trajectories of variables during the first two days of hospitalization revealed that white blood count, neutrophils percentage and glucose in blood increased among COVID-19 patients, while decreasing among other patients.
ConclusionsThe intrinsic virulence of COVID-19 appeared higher than influenza. In addition, several critical functions, such as immune response, coagulation, heart and respiratory function and metabolism were uniquely affected by COVID-19. | infectious diseases |
10.1101/2020.11.20.20234062 | Clinical judgement of General Practitioners for the diagnosis of dementia | BackgroundThe accuracy of General Practitioners (GPs) clinical judgement for dementia is uncertain.
AimInvestigate the accuracy of GPs clinical judgement for the diagnosis of dementia.
Design and SettingDiagnostic test accuracy study, recruiting from 21 practices around Bristol.
MethodThe clinical judgement of the treating GP (index test) was based on the information immediately available at their initial consultation with a person aged over 70 years who had cognitive symptoms. The reference standard was an assessment by a specialist clinician, based on a standardised clinical examination and made according to ICD-10 criteria for dementia.
Results240 people were recruited, with a median age of 80 years (IQR 75 to 84 years), of whom 126 (53%) were men and 132 (55%) had dementia. The median duration of symptoms was 24 months (IQR 12 to 36 months) and the median ACE-III score was 75 (IQR 65 to 87). GP clinical judgement had sensitivity 56% (95% CI 47% to 65%) and specificity 89% (95% CI 81% to 94%). Positive likelihood ratio was higher in people aged 70-79 years (6.5, 95% CI 2.9 to 15) compared to people aged [≥] 80 years (3.6, 95% CI 1.7 to 7.6), and in women (10.4, 95% CI 3.4 to 31.7) compared to men (3.2, 95% CI 1.7 to 6.2), whereas the negative likelihood ratio was similar in all groups.
ConclusionA GP clinical judgement of dementia is specific, but confirmatory testing is needed for symptomatic people who GPs judge as not having dementia.
How this fits inPrevious studies in this area have investigated the accuracy of GP clinical judgement as a screening test for dementia in unselected people attending a primary care clinic; or as a retrospective test based on their knowledge of their patient; or derived the accuracy of judgement from the medical records, which may not reflect the judgement of the clinician. The role of the GP in supporting a more effective route to diagnosis for people with dementia is a research priority for patients, carers and clinicians. This study shows that, in a symptomatic older adult, prospective clinical judgement may be useful for helping to confirm a diagnosis of dementia, whereas GP judgement should not by itself be used to exclude dementia. | primary care research |
10.1101/2020.11.20.20235473 | Cross-sectional association of blood pressure variability and night-time dipping with cardiac structure in adolescents | Greater blood pressure (BP) variability and reduced night-time BP dipping are associated with cardiovascular disease risk independently of mean BP in adults. This study examines whether these associations are apparent in a general population of adolescents. A cross-sectional analysis was undertaken in 587 UK adolescents (mean age 17.7 years; 43.1% male). BP was measured in a research clinic and using 24-hour ambulatory monitoring. We examined associations (for both systolic and diastolic BP) of: 1) clinic and 24-hour mean BP; 2) measures of 24-hour BP variability: standard deviation weighted for day/night (SDdn), variability independent of the mean (VIM) and average real variability (ARV); and 3) night-time dipping with cardiac structures. Cardiac structures were assessed by echocardiography: 1) left ventricular mass indexed to height2.7 (LVMi2.7); 2) relative wall thickness (RWT); 3) left atrial diameter indexed to height (LADi) and 4) left ventricular internal diameter in diastole (LVIDD). Higher systolic BP was associated with greater LVMi2.7. Systolic and diastolic BP were associated with greater RWT. Associations were inconsistent for LADi and LVIDD. There was evidence for associations between both greater SDdn and ARV and higher RWT (per 1 SD higher diastolic ARV, mean difference in RWT was 0.13 SDs, 95% CI 0.045 to 0.21); these associations with RWT remained after adjustment for mean BP. There was no consistent evidence of associations between night-time dipping and cardiac structure. In this general adolescent population study, associations between BP variability and cardiac structure were apparent. Measurement of BP variability might benefit cardiovascular risk assessment in adolescents. | epidemiology |
10.1101/2020.11.20.20235614 | ThinkCancer! The multi-method development of a complex behaviour change intervention to improve the early diagnosis of cancer in primary care | BackgroundRelatively poor UK cancer outcomes are blamed upon late diagnosis. Despite most cancer patients presenting to their GP with symptoms, diagnostic delay remains a common theme, with many clinical and non-clinical factors responsible. Early diagnosis is key to improving outcomes and survival. This paper reports the multi-method process to design a complex intervention to improve the timely diagnosis of symptomatic cancer.
MethodsA review of reviews, survey, discrete choice experiment, qualitative interviews and focus groups, all informed a realist evidence synthesis. This in turn informed the design of a complex intervention, guided by the Behaviour Change Wheel framework using a multi-step process.
ResultsKey themes from the realist evidence synthesis included effective safety netting at practitioner and practice system level, increased vigilance and lowering referral thresholds. Qualitative findings explored the tensions, barriers and facilitators affecting suspected cancer referral. The Think Cancer! intervention is an educational and quality improvement workshop directed at the whole primary care team. Bespoke cancer safety netting plans and appointment of cancer champions are key components.
ConclusionsThink Cancer! is a novel primary care early cancer diagnosis intervention, requiring evaluation through a cluster randomised control trial. | primary care research |
10.1101/2020.11.20.20235309 | Concurrent anatomical, physiological and network changes in cognitively impaired multiple sclerosis patients | Cognitive impairment in multiple sclerosis is associated with functional connectivity abnormalities, but the pathological substrates of these abnormalities are not well understood. It has been proposed that resting-state network nodes that integrate information from disparate regions are susceptible to metabolic stress, which may impact functional connectivity. In multiple sclerosis, pathology could increase metabolic stress within axons, damaging the anatomical connections of network regions, and leading to functional connectivity changes. We tested this hypothesis by assessing whether resting state network regions that show functional connectivity abnormalities in people with cognitive impairment also show anatomical connectivity abnormalities.
Multimodal MRI and neuropsychological assessments were performed in 102 relapsing remitting multiple sclerosis patients and 27 healthy controls. Patients were considered cognitively impaired if they obtained a z-score of [≤]1.5 on [≥]2 tests of the Brief Repeatable Battery of Neuropsychological Tests (n=55). Functional connectivity was assessed with Independent Component Analysis of resting state fMRI images, and anatomical connectivity with Anatomical Connectivity Mapping of diffusion-weighted MRI. Exploratory analyses of fractional anisotropy and cerebral blood flow changes were conducted to assess local tissue characteristics.
We found significantly decreased functional connectivity in the anterior and posterior default mode networks and significant increases in the right and left frontoparietal networks in cognitively impaired relative to cognitively preserved patients. Networks showing functional abnormalities also showed reduced anatomical connectivity and white matter microstructure integrity as well as reduced local tissue cerebral blood flow.
Our results identify key pathological correlates of functional connectivity abnormalities associated with impaired cognitive function in multiple sclerosis, consistent with metabolic dysfunction in functional network regions. | neurology |
10.1101/2020.11.21.20235283 | Aerial transmission of SARS-CoV-2 virus (and pathogens in general) through environmental e-cigarette aerosol | We examine the plausibility, scope and risks of aerial transmission of pathogens (including the SARS-CoV-2 virus) through respiratory droplets carried by exhaled e-cigarette aerosol (ECA). Given the lack of empiric evidence, we consider cigarette smoking and mouth breathing through a mouthpiece as convenient proxies to infer the respiratory mechanics and droplets sizes and their rate of emission that should result from vaping. To quantify direct exposure distance we model exhaled ECA flow as an intermittent turbulent jet evolving into an unstable puff, estimating for low intensity vaping (practiced by 80-90% of vapers) the emission of 6-200 (mean 79.82, standard deviation 74.66) respiratory submicron droplets per puff a horizontal distance spread of 1-2 meters, with intense vaping possibly emitting up to 1000 droplets per puff in the submicron range a distance spread over 2 meters. Since exhaled ECA acts effectively as a visual tracer of its expiratory flow, bystanders become instinctively aware that possible direct contagion might occur only in the direction and scope of the jet. | infectious diseases |
10.1101/2020.11.21.20235283 | Modeling aerial transmission of pathogens (including the SARS-CoV-2 virus) through aerosol emissions from e-cigarettes | We examine the plausibility, scope and risks of aerial transmission of pathogens (including the SARS-CoV-2 virus) through respiratory droplets carried by exhaled e-cigarette aerosol (ECA). Given the lack of empiric evidence, we consider cigarette smoking and mouth breathing through a mouthpiece as convenient proxies to infer the respiratory mechanics and droplets sizes and their rate of emission that should result from vaping. To quantify direct exposure distance we model exhaled ECA flow as an intermittent turbulent jet evolving into an unstable puff, estimating for low intensity vaping (practiced by 80-90% of vapers) the emission of 6-200 (mean 79.82, standard deviation 74.66) respiratory submicron droplets per puff a horizontal distance spread of 1-2 meters, with intense vaping possibly emitting up to 1000 droplets per puff in the submicron range a distance spread over 2 meters. Since exhaled ECA acts effectively as a visual tracer of its expiratory flow, bystanders become instinctively aware that possible direct contagion might occur only in the direction and scope of the jet. | infectious diseases |
10.1101/2020.11.19.20234542 | Poor in-utero growth, and reduced beta cell compensation and high fasting glucose from childhood, are harbingers of glucose intolerance in young Indians | ObjectiveIndia is a double world capital for early life undernutrition and type 2 diabetes. We aimed to characterise lifecourse growth and metabolic trajectories in those developing glucose intolerance as young adults, in the Pune Maternal Nutrition Study (PMNS).
Research design and MethodsPMNS is a community-based intergenerational birth cohort established in 1993, with serial information on parents and children through pregnancy, childhood and adolescence. We compared normal glucose tolerant and glucose intolerant participants for serial growth, estimates of insulin sensitivity and secretion (HOMA and dynamic indices) and beta cell compensation accounting for prevailing insulin sensitivity (disposition index).
ResultsAt 18 years (N=619) 37% men and 20% women were glucose intolerant (184 prediabetes, 1 diabetes) despite 48% being underweight (BMI<18.5 kg/m2). Glucose intolerant participants had higher fasting glucose from childhood. Mothers of glucose intolerant participants had higher glycemia in pregnancy. Glucose intolerant participants were shorter at birth. Insulin sensitivity decreased with age in all participants, and the glucose intolerant had consistently lower compensatory insulin secretion from childhood. Participants in the highest quintile of fasting glucose at 6 and 12 years had a 2.5- and 4.0-fold higher risk respectively of 18-year glucose intolerance; this finding was replicated in two other cohorts.
ConclusionInadequate compensatory insulin secretory response to increasing insulin insensitivity from early life is the major pathophysiology underlying glucose intolerance in thin rural Indians. Smaller birth size, maternal pregnancy hyperglycemia, and higher glycemia in childhood herald future glucose intolerance, mandating a strategy for diabetes prevention from early life, preferably intergenerationally. | endocrinology |
10.1101/2020.11.22.20236547 | Correcting B0 inhomogeneity-induced distortions in whole-body diffusion MRI of bone | ObjectivesDiffusion-weighted magnetic resonance imaging (DWI) of the musculoskeletal system has various applications, including visualization of bone tumors. However, DWI acquired with echo-planar imaging is susceptible to distortions due to static magnetic field inhomogeneities. This study aimed to estimate spatial displacements of bone and to examine whether distortion corrected DWI images more accurately reflect underlying anatomy.
MethodsWhole-body MRI data from 127 prostate cancer patients were analyzed. The reverse polarity gradient (RPG) technique was applied to DWI data to estimate voxel-level distortions and to produce a distortion corrected DWI dataset. First, an anatomic landmark analysis was conducted, in which corresponding vertebral landmarks on DWI and anatomic T2-weighted images were annotated. Changes in distance between DWI- and T2-defined landmarks (i.e., changes in error) after distortion correction were calculated. In secondary analyses, distortion estimates from RPG were used to assess spatial displacements of bone metastases. Lastly, changes in mutual information between DWI and T2-weighted images of bone metastases after distortion correction were calculated.
ResultsDistortion correction reduced anatomic error of vertebral DWI up to 29 mm. Error reductions were consistent across subjects (Wilcoxon signed-rank p<10-20). On average ({+/-}SD), participants largest error reduction was 11.8 mm ({+/-}3.6). Mean (95% CI) displacement of bone lesions was 6.0 mm (95% CI: 5.1-7.0); maximum displacement was 17.1 mm. Corrected diffusion images were more similar to structural MRI, as evidenced by consistent increases in mutual information (Wilcoxon signed-rank p<10-12).
DiscussionThese findings support the use of distortion correction techniques to improve localization of bone on DWI.
Key Points- Diffusion weighted images of bone tissue undergo substantial spatial distortions when acquired with echo-planar imaging.
- These distortions can be efficiently corrected with the reverse polarity gradient technique to generate diffusion images that more accurately reflect underlying anatomy.
- In the context of bone tumor imaging where precise localization may be required, distortion correction techniques, such as reverse polarity gradient, should be applied. | radiology and imaging |
10.1101/2020.11.22.20236547 | Correcting B0 inhomogeneity-induced distortions in whole-body diffusion MRI of bone | ObjectivesDiffusion-weighted magnetic resonance imaging (DWI) of the musculoskeletal system has various applications, including visualization of bone tumors. However, DWI acquired with echo-planar imaging is susceptible to distortions due to static magnetic field inhomogeneities. This study aimed to estimate spatial displacements of bone and to examine whether distortion corrected DWI images more accurately reflect underlying anatomy.
MethodsWhole-body MRI data from 127 prostate cancer patients were analyzed. The reverse polarity gradient (RPG) technique was applied to DWI data to estimate voxel-level distortions and to produce a distortion corrected DWI dataset. First, an anatomic landmark analysis was conducted, in which corresponding vertebral landmarks on DWI and anatomic T2-weighted images were annotated. Changes in distance between DWI- and T2-defined landmarks (i.e., changes in error) after distortion correction were calculated. In secondary analyses, distortion estimates from RPG were used to assess spatial displacements of bone metastases. Lastly, changes in mutual information between DWI and T2-weighted images of bone metastases after distortion correction were calculated.
ResultsDistortion correction reduced anatomic error of vertebral DWI up to 29 mm. Error reductions were consistent across subjects (Wilcoxon signed-rank p<10-20). On average ({+/-}SD), participants largest error reduction was 11.8 mm ({+/-}3.6). Mean (95% CI) displacement of bone lesions was 6.0 mm (95% CI: 5.1-7.0); maximum displacement was 17.1 mm. Corrected diffusion images were more similar to structural MRI, as evidenced by consistent increases in mutual information (Wilcoxon signed-rank p<10-12).
DiscussionThese findings support the use of distortion correction techniques to improve localization of bone on DWI.
Key Points- Diffusion weighted images of bone tissue undergo substantial spatial distortions when acquired with echo-planar imaging.
- These distortions can be efficiently corrected with the reverse polarity gradient technique to generate diffusion images that more accurately reflect underlying anatomy.
