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10.1101/2021.01.19.21250085 | Incidence and Relative Risk of infection with SARS-CoV-2 virus (Covid-19) in European Soccer Players. | The purpose of the present study was to investigate the incidence and relative risk of infection Covid-virus in soccer players. Data from five leagues was used and compared to data from the normal population in each country. Our results revealed that the relative risk was higher in soccer players in three countries when correcting for the estimated true number of infected people in the populations. We discuss that the reason for the higher incidence in soccer players is caused by the virus entering a group of players that work closely together. | public and global health |
10.1101/2021.01.19.21249790 | COVID-19: making the best out of a forced transition to online medical teaching. A mixed methods study | Introductionthe COVID-19 pandemic resulted in a decreed confinement in our country from March until the end of term in June 2020. This forced a transition exclusively to distance learning. The aim of this study was to broaden the understanding of fully online distance learning from the experiences of undergraduate medical students and faculty members during confinement, and identify its key elements.
MethodsA convergent mixed methods study analyzing: (a) an online teaching follow- up program, (b) two focus groups and a nominal group with students and faculty, respectively, and (c) a survey with students from 1st to 5th year.
ResultsThirteen strongly interconnected categories were identified. Four played an organizational role: course planning, coordination, communication and pedagogical coherence. The remaining nine categories were: learning outcomes, teaching methodology, online resources, evaluation, time management, workload, student motivation, participation, and teacher-student relationship. Among the key aspects of learning were those that promoted rapport between faculty and students, such as synchronous sessions, especially those based on clinical cases.
Conclusionthe experiences from confinement allowed us to gain insight into some of the key aspects of online medical teaching. Promoting student motivation and participation at all levels was essential to distance learning in Medicine. | medical education |
10.1101/2021.01.16.21249949 | Exposure to glucagon-like peptide 1 receptor (GLP-1R) agonists reduces glaucoma risk. | ImportanceGlucagon-like peptide-1 receptor (GLP-1R) agonists regulate blood glucose and are commonly used to treat Type II Diabetes Mellitus. Recent work has shown that treatment with the novel GLP-1R agonist, NLY01, decreased retinal neuroinflammation and glial activation to rescue retinal ganglion cells in an animal model of glaucoma.
ObjectiveIn this study, we used an insurance claims database to examine whether GLP-1R agonist exposure impacts glaucoma risk.
Design, Setting, and ParticipantsA retrospective cohort of adult patients who initiated a new GLP-1R agonist (i.e., exenatide, liraglutide, albiglutide, dulaglutide, semaglutide, or lixisenatide) was 1:3 age, gender, race, active diabetes medication classes, and year of index date matched to a cohort of patients who initiated a different class of oral diabetic medication during their time in the database. Exclusion occurred for <2 years in the database, age <18 years old, no visit to an eyecare provider prior to the index date, a prior diagnosis of glaucoma, glaucoma suspect, or ocular hypertension, or prior glaucoma medication, procedure, or surgery. Diabetes severity was assessed using hemoglobin A1c and the Diabetes Complications Severity Index (DCSI), a validated metric based on six categories of diabetic complications. Inverse probability of treatment weighting (IPTW) was used within a multivariable Cox proportional hazard regression model to test the association between GLP-1R agonist exposure and the primary outcome. IPTW was derived from a propensity score model based on the DCSI, HbA1c, demographic factors and other systemic health conditions.
ExposureGlucagon-like peptide 1 receptor agonist.
Main Outcomes and MeasuresNew diagnosis of primary open angle glaucoma, glaucoma suspect, or low tension glaucoma.
ResultsCohorts were comprised of 1,961 new users of GLP-1R agonists matched to 4,371 unexposed controls. After IPTW, age was the only covariate imbalanced (SMD >0.1) between cohorts. Ten new diagnoses of glaucoma (0.51%) were present in the GLP-1R agonist cohort compared to 58 (1.33%) in the unexposed controls. After adjustment, GLP-1R exposure conferred a reduced hazard of 0.54 (95%CI: 0.35-0.85, P =0.007), suggesting that GLP-1R agonists reduce the risk for glaucoma.
Conclusions and RelevanceGLP-1R agonist use was associated with a statistically significant hazard reduction for a new glaucoma diagnosis. Our findings support further investigations into the use of GLP-1R agonists in glaucoma prevention. | ophthalmology |
10.1101/2021.01.19.21250080 | Estimating dates of origin and end of COVID-19 epidemics | Estimating the date at which an epidemic started in a country and the date at which it can end depending on interventions intensity are important to guide public health responses. Both are potentially shaped by similar factors including stochasticity (due to small population sizes), superspreading events, and memory effects (the fact that the occurrence of some events, e.g. recovering from an infection, depend on the past, e.g. the number of days since the infection). Focusing on COVID-19 epidemics, we develop and analyse mathematical models to explore how these three factors may affect early and final epidemic dynamics. Regarding the date of origin, we find limited effects on the mean estimates, but strong effects on their variances. Regarding the date of extinction following lockdown onset, mean values decrease with stochasticity or with the presence of superspreading events. These results underline the importance of accounting for heterogeneity in infection history and transmission patterns to accurately capture early and late epidemic dynamics. | epidemiology |
10.1101/2021.01.19.21250080 | Estimating dates of origin and end of COVID-19 epidemics | Estimating the date at which an epidemic started in a country and the date at which it can end depending on interventions intensity are important to guide public health responses. Both are potentially shaped by similar factors including stochasticity (due to small population sizes), superspreading events, and memory effects (the fact that the occurrence of some events, e.g. recovering from an infection, depend on the past, e.g. the number of days since the infection). Focusing on COVID-19 epidemics, we develop and analyse mathematical models to explore how these three factors may affect early and final epidemic dynamics. Regarding the date of origin, we find limited effects on the mean estimates, but strong effects on their variances. Regarding the date of extinction following lockdown onset, mean values decrease with stochasticity or with the presence of superspreading events. These results underline the importance of accounting for heterogeneity in infection history and transmission patterns to accurately capture early and late epidemic dynamics. | epidemiology |
10.1101/2021.01.19.21250080 | Estimating dates of origin and end of COVID-19 epidemics | Estimating the date at which an epidemic started in a country and the date at which it can end depending on interventions intensity are important to guide public health responses. Both are potentially shaped by similar factors including stochasticity (due to small population sizes), superspreading events, and memory effects (the fact that the occurrence of some events, e.g. recovering from an infection, depend on the past, e.g. the number of days since the infection). Focusing on COVID-19 epidemics, we develop and analyse mathematical models to explore how these three factors may affect early and final epidemic dynamics. Regarding the date of origin, we find limited effects on the mean estimates, but strong effects on their variances. Regarding the date of extinction following lockdown onset, mean values decrease with stochasticity or with the presence of superspreading events. These results underline the importance of accounting for heterogeneity in infection history and transmission patterns to accurately capture early and late epidemic dynamics. | epidemiology |
10.1101/2021.01.18.21250072 | Evaluation of crowdsourced mortality prediction models as a framework for assessing AI in medicine | Applications of machine learning in healthcare are of high interest and have the potential to significantly improve patient care. Yet, the real-world accuracy and performance of these models on different patient subpopulations remains unclear. To address these important questions, we hosted a community challenge to evaluate different methods that predict healthcare outcomes. To overcome patient privacy concerns, we employed a Model-to-Data approach, allowing citizen scientists and researchers to train and evaluate machine learning models on private health data without direct access to that data. We focused on the prediction of all-cause mortality as the community challenge question. In total, we had 345 registered participants, coalescing into 25 independent teams, spread over 3 continents and 10 countries. The top performing team achieved a final area under the receiver operator curve of 0.947 (95% CI 0.942, 0.951) and an area under the precision-recall curve of 0.487 (95% CI 0.458, 0.499) on patients prospectively collected over a one year observation of a large health system. Post-hoc analysis after the challenge revealed that models differ in accuracy on subpopulations, delineated by race or gender, even when they are trained on the same data and have similar accuracy on the population. This is the largest community challenge focused on the evaluation of state-of-the-art machine learning methods in a healthcare system performed to date, revealing both opportunities and pitfalls of clinical AI. | health informatics |
10.1101/2021.01.17.21249963 | Maternal prenatal anxiety and depression and trajectories of cardiometabolic risk factors across childhood and adolescence: a prospective cohort study | BackgroundQuantifying long-term offspring cardiometabolic health risks associated with maternal prenatal anxiety and depression can guide cardiometabolic risk prevention. This study examines associations between maternal prenatal anxiety and depression, and offspring cardiometabolic risk from birth to 18 years.
MethodsParticipants were 526-8,606 mother-offspring pairs from the Avon Longitudinal Study of Parents and Children (ALSPAC). Exposures were anxiety (Crown-Crisp Inventory score) and depression (Edinburgh Postnatal Depression Scale score) measured at 18 and 32 weeks gestation. Outcomes were trajectories of offspring body mass index; fat mass; lean mass; pulse rate; glucose, diastolic and systolic blood pressure; triglycerides, high-density lipoprotein cholesterol and non-high-density lipoprotein cholesterol, and insulin from birth/early childhood to 18 years. Exposures were analysed categorically using clinically relevant, cut-offs and continuously to examine associations across the distribution of prenatal anxiety and depression.
ResultsWe found no strong evidence of associations between maternal anxiety and depression, and offspring trajectories of any cardiometabolic risk factors, except for small, inconsistent associations with fat mass trajectories that attenuated upon confounder adjustment. For instance, in unadjusted analyses, anxiety at both 18 and 32 weeks was associated with a 1.8% (95% Confidence Interval (CI), 0.29,3.33) higher mean BMI, which spanned the null (difference (95% CI): 0.7% (-0.76,2.13) after adjustment for confounders.
ConclusionsThis is the first examination of maternal prenatal anxiety and depression and trajectories of offspring cardiometabolic risk. Our findings suggest that prevention of maternal prenatal anxiety and depression may have limited impact on offspring cardiometabolic health across the first two decades of life. | pediatrics |
10.1101/2021.01.20.21250150 | Exploring overcrowding trends in an inner city emergence department in the UK before and during COVID-19 epidemic | BackgroundWe compared impact of three pre-COVID-19 interventions and of the COVID-19 UK-epidemic and the first UK national lockdown on overcrowding within University College London Hospital Emergency Department (UCLH ED). The three interventions: target the influx of patients at ED (A), reduce the pressure on in-patients beds (B) and improve ED processes to improve the flow of patents out from ED (C).
MethodsWe analysed the change in overcrowding metrics (daily attendances, the proportion of people leaving within four hours of arrival (four-hours target) and the reduction in overall waiting time) across three analysis. The first analysis used data 01/04/2017-31/12-2019 to calculate changes over a period of six months before and after the start of interventions A-C. The second and third analyses focused on evaluating the impact of the COVID-19 epidemic, comparing the first 10 months in 2020 and 2019, and of the first national lockdown (23/03/2020-31/05/2020).