- In the context of bone tumor imaging where precise localization may be required, distortion correction techniques, such as reverse polarity gradient, should be applied. | radiology and imaging |
10.1101/2020.11.23.20237107 | Long-Term Downwind Exposure to Air Pollution from Power Plants and Adult Mortality: Evidence from COVID-19 | We estimate the causal effects of long-term exposure to air pollution emitted from fossil fuel power plants on adult mortality. We leverage quasi-experimental variation in daily wind patterns, which is further instrumented by the county orientation from the nearest power plant. We find that the countys fraction of days spent downwind of plants within 20 miles in the last 10 years is associated with increased mortality from COVID-19 through the third peak in mortality in January 2021. This effect is more pronounced in fenceline communities with high poverty rates, low health insurance coverage, and low educational attainment. | health economics |
10.1101/2020.11.22.20232959 | Use of Artificial Intelligence on spatio-temporal data to generate insights during COVID-19 pandemic: A Review | The COVID-19 pandemic, within a short time span, has had a significant impact on every aspect of life in almost every country on the planet. As it evolved from a local epidemic isolated to certain regions of China, to the deadliest pandemic since the influenza outbreak of 1918, scientists all over the world have only amplified their efforts to combat it. In that battle, Artificial Intelligence, or AI, with its wide ranging capabilities and versatility, has played a vital role and thus has had a sizable impact. In this review, we present a comprehensive analysis of the use of AI techniques for spatio-temporal modeling and forecasting and impact modeling on diverse populations as it relates to COVID-19. Furthermore, we catalogue the articles in these areas based on spatio-temporal modeling, intrinsic parameters, extrinsic parameters, dynamic parameters and multivariate inputs (to ascertain the penetration of AI usage in each sub area). The manner in which AI is used and the associated techniques utilized vary for each body of work. Majority of articles use deep learning models, compartment models, stochastic methods and numerous statistical methods. We conclude by listing potential paths of research for which AI based techniques can be used for greater impact in tackling the pandemic. | health informatics |
10.1101/2020.11.22.20232959 | Use of Artificial Intelligence on spatio-temporal data to generate insights during COVID-19 pandemic: A Review | The COVID-19 pandemic, within a short time span, has had a significant impact on every aspect of life in almost every country on the planet. As it evolved from a local epidemic isolated to certain regions of China, to the deadliest pandemic since the influenza outbreak of 1918, scientists all over the world have only amplified their efforts to combat it. In that battle, Artificial Intelligence, or AI, with its wide ranging capabilities and versatility, has played a vital role and thus has had a sizable impact. In this review, we present a comprehensive analysis of the use of AI techniques for spatio-temporal modeling and forecasting and impact modeling on diverse populations as it relates to COVID-19. Furthermore, we catalogue the articles in these areas based on spatio-temporal modeling, intrinsic parameters, extrinsic parameters, dynamic parameters and multivariate inputs (to ascertain the penetration of AI usage in each sub area). The manner in which AI is used and the associated techniques utilized vary for each body of work. Majority of articles use deep learning models, compartment models, stochastic methods and numerous statistical methods. We conclude by listing potential paths of research for which AI based techniques can be used for greater impact in tackling the pandemic. | health informatics |
10.1101/2020.11.22.20232959 | Use of Artificial Intelligence on spatio-temporal data to generate insights during COVID-19 pandemic: A Review | The COVID-19 pandemic, within a short time span, has had a significant impact on every aspect of life in almost every country on the planet. As it evolved from a local epidemic isolated to certain regions of China, to the deadliest pandemic since the influenza outbreak of 1918, scientists all over the world have only amplified their efforts to combat it. In that battle, Artificial Intelligence, or AI, with its wide ranging capabilities and versatility, has played a vital role and thus has had a sizable impact. In this review, we present a comprehensive analysis of the use of AI techniques for spatio-temporal modeling and forecasting and impact modeling on diverse populations as it relates to COVID-19. Furthermore, we catalogue the articles in these areas based on spatio-temporal modeling, intrinsic parameters, extrinsic parameters, dynamic parameters and multivariate inputs (to ascertain the penetration of AI usage in each sub area). The manner in which AI is used and the associated techniques utilized vary for each body of work. Majority of articles use deep learning models, compartment models, stochastic methods and numerous statistical methods. We conclude by listing potential paths of research for which AI based techniques can be used for greater impact in tackling the pandemic. | health informatics |
10.1101/2020.11.23.20236828 | HIV status alters disease severity and immune cell responses in beta variant SARS-CoV-2 infection wave | There are conflicting reports on the effects of HIV on COVID-19. Here we analyzed disease severity and immune cell changes during and after SARS-CoV-2 infection in 236 participants from South Africa, of which 39% were people living with HIV (PLWH), during the first and second ({beta} dominated) infection waves. The second wave had more PLWH requiring supplemental oxygen relative to HIV negative participants. Higher disease severity was associated with low CD4 T cell counts and higher neutrophil to lymphocyte ratios (NLR). Yet, CD4 counts recovered and NLR stabilized after SARS-CoV-2 clearance in wave 2 infected PLWH, arguing for an interaction between SARS-CoV-2 and HIV infection leading to low CD4 and high NLR. The first infection wave, where severity in HIV negative and PLWH was similar, still showed some HIV modulation of SARS-CoV-2 immune responses. Therefore, HIV infection can synergize with the SARS-CoV-2 variant to change COVID-19 outcomes. | hiv aids |
10.1101/2020.11.23.20237149 | Experimental efficacy of the face shield and the mask against emitted and potentially received particles | There is currently not sufficient evidence to support the effectiveness of face shields for source control. In order to evaluate the comparative barrier performance effect of face masks versus face shields, we used an aerosol generator and a particle counter to evaluate the performance of the various devices in comparable situations. We tested different configurations in an experimental setup with manikin heads wearing masks (surgical type I), face shields (22.5 cm high with overhang under the chin of 7 cm and circumference of 35 cm) on an emitter or a receiver manikin head, or both. The mannequins were face to face, 25 cm apart, with an intense particle emission (52.5 l/min) for 30 seconds. In our experimental conditions, when the receiver alone wore a protection, the face shield was more effective (reduction factor=54.8%), while reduction was lower with a mask (reduction factor=21.8%) (p=0.002). The wearing of a protective device by the emitter alone reduced the level of received particles by 96.8% for both the mask and face shield (p= NS). When both the emitter and receiver manikin heads wore a face shield, the ensuing double protection allowed for better results: 98% reduction for the face shields vs. 97.3% for the masks (p=0.01). Face shields offered an even better barrier effect than the mask against small inhaled particles (<0.3{micro}m - 0.3 to 0.5{micro}m - 0.5 to 1{micro}m) in all configurations. Therefore, it would be interesting to include face shields as used in our study as part of strategies to safely significantly reduce transmission within the community setting. | public and global health |
10.1101/2020.11.23.20237099 | Rapid Microscopic Fractional Anisotropy Imaging via an Optimized Kurtosis Formulation | Water diffusion anisotropy in the human brain is affected by disease, trauma, and development. Microscopic fractional anisotropy (FA) is a diffusion MRI (dMRI) metric that can quantify water diffusion anisotropy independent of neuron fiber orientation dispersion. However, there are several different techniques to estimate FA and few have demonstrated full brain imaging capabilities within clinically viable scan times and resolutions. Here, we present an optimized spherical tensor encoding (STE) technique to acquire FA directly from the 2nd order cumulant expansion of the dMRI signal (i.e. diffusion kurtosis) which requires fewer powder-averaged signals than other STE fitting techniques and can be rapidly computed. We found that the optimal dMRI parameters for white matter FA imaging were a maximum b-value of 2000 s/mm2 and a ratio of isotropic to linear tensor encoded acquisitions of 1.7 for our system specifications. We then compared two implementations of the direct approach to the well-established gamma model in 4 healthy volunteers on a 3 Tesla system. One implementation of the direct cumulant approach used mean diffusivity (D) obtained from a 2nd order fit of the cumulant expansion, while the other used a linear estimation of D from the low b-values. Both implementations of the direct approach showed strong linear correlations with the gamma model ({rho}=0.97 and {rho}=0.90) but mean biases of -0.11 and -0.02 relative to the gamma model were also observed, respectively. All three FA measurements showed good test-retest reliability ({rho}[≥]0.79 and bias=0). To demonstrate the potential scan time advantage of the direct approach, 2 mm isotropic resolution FA was demonstrated over a 10 cm slab using a subsampled data set with fewer powder-averaged signals that would correspond to a 3.3-minute scan. Accordingly, our results introduce an optimization procedure that has enabled clinically relevant, nearly full brain FA in only several minutes.
HighlightsO_LIDemonstrated method to acquire optimal parameters for regression FA imaging
C_LIO_LIFA measured using an optimized linear regression method at 3T
C_LIO_LIFirst FA comparison between direct regression approach and the gamma model
C_LIO_LIBoth approaches correlated strongly in white matter in healthy volunteers
C_LIO_LINearly full brain FA demonstrated in a 3.3-minute scan at 2 mm isotropic resolution
C_LI | neurology |
10.1101/2020.11.23.20236885 | Integrated Protein Network Analysis of Whole Exome Sequencing Study of Severe Preeclampsia | Preeclampsia is a hypertensive disorder of pregnancy, which complicates up to 15 % of US deliveries. It is an idiopathic disorder with complex disease genetics associated with several different phenotypes. We sought to determine if the genetic architecture of preeclampsia can be described by clusters of patients with variants in genes in shared protein interaction networks. We performed a case-control study using whole exome sequencing on early onset preeclamptic mothers with severe features and control mothers with uncomplicated pregnancies. The study was conducted at Women & Infants Hospital of Rhode Island (WIH). A total of 143 patients were enrolled, 61 women with early onset preeclampsia with severe features based on ACOG criteria, and 82 control women at term, matched for race and ethnicity. The main outcomes are variants associated with severe preeclampsia and demonstration of the genetic architecture of preeclampsia. A network analysis and visualization tool, Proteinarium, was used to confirm there are clusters of patients with shared gene networks associated with severe preeclampsia. The majority of the sequenced patients appear in two significant clusters. We identified one case dominant and one control dominant cluster. Thirteen genes were unique to the case dominated cluster. Among these genes, LAMB2, PTK2, RAC1, QSOX1, FN1, and VCAM1 have known associations with the pathogenic mechanisms of preeclampsia. Using the exome-wide sequence variants, combined with these 13 identified network genes, we generated a polygenetic risk score for severe preeclampsia with an AUC of 0.57. Using bioinformatic analysis, we were able to identify subsets of patients with shared protein interaction networks, thus confirming our hypothesis about the genetic architecture of preeclampsia. The unique genes identified in the cluster associated with severe preeclampsia were able to increase the predictive power of the polygenic risk score. | obstetrics and gynecology |
10.1101/2020.11.23.20235945 | Uncovering the important acoustic features for detecting vocal fold paralysis with explainable machine learning | ObjectiveTo detect unilateral vocal fold paralysis (UVFP) from voice recordings using an explainable model of machine learning.
Study DesignCase series - retrospective with a control group.
SettingTertiary care laryngology practice between 2009 to 2019.
MethodsPatients with confirmed UVFP through endoscopic examination (N=77) and controls with normal voices matched for age and sex (N=77) were included. Two tasks were used to elicit voice samples: reading the Rainbow Passage and sustaining phonation of the vowel "a". The 88 extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS) features were extracted as inputs for four machine learning models of differing complexity. SHAP was used to identify important features.
ResultsThe median bootstrapped Area Under the Receiver Operating Characteristic Curve (ROC AUC) score ranged from 0.79 to 0.87 depending on model and task. After removing redundant features for explainability, the highest median ROC AUC score was 0.84 using only 13 features for the vowel task and 0.87 using 39 features for the reading task. The most important features included intensity measures, mean MFCC1, mean F1 amplitude and frequency, and shimmer variability depending on model and task.
ConclusionUsing the largest dataset studying UVFP to date, we achieve high performance from just a few seconds of voice recordings. Notably, we demonstrate that while similar categories of features related to vocal fold physiology were conserved across models, the models used different combinations of features and still achieved similar effect sizes. Machine learning thus provides a mechanism to detect UVFP and contextualize the accuracy relative to both model architecture and pathophysiology. | otolaryngology |
10.1101/2020.11.23.20235945 | Uncovering the important acoustic features for detecting vocal fold paralysis with explainable machine learning | ObjectiveTo detect unilateral vocal fold paralysis (UVFP) from voice recordings using an explainable model of machine learning.
Study DesignCase series - retrospective with a control group.
SettingTertiary care laryngology practice between 2009 to 2019.
MethodsPatients with confirmed UVFP through endoscopic examination (N=77) and controls with normal voices matched for age and sex (N=77) were included. Two tasks were used to elicit voice samples: reading the Rainbow Passage and sustaining phonation of the vowel "a". The 88 extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS) features were extracted as inputs for four machine learning models of differing complexity. SHAP was used to identify important features.
ResultsThe median bootstrapped Area Under the Receiver Operating Characteristic Curve (ROC AUC) score ranged from 0.79 to 0.87 depending on model and task. After removing redundant features for explainability, the highest median ROC AUC score was 0.84 using only 13 features for the vowel task and 0.87 using 39 features for the reading task. The most important features included intensity measures, mean MFCC1, mean F1 amplitude and frequency, and shimmer variability depending on model and task.
ConclusionUsing the largest dataset studying UVFP to date, we achieve high performance from just a few seconds of voice recordings. Notably, we demonstrate that while similar categories of features related to vocal fold physiology were conserved across models, the models used different combinations of features and still achieved similar effect sizes. Machine learning thus provides a mechanism to detect UVFP and contextualize the accuracy relative to both model architecture and pathophysiology. | otolaryngology |
10.1101/2020.11.23.20237313 | Optimal symptom combinations to aid COVID-19 case identification: analysis from a community-based, prospective, observational cohort | ObjectivesDiagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health.
MethodsUK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity.
FindingsUK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC.
InterpretationWe confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings.
HighlightsO_LIWidely recommended symptoms identified only [~]70% COVID-19 cases
C_LIO_LIAdditional symptoms increased case finding to > 90% but tests needed doubled
C_LIO_LIOptimal symptom combinations maximise case capture considering available resources
C_LIO_LIImplications for COVID-19 vaccine efficacy trials and wider public health
C_LI | health informatics |
10.1101/2020.11.24.20235952 | Pro108Ser mutant of SARS-CoV-2 3CLpro reduces the enzymatic activity and ameliorates COVID-19 severity in Japan | SARS-CoV-2 genome accumulates point mutations constantly. However, whether non-synonymous mutations affect COVID-19 severity through altering viral protein function remains unknown. SARS-CoV-2 genome sequencing revealed that the number of non-synonymous mutations correlated inversely with COVID-19 severity in Tokyo Metropolitan area. Phylogenic tree analyses identified two predominant groups which were differentiated by a set of six-point mutations (four non-synonymous amino acid mutations). Among them, Pro108Ser in 3 chymotrypsin-like protease (3CLpro) and Pro151Leu in nucleocapsid protein occurred at conserved locations among {beta}-coronaviruses. Patients with these mutations (N = 48) indicated significantly lower odds ratio for developing hypoxia which required supplemental oxygen (odds ratio 0.24 [95% CI 0.07-0.88, p-value = 0.032]) after adjustments for age and sex, versus those lacking this haplotype in the canonical Clade 20B (N = 37). The Pro108Ser 3CLpro enzyme in vitro decreases in the activity by 58%, and the hydrogen/deuterium exchange mass spectrometry reveals that mechanisms for reduced activities involve structural perturbation at the substrate-binding region which is positioned behind and distant from the 108th amino acid residue of the enzyme. This mutant strain rapidly outcompeted pre-existing variants to become predominant in Japan. Our results may benefit the efforts underway to design small molecular compounds or antibodies targeting 3CLpro. | infectious diseases |
10.1101/2020.11.23.20236968 | Deciphering early-warning signals of the elimination and resurgence potential of SARS-CoV-2 from limited data at multiple scales | Inferring the transmission potential of an infectious disease during low-incidence periods following epidemic waves is crucial for preparedness. In such periods, scarce data may hinder existing inference methods, blurring early-warning signals essential for discriminating between the likelihoods of resurgence versus elimination. Advanced insight into whether elevating caseloads (requiring swift community-wide interventions) or local elimination (allowing controls to be relaxed or refocussed on case-importation) might occur, can separate decisive from ineffective policy. By generalising and fusing recent approaches, we propose a novel early-warning framework that maximises the information extracted from low-incidence data to robustly infer the chances of sustained local-transmission or elimination in real time, at any scale of investigation (assuming sufficiently good surveillance). Applying this framework, we decipher hidden disease-transmission signals in prolonged low-incidence COVID-19 data from New Zealand, Hong Kong and Victoria, Australia. We uncover how timely interventions associate with averting resurgent waves, support official elimination declarations and evidence the effectiveness of the rapid, adaptive COVID-19 responses employed in these regions. | infectious diseases |
10.1101/2020.11.23.20236968 | Deciphering early-warning signals of the elimination and resurgence potential of SARS-CoV-2 from limited data at multiple scales | Inferring the transmission potential of an infectious disease during low-incidence periods following epidemic waves is crucial for preparedness. In such periods, scarce data may hinder existing inference methods, blurring early-warning signals essential for discriminating between the likelihoods of resurgence versus elimination. Advanced insight into whether elevating caseloads (requiring swift community-wide interventions) or local elimination (allowing controls to be relaxed or refocussed on case-importation) might occur, can separate decisive from ineffective policy. By generalising and fusing recent approaches, we propose a novel early-warning framework that maximises the information extracted from low-incidence data to robustly infer the chances of sustained local-transmission or elimination in real time, at any scale of investigation (assuming sufficiently good surveillance). Applying this framework, we decipher hidden disease-transmission signals in prolonged low-incidence COVID-19 data from New Zealand, Hong Kong and Victoria, Australia. We uncover how timely interventions associate with averting resurgent waves, support official elimination declarations and evidence the effectiveness of the rapid, adaptive COVID-19 responses employed in these regions. | infectious diseases |
10.1101/2020.11.23.20236968 | Deciphering early-warning signals of the elimination and resurgence potential of SARS-CoV-2 from limited data at multiple scales | Inferring the transmission potential of an infectious disease during low-incidence periods following epidemic waves is crucial for preparedness. In such periods, scarce data may hinder existing inference methods, blurring early-warning signals essential for discriminating between the likelihoods of resurgence versus elimination. Advanced insight into whether elevating caseloads (requiring swift community-wide interventions) or local elimination (allowing controls to be relaxed or refocussed on case-importation) might occur, can separate decisive from ineffective policy. By generalising and fusing recent approaches, we propose a novel early-warning framework that maximises the information extracted from low-incidence data to robustly infer the chances of sustained local-transmission or elimination in real time, at any scale of investigation (assuming sufficiently good surveillance). Applying this framework, we decipher hidden disease-transmission signals in prolonged low-incidence COVID-19 data from New Zealand, Hong Kong and Victoria, Australia. We uncover how timely interventions associate with averting resurgent waves, support official elimination declarations and evidence the effectiveness of the rapid, adaptive COVID-19 responses employed in these regions. | infectious diseases |
10.1101/2020.11.23.20237487 | How closely is COVID-19 related to HCoV, SARS, and MERS? : Clinical comparison of coronavirus infections and identification of risk factors influencing the COVID-19 severity using common data model (CDM) | BackgroundSouth Korea was one of the epicenters for both the 2015 Middle East Respiratory Syndrome and 2019 COVID-19 outbreaks. However, there has been a lack of published literature, especially using the Electronic Medical Records (EMR), that provides a comparative summary of the prognostic factors present in the coronavirus-derived diseases. Therefore, in this study, we aimed to evaluate the distinct clinical traits between the infected patients of different coronaviruses to observe the extent of resemblance within the clinical features and to identify unique factors by disease severity that may influence the prognosis of COVID-19 patients.
MethodsWe utilized the common data model (CDM), which is the database that houses the standardized EMR. We set COVID-19 as a reference group in comparative analyses. For statistical methods, we used Levenes test, one-way Anova test, Scheffe post-hoc test, Games-howell post-hoc test, and Students t-test for continuous variables, and chi-squared test and Fishers exact test for categorical variables. With the variables that reflected similarity in more than two comparisons between the disease groups yet significantly different between the COVID-19 severity groups, we performed univariate logistic regression to identify which common manifestations in coronaviruses are risk factors for severe COVID-19 outcomes.
FindingsWe collected the records of 2840 COVID-19 patients, 67 MERS patients (several suspected cases included), 43 SARS suspected patients, and 87 HCoV patients. We found that a significantly higher number of COVID-19 patients had been diagnosed with comorbidities compared to the MERS and HCoV groups (48.5% vs. 10.4 %, p < 0.001 and 48.5% vs. 35.6%, p < 0.05) and also that the non-mild COVID-19 patients reported more comorbidities than the mild group (55.7% vs. 47.8%, p < 0.05). There were overall increases in the levels of fibrinogen in both sets of disease and severity groups. The univariate logistic regression showed that the male sex (OR: 1.66; CI: 1.29-2.13, p < 0.001), blood type A (OR: 1.80; CI: 1.40-2.31, p < 0.001), renal disease (OR: 3.27; CI: 2.34-4.55, p < 0.001), decreased creatinine level (OR: 2.05; CI: 1.45-2.88, p < 0.001), and elevated fibrinogen level (OR: 1.59, CI: 1.21-2.09, p < 0.001) are associated with the severe COVID-19 prognosis, whereas the patients reporting gastrointestinal symptoms (OR: 0.42; CI: 0.23-0.72, p < 0.01) and increased alkaline phosphatase (OR: 0.73; CI: 0.56-0.94, p < 0.05) are more less likely to experience complications and other severe outcomes from the SARS-CoV-2 infection.
InterpretationThe present study observed the highest resemblance between the COVID-19 and SARS groups as clinical manifestations that were present in SARS group were linked to the severity of COVID-19. In particular, male individuals with blood type A and previous diagnosis of kidney failure were shown to be more susceptible to developing the poorer outcomes during COVID-19 infection, with a presentation of elevated level of fibrinogen. | epidemiology |
10.1101/2020.11.23.20237487 | How closely is COVID-19 related to HCoV, SARS, and MERS? : Clinical comparison of coronavirus infections and identification of risk factors influencing the COVID-19 severity using common data model (CDM) | BackgroundSouth Korea was one of the epicenters for both the 2015 Middle East Respiratory Syndrome and 2019 COVID-19 outbreaks. However, there has been a lack of published literature, especially using the Electronic Medical Records (EMR), that provides a comparative summary of the prognostic factors present in the coronavirus-derived diseases. Therefore, in this study, we aimed to evaluate the distinct clinical traits between the infected patients of different coronaviruses to observe the extent of resemblance within the clinical features and to identify unique factors by disease severity that may influence the prognosis of COVID-19 patients.
MethodsWe utilized the common data model (CDM), which is the database that houses the standardized EMR. We set COVID-19 as a reference group in comparative analyses. For statistical methods, we used Levenes test, one-way Anova test, Scheffe post-hoc test, Games-howell post-hoc test, and Students t-test for continuous variables, and chi-squared test and Fishers exact test for categorical variables. With the variables that reflected similarity in more than two comparisons between the disease groups yet significantly different between the COVID-19 severity groups, we performed univariate logistic regression to identify which common manifestations in coronaviruses are risk factors for severe COVID-19 outcomes.
FindingsWe collected the records of 2840 COVID-19 patients, 67 MERS patients (several suspected cases included), 43 SARS suspected patients, and 87 HCoV patients. We found that a significantly higher number of COVID-19 patients had been diagnosed with comorbidities compared to the MERS and HCoV groups (48.5% vs. 10.4 %, p < 0.001 and 48.5% vs. 35.6%, p < 0.05) and also that the non-mild COVID-19 patients reported more comorbidities than the mild group (55.7% vs. 47.8%, p < 0.05). There were overall increases in the levels of fibrinogen in both sets of disease and severity groups. The univariate logistic regression showed that the male sex (OR: 1.66; CI: 1.29-2.13, p < 0.001), blood type A (OR: 1.80; CI: 1.40-2.31, p < 0.001), renal disease (OR: 3.27; CI: 2.34-4.55, p < 0.001), decreased creatinine level (OR: 2.05; CI: 1.45-2.88, p < 0.001), and elevated fibrinogen level (OR: 1.59, CI: 1.21-2.09, p < 0.001) are associated with the severe COVID-19 prognosis, whereas the patients reporting gastrointestinal symptoms (OR: 0.42; CI: 0.23-0.72, p < 0.01) and increased alkaline phosphatase (OR: 0.73; CI: 0.56-0.94, p < 0.05) are more less likely to experience complications and other severe outcomes from the SARS-CoV-2 infection.
InterpretationThe present study observed the highest resemblance between the COVID-19 and SARS groups as clinical manifestations that were present in SARS group were linked to the severity of COVID-19. In particular, male individuals with blood type A and previous diagnosis of kidney failure were shown to be more susceptible to developing the poorer outcomes during COVID-19 infection, with a presentation of elevated level of fibrinogen. | epidemiology |
10.1101/2020.11.25.20238386 | Explainable Machine Learning models for Rapid Risk Stratification in the Emergency Department: A multi-center study | BackgroundRisk stratification of patients presenting to the emergency department (ED) is important for appropriate triage. Diagnostic laboratory tests are an essential part of the work-up and risk stratification of these patients. Using machine learning, the prognostic power and clinical value of these tests can be amplified greatly. In this study, we applied machine learning to develop an accurate and explainable clinical decision support tool model that predicts the likelihood of 31-day mortality in ED patients (the RISKINDEX). This tool was developed and evaluated in four Dutch hospitals.
MethodsMachine learning models included patient characteristics and available laboratory data collected within the first two hours after ED presentation, and were trained using five years of data from consecutive ED patients from the Maastricht University Medical Centre+ (Maastricht), Meander Medical Center (Amersfoort), and Zuyderland (Sittard and Heerlen). A sixth year of data was used to evaluate the models using area-under-the-receiver-operating-characteristic curve (AUROC) and calibration curves. The SHapley Additive exPlanations (SHAP) algorithm was used to obtain explainable machine learning models.
ResultsThe present study included 266,327 patients with 7.1 million laboratory results available. Models show high diagnostic performance with AUROCs of 0.94,0.98,0.88, and 0.90 for Maastricht, Amersfoort, Sittard and Heerlen, respectively. The SHAP algorithm was utilized to visualize patient characteristics and laboratory data patterns that underlie individual RISKINDEX predictions.
ConclusionsOur clinical decision support tool has excellent diagnostic performance in predicting 31-day mortality in ED patients. Follow-up studies will assess whether implementation of these algorithm can improve clinically relevant endpoints. | emergency medicine |
10.1101/2020.11.25.20238220 | Genetic links in angioimmunoblastic T-cell lymphoma (AITL), clonal hematopoiesis and concomitant hematologic malignancies provide insights into the cell of origin, etiology and biomarker discovery for AITL | We generated and compared the mutation profiles through targeted sequencing of the primary tumors and matched bone marrow/peripheral blood samples in 25 patients with angioimmunoblastic T-cell lymphoma (AITL) and 2 with peripheral T-cell lymphoma, not otherwise specified (PTCL-NOS). Our results provided strong evidence that AITL/PTCL-NOS, clonal hematopoiesis (CH) as well as other concomitant myeloid and even B-cell hematologic neoplasms (CHN), frequently arose from common mutated hematopoietic stem cell clones. Aberrant AID/APOBEC activity-associated substitutions and tobacco smoking-associated substitutions were enriched in the early CH-associated mutations and late non-CH associated mutations during AITL/PTCL-NOS development, respectively. Moreover, survival analysis showed that the presence of CH harboring [≥] 2 pathogenic TET2 variants with [≥] 15% of allele burden conferred higher risk for CHN (P = 0.0034, hazard ratio = 10.81). These findings provide insights into the cell origin and etiology of AITL, and provide a novel stratification biomarker for CHN risk in AITL/PTCL-NOS patients. | oncology |
10.1101/2020.11.19.20234658 | Exploring Risks of Human Challenge Trials for COVID-19 | Human Challenge Trials (HCTs) are a potential method to accelerate development of vaccines and therapeutics. However, HCTs for COVID-19 pose ethical and practical challenges, in part due to the unclear and developing risks. In this paper, we introduce an interactive model for exploring some risks of a SARS-COV-2 dosing study, a prerequisite for any COVID-19 challenge trials. The risk estimates we use are based on a Bayesian evidence synthesis model which can incorporate new data on infection fatality risks (IFRs) to patients, and infer rates of hospitalization. The model estimates individual risk, which we then extrapolate to overall mortality and hospitalization risk in a dosing study. We provide a web tool to explore risk under different study designs.
Based on the Bayesian model, IFR for someone between 20 and 30 years of age is 15.1 in 100,000, with a 95% uncertainty interval from 11.8 to 19.2, while risk of hospitalization is 130 per 100,000 (100 to 160). However, risk will be reduced in an HCT via screening for comorbidities, selecting lower-risk population, and providing treatment. Accounting for this with stronger assumptions, we project the fatality risk to be as low as 2.5 per 100,000 (1.6 to 3.9) and the hospitalization risk to be 22.0 per 100,000 (14.0 to 33.7). We therefore find a 50-person dosing trial has a 99.74% (99.8% to 99.9%) chance of no fatalities, and a 98.9% (98.3% to 99.3%) probability of no cases requiring hospitalization. | infectious diseases |
10.1101/2020.11.24.20237354 | Highly Robust Prediction of Lung Nodule Malignancy by Deep Learning Model: A Multiracial, Multinational Study | The authors have withdrawn this manuscript because the authors have discovered errors in the methods and data analysis, which could alter the conclusions of the manuscript. 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. | oncology |
10.1101/2020.11.25.20234195 | Are we ready for COVID-19's Golden Passport? Insights from a Global Physician Survey | IntroductionCOVID-19 immunity passports could protect the right to free movement, but critics worry about insufficient evidence, privacy, fraud, and discrimination. We aimed to characterize the global physician communitys opinion regarding immunity passports.
MethodsCross sectional, random stratified sample of physicians registered with Sermo, a global networking platform open to verified and licensed physicians. The survey aimed to sample 1,000 physicians divided among the USA, EU and rest of the world. The survey question on immunology asked physicians to offer their insights into whether we know enough about COVID-19 immunity and its duration to offer immunity passports at the present time.
ResultsThe survey was completed by 1004 physicians (67 specialties, 40 countries, 49% frontline specialties) with a mean (SD) age of 49.14 (12) years. Overall, 52% answered NO, 17% were UNCERTAIN, and 31% answered YES (P <0.05). EU physicians were more likely to sayYES but even among them it did not exceed 35% approval. US physicians (60%) were more likely to say NO.
ConclusionOur findings suggest a current lack of support among physicians for immunity passports. It is hoped that ongoing research and vaccine trials will provide further clarity. | infectious diseases |
10.1101/2020.11.25.20234195 | Are we ready for COVID-19's Golden Passport? Insights from a Global Physician Survey | IntroductionCOVID-19 immunity passports could protect the right to free movement, but critics worry about insufficient evidence, privacy, fraud, and discrimination. We aimed to characterize the global physician communitys opinion regarding immunity passports.
MethodsCross sectional, random stratified sample of physicians registered with Sermo, a global networking platform open to verified and licensed physicians. The survey aimed to sample 1,000 physicians divided among the USA, EU and rest of the world. The survey question on immunology asked physicians to offer their insights into whether we know enough about COVID-19 immunity and its duration to offer immunity passports at the present time.
ResultsThe survey was completed by 1004 physicians (67 specialties, 40 countries, 49% frontline specialties) with a mean (SD) age of 49.14 (12) years. Overall, 52% answered NO, 17% were UNCERTAIN, and 31% answered YES (P <0.05). EU physicians were more likely to sayYES but even among them it did not exceed 35% approval. US physicians (60%) were more likely to say NO.
ConclusionOur findings suggest a current lack of support among physicians for immunity passports. It is hoped that ongoing research and vaccine trials will provide further clarity. | infectious diseases |
10.1101/2020.11.24.20237909 | Psychological distress among people with probable COVID-19 infection: analysis of the UK Household Longitudinal Study | Studies exploring the longer-term effects of experiencing COVID-19 infection on mental health are lacking. We explored the relationship between reporting probable COVID-19 symptoms in April 2020 and psychological distress (measured using the General Health Questionnaire) one, two, three, five and seven months later. Data were taken from the UK Household Longitudinal Study, a nationally representative household panel survey of UK adults. Elevated levels of psychological distress were found up to seven months after probable COVID-19, compared to participants with no likely infection. Associations were stronger among younger age groups and men. Further research into the psychological sequalae of COVID-19 is urgently needed. | public and global health |
10.1101/2020.11.24.20237990 | Multiday cycles of heart rate are associated with seizure likelihood | Circadian and multiday rhythms are found across many biological systems, including cardiology, endocrinology, neurology, and immunology. In people with epilepsy, epileptic brain activity and seizure occurrence have been found to follow circadian, weekly, and monthly rhythms. Understanding the relationship between these cycles of brain excitability and other physiological systems can provide new insight into the causes of multiday cycles. The brain-heart link is relevant for epilepsy, with implications for seizure forecasting, therapy, and mortality (i.e., sudden unexpected death in epilepsy).