ResultsPre-COVID-19 all interventions led to small reductions in waiting time (17%, p<0.001 for A and C;9%, p=0.322 for B) but also to a small decrease in the number of patients leaving within four hours of arrival (6.6%,7.4%,6.2% respectively A-C,p<0.001).
In presence of the COVID-19 pandemic, attendance and waiting time were reduced (40% and 8%;p<0.001), and the number of people leaving within four hours of arrival was increased (6%,p<0.001). During the first lockdown, there was 65% reduction in attendance, 22% reduction in waiting time and 8% increase in number of people leaving within 4 hours of arrival (p<0.001). Crucially, when the lockdown was lifted, there was an increase (6.5%,p<0.001) in the percentage of people leaving within four hours, together with a larger (12.5%,p<0.001) decrease in waiting time. This occurred despite the increase of 49.6%(p<0.001) in attendance after lockdown ended.
ConclusionsThe mixed results pre-COVID-19 (significant improvements in waiting time with some interventions but not improvement in the four-hours target), may be due to a spill-over effect where clogging up one part of the ED system affects other parts. Hence multifaceted interventions and a system-wide approach to improve the pathway of flow through the ED system is necessary.
During 2020 and in presence of the COVID-19 epidemic, a shift in public behaviour with anxiety over attending hospitals and higher use of virtual consultations, led to notable drop in UCLH ED attendance and consequential curbing of overcrowding.
Importantly, once the lockdown was lifted, although there was an increase in arrivals at UCLH ED, overcrowding metrics were reduced. Thus, the combination of shifted public behaviour and the restructuring changes during COVID-19 epidemic, maybe be able to curb future ED overcrowding, but longer timeframe analysis is required to confirm this. | emergency medicine |
10.1101/2021.01.19.21250144 | Fecal biomarkers of environmental enteric dysfunction and the gut microbiota of rural Malawian children: an observational study | Environmental enteric dysfunction (EED) is a subclinical condition of the gut characterized by changes in morphology and function with underlying chronic inflammatory responses. This study characterized composition and diversity of the gut microbiota in rural Malawian children with and without signs of EED. Fecal samples were collected from children aged 1-59 months. Neopterin, myeloperoxidase and alpha-1 antitrypsin concentrations were quantified by ELISA and combined to form a composite EED score using principal component analysis. DNA was extracted from fecal samples and V4-16S rRNA sequencing was used to characterize the gut microbiota. The concentrations of all three biomarkers decreased with increasing age, which is consistent with other studies of children living in similar low-income settings. Firmicutes, Bacteroidetes, Proteobacteria and Actinobacteria were the dominant phyla while Faecalibacterium and Bifidobacterium were the most prevalent genera. Increased alpha diversity was associated with a reduction in neopterin concentration. Microbiota composition was associated with the composite EED score. Increased abundance of Succinivibrio was associated with reduced composite EED scores.
HighlightsO_LIIn Malawian children, fecal concentrations of myeloperoxidase, alpha-1 antitrypsin and neopterin decreased with age
C_LIO_LIA marginal negative association was found between alpha diversity of the gut microbiota and fecal neopterin concentration
C_LIO_LIA higher abundance of Succinivibrio was found in children with lower concentrations of biomarker of environmental enteric dysfunction
C_LIO_LIFatty acid biosynthesis, tetrapyrrole biosynthesis and pyrimidine nucleotide degradation pathways were associated with environmental enteric dysfunction biomarker score
C_LI | gastroenterology |
10.1101/2021.01.19.21250128 | Sleep in Frontline Healthcare Workers on Social Media During the COVID-19 Pandemic | ImportanceDuring the pandemic, healthcare workers on social media are sharing their challenges, including sleep disturbances.
ObjectiveTo assess sleep using validated measures among frontline healthcare workers on social media
DesignA self-selection survey was distributed on Facebook, Twitter, and Instagram for 16 days (August 31-September 15, 2020) targeting healthcare workers (HCW) who were clinically active during the pandemic. Study participants completed the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), and reported demographic/career information. Poor sleep quality was defined as PSQI>5. Moderate-to-severe insomnia was defined as an ISI>14. The mini-Z was used to measure burnout. Multivariate logistic regression tested associations between demographics, career characteristics, and sleep outcomes.
SettingOnline self-selection survey on social media
Participants963 surveys were completed. Participants were predominantly White (92.8%), female (73.4%), aged 30-49 (71.9%), and physicians (64.4%). Mean sleep duration was 6.1 (SD 1.2) hours. Nearly 90% reported poor sleep (PSQI). One third (33.0%) reported moderate or severe insomnia. Many (60%) experienced sleep disruptions due to device usage or had bad dreams at least once per week (45%). Over 50% reported burnout. In multivariable logistic regressions, non-physician (OR 2.4; CI: 1.7, 3.4), caring for COVID-19 patients (OR 1.8; CI 1.2, 2.8), Hispanic ethnicity (OR 2.2; CI: 1.4, 3.5), being female (OR 1.6; CI 1.1, 2.4), and having a sleep disorder (OR 4.3; CI 2.7,6.9) were associated with increased odds of insomnia. In open-ended comments (n=310), poor sleep mapped to four categories: children and family, work demands, personal health, and pandemic-related sleep disturbances.
ConclusionDuring the COVID-19 pandemic, 90% of frontline healthcare workers surveyed on social media reported poor sleep, over one-third reported insomnia, and over half reported burnout. Many also reported sleep disruptions due to device usage and nightmares. Sleep interventions for frontline healthcare workers are urgently needed.
Key pointsO_ST_ABSQuestionC_ST_ABSHow are frontline healthcare workers on social media sleeping during the pandemic?
FindingsDuring the COVID-19 pandemic, 90% of frontline healthcare workers on social media are reporting poor sleep, and one third are reporting insomnia. Those who report sleep disturbances were more likely to report burnout.
MeaningInterventions aimed at improving the sleep of frontline healthcare workers are warranted. | occupational and environmental health |
10.1101/2021.01.19.21250124 | Deficient hand washing facilities in public toilets in the time of the COVID-19 pandemic: A survey in one high-income country | AimsTo identify the extent of the provision of water and soap for hand washing in public toilets at the time of the COVID-19 pandemic. To also make comparisons with a pre-pandemic survey that included a sample of the same facilities.
MethodsWe collected data from 400 toilets that were open to the public; all those in three contiguous city council territories (228) and a further convenience sample of 172 around the rest of New Zealand. Comparisons were made with the data on the same facilities included in a 2012/2013 survey.
ResultsFor all the toilets in this survey, 2.5% had no water for hand washing and 14.8% had no soap. There was COVID-19 related health messaging signage in 19.5% of toilets, with posters of the COVID-19 QR code used to facilitate contact tracing in 12.3%, and generic hand washing signage in 1.8%. The hand washing water had "no touch" activation at 28.0% of toilets and at 18.5% for toilet bowl flushing. Toilet bowl lids were not present at 32.8%, and 2.3% of toilets had damage which would impair their functionality (eg, broken toilet seats). For the 128 sites that had also been examined in the previous survey, this new survey found significantly increased provision of soap (risk ratio = 1.47; 95%CI: 1.25 to 1.72), but no increased provision of water.
ConclusionsDespite the serious threat of the COVID-19 pandemic, the majority of hand washing facilities in public toilets sampled required tap touching, and did not have health messaging. Nevertheless there has been some modest improvements in soap (but not water) provision since the previous survey eight years before. | infectious diseases |
10.1101/2021.01.19.21250079 | Head-to-head comparison of direct-input RT-PCR and RT-LAMP against RTqPCR on extracted RNA for rapid SARS-CoV-2 diagnostics | Viral pandemics, such as Covid-19, pose serious threats to human societies. To control the spread of highly contagious viruses such as SARS-CoV-2, effective test-trace-isolate strategies require population-wide, systematic testing. Currently, RT-qPCR on extracted RNA is the only broadly accepted test for SARS-CoV-2 diagnostics, which bears the risk of supply chain bottlenecks, often exaggerated by dependencies on proprietary reagents. Here, we directly compare the performance of gold standard diagnostic RT-qPCR on extracted RNA to direct input RT-PCR, RT-LAMP and bead-LAMP on 384 primary patient samples collected from individuals with suspected Covid-19 infection. With a simple five minute crude sample inactivation step and one hour of total reaction time, we achieve assay sensitivities of 98% (direct RT-PCR), 93% (bead-LAMP) and 82% (RT-LAMP) for clinically relevant samples (diagnostic RT-qPCR Ct <35) and a specificity of >98%. For direct RT-PCR, our data further demonstrate a perfect agreement between real-time and end-point measurements, which allow a simple binary classification similar to the powerful visual readout of colorimetric LAMP assays. Our study provides highly sensitive and specific, easy to implement, rapid and cost-effective alternatives to diagnostic RT-qPCR tests. | infectious diseases |
10.1101/2021.01.19.21249592 | The N501Y mutation in SARS-CoV-2 spike leads to morbidity in obese and aged mice and is neutralized by convalescent and post-vaccination human sera | The current COVID-19 (coronavirus disease 19) pandemic, caused by SARS-CoV-2, disproportionally affects the elderly and people with comorbidities like obesity and associated type 2 diabetes mellitus. Small animal models are crucial for the successful development and validation of antiviral vaccines, therapies and to study the role that comorbidities have on the outcome of viral infections. The initially available SARS-CoV-2 isolates require adaptation in order to use the mouse angiotensin converting enzyme 2 (mACE-2) entry receptor and to productively infect the cells of the murine respiratory tract. We have "mouse-adapted" SARS-CoV-2 by serial passaging a clinical virus isolate in the lungs of mice. We then used low doses of this virus in mouse models for advanced age, diabetes and obesity. Similar to SARS-CoV-2 infection in humans, the outcome of infection with mouse-adapted SARS-CoV-2 resulted in enhanced morbidity in aged and diabetic obese mice. Mutations associated with mouse adaptation occurred in the S, M, N and ORF8 genes. Interestingly, one mutation in the receptor binding domain of the S protein results in the change of an asparagine to tyrosine residue at position 501 (N501Y). This mutation is also present in the newly emerging SARS-CoV-2 variant viruses reported in the U.K. (20B/501Y.V1, B1.1.7 lineage) that is epidemiologically associated with high human to human transmission. We show that human convalescent and post vaccination sera can neutralize the newly emerging N501Y virus variant with similar efficiency as that of the reference USA-WA1/2020 virus, suggesting that current SARS-CoV-2 vaccines will protect against the 20B/501Y.V1 strain. | infectious diseases |
10.1101/2021.01.19.21250115 | Excessive matrix metalloproteinase-1 and hyperactivation of endothelial cells occurred in COVID-19 patients and were associated with the severity of COVID-19 | COVID-19 starts as a respiratory disease that can progress to pneumonia, severe acute respiratory syndrome (SARS), and multi-organ failure. Growing evidence suggests that COVID-19 is a systemic illness that primarily injures the vascular endothelium, yet the underlying mechanisms remain unknown. SARS-CoV-2 infection is believed to trigger a cytokine storm that plays a critical role in the pathogenesis of endothelialitis and vascular injury, eventually leading to respiratory and multi-organ failure in COVID-19 patients. We used a multiplex immunoassay to systematically profile and compare 65 inflammatory cytokines/chemokines/growth factors in plasma samples from 24 hospitalized (severe/critical) COVID-19 patients, 14 mild/moderate cases, and 13 healthy controls (HCs). Patients with severe/critical and mild/moderate COVID-19 had significantly higher plasma levels of 20 analytes than HCs. Surprisingly, only one cytokine (MIF) was among these altered analytes, while the rest were chemokines and growth factors. In addition, only MMP-1 and VEGF-A were significantly elevated in hospitalized COVID-19 patients when compared to mild/moderate cases. Given that excessive MMP-1 plays a central role in tissue destruction in a wide variety of vascular diseases and that elevated VEGF-A, an EC activation marker, increases vascular permeability, we further studied MMP-1 enzymatic activity and other EC activation markers such as soluble forms of CD146, ICAM-1, and VCAM-1. We found that plasma MMP-1 enzymatic activity and plasma levels of MMP-1 and EC activation markers were highly dysregulated in COVID-19 patients. Some dysregulations were associated with patients age or gender, but not with race. Our results demonstrate that COVID-19 patients have distinct inflammatory profiles that are distinguished from the cytokine storms in other human diseases. Excessive MMP-1 and hyperactivation of ECs occur in COVID-19 patients and are associated with the severity of COVID-19. | infectious diseases |
10.1101/2021.01.19.21250139 | Overcrowding and Exposure to Secondhand Smoke Increase Risk for COVID-19 Infection Among Latinx Families in Greater San Francisco Bay Area | BackgroundThe novel coronavirus (COVID-19) has disproportionately impacted the Latinx community in the United States. Environmental risk factors, including community level pollution burden and exposure to smoking and secondhand smoke, have not been evaluated in relation to risk for infection with COVID-19.
MethodsWe evaluated self-reported infection rates of COVID-19 in three, preexisting, longitudinal, Latinx family cohorts in the San Francisco Bay Area from May through September 2020 (N=383 households, 1,875 people). All households were previously recruited during pregnancy and postpartum at Zuckerberg San Francisco General Hospital (ZSFG) and UCSF Benioff before the pandemic. For the COVID-19 sub-study, participants responded to a 15-minute telephonic interview where we assessed food consumption patterns, housing and employment status, and history of COVID-19 infection based on community and hospital-based testing. We also evaluated secondhand smoke exposure based on previously collected self-reported data. Environmental pollution exposure was determined from census tract residence using Californias EnviroScreen 2.0 data. Non-parametric tests and multiple logistic regression were used to assess possible associations and independent predictors of COVID-19 infection.
ResultsIn the combined Latinx, Eating and Diabetes Cohort (LEAD) and Hispanic, Eating and Nutrition (HEN) cohorts there was a 7.6% household infection rate (14/183) with a lower rate of 3.5% (7/200) in the Telomeres at Birth (TAB) cohort. Larger household size increased risk for infection (OR, 1.43 (95%CI 1.10-1.87)) in the combined LEAD/HEN cohorts and increasing number of children trended towards significance in the TAB cohort (OR 1.82, 95% CI 0.98-3.37). Any exposure to secondhand smoke in the household also trended towards increasing risk after adjusting for household size and other exposures (OR 3.20, 95%CI 0.80-12.73) and (OR 4.37, 95% CI 0.80-23.70). We did not find any associations between neighborhood pollution level based on census track location and risk of infection. Furthermore, we found weak evidence between dietary exposure and risk of COVID-19 infection after adjusting for possible confounders.
ConclusionCrowding as indicated by household size increases risk for COVID-19 infection in Latinx families. Exposure to secondhand smoke may also increase risk for COVID-19 through increased coughing, respiratory impairment and increased travel of virus on smoke particles. Public policy and health interventions need to ensure that multiunit residential complexes prevent any exposure to secondhand smoke. | infectious diseases |
10.1101/2021.01.19.21250139 | Overcrowding and Exposure to Secondhand Smoke Increase Risk for COVID-19 Infection Among Latinx Families in Greater San Francisco Bay Area | BackgroundThe novel coronavirus (COVID-19) has disproportionately impacted the Latinx community in the United States. Environmental risk factors, including community level pollution burden and exposure to smoking and secondhand smoke, have not been evaluated in relation to risk for infection with COVID-19.
MethodsWe evaluated self-reported infection rates of COVID-19 in three, preexisting, longitudinal, Latinx family cohorts in the San Francisco Bay Area from May through September 2020 (N=383 households, 1,875 people). All households were previously recruited during pregnancy and postpartum at Zuckerberg San Francisco General Hospital (ZSFG) and UCSF Benioff before the pandemic. For the COVID-19 sub-study, participants responded to a 15-minute telephonic interview where we assessed food consumption patterns, housing and employment status, and history of COVID-19 infection based on community and hospital-based testing. We also evaluated secondhand smoke exposure based on previously collected self-reported data. Environmental pollution exposure was determined from census tract residence using Californias EnviroScreen 2.0 data. Non-parametric tests and multiple logistic regression were used to assess possible associations and independent predictors of COVID-19 infection.
ResultsIn the combined Latinx, Eating and Diabetes Cohort (LEAD) and Hispanic, Eating and Nutrition (HEN) cohorts there was a 7.6% household infection rate (14/183) with a lower rate of 3.5% (7/200) in the Telomeres at Birth (TAB) cohort. Larger household size increased risk for infection (OR, 1.43 (95%CI 1.10-1.87)) in the combined LEAD/HEN cohorts and increasing number of children trended towards significance in the TAB cohort (OR 1.82, 95% CI 0.98-3.37). Any exposure to secondhand smoke in the household also trended towards increasing risk after adjusting for household size and other exposures (OR 3.20, 95%CI 0.80-12.73) and (OR 4.37, 95% CI 0.80-23.70). We did not find any associations between neighborhood pollution level based on census track location and risk of infection. Furthermore, we found weak evidence between dietary exposure and risk of COVID-19 infection after adjusting for possible confounders.
ConclusionCrowding as indicated by household size increases risk for COVID-19 infection in Latinx families. Exposure to secondhand smoke may also increase risk for COVID-19 through increased coughing, respiratory impairment and increased travel of virus on smoke particles. Public policy and health interventions need to ensure that multiunit residential complexes prevent any exposure to secondhand smoke. | infectious diseases |
10.1101/2021.01.19.21250137 | A Label-Free SARS-CoV-2 Surrogate Virus Neutralization Test and a Longitudinal Study of Antibody Characteristics in COVID-19 Patients | Background. The laboratory-based methods to measure the SARS-CoV-2 humoral response include virus neutralization tests (VNTs) to determine antibody neutralization potency. For ease of use and universal applicability, surrogate virus neutralization tests (sVNTs) based on antibody-mediated blockage of molecular interactions have been proposed. Methods. A surrogate virus neutralization test established on a label-free immunoassay platform (LF-sVNT). The LF-sVNT analyzes the binding ability of RBD to ACE2 after neutralizing RBD with antibodies in serum. Results. The LF-sVNT neutralizing antibody titers (IC50) were determined from serum samples (n=246) from COVID-19 patients (n=113), as well as the IgG concentrations and the IgG avidity indices. Although there is variability in the kinetics of the IgG concentrations and neutralizing antibody titers between individuals, there is an initial rise, plateau and then in some cases a gradual decline at later timepoints after 40 days post-symptom onset. The IgG avidity indices, in the same cases, plateau after the initial rise and did not show a decline. Conclusions. The LF-sVNT can be a valuable tool in clinical laboratories for the assessment of the presence of neutralizing antibodies to COVID-19. This study is the first to provide longitudinal neutralizing antibody titers beyond 200 days post-symptom onset. Despite the decline of IgG concentration and neutralizing antibody titer, IgG avidity index increases, reaches a plateau and then remains constant up to 8 months post-infection. The decline of antibody neutralization potency can be attributed to the reduction in antibody quantity rather than the deterioration of antibody avidity, a measure of antibody quality. | infectious diseases |
10.1101/2021.01.19.21250137 | A SARS-CoV-2 Label-Free Surrogate Virus Neutralization Test and a Longitudinal Study of Antibody Characteristics in COVID-19 Patients | Background. The laboratory-based methods to measure the SARS-CoV-2 humoral response include virus neutralization tests (VNTs) to determine antibody neutralization potency. For ease of use and universal applicability, surrogate virus neutralization tests (sVNTs) based on antibody-mediated blockage of molecular interactions have been proposed. Methods. A surrogate virus neutralization test established on a label-free immunoassay platform (LF-sVNT). The LF-sVNT analyzes the binding ability of RBD to ACE2 after neutralizing RBD with antibodies in serum. Results. The LF-sVNT neutralizing antibody titers (IC50) were determined from serum samples (n=246) from COVID-19 patients (n=113), as well as the IgG concentrations and the IgG avidity indices. Although there is variability in the kinetics of the IgG concentrations and neutralizing antibody titers between individuals, there is an initial rise, plateau and then in some cases a gradual decline at later timepoints after 40 days post-symptom onset. The IgG avidity indices, in the same cases, plateau after the initial rise and did not show a decline. Conclusions. The LF-sVNT can be a valuable tool in clinical laboratories for the assessment of the presence of neutralizing antibodies to COVID-19. This study is the first to provide longitudinal neutralizing antibody titers beyond 200 days post-symptom onset. Despite the decline of IgG concentration and neutralizing antibody titer, IgG avidity index increases, reaches a plateau and then remains constant up to 8 months post-infection. The decline of antibody neutralization potency can be attributed to the reduction in antibody quantity rather than the deterioration of antibody avidity, a measure of antibody quality. | infectious diseases |
10.1101/2021.01.19.21250137 | A SARS-CoV-2 Label-Free Surrogate Virus Neutralization Test and a Longitudinal Study of Antibody Characteristics in COVID-19 Patients | Background. The laboratory-based methods to measure the SARS-CoV-2 humoral response include virus neutralization tests (VNTs) to determine antibody neutralization potency. For ease of use and universal applicability, surrogate virus neutralization tests (sVNTs) based on antibody-mediated blockage of molecular interactions have been proposed. Methods. A surrogate virus neutralization test established on a label-free immunoassay platform (LF-sVNT). The LF-sVNT analyzes the binding ability of RBD to ACE2 after neutralizing RBD with antibodies in serum. Results. The LF-sVNT neutralizing antibody titers (IC50) were determined from serum samples (n=246) from COVID-19 patients (n=113), as well as the IgG concentrations and the IgG avidity indices. Although there is variability in the kinetics of the IgG concentrations and neutralizing antibody titers between individuals, there is an initial rise, plateau and then in some cases a gradual decline at later timepoints after 40 days post-symptom onset. The IgG avidity indices, in the same cases, plateau after the initial rise and did not show a decline. Conclusions. The LF-sVNT can be a valuable tool in clinical laboratories for the assessment of the presence of neutralizing antibodies to COVID-19. This study is the first to provide longitudinal neutralizing antibody titers beyond 200 days post-symptom onset. Despite the decline of IgG concentration and neutralizing antibody titer, IgG avidity index increases, reaches a plateau and then remains constant up to 8 months post-infection. The decline of antibody neutralization potency can be attributed to the reduction in antibody quantity rather than the deterioration of antibody avidity, a measure of antibody quality. | infectious diseases |
10.1101/2021.01.19.21250118 | Characterization of influenza vaccination recommendation across spatial scales in the United States | The US public health system is organized in 3 levels: national, state-level, and county-level. Public health messaging both within and across these scales may not always be consistent, and for transmissible public health threats where cases in one spatial location may impact other areas, this lack of consistency could create problems. Here, we collected and analyzed data on influenza vaccination recommendations across public health administration levels. We assess spatial heterogeneity at the county level, and analyze consistency in recommendations across spatial scales. We also compare information accessibility with influenza vaccine affordability and availability to identify factors that may be most related to vaccine uptake. We find that influenza vaccine recommendations are highly variable in both their priority group specificity and in their ease of access, and there is poor agreement across spatial scales. This lack of consistency results in a lack of clear relationship between vaccination information and vaccine uptake. This work highlights the need for greater consistency in specific, easily accessed public health information from trusted sources. | epidemiology |
10.1101/2021.01.19.21250114 | Modeling the population effects of epitope specific escape mutations in SARS-CoV-2 to guide vaccination strategies | Escape mutations (EM) to SARS-Cov-2 have been detected and are spreading. Vaccines may need adjustment to respond to these or future mutations. We designed a population level model integrating both waning immunity and EM. We also designed a set of criteria for elaborating and fitting this model to cross-neutralization and other data in a manner that minimizes vaccine decision errors. We formulated four model variations. These define criteria for which prior infections provide immunity that can be escaped. They also specify different sequences where one EM follows another. At all reasonable parameter values, these model variations led to patterns where: 1) EM were rare in the first epidemic, 2) rebound epidemics after the first epidemic were accelerated more by increasing drifting than by increasing waning (with some exceptions), 3) the long term endemic level of infection was determined mostly by waning rates with small effects of the drifting parameter, 4) EM caused loss of vaccine effectiveness and under some conditions, vaccines induced EM that caused higher levels of infection with vaccines than without them. The differences and similarities across the four models suggest paths for developing models specifying the epitopes where EM act. This model is a base on which to construct epitope specific evolutionary models using new high-throughput assay data from population samples to guide vaccine decisions.