We report the results from a non-interventional, observational cohort study, Tracking Seizure Cycles. This study sought to examine multiday cycles of heart rate and seizures in adults with diagnosed uncontrolled epilepsy (N=31) and healthy adult controls (N=15) using wearable smartwatches and mobile seizure diaries over at least four months (M=12.0, SD=5.9; control M=10.6, SD=6.4). Cycles in heart rate were detected using a continuous wavelet transform. Relationships between heart rate cycles and seizure occurrence were measured from the distributions of seizure likelihood with respect to underlying cycle phase.
Heart rate cycles were found in all 46 participants (people with epilepsy and healthy controls), with circadian (N=46), about-weekly (N=25) and about-monthly (N=13) rhythms being the most prevalent. Of the participants with epilepsy, 19 people had at least 20 reported seizures, and 10 of these had seizures significantly phase locked to their multiday heart rate cycles.
Heart rate cycles showed similarities to multiday epileptic rhythms and may be comodulated with seizure likelihood. The relationship between heart rate and seizures is relevant for epilepsy therapy, including seizure forecasting, and may also have implications for cardiovascular disease. More broadly, understanding the link between multiday cycles in the heart and brain can shed new light on endogenous physiological rhythms in humans. | neurology |
10.1101/2020.11.24.20238204 | The economic value of quarantine is higher at lower case prevalence, with quarantine justified at lower risk of infection | 1.Some infectious diseases, such as COVID-19, are so harmful that they justify broad scale social distancing. Targeted quarantine can reduce the amount of indiscriminate social distancing needed to control transmission. Finding the optimal balance between targeted vs. broad scale policies can be operationalized by minimizing the total amount of social isolation needed to achieve a target reproductive number. Optimality is achieved by quarantining on the basis of a risk threshold that depends strongly on current disease prevalence, suggesting that very different disease control policies should be used at different times or places. Aggressive quarantine is warranted given low disease prevalence, while populations with a higher base rate of infection should rely more on social distancing by all. The total value of a quarantine policy rises as case counts fall, is relatively insensitive to vaccination unless the vaccinated are exempt from distancing policies, and is substantially increased by the availability of modestly more information about individual risk of infectiousness. | health economics |
10.1101/2020.11.24.20238204 | The economic value of quarantine is higher at lower case prevalence, with quarantine justified at lower risk of infection | 1.Some infectious diseases, such as COVID-19, are so harmful that they justify broad scale social distancing. Targeted quarantine can reduce the amount of indiscriminate social distancing needed to control transmission. Finding the optimal balance between targeted vs. broad scale policies can be operationalized by minimizing the total amount of social isolation needed to achieve a target reproductive number. Optimality is achieved by quarantining on the basis of a risk threshold that depends strongly on current disease prevalence, suggesting that very different disease control policies should be used at different times or places. Aggressive quarantine is warranted given low disease prevalence, while populations with a higher base rate of infection should rely more on social distancing by all. The total value of a quarantine policy rises as case counts fall, is relatively insensitive to vaccination unless the vaccinated are exempt from distancing policies, and is substantially increased by the availability of modestly more information about individual risk of infectiousness. | health economics |
10.1101/2020.11.24.20238337 | Transition to multi-type mixing in d-dimensional spreading dynamics | The spreading dynamics of infectious diseases is determined by the interplay between geography and population mixing. There is homogeneous mixing at the local level and human mobility between distant populations. Here I model spatial location as a type and the population mixing by intra- and inter-type mixing patterns. Using the theory of multi-type branching process, I calculate the expected number of new infections as a function of time. In 1-dimension the analysis is reduced to the eigenvalue problem of a tridiagonal Teoplitz matrix. In d-dimensions I take advantage of the graph cartesian product to construct the eigenvalues and eigenvectors from the eigenvalue problem in 1-dimension. Using numerical simulations I uncover a transition from linear to multi-type mixing exponential growth with increasing the population size. Given that most countries are characterized by a network of cities with more than 100,000 habitants, I conclude that the multi-type mixing approximation should be the prevailing scenario. | infectious diseases |
10.1101/2020.11.24.20238055 | How Timing of Stay-home Orders and Mobility Reductions Impacted First-Wave COVID-19 Deaths in US Counties | As SARS-CoV-2 transmission continues to evolve, understanding how location-specific variations in non-pharmaceutical interventions and behaviors contributed to disease transmission during the initial epidemic wave will be key for future control strategies. We offer a rigorous statistical analysis of the relative effectiveness of the timing of both official stay-at-home orders and population mobility reductions during the initial stage of the US epidemic. We use a Bayesian hierarchical regression to fit county-level mortality data from the first case on Jan 21 2020 through Apr 20 2020 and quantify associations between the timing of stay-at-home orders and population mobility with epidemic control. We find that among 882 counties with an early local epidemic, a 10-day delay in the enactment of stay-at-home orders would have been associated with 14,700 additional deaths by Apr 20 (95% credible interval: 9,100, 21,500), whereas shifting orders 10 days earlier would have been associated with nearly 15,700 fewer lives lost (95% credible interval: 11,350, 18,950). Analogous estimates are available for reductions in mobility--which typically occurred before stay-at-home orders--and are also stratified by county urbanicity, showing significant heterogeneity. Results underscore the importance of timely policy and behavioral action for early-stage epidemic control. | infectious diseases |
10.1101/2020.11.24.20237651 | How local interactions impact the dynamics of an epidemic | Susceptible-Infected-Recovered (SIR) models have long formed the basis for exploring epidemiological dynamics in a range of contexts, including infectious disease spread in human populations. Classic SIR models take a mean-field assumption, such that a susceptible individual has an equal chance of catching the disease from any infected individual in the population. In reality, spatial and social structure will drive most instances of disease transmission. Here we explore the impacts of including spatial structure in a simple SIR model. We combine an approximate mathematical model (using a pair approximation) and stochastic simulations to consider the impact of increasingly local interactions on the epidemic. Our key development is to allow not just extremes of local (neighbour-to-neighbour) or global (random) transmission, but all points in between. We find that even medium degrees of local interactions produce epidemics highly similar to those with entirely global interactions, and only once interactions are predominantly local do epidemics become substantially lower and later. We also show how intervention strategies to impose local interactions on a population must be introduced early if significant impacts are to be seen. | epidemiology |
10.1101/2020.11.24.20238212 | Comprehensive Joint Modeling of First-Line Therapeutics in Non-Small Cell Lung Cancer | First-line antiproliferatives for non-small cell lung cancer (NSCLC) have a relatively high failure rate due to high intrinsic resistance rates and acquired resistance rates to therapy. 57% patients are diagnosed in late-stage disease due to the tendency of early-stage NSCLC to be asymptomatic. For patients first diagnosed with metastatic disease the 5-year survival rate is approximately 5%. To help accelerate the development of novel therapeutics and computer-based tools for optimizing individual therapy, we have collated data from 11 different clinical trials in NSCLC and developed a semi-mechanistic, clinical model of NSCLC growth and pharmacodynamics relative to the various therapeutics represented in the study. In this study, we have produced extremely precise estimates of clinical parameters fundamental to cancer modeling such as the rate of acquired resistance to various pharmaceuticals, the relationship between drug concentration and rate of cancer cell death, as well as the fine temporal dynamics of anti-VEGF therapy. In the simulation sets documented in this study, we have used the model to make meaningful descriptions of efficacy gain in making bevacizumab-antiproliferative combination therapy sequential, over a series of days, rather than concurrent. | oncology |
10.1101/2020.11.25.20238592 | Airway antibodies emerge according to COVID-19 severity and wane rapidly but reappear after SARS-CoV-2 vaccination | Understanding the presence and durability of antibodies against SARS-CoV-2 in the airways is required to provide insights on the ability of individuals to neutralize the virus locally and prevent viral spread. Here, we longitudinally assessed both systemic and airway immune responses upon SARS-CoV-2 infection in a clinically well-characterized cohort of 147 infected individuals representing the full spectrum of COVID-19 severity; from asymptomatic infection to fatal disease. In addition, we evaluated how SARS-CoV-2 vaccination influenced the antibody responses in a subset of these individuals during convalescence as compared to naive individuals. Not only systemic but also airway antibody responses correlated with the degree of COVID-19 disease severity. However, while systemic IgG levels were durable for up to 8 months, airway IgG and IgA had declined significantly within 3 months. After vaccination, there was an increase in both systemic and airway antibodies, in particular IgG, often exceeding the levels found during acute disease. In contrast, naive individuals showed low airway antibodies after vaccination. In the former COVID-19 patients, airway antibody levels were significantly elevated after the boost vaccination, highlighting the importance of prime and boost vaccination also for previously infected individuals to obtain optimal mucosal protection. | infectious diseases |
10.1101/2020.11.25.20238592 | Airway antibodies emerge according to COVID-19 severity and wane rapidly but reappear after SARS-CoV-2 vaccination | Understanding the presence and durability of antibodies against SARS-CoV-2 in the airways is required to provide insights on the ability of individuals to neutralize the virus locally and prevent viral spread. Here, we longitudinally assessed both systemic and airway immune responses upon SARS-CoV-2 infection in a clinically well-characterized cohort of 147 infected individuals representing the full spectrum of COVID-19 severity; from asymptomatic infection to fatal disease. In addition, we evaluated how SARS-CoV-2 vaccination influenced the antibody responses in a subset of these individuals during convalescence as compared to naive individuals. Not only systemic but also airway antibody responses correlated with the degree of COVID-19 disease severity. However, while systemic IgG levels were durable for up to 8 months, airway IgG and IgA had declined significantly within 3 months. After vaccination, there was an increase in both systemic and airway antibodies, in particular IgG, often exceeding the levels found during acute disease. In contrast, naive individuals showed low airway antibodies after vaccination. In the former COVID-19 patients, airway antibody levels were significantly elevated after the boost vaccination, highlighting the importance of prime and boost vaccination also for previously infected individuals to obtain optimal mucosal protection. | infectious diseases |
10.1101/2020.11.29.20240432 | Influencers of effective behavior change communication interventions delivered by community health workers in adults: A Scoping Review Protocol | IntroductionBehavior Change Communication (BCC) serves as a key pathway for delivery of messages for modifying risky behaviors such as unsafe sex, tobacco use, consumption of unhealthy diet and sedentary lifestyle. Behavior Change Communication has been successfully applied in various health conditions, settings and on different participants. In Low- and Middle-Income Countries (LMICs), the delivery of BCC is achieved through Community Health Workers (CHWs) due to limited availability of medical personnel. Current evidence indicates that delivering such interventions through CHWs is a promising approach to achieve desired behavior change and has potential to be upscaled. However, unavailability of information regarding the applicability of these interventions at different community settings, health conditions, and medium for intervention delivery, has made upscale and implementation a challenge. This scoping review will summarize the scope of settings, communication channels, and characteristics of message delivery protocols of behavior change communication interventions targeted at adults delivered via CHWs.
Methods and analysisThe scoping review methodology framework outlined by Arskey and OMalley will guide this review. We will search the following databases, MEDLINE, ERIC, JSTOR, ScienceDirect, using pre-defined search strategy. We will include studies published in English language, without any limits on the time of publication. Firstly, titles and abstracts will be screened, followed by full-length articles, for inclusion in the review. We will extract the data in a well-defined template developed for the purpose. All the reviewers will synthesize the evidence regarding and present the results using descriptive statistics and narrative.
Ethics and disseminationThis review is being conducted as a part of a doctoral thesis approved by the institutional ethics committee. The results of this scoping review will be disseminated in the form of peer-reviewed publication, and presented in conferences and will be used to design behavior change intervention to be introduced in community.
Strengths and limitationsO_LIThis will be the first scoping review to scale the community settings where behavior change communication interventions have been delivered.
C_LIO_LIThis review will also scale the characteristics of such interventions, viz, modality and medium of communication, and duration and periodicity of interventions.
C_LIO_LIThis review will only include articles published in English language across the named freely searchable databases.
C_LIO_LIAssessment of quality of the included studies is beyond the scope of this review and hence will not be carried out.
C_LI | public and global health |
10.1101/2020.11.26.20238469 | The association of smoking status with hospitalisation for COVID-19 compared with other respiratory viruses a year previous: A case-control study at a single UK National Health Service trust | BackgroundIt is unclear whether smoking increases the risk of COVID-19 hospitalisation. We examined i) the association of smoking status with hospitalisation for COVID-19 compared with hospitalisation for other respiratory viral infections a year previous; and ii) concordance between smoking status recorded on the electronic health record (EHR) and the contemporaneous medical notes.
MethodsThis case-control study enrolled adult patients (446 cases and 211 controls) at a single National Health Service trust in London, UK. The outcome variable was type of hospitalisation (COVID-19 vs. another respiratory virus a year previous). The exposure variable was smoking status (never/former/current smoker). Logistic regression analyses adjusted for age, sex, socioeconomic position and comorbidities were performed. The study protocol and analyses were pre-registered in April 2020 on the Open Science Framework.
ResultsCurrent smokers had lower odds of being hospitalised with COVID-19 compared with other respiratory viruses a year previous (ORadj=0.55, 95% CI=0.31-0.96, p=.04). There was no significant association among former smokers (ORadj=1.08, 95% CI=0.72-1.65, p=.70). Smoking status recorded on the EHR (compared with the contemporaneous medical notes) was incorrectly recorded for 168 (79.6%) controls ({chi}2(3)=256.5, p=<0.001) and 60 cases (13.5%) ({chi}2(3)=34.2, p=<0.001).
ConclusionsIn a single UK hospital trust, current smokers had reduced odds of being hospitalised with COVID-19 compared with other respiratory viruses a year previous, although it is unclear whether this association is causal. Targeted post-discharge recording of smoking status may account for the greater EHR- medical notes concordance observed in cases compared with controls. | infectious diseases |
10.1101/2020.11.29.20239962 | Estimating pulse wave velocity from the radial pressure wave using machine learning algorithms | One of the European gold standard measurement of vascular ageing, a risk factor for cardiovascular disease, is the carotid-femoral pulse wave velocity (cfPWV), which requires an experienced operator to measure pulse waves at two sites. In this work, two machine learning pipelines were proposed to estimate cfPWV from the peripheral pulse wave measured at a single site, the radial pressure wave measured by applanation tonometry. The study populations were the Twins UK cohort containing 3,082 subjects aged from 18 to 110 years, and a database containing 4,374 virtual subjects aged from 25 to 75 years. The first pipeline uses Gaussian process regression to estimate cfPWV from features extracted from the radial pressure wave using pulse wave analysis. The mean difference and upper and lower limits of agreement (LOA) of the estimation on the 924 hold-out test subjects from the Twins UK cohort were 0.2 m/s, and 3.75 m/s & -3.34 m/s, respectively. The second pipeline uses a recurrent neural network (RNN) to estimate cfPWV from the entire radial pressure wave. The mean difference and upper and lower LOA of the estimation on the 924 hold-out test subjects from the Twins UK cohort were 0.05 m/s, and 3.21 m/s & -3.11m/s, respectively. The percentage error of the RNN estimates on the virtual subjects increased by less than 2% when adding 20% of random noise to the pressure waveform. These results show the possibility of assessing the vascular ageing using a single peripheral pulse wave (e.g. the radial pressure wave), instead of cfPWV. The proposed code for the machine learning pipelines is available from the following online depository (https://github.com/WeiweiJin/Estimate-Cardiovascular-Risk-from-Pulse-Wave-Signal). | cardiovascular medicine |
10.1101/2020.11.29.20240481 | Are psychiatric disorders risk factors for COVID-19 susceptibility and severity? a two-sample, bidirectional, univariable and multivariable Mendelian Randomization study | Observational studies have suggested bidirectional associations between psychiatric disorders and COVID-19 phenotypes, but results of such studies are inconsistent. Mendelian Randomization (MR) may overcome limitations of observational studies, e.g. unmeasured confounding and uncertainties about cause and effect. We aimed to elucidate associations between neuropsychiatric disorders and COVID-19 susceptibility and severity. To that end, we applied a two-sample, bidirectional, univariable and multivariable MR design to genetic data from genome-wide association studies (GWASs) of neuropsychiatric disorders and COVID-19 phenotypes (released on 20 Oct. 2020). In single-variable Generalized Summary MR analysis the most significant and only Bonferroni-corrected significant result was found for genetic liability to BIP-SCZ (a combined GWAS of bipolar disorder and schizophrenia as cases vs. controls) increasing risk of COVID-19 (OR = 1.17, 95% CI, 1.06-1.28). However, we found a significant, positive genetic correlation between BIP-SCZ and COVID-19 of 0.295 and could not confirm causal or horizontally pleiotropic effects using another method. No genetic liabilities to COVID-19 phenotypes increased risk of (neuro)psychiatric disorders. In multivariable MR using both neuropsychiatric and a range of other phenotypes, only genetic instruments of BMI remained causally associated with COVID-19. All sensitivity analyses confirmed the results. In conclusion, while genetic liability to bipolar disorder and schizophrenia combined slightly increased COVID-19 susceptibility in one univariable analysis, other MR and multivariable analyses could only confirm genetic underpinnings of BMI to be causally implicated in COVID-19 susceptibility. Thus, using MR we found no consistent proof of genetic liabilities to (neuro)psychiatric disorders contributing to COVID-19 liability or vice versa, which is in line with at least two observational studies. Previously reported positive associations between psychiatric disorders and COVID-19 by others may have resulted from statistical models incompletely capturing BMI as a continuous covariate. | psychiatry and clinical psychology |
10.1101/2020.11.26.20236489 | The pathogenic p.(R391G) ABCC6 displays incomplete penetrance implying the necessity of an interacting partner for the development of pseudoxanthoma elasticum | ABCC6 promotes the efflux of ATP from hepatocytes to the bloodstream. ATP is then cleaved to AMP and pyrophosphate, a major inhibitor of ectopic calcification. Pathogenic variants of ABCC6 cause pseudoxanthoma elasticum, a recessive ectopic calcification disease of highly variable severity. One of the mechanisms influencing the heterogeneity of a disorder is the penetrance of pathogenic variants. Penetrance shows the proportion of carriers developing the phenotype; hence incomplete penetrance indicates that the disease does not necessarily develop in the presence of specific variants. Here, we investigated whether incomplete penetrance contributes to the heterogeneity of pseudoxanthoma elasticum. By integrating the clinical and genetic data of 589 patients, we created the largest European cohort. Based on allele frequencies compared to a reference cohort, we identified two incomplete penetrant variants, p.V787I and p.R391G, 6.5% and 2% penetrance, respectively. The characterization of the p.R391G variant suggested unaltered severity of the clinical phenotype. Based on our biochemical and localization studies, we hypothesize that the variant becomes deleterious only if an interacting partner is mutated simultaneously. Our data reveal the potential existence of the first interacting partner of ABCC6. Our data are also important for genetic counseling, as they suggest lower disease heritability of some variants. | genetic and genomic medicine |
10.1101/2020.11.26.20239152 | Altered Smell and Taste: anosmia, parosmia and the long impact of Covid-19 | BackgroundQualitative olfactory (smell) dysfunctions are a common side effect of post-viral illness and known to impact quality of life and health status. Evidence is emerging that taste and smell loss are common symptoms of Covid-19 that may emerge and persist long after initial infection. The aim of the present study was to document the impact of post Covid-19 alterations to taste and smell.