HighlightsO_LIThis model is the first to integrate both antigenic drifting from escape mutations and immunity waning in continuous time.
C_LIO_LITiny amounts of only waning or only escape mutation drifting have small or no effects. Together, they have large effects.
C_LIO_LIThere are no or few escape mutations during the first epidemic peak and no effect of drifting parameters on the size of that wave.
C_LIO_LIAfter the first epidemic peak, escape mutations accumulate rapidly. They increase with increases in waning rates and with increases in the drifting rate. Escape mutations then amplify other escape mutations since these raise the frequency of reinfections.
C_LIO_LIEscape mutations can completely negate the effects of vaccines and even lead to more infections with vaccination than without, especially at very low waning rates.
C_LIO_LIThe model generates population level cross-neutralization patterns that enable the model to be fitted to population level serological data.
C_LIO_LIThe model can be modified to use laboratory data that determine the epitope specific effects of mutations on ACE2 attachment strength or escape from antibody effects.
C_LIO_LIThe model, although currently unable to predict the effects of escape mutations in the real world, opens up a path that can guide model incorporation of molecularly studied escape mutations and improve predictive value. We describe that path.
C_LIO_LIModel analysis indicates that vaccine trials and serological surveys are needed now to detect the effects of epitope specific escape mutations that could cause the loss of vaccine efficacy.
C_LI | epidemiology |
10.1101/2021.01.20.21249931 | Alcohol consumption in the general population is associated with structural changes in multiple organ systems: A population-based study in UK Biobank | Excessive alcohol consumption is associated with damage to various organs, but its multi-organ effects have not been characterised across the usual range of alcohol drinking in a large general population sample. We assessed global effects of alcohol consumption on quantitative magnetic resonance imaging phenotypic measures of the brain, heart, aorta and liver of UK-Biobank participants who reported drinking alcohol. We found a monotonic association of higher alcohol consumption with lower normalised brain volume across the range of alcohol intakes (-1.7x10-3{+/-}0.76x10-3 per doubling of alcohol consumption, P=3.0x10-14). Alcohol consumption also was associated directly with measures of left ventricular mass index and left ventricular and atrial volume indices. Liver fat increased by a mean of 0.15% per doubling of alcohol consumption. Our results imply that there is not a "safe threshold" below which there are no toxic effects of alcohol. Current public health guidelines concerning alcohol consumption may need to be revisited. | epidemiology |
10.1101/2021.01.20.21249506 | Heart Rate Variability in Patients with Cirrhosis: A Systematic Review and Meta-analysis | BackgroundCirrhosis is associated with abnormal autonomic function and regulation of cardiac rhythm. Measurement of heart rate variability (HRV) provides an accurate and non-invasive measurement of autonomic function as well as liver disease severity currently calculated using the MELD, UKELD, or ChildPugh scores. This review assesses the methods employed for the measurement of HRV, and evaluates the alteration of HRV indices in cirrhosis, as well as their value in prognosis.
MethodWe undertook a systematic review using Medline, Embase and Pubmed databases in July 2020. Data were extracted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Risk of bias of included studies was assessed by a modified version of the Newcastle Ottawa Scale. The studies descriptive were analysed and the standardized mean differences of HRV indices were pooled.
ResultsOf the 247 studies generated from our search, 14 studies were included. One of the 14 studies was excluded from meta-analysis because it reported only median of HRV indices. The studies included have a low risk of bias, and include 583 patients with cirrhosis and 349 healthy controls. The HRV time and frequency domains were significantly lower in cirrhotic patients. Between-studies heterogeneity was high in most of the pooled studies (P<0.05). Further, HRV indices predict survival independent of the severity of liver disease as assessed by MELD.
ConclusionHRV is decreased in patients with cirrhosis compared with healthy matched controls. HRV correlated with severity of liver disease and independently predicted survival. There was considerable variation in the methods used for HRV analysis, and this impedes interpretation and clinical applicability. Based on the data analysed, SDNN (standard deviation of inter-beat intervals) and cSDNN (i.e. SDNN corrected for basal heart rate) are the most suitable indices for prognosis in patients with cirrhosis. | gastroenterology |
10.1101/2021.01.19.21250122 | Novel deep learning algorithm predicts the status of molecular pathways and key mutations in colorectal cancer from routine histology images | BackgroundDetermining molecular pathways involved in the development of colorectal cancer (CRC) and knowing the status of key mutations are crucial for deciding optimal target therapy. The goal of this study is to explore machine learning to predict the status of the three main CRC molecular pathways - microsatellite instability (MSI), chromosomal instability (CIN), CpG island methylator phenotype (CIMP) - and to detect BRAF and TP53 mutations as well as to predict hypermutated (HM) CRC tumors from whole-slide images (WSIs) of colorectal cancer (CRC) slides stained with Hematoxylin and Eosin (H&E).
MethodsWe propose a novel iterative draw-and-rank sampling (IDaRS) algorithm to select representative sub-images or tiles from a WSI given a single WSI-level label, without needing any detailed annotations at the cell or region levels. IDaRS is used to train a deep convolutional network for predicting key molecular parameters in CRC (in particular, prediction of HM tumors and the status of three main CRC molecular pathways - MSI, CIN, CIMP - as well as the detection of two key mutations, BRAF and TP53) from digitized images of routine H&E stained tissue slides of CRC patients (n=497 for TCGA cohort and n=47 cases for the Pathology AI Platform or PAIP cohort). Visual fields most predictive of each pathway and HM tumors identified by IDaRS are analyzed for verification of known histological features for the first time to reveal novel histological features. This is achieved by systematic, data-driven analysis of the cellular composition of strongly predictive tiles.
FindingsIDaRS yields high prediction accuracy for prediction of the three main CRC genetic pathways and key mutations by deep learning based analysis of the WSIs of H&E stained slides. It achieves the state-of-the-art AUROC values of 0.90, 0.83, and 0.81 for prediction of the status of MSI, CIN, and HM tumors for the TCGA cohort, which is significantly higher than any other currently published methods on that cohort. We also report prediction of status of CIMP pathway (CIMP-High and CIMP-Low) from H&E slides, with an AUROC of 0.79. We analyzed key discriminative histological features associated with HM tumors and each molecular pathway in a data-driven manner, via an automated quantitative analysis of the cellular composition of tiles strongly predictive of the corresponding molecular status. A key feature of the proposed method is that it enables a systematic and data-driven analysis of the cellular composition of image tiles strongly predictive of the various molecular parameters. We found that relatively high proportion of tumor infiltrating lymphocytes and necrosis are found to be strongly associated with HM and MSI, and moderately associated with CIMP-H and genome-stable (GS) cases, whereas relatively high proportions of neoplastic epithelial type 2 (NEP2), mesenchymal and neoplastic epithelial type 1 (NEP1) cells are found to be associated with CIN cases.
InterpretationAutomated prediction of genetic pathways and key mutations from image analysis of simple H&E stained sections with a high accuracy can provide time and cost-effective decision support. This work shows that a deep learning algorithm can mine both visually recognizable as well as sub-visual histological patterns associated with molecular pathways and key mutations in CRC in a data-driven manner.
FundingThis study was funded by the UK Medical Research Council (award MR/P015476/1). | pathology |
10.1101/2021.01.19.21250122 | Novel deep learning algorithm predicts the status of molecular pathways and key mutations in colorectal cancer from routine histology images | BackgroundDetermining molecular pathways involved in the development of colorectal cancer (CRC) and knowing the status of key mutations are crucial for deciding optimal target therapy. The goal of this study is to explore machine learning to predict the status of the three main CRC molecular pathways - microsatellite instability (MSI), chromosomal instability (CIN), CpG island methylator phenotype (CIMP) - and to detect BRAF and TP53 mutations as well as to predict hypermutated (HM) CRC tumors from whole-slide images (WSIs) of colorectal cancer (CRC) slides stained with Hematoxylin and Eosin (H&E).
MethodsWe propose a novel iterative draw-and-rank sampling (IDaRS) algorithm to select representative sub-images or tiles from a WSI given a single WSI-level label, without needing any detailed annotations at the cell or region levels. IDaRS is used to train a deep convolutional network for predicting key molecular parameters in CRC (in particular, prediction of HM tumors and the status of three main CRC molecular pathways - MSI, CIN, CIMP - as well as the detection of two key mutations, BRAF and TP53) from digitized images of routine H&E stained tissue slides of CRC patients (n=497 for TCGA cohort and n=47 cases for the Pathology AI Platform or PAIP cohort). Visual fields most predictive of each pathway and HM tumors identified by IDaRS are analyzed for verification of known histological features for the first time to reveal novel histological features. This is achieved by systematic, data-driven analysis of the cellular composition of strongly predictive tiles.
FindingsIDaRS yields high prediction accuracy for prediction of the three main CRC genetic pathways and key mutations by deep learning based analysis of the WSIs of H&E stained slides. It achieves the state-of-the-art AUROC values of 0.90, 0.83, and 0.81 for prediction of the status of MSI, CIN, and HM tumors for the TCGA cohort, which is significantly higher than any other currently published methods on that cohort. We also report prediction of status of CIMP pathway (CIMP-High and CIMP-Low) from H&E slides, with an AUROC of 0.79. We analyzed key discriminative histological features associated with HM tumors and each molecular pathway in a data-driven manner, via an automated quantitative analysis of the cellular composition of tiles strongly predictive of the corresponding molecular status. A key feature of the proposed method is that it enables a systematic and data-driven analysis of the cellular composition of image tiles strongly predictive of the various molecular parameters. We found that relatively high proportion of tumor infiltrating lymphocytes and necrosis are found to be strongly associated with HM and MSI, and moderately associated with CIMP-H and genome-stable (GS) cases, whereas relatively high proportions of neoplastic epithelial type 2 (NEP2), mesenchymal and neoplastic epithelial type 1 (NEP1) cells are found to be associated with CIN cases.
InterpretationAutomated prediction of genetic pathways and key mutations from image analysis of simple H&E stained sections with a high accuracy can provide time and cost-effective decision support. This work shows that a deep learning algorithm can mine both visually recognizable as well as sub-visual histological patterns associated with molecular pathways and key mutations in CRC in a data-driven manner.
FundingThis study was funded by the UK Medical Research Council (award MR/P015476/1). | pathology |
10.1101/2021.01.19.21250106 | Spatio-temporal analysis between the incidence of COVID-19 and human development in Mato Grosso do Sul, Brazil. | ObjetiveTo analyze the spatial distribution of the Covid-19 incidence and its correlation with the municipal human development index (IDHM) in the state of Mato Grosso do Sul (MS), Brazil.
MethodsThis is an ecological, exploratory and analytical study whose units of analysis were the 79 municipalities that make up the state of MS. Covid-19 incidence coefficients, death numbers, lethality rate, mortality rate and Human Development Index for municipalities (IDHM) in the period from March 2020 to December 31, 2020 were used. spatial correlations between the variables mentioned above.
ResultsThe incidence of Covid-19 has spatial dependence with moderate positive correlation and formation of clusters located in the Metropolitan Region of Campo Grande (RMCG) and municipalities in the region.
ConclusionThe uneven mapping of Covid-19 and its relationship with IDHM in the Ministry of Health can contribute to actions to address the regional pandemic. | public and global health |
10.1101/2021.01.19.21250091 | Using numerical modelling and simulation to assess the ethical burden in clinical trials and how it relates to the proportion of responders in a trial sample | In order to propose a more precise definition and explore how to reduce ethical losses in randomized controlled clinical trials (RCTs), we set out to identify trial participants who do not contribute to demonstrating that the treatment in the experimental arm is superior to that in the control arm. RCTs emerged mid-last century as the gold standard for assessing efficacy, becoming the cornerstone of the value of new therapies, yet their ethical grounds are a matter of debate. We introduce the concept of unnecessary participants in RCTs, the sum of non-informative participants and non-responders. The non-informative participants are considered not informative with respect to the efficacy measured in the trial in contrast to responders who carry all the information required to conclude on the treatments efficacy. The non-responders present the event whether or not they are treated with the experimental treatment. The unnecessary participants carry the burden of having to participate in a clinical trial without benefiting from it, which might include experiencing side effects. Thus, these unnecessary participants carry the ethical loss that is inherent to the RCT methodology. On the contrary, responders to the experimental treatment bear its entire efficacy in the RCT. Starting from the proportions observed in a real placebo-controlled trial from the literature, we carried out simulations of RCTs progressively increasing the proportion of responders up to 100%. We show that the number of unnecessary participants decreases steadily until the RCTs ethical loss reaches a minimum. In parallel, the trial sample size decreases (presumably its cost as well), although the trials statistical power increases as shown by the increase of the chi-square comparing the event rates between the two arms. Thus, we expect that increasing the proportion of responders in RCTs would contribute to making them more ethically acceptable, with less false negative outcomes. | medical ethics |
10.1101/2021.01.19.21250091 | Using numerical modelling and simulation to assess the ethical burden in clinical trials and how it relates to the proportion of responders in a trial sample | In order to propose a more precise definition and explore how to reduce ethical losses in randomized controlled clinical trials (RCTs), we set out to identify trial participants who do not contribute to demonstrating that the treatment in the experimental arm is superior to that in the control arm. RCTs emerged mid-last century as the gold standard for assessing efficacy, becoming the cornerstone of the value of new therapies, yet their ethical grounds are a matter of debate. We introduce the concept of unnecessary participants in RCTs, the sum of non-informative participants and non-responders. The non-informative participants are considered not informative with respect to the efficacy measured in the trial in contrast to responders who carry all the information required to conclude on the treatments efficacy. The non-responders present the event whether or not they are treated with the experimental treatment. The unnecessary participants carry the burden of having to participate in a clinical trial without benefiting from it, which might include experiencing side effects. Thus, these unnecessary participants carry the ethical loss that is inherent to the RCT methodology. On the contrary, responders to the experimental treatment bear its entire efficacy in the RCT. Starting from the proportions observed in a real placebo-controlled trial from the literature, we carried out simulations of RCTs progressively increasing the proportion of responders up to 100%. We show that the number of unnecessary participants decreases steadily until the RCTs ethical loss reaches a minimum. In parallel, the trial sample size decreases (presumably its cost as well), although the trials statistical power increases as shown by the increase of the chi-square comparing the event rates between the two arms. Thus, we expect that increasing the proportion of responders in RCTs would contribute to making them more ethically acceptable, with less false negative outcomes. | medical ethics |
10.1101/2021.01.13.21249597 | A Whole-Brain Functional Connectivity Model of Alzheimers Disease Pathology | Early detection of Alzheimers disease (AD) is a necessity as prognosis is poor upon symptom onset. Although previous work diagnosing AD from protein-based biomarkers has been encouraging, cerebrospinal (CSF) biomarker measurement of AD proteins requires invasive lumbar puncture, whereas assessment of direct accumulation requires radioactive substance exposure in positron emission tomography (PET) imaging. Functional magnetic resonance imaging (fMRI)-based neuromarkers, offers an alternative, especially those built by capitalizing on variance distributed across the entire human connectome. In this study, we employed connectome-based predictive modeling (CPM) to build a model of functional connections that would predict CSF p-tau/A{beta}42 (PATH-fc model) in individuals diagnosed with Mild Cognitive Impairment (MCI) and AD dementia. fMRI, CSF-based biomarker data, and longitudinal data from neuropsychological testing from the Alzheimers Disease NeuroImaging Initiative (ADNI) were utilized to build the PATH-fc model. Our results provide support for successful in-sample fit of the PATH-fc model in predicting AD pathology in MCI and AD dementia individuals. The PATH-fc model, distributed across all ten canonical networks, additionally predicted cognitive decline on composite measures of global cognition and executive functioning. Our highly distributed pathology-based model of functional connectivity disruptions had a striking overlap with the spatial affinities of amyloid and tau pathology, and included the default mode network as the hub of such network-based disruptions in AD. Future work validating this model in other external datasets, and to midlife adults and older adults with no known diagnosis, will critically extend this neuromarker development work using fMRI.
Significance StatementAlzheimers disease (AD) is clinical-pathological syndrome with multi-domain amnestic symptoms considered the hallmark feature of the disease. However, accumulating evidence from autopsy studies evince support for the onset of pathophysiological processes well before the onset of symptoms. Although CSF- and PET-based biomarkers provide indirect and direct estimates of AD pathology, both methodologies are invasive. In here, we implemented a supervised machine learning algorithm - connectome-based predictive modeling - on fMRI data and found support for a whole-brain model of functional connectivity to predict AD pathology and decline in cognitive functioning over a two-year period. Our study provides support for AD pathology dependent functional connectivity disturbances in large-scale functional networks to influence the trajectory of key cognitive domains in MCI and AD patients. | neurology |
10.1101/2021.01.19.21250126 | Changes in healthcare workers' knowledge, attitudes, practices, and stress during the COVID-19 pandemic | IntroductionCoronavirus disease 2019 (COVID-19) has caused an unprecedented health crisis around the world, not least because of its heterogeneous clinical presentation and course. The new information on the pandemic emerging daily has made it challenging for healthcare workers (HCWs) to stay current with the latest knowledge, which could influence their attitudes and practices during patient care.
MethodsThis study is a follow-up evaluation of changes in HCWs knowledge, attitudes, and practices as well as anxiety levels regarding COVID-19 since the beginning of the pandemic. Data were collected through an anonymous, predesigned, self-administered questionnaire that was sent online to HCWs in Saudi Arabia.
ResultsThe questionnaire was sent to 1500 HCWs, with a 63.8% response rate (N=957). The majority of respondents were female (83%), and the most common age group was 31-40 years (52.2%). Nurses constituted 86.3% of the respondents. HCWs reported higher anxiety during the COVID-19 pandemic which increased from 4.91{+/-}2.84 to 8.6{+/-}2.27 on an 11-point Likert scale compared to other viral outbreaks. HCWs believed that their own preparedness as well as that of their hospitals intensive care unit (ICU) or emergency room (ER) was higher during the COVID-19 pandemic than during the Middle East respiratory syndrome coronavirus pandemic (2012-2015). About 58% of HCWs attended one or more simulations concerning the management of COVID-19 patients in their ICU/ER, and nearly all had undergone N95 mask fit testing. The mean score of HCWs knowledge of COVID-19 was 9.89/12. For most respondents (94.6%), the perception of being at increased risk of infection was the main cause of anxiety related to COVID-19; the mean score of anxiety over COVID-19 increased from 4.91{+/-}2.84 before to 8.6{+/-}2.27 during the pandemic in Saudi Arabia.