MethodsWe conducted exploratory thematic analysis of user-generated text from 9000 users of the AbScent Covid-19 Smell and Taste Loss moderated Facebook support group from March 24 to 30th September 2020.
ResultsParticipants reported difficulty explaining and managing an altered sense of taste and smell; a lack of interpersonal and professional explanation or support; altered eating; appetite loss, weight change; loss of pleasure in food, eating and social engagement; altered intimacy and an altered relationship to self and others.
ConclusionsOur findings suggest altered taste and smell with Covid-19 may lead to severe disruption to daily living that impacts on psychological well-being, physical health, relationships and sense of self. More specifically, participants reported impacts that related to reduced desire and ability to eat and prepare food; weight gain, weight loss and nutritional insufficiency; emotional wellbeing; professional practice; intimacy and social bonding; and the disruption of peoples sense of reality and themselves. Our findings should inform further research and suggest areas for the training, assessment and treatment practices of health care professionals working with long Covid. | infectious diseases |
10.1101/2020.11.26.20238923 | Altered anterior default mode network dynamics in progressive multiple sclerosis | BackgroundModifications in brain function remain relatively unexplored in progressive multiple sclerosis (PMS), despite their potential to provide new insights into the pathophysiology of this disease stage.
ObjectivesTo characterize the dynamics of functional networks at rest in patients with PMS, and the relation with clinical disability.
MethodsThirty-two patients with PMS underwent clinical and cognitive assessment. The dynamic properties of functional networks, retrieved from transient brain activity, were obtained from patients and 25 healthy controls (HC). Sixteen HC and 19 patients underwent a one-year follow-up clinical and imaging assessment. Differences in the dynamic metrics between groups, their longitudinal changes, and the correlation with clinical disability were explored.
ResultsPMS patients, compared to HC, showed a reduced dynamic functional activation of the anterior default mode network (aDMN) and its opposite-signed coactivation with the executive-control network, at baseline and follow-up. Processing speed and visuo-spatial memory negatively correlated to aDMN dynamic activity. The anti-coupling between aDMN and auditory/sensory-motor network, temporal-pole/amygdala or salience networks were differently associated to separate cognitive domains.
ConclusionPatients with PMS presented an altered aDMN functional recruitment and anti-correlation with ECN. The aDMN dynamic functional activity and interaction with other networks explained cognitive disability. | neurology |
10.1101/2020.11.26.20239509 | Auricular Vagus Neuromodulation - A Systematic Review on Quality of Evidence and Clinical Effects | This review is intended to identify key gaps in the mechanistic knowledge and execution of aVNS studies, to be addressed in future works, and aid the successful translation of neuromodulation therapies.
BackgroundThe auricular branch of the vagus nerve runs superficial to the surface of the skin, which makes it a favorable target for non-invasive stimulation techniques to modulate vagal activity. For this reason, there have been many early-stage clinical trials on a diverse range of conditions. These trials often report conflicting results for the same indication.
MethodsUsing the Cochrane Risk of Bias tool we conducted a systematic review of auricular vagus nerve stimulation (aVNS) randomized controlled trials (RCTs) to identify the factors that led to these conflicting results. As is common for early-stage studies, the majority of aVNS studies were assessed as having some or high risk of bias, which makes it difficult to interpret their results in a broader context.
ResultsThere is evidence of a modest decrease in heart rate during higher stimulation dosages, sometimes at above the level of sensory discomfort. Findings on heart rate variability conflict between studies and are hindered by trial design, including inappropriate washout periods, and multiple methods used to quantify heart rate variability. There is early-stage evidence to suggest aVNS may reduce circulating levels and endotoxin-induced levels of inflammatory markers. Studies on epilepsy reached primary endpoints similar to previous RCTs testing implantable vagus nerve stimulation (VNS) therapy, albeit with concerns over quality of blinding. Preliminary evidence shows that aVNS ameliorated pathological pain but not evoked pain.
DiscussionBased on results of the Cochrane analysis we list common improvements for the reporting of results, which can be implemented immediately to improve the quality of evidence. In the long term, existing data from aVNS studies and salient lessons from drug development highlight the need for direct measures of local neural target engagement. Direct measures of neural activity around the electrode will provide data for the optimization of electrode design, placement, and stimulation waveform parameters to improve on-target engagement and minimize off-target activation. Furthermore, direct measures of target engagement, along with consistent evaluation of blinding success, must be used to improve the design of controls in the long term - a major source of concern identified in the Cochrane analysis.
ConclusionThe need for direct measures of neural target engagement and consistent evaluation of blinding success is applicable to the development of other paresthesia-inducing neuromodulation therapies and their control designs. | neurology |
10.1101/2020.11.26.20239509 | Auricular Vagus Neuromodulation - A Systematic Review on Quality of Evidence and Clinical Effects | This review is intended to identify key gaps in the mechanistic knowledge and execution of aVNS studies, to be addressed in future works, and aid the successful translation of neuromodulation therapies.
BackgroundThe auricular branch of the vagus nerve runs superficial to the surface of the skin, which makes it a favorable target for non-invasive stimulation techniques to modulate vagal activity. For this reason, there have been many early-stage clinical trials on a diverse range of conditions. These trials often report conflicting results for the same indication.
MethodsUsing the Cochrane Risk of Bias tool we conducted a systematic review of auricular vagus nerve stimulation (aVNS) randomized controlled trials (RCTs) to identify the factors that led to these conflicting results. As is common for early-stage studies, the majority of aVNS studies were assessed as having some or high risk of bias, which makes it difficult to interpret their results in a broader context.
ResultsThere is evidence of a modest decrease in heart rate during higher stimulation dosages, sometimes at above the level of sensory discomfort. Findings on heart rate variability conflict between studies and are hindered by trial design, including inappropriate washout periods, and multiple methods used to quantify heart rate variability. There is early-stage evidence to suggest aVNS may reduce circulating levels and endotoxin-induced levels of inflammatory markers. Studies on epilepsy reached primary endpoints similar to previous RCTs testing implantable vagus nerve stimulation (VNS) therapy, albeit with concerns over quality of blinding. Preliminary evidence shows that aVNS ameliorated pathological pain but not evoked pain.
DiscussionBased on results of the Cochrane analysis we list common improvements for the reporting of results, which can be implemented immediately to improve the quality of evidence. In the long term, existing data from aVNS studies and salient lessons from drug development highlight the need for direct measures of local neural target engagement. Direct measures of neural activity around the electrode will provide data for the optimization of electrode design, placement, and stimulation waveform parameters to improve on-target engagement and minimize off-target activation. Furthermore, direct measures of target engagement, along with consistent evaluation of blinding success, must be used to improve the design of controls in the long term - a major source of concern identified in the Cochrane analysis.
ConclusionThe need for direct measures of neural target engagement and consistent evaluation of blinding success is applicable to the development of other paresthesia-inducing neuromodulation therapies and their control designs. | neurology |
10.1101/2020.11.26.20239368 | Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2 | The effective reproductive number Re is a key indicator of the growth of an epidemic. Since the start of the SARS-CoV-2 pandemic, many methods and online dashboards have sprung up to monitor this number through time. However, these methods are not always thoroughly tested, correctly placed in time, or are overly confident during high incidence periods. Here, we present a method for near real time estimation of Re, applied to epidemic data from 170 countries. We thoroughly evaluate the method on simulated data, and present an intuitive web interface for interactive data exploration. We show that in the majority of countries the estimated Re dropped below 1 only after the introduction of major non-pharmaceutical interventions. For Europe the implementation of non-pharmaceutical interventions was broadly associated with reductions in the estimated Re. Globally though, relaxing non-pharmaceutical interventions had more varied effects on subsequent Re estimates. Our framework is useful to inform governments and the general public on the status of the epidemic in their country, and is used as the official source of Re estimates in Switzerland. It further allows detailed comparison between countries and in relation to covariates such as implemented public health policies, mobility, behaviour, or weather data. | epidemiology |
10.1101/2020.11.26.20239368 | Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2 | The effective reproductive number Re is a key indicator of the growth of an epidemic. Since the start of the SARS-CoV-2 pandemic, many methods and online dashboards have sprung up to monitor this number through time. However, these methods are not always thoroughly tested, correctly placed in time, or are overly confident during high incidence periods. Here, we present a method for near real time estimation of Re, applied to epidemic data from 170 countries. We thoroughly evaluate the method on simulated data, and present an intuitive web interface for interactive data exploration. We show that in the majority of countries the estimated Re dropped below 1 only after the introduction of major non-pharmaceutical interventions. For Europe the implementation of non-pharmaceutical interventions was broadly associated with reductions in the estimated Re. Globally though, relaxing non-pharmaceutical interventions had more varied effects on subsequent Re estimates. Our framework is useful to inform governments and the general public on the status of the epidemic in their country, and is used as the official source of Re estimates in Switzerland. It further allows detailed comparison between countries and in relation to covariates such as implemented public health policies, mobility, behaviour, or weather data. | epidemiology |
10.1101/2020.11.27.20240002 | Comparative Genomic Study for Revealing the Complete Scenario of COVID-19 Pandemic in Bangladesh | As the COVID-19 pandemic continues to ravage across the globe and take millions of lives and like many parts of the world, the second wave of the pandemic hit Bangladesh, this study aimed at understanding its causative agent, SARS-CoV-2 at the genomic and proteomic level and provide precious insights about the pathogenesis, evolution, strengths and weaknesses of the virus. As of Mid-June 2021, over 1500 SARS-CoV-2 genomes have been sequenced across the country. From our analyses, it was discovered that the wave-2 samples had a significantly greater average rate of mutation/sample (30.79%) than the wave-1 samples (12.32%). Wave-2 samples also had a higher frequency of deletion, and transversion events. During the first wave, the GR clade was the most predominant but it was replaced by the GH clade in the latter wave. The B.1.1.25 variant showed the highest frequency in wave-1 while in case of wave-2, the B.1.351.3 variant, was the most common one. A notable presence of the delta variant, which is currently at the center of concern, was also observed. Comparison of the Spike protein found in the reference and the 3 most common lineages found in Bangladesh namely, B.1.1.7, B.1.351, B.1.617 in terms of their ability to form stable complexes with ACE2 receptor revealed that B.1.617 had the potential to be more transmissible than others. Importantly, no indigenous variants have been detected so far which implies that the successful prevention of import of foreign variants can diminish the outbreak in the country. | infectious diseases |
10.1101/2020.11.27.20234997 | A Randomized trial on the regular use of potent mouthwash in COVID-19 treatment | 1.In this work we tried to study the effect of the regular use of potent mouthwash in COVID19 cases, on the premise that it may speedup the recovery, through the repeated reduction of microbial load, of both, the 2019-nCOV and oral microbiota; thus slowing the disease progression and lowering the incidence of superinfections.
Through a randomized controlled trial, a mixed solution of Hydrogen peroxide 2% and chlorhexidine gluconate, to be used for oral rinsing and gargling three times daily, was tested in cases admitted to COVID treatment facility, versus the standard (only) COVID19-treatment protocol, starting with 46 cases in each group, matched in terms of disease severity, of symptoms, and average cycle threshold value (CT-value) for the COVID PCR test on diagnosis.
Our findings showed statistically significant improvement in terms of a higher conversion rate to "COVID19-negative PCR" by five days of treatment (6/46 Vs 0/46), improvement in "symptoms severity" after two days of treatment, and less intubation and mortality (0/46 Vs 3/46) with all P-value < 0.05. There was also a trend of improvement in other outcome variables, though with no statistically significant difference; namely "shorter hospital stays," "less progression in Oxygen requirements", "less rate of plasma transfusion", and better "gross extent of improvement".
Our findings support a beneficial role in treating active cases (Disease) and anticipates better outcome should implemented earlier in course of the disease; thus, suggest a role in limiting the spread (Pandemic), as an additional preventive method. Additionally, we think the repeated reduction in the microbial load might have been sufficient to induce a strain in a possible viral-microbial interaction, resulting in slowing down of the disease progress. | infectious diseases |
10.1101/2020.11.27.20237966 | Predicting critical illness on initial diagnosis of COVID-19 based on easily-obtained clinical variables: Development and validation of the PRIORITY model | ObjectivesCurrently available COVID-19 prognostic models have focused on laboratory and radiological data obtained following admission. However, these tests are not available on initial assessment or in resource-limited settings. We aim to develop and validate a prediction model, based on clinical history and examination findings on initial diagnosis of COVID-19, to identify patients at risk of critical outcomes.
MethodsWe used data from the SEMI-COVID-19 Registry, a nationwide multicenter cohort of consecutive patients hospitalized for COVID-19 from 132 centers in Spain. Clinical signs and symptoms, demographic variables, and medical history ascertained at hospital admission were screened using Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression to construct a predictive model. We externally validated the final model in a separate cohort of patients admitted at less-complex hospitals (< 300 beds).We undertook decision curve analysis to assess the clinical usefulness of the predictive model. The primary outcome was a composite of in-hospital death, mechanical ventilation or admission to intensive care unit.
ResultsThere were 10,433 patients, 7,850 (primary outcome 25.1%) in the development cohort and 2,583 (primary outcome 27.0%) in the validation cohort. Variables in the final model included: age, cardiovascular disease, chronic kidney disease, dyspnea, tachypnea, confusion, systolic blood pressure, and SpO2[≤]93% or oxygen requirement.The C-statistic in the development cohort was 0.823 (95% CI,0.813-0.834). On external validation, the C-statistic was 0.792 (95% CI,0.772-0.812). The model showed a positive net benefit for threshold probabilities between 3% and 79%.