ConclusionsHCWs anxiety levels regarding COVID-19 have increased since a pandemic was declared. It is vital that healthcare facilities provide more emotional and psychological support for all HCWs. | infectious diseases |
10.1101/2021.01.19.21250111 | SARS-CoV-2 B.1.1.7 lineage-related perceptions and travel worry among healthcare workers | BackgroundHealthcare workers (HCWs) travel-related anxiety needs to be assessed in light of the emergence of SARS-CoV-2 mutations.
MethodsAn online, cross-sectional questionnaire among HCWs between December 21, 2020 to January 7, 2021. The outcome variables were HCWs knowledge and awareness of the SARS-CoV-2 B.1.1.7 lineage, and its associated travel worry and Generalized Anxiety Disorder (GAD-7) score.
ResultsA total of 1,058 HCWs completed the survey; 66.5% were female, 59.0% were nurses. 9.0% indicated they had been previously diagnosed with COVID-19. Regarding the B.1.1.7 lineage, almost all (97.3%) were aware of its emergence, 73.8% were aware that it is more infectious, 78.0% thought it causes more severe disease, and only 50.0% knew that current COVID-19 vaccines are effective in preventing it. Despite this, 66.7% of HCWs were not registered to receive the vaccine. HCWs most common source of information about the new variant was social media platforms (67%), and this subgroup was significantly more worried about traveling. Nurses were more worried than physicians (P=0.001).
ConclusionsMost HCWs were aware of the emergence of SARS-CoV-2 B.1.1.7 variant and expressed substantial travel worries. Increased worry levels were found among HCWs who used social media as their main source of information, those with lower levels of COVID-19 vaccine uptake, and those with higher GAD-7 scores. The utilization of official social media platforms could improve accurate information dissemination among HCWs regarding the pandemics evolving mutations. Targeted vaccine campaigns are warranted to assure HCWs about the efficacy of COVID-19 vaccines toward SARS-CoV-2 variants. | infectious diseases |
10.1101/2021.01.19.21250111 | SARS-CoV-2 B.1.1.7 lineage-related perceptions, COVID-19 vaccine acceptance and travel worry among healthcare workers | BackgroundHealthcare workers (HCWs) travel-related anxiety needs to be assessed in light of the emergence of SARS-CoV-2 mutations.
MethodsAn online, cross-sectional questionnaire among HCWs between December 21, 2020 to January 7, 2021. The outcome variables were HCWs knowledge and awareness of the SARS-CoV-2 B.1.1.7 lineage, and its associated travel worry and Generalized Anxiety Disorder (GAD-7) score.
ResultsA total of 1,058 HCWs completed the survey; 66.5% were female, 59.0% were nurses. 9.0% indicated they had been previously diagnosed with COVID-19. Regarding the B.1.1.7 lineage, almost all (97.3%) were aware of its emergence, 73.8% were aware that it is more infectious, 78.0% thought it causes more severe disease, and only 50.0% knew that current COVID-19 vaccines are effective in preventing it. Despite this, 66.7% of HCWs were not registered to receive the vaccine. HCWs most common source of information about the new variant was social media platforms (67%), and this subgroup was significantly more worried about traveling. Nurses were more worried than physicians (P=0.001).
ConclusionsMost HCWs were aware of the emergence of SARS-CoV-2 B.1.1.7 variant and expressed substantial travel worries. Increased worry levels were found among HCWs who used social media as their main source of information, those with lower levels of COVID-19 vaccine uptake, and those with higher GAD-7 scores. The utilization of official social media platforms could improve accurate information dissemination among HCWs regarding the pandemics evolving mutations. Targeted vaccine campaigns are warranted to assure HCWs about the efficacy of COVID-19 vaccines toward SARS-CoV-2 variants. | infectious diseases |
10.1101/2021.01.19.21250134 | Hyperinflammatory conditions, gender differences and mortality in Indian COVID-19 patients | PurposeEvidence suggests that COVID-19 induces hyperinflammatory conditions and causes relatively more deaths in males than females. The purpose of this study was to analyze gender differences associated with various hyperinflammatory conditions (HIC) and mortality in the Indian COVID-19 patients
MethodsThis study was conducted at the Eras Lucknow Medical College and Hospital (ELMCH), ERA University, which is located in the northern part of India. Starting from July 4, 2020 till December 3, 2020 a total of 2997 patients were treated at ELMCH. We randomly collected blood samples from 150 severe COVID-19 patients (required oxygen) between August 10 and September 15, 2020 for analyzing the following HIC and associated laboratory markers: hyperferritinaemia (serum ferritin), hematological dysfunctions (lymphocytopenia and neutrophil to lymphocyte ratio), cytokinaemia (C-reactive protein), coagulopathy (D-dimer), liver inflammation (aspartate aminotransferase), renal inflammation (blood urea and creatinine), and hyperglycemia (random blood glucose). The threshold values/cut off limits of these laboratory markers used for analyzing the risk of mortality in male and female COVID-19 patients were set according to the scale validated recently by Webb et al, (2020).
ResultsIn the above cohort of consecutively admitted COVID-19 patients, analysis of various HIC revealed hyperferritinaemia (odd ratio: 2.9, 95% CI 1.4-6.0), hematological dysfunctions (odd ratio: 2.10, 95% CI 1.0-4.2), hepatic inflammation (odd ratio: 2.0, 95% CI 0.52-7.40), and coagulopathy (odd ratio: 1.5, 95% CI 1.50, 95% CI 0.50-4.60) were more prevalent and sever in male COVID-19 patients. Approximately 86% male to 64% female COVID-19 patients developed lymphocytopenia. Regarding mortality, while hyperferritinaemia (odd ratio: 1.70, 95% CI 0.37-7.43) and cytokinaemia (odd ratio: 1.60, 95% CI 0.37 -7.30) were strongly associated with mortality in male COVID-19 patients, coagulopathy (odd ratio: 3.30, 95% CI 0.31-35), and hematological dysfunctions (odd ratio: 1.70, 95% CI 0.27-10) were more commonly associated with mortality in female COVID-19 patients. Nearly 80% male and female COVID-19 patients, who died had developed [≥]2 criteria of HIS criteria. Chronic renal disease was associated with more deaths in female than male COVID-19 patients (odd ratio: 2.0, 95% CI 0.54 - 7.4). While the mortality proportion was slightly higher in male (6.3%) than female (4.5%) COVID-19 patients, survival curves of the two genders were not different (hazard ratio: 1.02, 95% CI 0.71-1.40, P = 0. 953).
ConclusionDistinct HIC were associated with the severity, and mortality in male and female COVID-19 patients. Coagulopathy and renal injury were detrimental, specifically, for female COVID-19 patients. The overall mortality proportion was around 5.3%. The above results suggest that gender differences associated with COVID-19 severity and mortality arise due to differences in various HIC. These results may help in developing personalized or gender based treatments for COVID-19 patients. | infectious diseases |
10.1101/2021.01.19.21250100 | Impact of immediate and preferential relaxation of social and travel restrictions for vaccinated people on the spreading dynamics of COVID-19 : a model-based analysis | BackgroundFour COVID-19 vaccine candidates developed by Pfizer, Moderna, University of Oxford/ Astra Zeneca (also Oxford/ Serum Institute of India) and ICMR/ Bharat Biotech have been granted emergency use authorization in the democratic world following established clinical trial procedures in their respective countries. Vaccination of the general public is expected to begin in several weeks. We consider the question of whether people who have received the vaccine can be selectively and immediately cleared to return to normal activities, including hassle-free travel.
MethodsWe use a delay differential equation model developed previously by our group to calculate the effects of vaccinee "immunity passports" on the spreading trajectories of the disease. We consider default virus strains as well as high-transmissibility variants such as B1.1.7 in our analysis.
ResultsWe find that with high vaccine efficacy of 80 percent or greater, vaccinees may be immediately cleared for normal life with no significant increase in case counts. Free travel of such vaccinees between two regions should not jeopardize the infection control performance of either. At current vaccine administration rates, it may be eight months or more before COVID-19 transmission is significantly reduced or eliminated. With lower vaccine efficacy of approximately 60 percent however, social as well as travel restrictions for vaccinees may need to remain in place until transmission of the disease is eliminated.
ConclusionsDesigning high-efficacy vaccines with easily scalable manufacturing and distribution capacity should remain on the priority list in academic as well as industrial circles. Performance of all vaccines should continue to be monitored in real time during vaccination drive with a view to analysing socio-demographic determinants if any of efficacy, and optimizing distribution accordingly. A speedy and efficacious vaccination drive will provide the smoothest path out of the pandemic with the least additional caseloads, death toll and socioeconomic cost. | infectious diseases |
10.1101/2021.01.19.21250110 | External Validations of Cardiovascular Clinical Prediction Models: A Large-scale Review of the Literature | BackgroundThere are many clinical prediction models (CPMs) available to inform treatment decisions for patients with cardiovascular disease. However, the extent to which they have been externally tested and how well they generally perform has not been broadly evaluated.
MethodsA SCOPUS citation search was run on March 22, 2017 to identify external validations of cardiovascular CPMs in the Tufts PACE CPM Registry. We assessed the extent of external validation, performance heterogeneity across databases, and explored factors associated with model performance, including a global assessment of the clinical relatedness between the derivation and validation data.
Results2030 external validations of 1382 CPMs were identified. 807 (58%) of the CPMs in the Registry have never been externally validated. On average there were 1.5 validations per CPM (range 0-94). The median external validation AUC was 0.73 (25th -75th percentile [IQR] 0.66, 0.79), representing a median percent decrease in discrimination of -11.1% (IQR -32.4%, +2.7%) compared to performance on derivation data. 81% (n = 1333) of validations reporting AUC showed discrimination below that reported in the derivation dataset. 53% (n = 983) of the validations report some measure of CPM calibration. For CPMs evaluated more than once, there was typically a large range of performance. Of 1702 validations classified by relatedness, the percent change in discrimination was -3.7% (IQR -13.2, 3.1) for closely related validations (n=123), -9.0 (IQR -27.6, 3.9) for related validations (n=862) and -17.2% (IQR -42.3, 0) for distantly related validations (n=717) (p<0.001).