ConclusionsAmong patients presenting with COVID-19, the model based on easily-obtained clinical information had good discrimination and generalizability for identifying patients at risk of critical outcomes without the need of additional testing. The online calculator provided would facilitate triage of patients during the pandemic. This study could provide a useful tool for decision-making in health systems under pandemic pressure and resource-limited settings. | infectious diseases |
10.1101/2020.11.27.20240051 | The impact of vaccination on COVID-19 outbreaks in the United States | BackgroundGlobal vaccine development efforts have been accelerated in response to the devastating COVID-19 pandemic. We evaluated the impact of a 2-dose COVID-19 vaccination campaign on reducing incidence, hospitalizations, and deaths in the United States (US).
MethodsWe developed an agent-based model of SARS-CoV-2 transmission and parameterized it with US demographics and age-specific COVID-19 outcomes. Healthcare workers and high-risk individuals were prioritized for vaccination, while children under 18 years of age were not vaccinated. We considered a vaccine efficacy of 95% against disease following 2 doses administered 21 days apart achieving 40% vaccine coverage of the overall population within 284 days. We varied vaccine efficacy against infection, and specified 10% pre-existing population immunity for the base-case scenario. The model was calibrated to an effective reproduction number of 1.2, accounting for current non-pharmaceutical interventions in the US.
ResultsVaccination reduced the overall attack rate to 4.6% (95% CrI: 4.3% - 5.0%) from 9.0% (95% CrI: 8.4% - 9.4%) without vaccination, over 300 days. The highest relative reduction (54-62%) was observed among individuals aged 65 and older. Vaccination markedly reduced adverse outcomes, with non-ICU hospitalizations, ICU hospitalizations, and deaths decreasing by 63.5% (95% CrI: 60.3% - 66.7%), 65.6% (95% CrI: 62.2% - 68.6%), and 69.3% (95% CrI: 65.5% - 73.1%), respectively, across the same period.
ConclusionsOur results indicate that vaccination can have a substantial impact on mitigating COVID-19 outbreaks, even with limited protection against infection. However, continued compliance with non-pharmaceutical interventions is essential to achieve this impact.
Key pointsVaccination with a 95% efficacy against disease could substantially mitigate future attack rates, hospitalizations, and deaths, even if only adults are vaccinated. Non-pharmaceutical interventions remain an important part of outbreak response as vaccines are distributed over time. | epidemiology |
10.1101/2020.11.28.20240259 | Forecasting COVID-19 cases: A comparative analysis between Recurrent and Convolutional Neural Networks | When the entire world is waiting restlessly for a safe and effective COVID-19 vaccine that could soon become a reality, numerous countries around the globe are grappling with unprecedented surges of new COVID-19 cases. As the number of new cases is skyrocketing, pandemic fatigue and public apathy towards different intervention strategies are posing new challenges to the government officials to combat the pandemic. Henceforth, it is indispensable for the government officials to understand the future dynamics of COVID-19 flawlessly in order to develop strategic preparedness and resilient response planning. In light of the above circumstances, probable future outbreak scenarios in Brazil, Russia and the United kingdom have been sketched in this study with the help of four deep learning models: long short term memory (LSTM), gated recurrent unit (GRU), convolutional neural network (CNN) and multivariate convolutional neural network (MCNN). In our analysis, CNN algorithm has outperformed other deep learning models in terms of validation accuracy and forecasting consistency. It has been unearthed in our study that CNN can provide robust long term forecasting results in time series analysis due to its capability of essential features learning, distortion invariance and temporal dependence learning. However, the prediction accuracy of LSTM algorithm has been found to be poor as it tries to discover seasonality and periodic intervals from any time series dataset, which were absent in our studied countries. Our study has highlighted the promising validation of using convolutional neural networks instead of recurrent neural networks when it comes to forecasting with very few features and less amount of historical data. | epidemiology |
10.1101/2020.11.28.20240366 | Second versus first wave of COVID-19 deaths: shifts in age distribution and in nursing home fatalities | OBJECTIVETo examine whether the age distribution of COVID-19 deaths and the share of deaths in nursing homes changed in the second versus the first pandemic wave.
ELIGIBLE DATAWe considered all countries that had at least 4000 COVID-19 deaths occurring as of January 14, 2020, at least 200 COVID-19 deaths occurring in each of the two epidemic wave periods; and which had sufficiently detailed information available on the age distribution of these deaths. We also considered countries with data available on COVID-19 deaths of nursing home residents for the two waves.
MAIN OUTCOME MEASURESChange in the second wave versus the first wave in the proportion of COVID-19 deaths occurring in people <50 years ("young deaths") among all COVID-19 deaths and among COVID-19 deaths in people <70 years old; and change in the proportion of COVID-19 deaths in nursing home residents among all COVID-19 deaths.
RESULTSData on age distribution were available for 14 eligible countries. Individuals <50 years old had small absolute difference in their share of the total COVID-19 deaths in the two waves across 13 high-income countries (absolute differences 0.0-0.4%). Their proportion was higher in Ukraine, but it decreased markedly in the second wave. The odds of young deaths was lower in the second versus the first wave (summary odds ratio 0.80, 95% CI 0.70-0.92) with large between-country heterogeneity. The odds of young deaths among deaths <70 years did not differ significantly across the two waves (summary odds ratio 0.95, 95% CI 0.85-1.07). Eligible data on nursing home COVID-19 deaths were available for 11 countries. The share of COVID-19 deaths that were accounted by nursing home residents decreased in the second wave significantly and substantially in 8 countries (odds ratio estimates: 0.22 to 0.66), remained the same in Denmark and Norway and markedly increased in Australia.
CONCLUSIONSIn the examined countries, age distribution of COVID-19 deaths has been fairly similar in the second versus the first wave, but the contribution of COVID-19 deaths in nursing home residents to total fatalities has decreased in most countries in the second wave. | public and global health |
10.1101/2020.11.28.20240358 | Prevalence, Patterns and Predictors of physical activity in Urban Population of Bhubaneswar smart city, India | BackgroundPhysical inactivity is a risk factor for mortality and morbidity. Physical activity and its predictors among urban population in this part of the country was unknown. Finding physical inactivity as a cause of current noncommunicable diseases (NCD) is difficult.
ObjectivesTo find out the prevalence, patterns and predictors of physical activity in urban population, and investigate its causal relationship with NCD.
Materials and methodsIt was a cross-sectional study using cluster random sampling. Sample size was 1203. Socio-demographic, health profile, physical activity levels, and stage of change for physical activity behaviour were collected. was used for analysis. Logistic regression and marginal structural model analysis (by IPTW) were done using IBM SPSS 20.0.Statistical significance were tested at p=0.05.
Results1221 subjects participated. Mean age was 35.25 years. 71.9% were physically inactive, 15.9% practised yogasana. General caste, presence of NCD, being in a static stage of change and a yogassana practitioner influenced physical activity positively. Physical inactivity had 1.54 times higher odds for NCD and was statistically significant.
ConclusionPrevalence of physical activity was low. Physical inactivity was a causative factor for NCD. | public and global health |
10.1101/2020.11.28.20240333 | Measuring Voluntary Responses in Healthcare Utilization During and After COVID-19 Pandemic: Evidence from Taiwan | Healthcare has been one of the most affected sectors during the coronavirus disease 2019 (COVID-19) pandemic. The utilization of related services for non-COVID-19 diseases fell dramatically following the point at which the virus broke out; however, little is known about whether this observed decline in healthcare use was due to voluntary behaviors or enforced measures. This paper quantifies the spontaneous change in healthcare utilization during the pandemic. We utilize a county-by-week-level dataset from Taiwans National Health Insurance (NHI) record, covering the entire Taiwanese population, and a difference-in-differences design. Our results indicate that even if there were no human mobility restrictions or supply-side constraints, people voluntarily reduced their demand for healthcare, due to fears of contagion, or COVID-related precautionary behaviors. We find that the number of outpatient visits (inpatient admissions) decreased by 21% (11%) during the pandemic period (February to May 2020). Furthermore, the demand response of healthcare for Influenza-like illness (ILI) was much greater and more persistent than for non-ILI, thereby suggesting that the substantial decline in accessing healthcare was induced by positive public health externality of prevention measures for COVID-19. Finally, we find that the demand for healthcare services did not get back to the pre-pandemic baseline, even when there were no local coronavirus cases for 253 consecutive days (mid-April to December 2020) in Taiwan. | public and global health |
10.1101/2020.11.28.20240333 | Measuring Voluntary Responses in Healthcare Utilization During and After COVID-19 Pandemic: Evidence from Taiwan | Healthcare has been one of the most affected sectors during the coronavirus disease 2019 (COVID-19) pandemic. The utilization of related services for non-COVID-19 diseases fell dramatically following the point at which the virus broke out; however, little is known about whether this observed decline in healthcare use was due to voluntary behaviors or enforced measures. This paper quantifies the spontaneous change in healthcare utilization during the pandemic. We utilize a county-by-week-level dataset from Taiwans National Health Insurance (NHI) record, covering the entire Taiwanese population, and a difference-in-differences design. Our results indicate that even if there were no human mobility restrictions or supply-side constraints, people voluntarily reduced their demand for healthcare, due to fears of contagion, or COVID-related precautionary behaviors. We find that the number of outpatient visits (inpatient admissions) decreased by 21% (11%) during the pandemic period (February to May 2020). Furthermore, the demand response of healthcare for Influenza-like illness (ILI) was much greater and more persistent than for non-ILI, thereby suggesting that the substantial decline in accessing healthcare was induced by positive public health externality of prevention measures for COVID-19. Finally, we find that the demand for healthcare services did not get back to the pre-pandemic baseline, even when there were no local coronavirus cases for 253 consecutive days (mid-April to December 2020) in Taiwan. | public and global health |
10.1101/2020.11.28.20240333 | Measuring Voluntary Responses in Healthcare Utilization During the COVID-19 Pandemic: Evidence from Taiwan | Healthcare has been one of the most affected sectors during the coronavirus disease 2019 (COVID-19) pandemic. The utilization of related services for non-COVID-19 diseases fell dramatically following the point at which the virus broke out; however, little is known about whether this observed decline in healthcare use was due to voluntary behaviors or enforced measures. This paper quantifies the spontaneous change in healthcare utilization during the pandemic. We utilize a county-by-week-level dataset from Taiwans National Health Insurance (NHI) record, covering the entire Taiwanese population, and a difference-in-differences design. Our results indicate that even if there were no human mobility restrictions or supply-side constraints, people voluntarily reduced their demand for healthcare, due to fears of contagion, or COVID-related precautionary behaviors. We find that the number of outpatient visits (inpatient admissions) decreased by 21% (11%) during the pandemic period (February to May 2020). Furthermore, the demand response of healthcare for Influenza-like illness (ILI) was much greater and more persistent than for non-ILI, thereby suggesting that the substantial decline in accessing healthcare was induced by positive public health externality of prevention measures for COVID-19. Finally, we find that the demand for healthcare services did not get back to the pre-pandemic baseline, even when there were no local coronavirus cases for 253 consecutive days (mid-April to December 2020) in Taiwan. | public and global health |
10.1101/2020.11.28.20240242 | On the anti-correlation between COVID-19 infection rate and natural UV light in the UK | While it is well established that the rate of COVID-19 infections can be suppressed by social distancing, environmental effects may also affect it. We consider the hypothesis that natural Ultra-Violet (UV) light is reducing COVID-19 infections by enhancing human immunity through increasing levels of Vitamin-D and Nitric Oxide or by suppressing the virus itself. We focus on the United Kingdom (UK), by examining daily COVID-19 infections (F) and UV Index (UVI) data from 23 March 2020 to 10 March 2021. We find an intriguing empirical anti-correlation between log10(F) and log10(UVI) with a correlation coefficient of -0.934 from 11 May 2020 (when the first UK lockdown ended) to 10 March 2021. The anti-correlation may reflect causation with other factors which are correlated with the UVI. We advocate that UVI should be added as a parameter in modelling the pattern of COVID-19 infections and deaths. We started quantifying such correlations in other countries and regions. | public and global health |
10.1101/2020.11.28.20240176 | 3D printed biomimetic cochleae and machine learning co-modelling provides clinical informatics for cochlear implant patients | Cochlear implants (CIs) restore hearing in patients with severe to profound deafness by delivering electrical stimuli inside the cochlea. Understanding CI stimulus spread, and how it correlates to patient-dependent factors, is hampered by the poor accessibility of the inner ear and by the lack of suitable in vitro, in vivo or in silico models. Here, we present 3D printing-neural network co-modelling for interpreting clinical electric field imaging (EFI) profiles of CI patients. With tuneable electro-anatomy, the 3D printed cochleae were shown to replicate clinical scenarios of EFI profiles at the off-stimuli positions. The co-modelling framework demonstrated autonomous and robust predictions of patient EFI or cochlear geometry, unfolded the electro-anatomical factors causing CI stimulus spread, assisted on-demand printing for CI testing, and inferred patients in vivo cochlear tissue resistivity (estimated mean = 6.6 k{Omega}cm) by CI telemetry. We anticipate our framework will facilitate physical modelling and digital twin innovations for electrical prostheses in healthcare. | otolaryngology |
10.1101/2020.11.30.20239954 | 'When will this end? Will it end?' The impact of the March-June 2020 UK Covid-19 lockdown response on mental health: a longitudinal survey of mothers in the Born in Bradford study. | ObjectivesTo explore clinically important increases in depression/anxiety from before to during the first UK Covid-19 lockdown and factors related to this change, with a particular focus on ethnic differences.
DesignPre-Covid-19 and lockdown surveys nested within two longitudinal Born in Bradford cohort studies.
Participants1,860 mothers with a child aged 0-5 or 9-13, 48% Pakistani heritage
Main outcome measuresOdds ratios (OR) for a clinically important increase (5 points or more) in depression (PHQ-8) and anxiety (GAD-7) in unadjusted regression analyses, repeated with exposures of interest separated by ethnicity to look for differences in magnitude of associations, and lived experience of mothers captured in open text questions.
ResultsThe number of women reporting clinically important depression/anxiety increased from 11% to 20% [10-13%;18-22%] and 10% to 16% [8-11%; 15-18%]) respectively. Increases in depression/anxiety were associated with: loneliness (OR: 8.37, [5.70-12.27]; 8.50, [5.71-12.65] respectively); financial (6.23, [3.96-9.80]; 6.03, [3.82-9.51]); food (3.33 [2.09-5.28]; 3.46 [2.15-5.58]); and housing insecurity (3.29 [2.36-4.58]; 3.0 [2.11-4.25]); a lack of physical activity (3.13 [2.15-4.56]; 2.55 [1.72-3.78]); and a poor partner relationship (3.6 [2.44-5.43]; 5.1 [3.37-7.62]. The magnitude of associations between key exposures and worsening mental health varied between ethnic groups.
Responses to open text questions illustrated a complex inter-play of challenges contributing to mental ill health including: acute health anxieties; the mental load of managing multiple responsibilities; loss of social support and coping strategies; pressures of financial and employment insecurity; and being unable to switch off from the pandemic.
ConclusionsMental ill health has worsened for many during the Covid-19 lockdown, particularly in those who are lonely and economically insecure. The magnitude of associations between key exposures and worsening mental health varied between ethnic groups. Mental health problems may have longer term consequences for public health and interventions that address the potential causes are needed.
STRENGTHS AND LIMITATIONS OF THIS STUDYO_LIThree key longitudinal studies have highlighted that the Covid-19 pandemic and lockdowns have had a negative impact on mental health, particular in younger adults, women and those from low socio-economic circumstances, but with participants of predominantly White European ethnicity.
C_LIO_LIThe Born in Bradford research programme offers a unique opportunity to investigate the impact of Covid-19 lockdown on mental health in a deprived and ethnically diverse population in whom mental ill health is often reported to be more prevalent.
C_LIO_LIThis is a longitudinal study containing linked data collected before the Covid-19 pandemic and during the March-June 2020 lockdown which has allowed us to explore change over that time period in a highly ethnically diverse population, the majority of whom live in the most deprived centiles in the UK.
C_LIO_LIRespondents in this study were mothers of children aged 0-5 and/or 9-13 which may limit the wider generalisability, though our findings are broadly similar (in prevalence and associations) to those from another longitudinal study that included adult men and women.
C_LIO_LIWe are not aware of other studies that have explored longitudinal change in mental health from before to during the Covid-19 lockdown in a similar ethnically diverse and deprived population.