ConclusionMany published cardiovascular CPMs have never been externally validated and for those that have, apparent performance during development is often overly optimistic. A single external validation appears insufficient to broadly understand the performance heterogeneity across different settings. | cardiovascular medicine |
10.1101/2021.01.19.21250132 | Association between COVID-19 Outcomes and Mask Mandates, Adherence, and Attitudes | We extend previous studies on the impact of masks on COVID-19 outcomes by investigating an unprecedented breadth and depth of health outcomes, geographical resolutions, types of mask mandates, early versus later waves and controlling for other government interventions, mobility testing rate and weather. We show that mask mandates are associated with a statistically significant decrease in new cases (-3.55 per 100K), deaths (-0.13 per 100K), and the proportion of hospital admissions (-2.38 percentage points) up to 40 days after the introduction of mask mandates both at the state and county level. These effects are large, corresponding to 14% of the highest recorded number of cases, 13% of deaths, and 7% of admission proportion. We also find that mask mandates are linked to a 23.4 percentage point increase in mask adherence in four diverse states. Lastly, using a large novel survey dataset of almost half a million people in 68 countries, we introduce the novel results that community mask adherence and community attitudes towards masks are associated with a reduction in COVID-19 cases and deaths. Our results have policy implications for reinforcing the need to maintain and encourage mask-wearing by the public, especially in light of some states starting to remove their mask mandates. | epidemiology |
10.1101/2021.01.19.21250132 | Association between COVID-19 Outcomes and Mask Mandates, Adherence, and Attitudes | We extend previous studies on the impact of masks on COVID-19 outcomes by investigating an unprecedented breadth and depth of health outcomes, geographical resolutions, types of mask mandates, early versus later waves and controlling for other government interventions, mobility testing rate and weather. We show that mask mandates are associated with a statistically significant decrease in new cases (-3.55 per 100K), deaths (-0.13 per 100K), and the proportion of hospital admissions (-2.38 percentage points) up to 40 days after the introduction of mask mandates both at the state and county level. These effects are large, corresponding to 14% of the highest recorded number of cases, 13% of deaths, and 7% of admission proportion. We also find that mask mandates are linked to a 23.4 percentage point increase in mask adherence in four diverse states. Lastly, using a large novel survey dataset of almost half a million people in 68 countries, we introduce the novel results that community mask adherence and community attitudes towards masks are associated with a reduction in COVID-19 cases and deaths. Our results have policy implications for reinforcing the need to maintain and encourage mask-wearing by the public, especially in light of some states starting to remove their mask mandates. | epidemiology |
10.1101/2021.01.19.21250132 | Association between COVID-19 Outcomes and Mask Mandates, Adherence, and Attitudes | We extend previous studies on the impact of masks on COVID-19 outcomes by investigating an unprecedented breadth and depth of health outcomes, geographical resolutions, types of mask mandates, early versus later waves and controlling for other government interventions, mobility testing rate and weather. We show that mask mandates are associated with a statistically significant decrease in new cases (-3.55 per 100K), deaths (-0.13 per 100K), and the proportion of hospital admissions (-2.38 percentage points) up to 40 days after the introduction of mask mandates both at the state and county level. These effects are large, corresponding to 14% of the highest recorded number of cases, 13% of deaths, and 7% of admission proportion. We also find that mask mandates are linked to a 23.4 percentage point increase in mask adherence in four diverse states. Lastly, using a large novel survey dataset of almost half a million people in 68 countries, we introduce the novel results that community mask adherence and community attitudes towards masks are associated with a reduction in COVID-19 cases and deaths. Our results have policy implications for reinforcing the need to maintain and encourage mask-wearing by the public, especially in light of some states starting to remove their mask mandates. | epidemiology |
10.1101/2021.01.19.21250140 | Clinical Associations of Functional Dyspepsia with Gastric Dysrhythmia on Electrogastrography: A Comprehensive Systematic Review and Meta-Analysis | BackgroundFunctional dyspepsia (FD) is a common gastroduodenal disorder, yet its pathophysiology remains poorly understood. Bioelectrical gastric slow wave abnormalities are thought to contribute to its multifactorial pathophysiology. Electrogastrography (EGG) has been used to record gastric electrical activity, however the clinical associations require further evaluation.
AimsThis study aimed to systematically assess the clinical associations of EGG in FD.
MethodsMEDLINE, EMBASE, and CENTRAL databases were systematically searched for articles using EGG in adults with FD. Primary outcomes were percentage normal vs abnormal rhythm (bradygastria, normogastria, tachygastria). Secondary outcomes were dominant power, dominant frequency, percentage coupling and the meal responses.
Results1751 FD patients and 555 controls from 47 studies were included. FD patients spent less time in normogastria while fasted (SMD -0.74; 95%CI -1.22 - -0.25) and postprandially (-0.86; 95%CI -1.35 - -0.37) compared to controls. FD patients also spent more fasted time in bradygastria (0.63; 95%CI 0.33 - 0.93) and tachygastria (0.45; 95%CI 0.12 - 0.78%). The power ratio (-0.17; 95%CI -0.83 - 0.48), and dominant frequency meal-response ratio (0.06; 95%CI -0.08 - 0.21) were not significantly different to controls. Correlations between EGG metrics and the presence and timing of FD symptoms were inconsistent. EGG methodologies were diverse and variably applied.
ConclusionAbnormal gastric slow wave rhythms are a consistent abnormality present in FD, as defined by EGG, and therefore likely play a role in pathophysiology. The aberrant electrophysiology identified in FD warrants further investigation, including into underlying mechanisms, associated spatial patterns, and symptom correlations. | gastroenterology |
10.1101/2021.01.19.21250116 | The Association of COVID-19 Incidence with Sport and Face Mask Use in United States High School Athletes | PurposeTo evaluate the influence of sport characteristics and face mask use on COVID-19 incidence among high school athletes.
MethodsSurveys were distributed to high school athletic directors throughout the United States regarding sport re-initiation, COVID-19 cases, and risk reduction procedures in fall 2020.
Separate mixed effects Poisson regression models were developed to evaluate the associations between reported COVID-19 incidence and 1) sport characteristics (contact/non-contact, individual/team, indoor/outdoor) and 2) face mask use while playing (yes/no).
Results991 schools had restarted fall sports, representing 152,484 athletes on 5,854 teams. 2,565 cases of COVID-19 were reported, representing a case rate of 1,682 cases per 100,000 athletes and an incidence rate of 24.6 cases per 100,000 player-days. COVID-19 incidence was lower among outdoor versus indoor sports (incidence rate ratio [IRR]=0.54, 95% CI=0.49-0.60, p<0.001) and non-contact versus contact sports (IRR=0.78 [0.70-0.87], p<0.001), but not team versus individual sports (IRR=0.96 [0.84-1.1], p=0.49). Face mask use was associated with a decreased incidence in girls volleyball (IRR=0.53 [0.37-0.73], p<0.001), boys basketball (IRR=0.53 [0.33-0.83], p=0.008) and girls basketball (IRR=0.36 [0.19-0.63], p<0.001), and approached statistical significance in football (IRR=0.79 [0.59-1.04], p=0.10) and cheer/dance (IRR=0.75 [0.53-1.03], p=0.081).
ConclusionsIn this nationwide survey of US high school athletic directors representing 152,484 athletes, lower COVID-19 incidence was independently associated with participation in outdoor versus indoor and non-contact versus contact sports, but not team versus individual sports. Face mask use was associated with decreased COVID-19 incidence among indoor sports, and may be protective among outdoor sports with prolonged close contact between participants. | sports medicine |
10.1101/2021.01.13.21249779 | Evaluating the Long-Term Efficacy of COVID-19 Vaccines | Large-scale deployment of safe and durably effective vaccines can curtail the COVID-19 pandemic.1-3 However, the high vaccine efficacy (VE) reported by ongoing phase 3 placebo-controlled clinical trials is based on a median follow-up time of only about two months4-5 and thus does not pertain to long-term efficacy. To evaluate the duration of protection while allowing trial participants timely access to efficacious vaccine, investigators can sequentially cross participants over from the placebo arm to the vaccine arm according to priority groups. Here, we show how to estimate potentially time-varying placebo-controlled VE in this type of staggered vaccination of participants. In addition, we compare the performance of blinded and unblinded crossover designs in estimating long-term VE.
Authors InformationDan-Yu Lin, Ph.D., is Dennis Gillings Distinguished Professor of Biostatistics, and Donglin Zeng, Ph.D., is Professor of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599-7420, USA. Peter B. Gilbert, Ph.D., is Member, Vaccine and Infectious Disease Division, Fred Hutch, Seattle, WA 98109-1024, USA.
SummaryWe show how to estimate the potentially waning long-term efficacy of COVID-19 vaccines using data from randomized, placebo-controlled clinical trials with staggered enrollment of participants and sequential crossover of placebo recipients. | infectious diseases |
10.1101/2021.01.13.21249779 | Evaluating the Long-Term Efficacy of COVID-19 Vaccines | Large-scale deployment of safe and durably effective vaccines can curtail the COVID-19 pandemic.1-3 However, the high vaccine efficacy (VE) reported by ongoing phase 3 placebo-controlled clinical trials is based on a median follow-up time of only about two months4-5 and thus does not pertain to long-term efficacy. To evaluate the duration of protection while allowing trial participants timely access to efficacious vaccine, investigators can sequentially cross participants over from the placebo arm to the vaccine arm according to priority groups. Here, we show how to estimate potentially time-varying placebo-controlled VE in this type of staggered vaccination of participants. In addition, we compare the performance of blinded and unblinded crossover designs in estimating long-term VE.
Authors InformationDan-Yu Lin, Ph.D., is Dennis Gillings Distinguished Professor of Biostatistics, and Donglin Zeng, Ph.D., is Professor of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599-7420, USA. Peter B. Gilbert, Ph.D., is Member, Vaccine and Infectious Disease Division, Fred Hutch, Seattle, WA 98109-1024, USA.
SummaryWe show how to estimate the potentially waning long-term efficacy of COVID-19 vaccines using data from randomized, placebo-controlled clinical trials with staggered enrollment of participants and sequential crossover of placebo recipients. | infectious diseases |
10.1101/2021.01.13.21249779 | Evaluating the Long-Term Efficacy of COVID-19 Vaccines | Large-scale deployment of safe and durably effective vaccines can curtail the COVID-19 pandemic.1-3 However, the high vaccine efficacy (VE) reported by ongoing phase 3 placebo-controlled clinical trials is based on a median follow-up time of only about two months4-5 and thus does not pertain to long-term efficacy. To evaluate the duration of protection while allowing trial participants timely access to efficacious vaccine, investigators can sequentially cross participants over from the placebo arm to the vaccine arm according to priority groups. Here, we show how to estimate potentially time-varying placebo-controlled VE in this type of staggered vaccination of participants. In addition, we compare the performance of blinded and unblinded crossover designs in estimating long-term VE.
Authors InformationDan-Yu Lin, Ph.D., is Dennis Gillings Distinguished Professor of Biostatistics, and Donglin Zeng, Ph.D., is Professor of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27599-7420, USA. Peter B. Gilbert, Ph.D., is Member, Vaccine and Infectious Disease Division, Fred Hutch, Seattle, WA 98109-1024, USA.