C_LI | public and global health |
10.1101/2020.11.30.20239954 | 'When will this end? Will it end?' The impact of the March-June 2020 UK Covid-19 lockdown response on mental health: a longitudinal survey of mothers in the Born in Bradford study. | ObjectivesTo explore clinically important increases in depression/anxiety from before to during the first UK Covid-19 lockdown and factors related to this change, with a particular focus on ethnic differences.
DesignPre-Covid-19 and lockdown surveys nested within two longitudinal Born in Bradford cohort studies.
Participants1,860 mothers with a child aged 0-5 or 9-13, 48% Pakistani heritage
Main outcome measuresOdds ratios (OR) for a clinically important increase (5 points or more) in depression (PHQ-8) and anxiety (GAD-7) in unadjusted regression analyses, repeated with exposures of interest separated by ethnicity to look for differences in magnitude of associations, and lived experience of mothers captured in open text questions.
ResultsThe number of women reporting clinically important depression/anxiety increased from 11% to 20% [10-13%;18-22%] and 10% to 16% [8-11%; 15-18%]) respectively. Increases in depression/anxiety were associated with: loneliness (OR: 8.37, [5.70-12.27]; 8.50, [5.71-12.65] respectively); financial (6.23, [3.96-9.80]; 6.03, [3.82-9.51]); food (3.33 [2.09-5.28]; 3.46 [2.15-5.58]); and housing insecurity (3.29 [2.36-4.58]; 3.0 [2.11-4.25]); a lack of physical activity (3.13 [2.15-4.56]; 2.55 [1.72-3.78]); and a poor partner relationship (3.6 [2.44-5.43]; 5.1 [3.37-7.62]. The magnitude of associations between key exposures and worsening mental health varied between ethnic groups.
Responses to open text questions illustrated a complex inter-play of challenges contributing to mental ill health including: acute health anxieties; the mental load of managing multiple responsibilities; loss of social support and coping strategies; pressures of financial and employment insecurity; and being unable to switch off from the pandemic.
ConclusionsMental ill health has worsened for many during the Covid-19 lockdown, particularly in those who are lonely and economically insecure. The magnitude of associations between key exposures and worsening mental health varied between ethnic groups. Mental health problems may have longer term consequences for public health and interventions that address the potential causes are needed.
STRENGTHS AND LIMITATIONS OF THIS STUDYO_LIThree key longitudinal studies have highlighted that the Covid-19 pandemic and lockdowns have had a negative impact on mental health, particular in younger adults, women and those from low socio-economic circumstances, but with participants of predominantly White European ethnicity.
C_LIO_LIThe Born in Bradford research programme offers a unique opportunity to investigate the impact of Covid-19 lockdown on mental health in a deprived and ethnically diverse population in whom mental ill health is often reported to be more prevalent.
C_LIO_LIThis is a longitudinal study containing linked data collected before the Covid-19 pandemic and during the March-June 2020 lockdown which has allowed us to explore change over that time period in a highly ethnically diverse population, the majority of whom live in the most deprived centiles in the UK.
C_LIO_LIRespondents in this study were mothers of children aged 0-5 and/or 9-13 which may limit the wider generalisability, though our findings are broadly similar (in prevalence and associations) to those from another longitudinal study that included adult men and women.
C_LIO_LIWe are not aware of other studies that have explored longitudinal change in mental health from before to during the Covid-19 lockdown in a similar ethnically diverse and deprived population.
C_LI | public and global health |
10.1101/2020.11.30.20240796 | Increasing efficacy of contact-tracing applications by user referrals and stricter quarantining | We study the effects of two mechanisms which increase the efficacy of contact-tracing applications (CTAs) such as the mobile phone contact-tracing applications that have been used during the COVID-19 epidemic. The first mechanism is the introduction of user referrals. We compare four scenarios for the uptake of CTAs -- (1) the p% of individuals that use the CTA are chosen randomly, (2) a smaller initial set of randomly-chosen users each refer a contact to use the CTA, achieving p% in total, (3) a small initial set of randomly-chosen users each refer around half of their contacts to use the CTA, achieving p% in total, and (4) for comparison, an idealised scenario in which the p% of the population that uses the CTA is the p% with the most contacts. Using agent-based epidemiological models incorporating a geometric space, we find that, even when the uptake percentage p% is small, CTAs are an effective tool for mitigating the spread of the epidemic in all scenarios. Moreover, user referrals significantly improve efficacy. In addition, it turns out that user referrals reduce the quarantine load. The second mechanism for increasing the efficacy of CTAs is tuning the severity of quarantine measures. Our modelling shows that using CTAs with mild quarantine measures is effective in reducing the maximum hospital load and the number of people who become ill, but leads to a relatively high quarantine load, which may cause economic disruption. Fortunately, under stricter quarantine measures, the advantages are maintained but the quarantine load is reduced. Our models incorporate geometric inhomogeneous random graphs to study the effects of the presence of super-spreaders and of the absence of long-distant contacts (e.g., through travel restrictions) on our conclusions. | epidemiology |
10.1101/2020.11.29.20235218 | Effective post-exposure prophylaxis of Covid-19 associated with hydroxychloroquine: Prospective dataset re-analysis incorporating novel, missing data | BACKGROUNDA key trial (NCT04308668) of post-exposure prophylaxis found hydroxychloroquine-associated (HCQ) reductions of Covid-19 by 17% overall and 31% to 49% in subgroups. To understand these trends, we re-analyzed the dataset.
METHODSOur protocol conformed to the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT). We compared the incidence of Covid-19 after HCQ or placebo, stratifying by intervention lag, age, and gender.
RESULTSNewly requested data missing from the dataset revealed that 52% and 19% of subjects received medication 1-2 days after intended and assumed overnight delivery or four-day intervention lag respectively. After re-analysis, we found reduced HCQ-associated incidence of Covid-19 with Early (up to 3 days post-exposure) (RR 0.58, 95%CI 0.35 - 0.97; p=0.044; NNT 14.5) but not Late (RR 1.22, 95%CI 0.72 - 2.04) prophylaxis.
We found a significant HCQ-associated Covid-19 reduction in subjects 18 to 45 years old with Early (RR 0.54, 95%CI 0.29-0.97; p=0.0448, NNT 11.5) but not Late (RR 1.02, 95%CI 0.55-1.89) prophylaxis, attenuated in older subjects (RR 0.75, 95%CI 0-27-2.05) and by co-morbidities. Although, we did not detect effects of gender, folate, zinc, or ascorbate, confounding effects cannot be excluded.
CONCLUSIONSUsing novel data and prospective re-analysis, hydroxychloroquine, in an age-dependent manner, was associated with reduced Covid-19 compatible illness when supplied for post-exposure prophylaxis between 1 and 3 days after high- or moderate-risk exposure, at higher loading and maintenance doses than in similar studies. The original study conclusions are controverted, and our finding warrants prospective confirmation.
Protocol registered at Open Science Framework: osf.io/fqtnw (last revised September 27, 2020,
HighlightsO_LIMissing data integrated with dataset re-analysis reversed findings of original study
C_LIO_LIHydroxychloroquine associated reduction (42%) of Covid-19 compatible illness found
C_LIO_LIEffect in Post-exposure Prophylaxis when received 1-3 days after exposure
C_LIO_LIRisk Ratio 0.58 (95% CI 0.35-0.97, p=0.044, NNT14.5)
C_LIO_LIFindings controvert the conclusions of original study
C_LI | infectious diseases |
10.1101/2020.11.30.20241083 | Risk assessment for airborne disease transmission by poly-pathogen aerosols | In the case of airborne diseases, pathogen copies are transmitted by droplets of respiratory tract fluid that are exhaled by the infectious that stay suspended in the air for some time and, after partial or full drying, inhaled as aerosols by the susceptible. The risk of infection in indoor environments is typically modelled using the Wells-Riley model or a Wells-Riley-like formulation, usually assuming the pathogen dose follows a Poisson distribution (mono-pathogen assumption). Aerosols that hold more than one pathogen copy, i.e. poly-pathogen aerosols, break this assumption even if the aerosol dose itself follows a Poisson distribution. For the largest aerosols where the number of pathogen in each aerosol can sometimes be several hundred or several thousand, the effect is non-negligible, especially in diseases where the risk of infection per pathogen is high. Here we report on a generalization of the Wells-Riley model and dose-response models for poly-pathogen aerosols by separately modeling each number of pathogen copies per aerosol, while the aerosol dose itself follows a Poisson distribution. This results in a model for computational risk assessment suitable for mono-/poly-pathogen aerosols. We show that the mono-pathogen assumption significantly overestimates the risk of infection for high pathogen concentrations in the respiratory tract fluid. The model also includes the aerosol removal due to filtering by the individuals which becomes significant for poorly ventilated environments with a high density of individuals, and systematically includes the effects of facemasks in the infectious aerosol source and sink terms and dose calculations. | epidemiology |
10.1101/2020.11.30.20239921 | Lost in time: temporal monitoring elicits clinical decrements in sustained attention post-stroke | ObjectiveMental fatigue, brain fog and difficulties maintaining engagement are commonly reported issues in a range of neurological and psychiatric conditions. Traditional sustained attention tasks commonly measure this capacity as the ability to detect target stimuli based on sensory features in the auditory or visual domains. However, with this approach, discrete target stimuli may exogenously capture attention to aid detection, thereby masking deficits in the ability to endogenously sustain attention over time.
MethodTo address this, we developed the continuous temporal expectancy test (CTET) where individuals continuously monitor a stream of patterned stimuli alternating at a fixed temporal interval (690ms) and detect an infrequently occurring target stimulus defined by a prolonged temporal duration (1020ms or longer). As such, sensory properties of target and non-target stimuli are perceptually identical and differ only in temporal duration. Using the CTET, we assessed stroke survivors with unilateral right hemisphere damage (N=14), a cohort in which sustained attention deficits have been extensively reported.
ResultsStroke survivors had overall lower target detection accuracy compared to neurologically-healthy age-matched older controls (N=18). In addition, performance of the stroke survivors was characterised by significantly steeper within-block performance decrements which occurred within short temporal windows (~3 [1/2] minutes) and were restored by the break periods between blocks.
ConclusionThese findings outline a precise measure of the endogenous processes hypothesized to underpin sustained attention deficits following right hemisphere stroke and suggest that continuous temporal monitoring taxes sustained attention process to capture clinical deficits in this capacity over time. | psychiatry and clinical psychology |
10.1101/2020.12.01.20241570 | The Acceleration Index as a Test-Controlled Reproduction Number: Application to COVID-19 in France | We provide a novel way to correct the effective reproduction number for the time-varying amount of tests, using the acceleration index as a simple measure of viral spread dynamics (Baunez et al., 2021). Not doing so results in the reproduction number being a biased estimate of viral acceleration and we provide a formal decomposition of the resulting bias, involving the useful notions of test and infectivity intensities. When applied to French data for the COVID-19 pandemic (May 13 - November 19, 2020), our decomposition shows that the reproduction number, when considered alone, consistently underestimates the resurgence of the pandemic since the summer of 2020, compared to the acceleration index which accounts for the time-varying volume of tests. Because the acceleration index aggregates all relevant information and captures in real time the sizable time variation featured by viral circulation, it is a more parsimonious indicator to track the dynamics of an infectious disease outbreak in real time, compared to the equivalent alternative which would be to complement the reproduction number with the test and infectivity intensities. | health economics |
10.1101/2020.12.01.20241570 | Correcting the Reproduction Number for Time-Varying Tests: a Proposal and an Application to COVID-19 in France | We provide a novel way to correct the effective reproduction number for the time-varying amount of tests, using the acceleration index as a simple measure of viral spread dynamics (Baunez et al., 2021). Not doing so results in the reproduction number being a biased estimate of viral acceleration and we provide a formal decomposition of the resulting bias, involving the useful notions of test and infectivity intensities. When applied to French data for the COVID-19 pandemic (May 13 - November 19, 2020), our decomposition shows that the reproduction number, when considered alone, consistently underestimates the resurgence of the pandemic since the summer of 2020, compared to the acceleration index which accounts for the time-varying volume of tests. Because the acceleration index aggregates all relevant information and captures in real time the sizable time variation featured by viral circulation, it is a more parsimonious indicator to track the dynamics of an infectious disease outbreak in real time, compared to the equivalent alternative which would be to complement the reproduction number with the test and infectivity intensities. | health policy |
10.1101/2020.11.30.20240986 | A Net Benefit Approach for the Optimal Allocation of a COVID-19 Vaccine | OBJECTIVEWe implement a model-based approach to identify the optimal allocation of a COVID-19 vaccine in the province of Alberta, Canada.
METHODSWe develop an epidemiologic model to evaluate allocation strategies defined by age and risk target groups, coverage, effectiveness, and cost of vaccine. The model simulates hypothetical immunization scenarios within a dynamic context, capturing concurrent public health strategies and population behaviour changes.
RESULTSIn a scenario with 80% vaccine effectiveness, 40% population coverage, and prioritisation of those over the age of 60 at high-risk of poor outcomes, active cases are reduced by 17% and net monetary benefit increased by $263 million dollars, relative to no vaccine. Concurrent implementation of policies such as school closure and senior contact reductions have similar impacts on incremental net monetary benefit ($352 vs. 292 million, respectively) when there is no prioritisation given to any age or risk group. When older age groups are given priority, the relative benefit of school closures is much larger ($214 vs. 118 million). Results demonstrate that the rank ordering of different prioritisation options varies by prioritisation criteria, vaccine effectiveness and coverage, and concurrently implemented policies.
CONCLUSIONSOur results have three implications: (i) optimal vaccine allocation will depend on the public health policies in place at the time of allocation and the impact of those policies on population behaviour; (ii) outcomes of vaccine allocation policies can be greatly supported with interventions targeting contact reduction in critical sub-populations; and (iii) identification of the optimal strategy depends on which outcomes are prioritised. | health economics |
10.1101/2020.11.30.20240945 | Beyond ratios - flexible and resilient nurse staffing options to deliver cost-effective hospital care and address staff shortages: a simulation and economic modelling study | BackgroundIn the face of pressure to contain costs and make best use of scarce nurses, flexible staff deployment (floating staff between units and temporary hires) guided by a patient classification system may appear an efficient approach to meeting variable demand for care in hospitals.
ObjectivesWe modelled the cost-effectiveness of different approaches to planning baseline numbers of nurses to roster on general medical/surgical units while using flexible staff to respond to fluctuating demand.
Design and SettingWe developed an agent-based simulation model, where hospital inpatient units move between being understaffed, adequately staffed or overstaffed as staff supply and demand, measured by a classification system (the Safer Nursing Care Tool) varies. Staffing shortfalls are addressed first by floating staff from overstaffed units, secondly by hiring temporary staff. We compared a standard staffing plan (baseline rosters set to match average demand) with a higher baseline resilient plan set to match higher demand, and a lower baseline flexible plan. We varied assumptions about temporary staff availability. We estimated the effect of unresolved low staffing on length of stay and death, calculating cost per life saved.
ResultsStaffing plans with higher baseline rosters led to higher costs but improved outcomes. Cost savings from low baseline staff largely arose because shifts were left understaffed. With limited temporary staff available, the higher baseline resilient staffing plan cost {pound}8,653 per life saved compared to the standard plan. The standard plan cost {pound}13,117 per life saved compared to the low baseline flexible plan.
Cost effectiveness for higher baseline staff was further improved with high temporary staff availability. With unlimited temporary staff, the high-baseline staffing plan cost {pound}3,693 per life saved compared to the standard plan and the standard plan cost {pound}4,520 per life saved compared with the low-baseline plan. Cost-effectiveness of higher baseline staffing was even more favourable when negative effects of high temporary staffing were modelled.
ConclusionFlexible staffing can be guided by shift-by-shift measurement of patient demand, but proper attention must be given to ensure that the baseline number of staff rostered is sufficient. Flexible staffing plans that minimise the number of nurses routinely rostered are likely to harm patients because temporary staff may not be available at short notice. Plans that involve low baseline staff rosters and high use of flexible staff therefore do not represent an efficient or effective use of nurses, whereas higher baseline rosters are more resilient in the face of variation and appear cost-effective.
Study registration: ISRCTN 12307968
Tweetable abstracEconomic simulation model of hospital units shows low baseline staff levels with high use of flexible staff are not cost-effective and dont solve nursing shortages.
What is already known?O_LIBecause nursing is the largest staff group, accounting for a significant proportion of hospitals variable costs, unit nurse staffing is frequently the target of cost containment measures
C_LIO_LIStaffing decisions need to address both the baseline staff establishment to roster, and how best to respond to fluctuating demand as patient census and care needs vary
C_LIO_LIFlexible deployment of staff, including floating staff and using temporary hires, has the potential to reduce expenditure while meeting varying patient need, but high use of temporary staff may be associated with adverse outcomes.
C_LI
What this paper addsO_LILow baseline staff rosters that rely heavily on flexible staff provide cost savings largely because units are often left short staffed, which results in adverse patient outcomes and increased non staff costs.
C_LIO_LIA staffing plan set to meet average demand appears to be cost effective compared to a plan with a lower baseline but is still associated with frequent short staffing even when using flexible deployments.
C_LIO_LIA staffing plan with a higher baseline, set to meet demand 90% of the time, is more resilient in the face of variation and may be highly cost effective
C_LI | health systems and quality improvement |
10.1101/2020.11.30.20241174 | Modeling the effectiveness of olfactory testing to limit SARS-CoV-2 transmission | A central problem in the COVID-19 pandemic is that there is not enough testing to prevent infectious spread of SARS-CoV-2, causing surges and lockdowns with human and economic toll. Molecular tests that detect viral RNAs or antigens will be unable to rise to this challenge unless testing capacity increases by at least an order of magnitude while decreasing turnaround times. Here, we evaluate an alternative strategy based on the monitoring of olfactory dysfunction, a symptom identified in 76-83% of SARS-CoV-2 infections--including those with no other symptoms--when a standardized olfaction test is used. We model how screening for olfactory dysfunction, with reflexive molecular tests, could be beneficial in reducing community spread of SARS-CoV-2 by varying testing frequency and the prevalence, duration, and onset time of olfactory dysfunction. We find that monitoring olfactory dysfunction could reduce spread via regular screening, and could reduce risk when used at point-of-entry for single-day events. In light of these estimated impacts, and because olfactory tests can be mass produced at low cost and self-administered, we suggest that screening for olfactory dysfunction could be a high impact and cost-effective method for broad COVID-19 screening and surveillance. | infectious diseases |
10.1101/2020.11.30.20239798 | Modeling MRSA decolonization: Interactions between body sites and the impact of site-specific clearance | Methicillin-resistant Staphylococcus aureus (MRSA) can colonize multiple body sites, and carriage is a risk factor for infection. Successful decolonization protocols reduce disease incidence; however, multiple protocols exist, comprising diverse therapies targeting multiple body sites, and the optimal protocol is unclear. Standard methods are inadequate to infer the impact of site-specific components on successful decolonization. Here, we formulate a Bayesian coupled hidden Markov model (CHMM), which estimates interactions between body sites, quantifies the contribution of each therapy to successful decolonization, and enables predictions of the efficacy of therapy combinations. We applied the model to longitudinal data from a randomized controlled trial (RCT) of an MRSA decolonization protocol consisting of chlorhexidine body and mouthwash and nasal mupirocin. Our findings 1) confirmed nares as a central hub for MRSA colonization and nasal mupirocin as the most crucial therapy, and 2) demonstrated that all components contributed significantly to the efficacy of the protocol and the protocol reduced self-inoculation. Finally, we assessed the impact of hypothetical increases on the effectiveness of each therapy in silico and found that enhancing MRSA clearance at the skin would yield the largest gains to the overall decolonization regimen. This study demonstrates the use of advanced modeling to go beyond what is typically achieved by RCTs, enabling evidence-based decision-making to streamline clinical protocols. | infectious diseases |
10.1101/2020.11.30.20239798 | Modeling MRSA decolonization: Interactions between body sites and the impact of site-specific clearance | Methicillin-resistant Staphylococcus aureus (MRSA) can colonize multiple body sites, and carriage is a risk factor for infection. Successful decolonization protocols reduce disease incidence; however, multiple protocols exist, comprising diverse therapies targeting multiple body sites, and the optimal protocol is unclear. Standard methods are inadequate to infer the impact of site-specific components on successful decolonization. Here, we formulate a Bayesian coupled hidden Markov model (CHMM), which estimates interactions between body sites, quantifies the contribution of each therapy to successful decolonization, and enables predictions of the efficacy of therapy combinations. We applied the model to longitudinal data from a randomized controlled trial (RCT) of an MRSA decolonization protocol consisting of chlorhexidine body and mouthwash and nasal mupirocin. Our findings 1) confirmed nares as a central hub for MRSA colonization and nasal mupirocin as the most crucial therapy, and 2) demonstrated that all components contributed significantly to the efficacy of the protocol and the protocol reduced self-inoculation. Finally, we assessed the impact of hypothetical increases on the effectiveness of each therapy in silico and found that enhancing MRSA clearance at the skin would yield the largest gains to the overall decolonization regimen. This study demonstrates the use of advanced modeling to go beyond what is typically achieved by RCTs, enabling evidence-based decision-making to streamline clinical protocols. | infectious diseases |
10.1101/2020.11.30.20241166 | Social network-based strategies for classroom size reduction can help limit outbreaks of SARS-CoV-2 in high schools. A simulation study in classrooms of four European countries | Dividing classrooms may reduce the risk of SARS-CoV-2 outbreaks in schools. We investigate how classroom cohorting strategies, which downsize and isolate groups, may curb the spread of SARS-CoV-2. Using agent-based modelling based on a rich multi-country network dataset comprising 507 classrooms and 12,291 students, we assess random cohorting and three network-based strategies that consider students out-of-school contacts with classmates. Investigating effects on the number of cross-cohort transmissions, overall infections, and quarantines, our findings suggest that all cohorting strategies help to contain outbreaks, but that minimizing out-of-school contact between cohorts is most effective. Since this strategy may be hard to implement in practice, we show that a network chain nomination procedure and splitting classes by gender, both of which are easier to realize, also outperform random cohorting considerably. For all cohorting strategies, we find that rota-systems with instruction in alternating weeks contain outbreaks more effectively than same-day in-person instruction. | epidemiology |
10.1101/2020.11.30.20241331 | Serological prevalence of SARS-CoV-2 infection and associated factors in healthcare workers in a "non-COVID" hospital in Mexico City | In spite of high mortality from COVID-19, in Mexico the number of confirmed cases and diagnostic tests per million population are lower than for other comparable countries, which leads to uncertainty about the actual extent of the pandemic. In Mexico City, healthcare workers represent an important fraction of individuals with SARS-CoV-2 infection. This work aims to estimate the frequency of antibodies to SARS-CoV-2 and identify associated factors in healthcare workers at a large hospital in Mexico City. We conducted a serological survey in a non-COVID national referral teaching hospital. We selected a representative sample of 300 individuals. Blood samples were collected and questionnaires were applied between August 10th and September 9th, 2020. ELISA results indicate a serological prevalence of SARS-CoV-2 infection of 13.0%. Working in the janitorial and security groups, having an educational level below a university degree, and living with a larger number of people, were also identified as sociodemographic factors that increase the risk of having SARS-CoV-2 infection. Thus, less favored socioeconomic groups are at significantly higher risk of experiencing SARS-CoV-2 infection. Even in healthcare workers there is still a majority of individuals that are seronegative, and thus the risk of continued epidemic waves and mortality remains high. | epidemiology |
10.1101/2020.12.01.20241539 | SARS-CoV-2 infections in 171 countries and over time | Understanding the dynamics of the COVID-19 pandemic, evaluating the efficacy of past and current control measures, and estimating vaccination needs, requires knowledge of the number of infections in the population over time. This number, however, generally differs substantially from the number of confirmed cases due to a large fraction of asymptomatic infections as well as geographically and temporally variable testing effort and strategies. Here I use age-stratified death count statistics, age-dependent infection fatality risks and stochastic modeling to estimate the prevalence and growth of SARS-CoV-2 infections among adults (age [≥] 20 years) in 171 countries, from early 2020 until April 9, 2021. The accuracy of the approach is confirmed through comparison to previous nationwide general-population seroprevalence surveys in multiple countries. Estimates of infections over time, compared to reported cases, reveal that the fraction of infections that are detected vary widely over time and between countries, and hence comparisons of confirmed cases alone (between countries or time points) often yield a false picture of the pandemics dynamics. As of April 9, 2021, the nationwide cumulative SARS-CoV-2 prevalence (past and current infections relative to the population size) is estimated at 61% (95%-CI 42-78) for Peru, 58% (39-83) for Mexico, 57% (31-75) for Brazil, 55% (34-72) for South Africa, 29% (19-48) for the US, 26% (16-49) for the United Kingdom, 19% (12-34) for France, 19% (11-33) for Sweden, 9.6% (6.5-15) for Canada, 11% (7-19) for Germany and 0.67% (0.47-1.1) for Japan. The presented time-resolved estimates expand the possibilities to study the factors that influenced and still influence the pandemics progression in 171 countries. Regular updates are available at: www.loucalab.com/archive/COVID19prevalence | epidemiology |
10.1101/2020.11.30.20234476 | Retinal implantation of electronic vision prostheses to treat retinitis pigmentosa: A systematic review | PurposeRetinitis pigmentosa is an hereditary disease causing photoreceptor degeneration and permanent vision loss. Retinal implantation of a stimulating electrode array is a new treatment for retinitis pigmentosa, but quantification of its efficacy is the subject of ongoing work. This review evaluates vision-related outcomes resulting from retinal implantation in participants with retinitis pigmentosa.
MethodsWe searched MEDLINE and Embase for journal articles published since 1 January 2015. We selected articles describing studies of implanted participants that reported post-implantation measurement of vision. We extracted study information including design, participants residual vision, comparators, and assessed outcomes. To assess risk of bias, we used signalling questions and a target trial.
ResultsOur search returned 425 abstracts. We reviewed the full text of 34 articles. We judged all studies to be at high risk of bias due to study design or experimental conduct. Regarding design, studies lacked the measures that typical clinical trials take to protect against bias (e.g., control groups and masking). Regarding experimental conduct, outcome measures were rarely comparable before and after implantation, and psychophysical methods were prone to bias (subjective, not forced-choice, methods). The most common comparison found was between post-implantation visual function with the device powered off versus on. This comparison is at high risk of bias.
ConclusionsThere is a need for high-quality evidence of efficacy of retinal implantation to treat retinitis pigmentosa.
Translational RelevanceFor patients and clinicians to make informed choices about retinitis pigmentosa treatment, visual function restored by retinal implantation must be properly quantified and reported. | ophthalmology |
10.1101/2020.11.30.20234476 | Retinal implantation of electronic vision prostheses to treat retinitis pigmentosa: A systematic review | PurposeRetinitis pigmentosa is an hereditary disease causing photoreceptor degeneration and permanent vision loss. Retinal implantation of a stimulating electrode array is a new treatment for retinitis pigmentosa, but quantification of its efficacy is the subject of ongoing work. This review evaluates vision-related outcomes resulting from retinal implantation in participants with retinitis pigmentosa.
MethodsWe searched MEDLINE and Embase for journal articles published since 1 January 2015. We selected articles describing studies of implanted participants that reported post-implantation measurement of vision. We extracted study information including design, participants residual vision, comparators, and assessed outcomes. To assess risk of bias, we used signalling questions and a target trial.
ResultsOur search returned 425 abstracts. We reviewed the full text of 34 articles. We judged all studies to be at high risk of bias due to study design or experimental conduct. Regarding design, studies lacked the measures that typical clinical trials take to protect against bias (e.g., control groups and masking). Regarding experimental conduct, outcome measures were rarely comparable before and after implantation, and psychophysical methods were prone to bias (subjective, not forced-choice, methods). The most common comparison found was between post-implantation visual function with the device powered off versus on. This comparison is at high risk of bias.
ConclusionsThere is a need for high-quality evidence of efficacy of retinal implantation to treat retinitis pigmentosa.
Translational RelevanceFor patients and clinicians to make informed choices about retinitis pigmentosa treatment, visual function restored by retinal implantation must be properly quantified and reported. | ophthalmology |
10.1101/2020.11.30.20240010 | Is Point-of-Care testing feasible and safe in care homes in England? An exploratory usability and accuracy evaluation of Point-of-Care Polymerase Chain Reaction test for SARS-COV-2 | IntroductionReliable rapid testing on COVID-19 is needed in care homes to reduce the risk of outbreaks and enable timely care. Point-of-care testing (POCT) in care homes could provide rapid actionable results. This study aimed to examine the usability and test performance of point of care polymerase chain reaction (PCR) for COVID-19 in care homes.
MethodsPoint-of-care PCR for detection of SARS-COV2 was evaluated in a purposeful sample of four UK care homes. Test agreement with laboratory real-time PCR and usability and use errors were assessed.
ResultsPoint of care and laboratory polymerase chain reaction (PCR) tests were performed on 278 participants. The point of care and laboratory tests returned uncertain results or errors for 17 and 5 specimens respectively. Agreement analysis was conducted on 256 specimens. 175 were from staff: 162 asymptomatic; 13 symptomatic. 69 were from residents: 59 asymptomatic; 10 symptomatic. Asymptomatic specimens showed 83.3% (95% CI: 35.9%-99.6%) positive agreement and 98.7% negative agreement (95% CI: 96.2%-99.7%), with overall prevalence and bias-adjusted kappa (PABAK) of 0.965 (95% CI: 0.932 - 0.999). Symptomatic specimens showed 100% (95% CI: 2.5%-100%) positive agreement and 100% negative agreement (95% CI: 85.8%-100%), with overall PABAK of 1. No usability-related hazards emerged from this exploratory study.
ConclusionApplications of point-of-care PCR testing in care homes can be considered with appropriate preparatory steps and safeguards. Agreement between POCT and laboratory PCR was good. Further diagnostic accuracy evaluations and in-service evaluation studies should be conducted, if the test is to be implemented more widely, to build greater certainty on this initial exploratory analysis.
Key pointsO_LIPoint of care tests (POCT) in care homes are feasible and could increase testing capacity for the control of COVID-19 infection.
C_LIO_LIThe test of agreement between POCT and laboratory PCR for care home residents and the staff was good.
C_LIO_LIAdoption of POCT in care homes can be considered with appropriate preparatory steps and safeguards in place.
C_LIO_LIRepetitive errors and test malfunctioning can be mitigated with bespoke training for care home staff.
C_LIO_LIIntegrated care pathways should be investigated to test the high variability of the context of use.
C_LI | health systems and quality improvement |
10.1101/2020.11.30.20190926 | Clinical Characteristics and Risk Factors for Myocardial Injury and Arrhythmia in COVID-19 patients | The authors have withdrawn this manuscript because of a lack of novelty of results and, with that, a lack of intention to publish in a peer reviewed journal. 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. | cardiovascular medicine |
10.1101/2020.12.01.20241067 | Impact of the Covid-19 pandemic on the mental health and wellbeing of adults with mental health conditions in the UK: A qualitative interview study | BackgroundPeople with mental health conditions have been identified as particularly vulnerable to poor mental health during the coronavirus disease 2019 (COVID-19) pandemic. However, why this population have faced these adverse effects, how they have experienced them and how they have coped remains under-explored.
AimsTo explore how the COVID-19 pandemic affected the mental health of people with existing mental health conditions, and to identify coping strategies for positive mental health.
MethodsSemi-structured qualitative interviews with 22 people with mental health conditions. Participants were purposively recruited via social media, study newsletters and third sector mental health organisations. Data were analysed using reflexive thematic analysis.
ResultsParticipants were aged 23-70 (mean age 43), predominantly female (59.1%) and of white ethnicity (68.2%). Fifty percent were unable to work due to illness and the most frequently reported mental health condition was depression. Five pandemic related factors contributed to deteriorating mental health: i) feeling safe but isolated at home ii) disruption to mental health services, iii) cancelled plans and changed routines iv) uncertainty and lack of control, v) rolling media coverage. Five coping strategies were identified for maintaining mental health: i) previous experience of adversity ii) social comparison and accountability iii) engaging in hobbies and activities, iv) staying connected with others, v) perceived social support.
ConclusionsChallenges were identified as a direct result of the pandemic and people with severe mental illnesses were particularly negatively affected. However, some found this period a time of respite, drew upon reserves of resilience and adapted their coping strategies to maintain positive wellbeing. | psychiatry and clinical psychology |