SummaryWe show how to estimate the potentially waning long-term efficacy of COVID-19 vaccines using data from randomized, placebo-controlled clinical trials with staggered enrollment of participants and sequential crossover of placebo recipients. | infectious diseases |
10.1101/2021.01.21.20240887 | The psychosocial impact of the COVID-19 pandemic on 4,378 UK healthcare workers and ancillary staff: initial baseline data from a cohort study collected during the first wave of the pandemic. | ObjectivesThis study reports preliminary findings on the prevalence of, and factors associated with, mental health and wellbeing outcomes of healthcare workers during the early months (April-June) of the COVID-19 pandemic in the UK.
MethodsPreliminary cross-sectional data were analysed from a cohort study (n=4,378). Clinical and non-clinical staff of three London-based NHS Trusts (UK), including acute and mental health Trusts, took part in an online baseline survey. The primary outcome measure used is the presence of probable common mental disorders (CMDs), measured by the General Health Questionnaire (GHQ-12). Secondary outcomes are probable anxiety (GAD-7), depression (PHQ-9), Post-Traumatic Stress Disorder (PTSD) (PCL-6), suicidal ideation (CIS-R), and alcohol use (AUDIT). Moral injury is measured using the Moray Injury Event Scale (MIES).
ResultsAnalyses showed substantial levels of CMDs (58.9%, 95%CI 58.1 to 60.8), and of PTSD (30.2%, 95%CI 28.1 to 32.5) with lower levels of depression (27.3%, 95%CI 25.3 to 29.4), anxiety (23.2%, 95%CI 21.3 to 25.3), and alcohol misuse (10.5%, 95%CI, 9.2 to 11.9). Women, younger staff, and nurses tended to have poorer outcomes than other staff, except for alcohol misuse. Higher reported exposure to moral injury (distress resulting from violation of ones moral code) was strongly associated with increased levels of CMDs, anxiety, depression, PTSD symptoms, and alcohol misuse.
ConclusionsOur findings suggest that mental health support for healthcare workers should consider those demographics and occupations at highest risk. Rigorous longitudinal data are needed in order to respond to the potential long-term mental health impacts of the pandemic.
HighlightsO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LILarge-scale population studies report increased prevalence of depression, anxiety, and psychological distress during the COVID-19 pandemic.
C_LIO_LIEvidence from previous epidemics indicates a high and persistent burden of adverse mental health outcomes among healthcare workers.
C_LI
What are the new findings?O_LISubstantial levels of probable common mental disorders and post-traumatic stress disorder were found among healthcare workers.
C_LIO_LIGroups at increased risk of adverse mental health outcomes included women, nurses, and younger staff, as well as those who reported higher levels of moral injury.
C_LI
How might this impact on policy or clinical practice in the foreseeable future?O_LIThe mental health offering to healthcare workers must consider the interplay of demographic, social, and occupational factors.
C_LIO_LIAdditional longitudinal research that emphasises methodological rigor, namely with use of standardised diagnostic interviews to establish mental health diagnoses, is necessary to better understand the mental health burden, identify those most at risk, and provide appropriate support without pathologizing ordinary distress responses.
C_LI | psychiatry and clinical psychology |
10.1101/2021.01.20.21250177 | Prevalence of malnutrition among children at primary cleft surgery: A cross-sectional analysis of a global database | BackgroundOrofacial clefts are common birth defects requiring prompt feeding support and timely surgery. Little information exists about the impact of inadequate care provision in poor-resource settings. We aimed to estimate the burden of malnutrition in children from 101 low- and middle-income countries (LMICs) using cleft surgery records collected by one cleft NGO.
MethodsWe conducted a cross-sectional study using anonymised records of children [≤]5 years who underwent cleft surgery between 2008 and 2018. The data included birth date, gender, weight at surgery, ethnicity, country of origin, and date of primary surgery and was analysed using descriptive statistics. The prevalence of malnutrition was derived from the generation of weight-for-age z scores and described in relation to cleft type, gender, and ethnicity/geography. For purpose of comparison, the most recent prevalence estimates for underweight in children under-5 were extracted from publicly available national surveys.
FindingsThe analysis included 602,568 children. The overall prevalence of underweight at the time of primary cleft surgery was 28{middle dot}6% - a figure well above the global underweight prevalence in under-5 children without cleft estimated at about 13{middle dot}5%. The prevalence of underweight varied with the age at primary surgery and the type of cleft, as well as with gender, ethnicity, and region of origin, and was positively correlated with country-specific estimates of underweight prevalence in children without cleft.
InterpretationOur findings support the need for advancing universal health coverage with special efforts to increase timely nutrition care and access to surgery for the most disadvantaged children.
FundingNone.
Research in contextO_ST_ABSEvidence before this studyC_ST_ABSRegardless of the setting, infants born with an orofacial cleft have a heightened risk of failure to thrive (FTT), especially when their ability to suck and swallow is compromised.(1-3) Timely identification of feeding problems and appropriate nutrition support are essential to ensure healthy child development.(4-6) Limited access to (specialist) care in LMICs increases the risk of FTT in babies with unrepaired cleft, yet limited research has described the extent of the problem in these settings.
We searched Medline and Google Scholar up to April 2020 for studies that estimated the scale of malnutrition in children with cleft born in limited-resource settings. A 2019 systematic review of the literature identified seven cross-sectional or case-control studies conducted in LMICs (three in Africa(7-9), three in Latin America(10-12), one in Iran(13)).(14) We excluded one study in Brazil(10) which did not estimate undernutrition and found one additional cross-sectional study from South Africa.(15) Overall, seven hospital-based studies published between 1999 and 2017 included a total of 2,300 children <5 years old. They all provided evidence of malnutrition in this population, yet none was designed to give a global prevalence estimate.
Added value of this studyThis study is the first that attempted to provide a global prevalence estimate of malnutrition in children with unrepaired cleft in LMICs. Using pre-surgery clinical records from over 600,000 of patients operated by Smile Trains global partners, we identified underweight in 28{middle dot}6% of children [≤]5 years. Country-specific figures ranging from 6{middle dot}9% in Kazakhstan to 48{middle dot}2% in Chad were above national statistics on the prevalence of underweight in children in the general populations. Cleft epidemiology contributes to variations in malnutrition rates across LMIC settings but do not explain health disparities between children with cleft and those without cleft within countries.
Implications of all the available evidenceThere is an urgent need to identify and/or address the barriers that prevent children with cleft from receiving immediate feeding and nutritional support and timely reparative surgery. Current health services and nutrition programmes in LMICs should consider opportunities to help meet the health care needs of these children. Poor early-life nutrition has well-documented detrimental consequences on child physical, functional, and cognitive development. Accordingly, a higher prevalence of malnutrition in children born with a cleft means that this population likely experiences higher rates of morbidity and mortality - even if they are eventually operated. | nutrition |
10.1101/2021.01.21.21250117 | Symptoms of anxiety and depression in relation to work patterns during the first wave of the COVID-19 epidemic in Philadelphia PA: a cross-sectional survey | ObjectiveWe investigated whether patterns of work during COVID-19 pandemic altered by effort to contain the outbreak affected anxiety and depression.
MethodsWe conducted a cross-sectional online survey of 911 residents of Philadelphia, inquiring about their working lives during early months of the epidemic, symptoms of anxiety and depression, plus demographics, perceived sources of support, and general health.
ResultsOccupational contact with suspected COVID-19 cases was associated with anxiety. Concerns about return to work, childcare, lack of sick leave, and loss/reduction in work correlated with anxiety and depression, even when there was no evidence of occupational contact with infected persons; patterns differed by gender.
ConclusionsHeightened anxiety and depression during COVID-19 pandemic can be due to widespread disruption of working lives, especially in "non-essential" low-income industries, on par with experience in healthcare.
The significance to clinical practice of the information being presented: Anxiety and depression symptoms that emerged during COVID-19 pandemic may be related to disruption of working lives even among people who are not the "essential" workers with one-one-one contact with infected persons. Clinicians may find this evidence of occupational correlates and articulated specific worries useful in treating such patients. | occupational and environmental health |
10.1101/2021.01.20.21249888 | Exploring support needs of people living with diabetes during the coronavirus COVID-19 pandemic: insights from a UK survey. | BackgroundThe coronavirus COVID-19 pandemic has radically compromised healthcare for people living with chronic conditions such as diabetes. Government-imposed restrictions to contain the spread of the virus has forced people to suddenly adjust their lifestyle. This study aimed to capture the impact of the pandemic on people living with diabetes and the views of these individuals on ways in which the information, advice and support they are receiving could be improved.
Research design and methodsAn online anonymous survey was distributed across the UK during the first lockdown and initial easing. The survey comprised questions about confidence in diabetes self-management, resources used to obtain information, advice and support, and opinions on how these could be improved. Open-ended captured subjective experiences.
ResultsThe survey was completed by 773 adults living with diabetes (69.2% type 1, 28.5% type 2). There was notable variability in the impact of the pandemic on confidence in self-management, with confidence having deteriorated most commonly in the ability to take care of own mental wellbeing (37.0% respondents) and improved most commonly in maintaining a healthy weight (21.1% respondents). 41.2% of respondents living alone reported not receiving any outside support. The quality of information, advice and support received from the healthcare team was rated poorly by 37.2%. Respondents sought greater communication and tailored advice from their care team, clear and consistent information from the government and news channels, and improved understanding of diabetes and its challenges from their personal networks and employers.
ConclusionAdjusting to the COVID-19 pandemic has strained the mental health and wellbeing of people living with diabetes. Diabetes care teams must receive assistance to support these individuals without risking further inequalities in access to healthcare. Equipping personal networks and employers with knowledge on diabetes and skills to support self-management may reduce the burden on the NHS.
O_TEXTBOXSignificance of this study
O_LIWhat is already known about this subject?
O_LIThe COVID-19 pandemic has posed multiple challenges to the everyday life of people across the world.
C_LIO_LIPeople living with diabetes mellitus, particularly those with poor blood glucose are more vulnerable to developing the severe outcomes of COVID-19.
C_LIO_LINHS prioritisation of COVID-19 has disrupted the availability of care for patients with chronic health conditions, including diabetes mellitus.
C_LI
C_LIO_LIWhat are the new findings?
O_LIThe pandemic generated a decrease in confidence in diabetes self-management, particularly regarding mental wellbeing (37.0%) and adhering to physical activity recommendations (32.0%) and a healthy eating pattern (29.6%). Greater access to the healthcare team and services, strategies to adjust self-care (with greater focus on mental health) and more external support are deemed as important to reinstate diabetes self-management.
C_LIO_LICancellation of appointments reduced patients access to knowledge on their glucose control and their confidence in diabetes self-management, it generated difficulties in switching between treatments and resulted in impoverished mental health and motivation to self-manage.
C_LIO_LI41.2% of respondents living alone report not receiving support from outside their household.
C_LIO_LIQuality of information, advice and support received from the government and healthcare teams were perceived most poorly (% of respondents giving a rating of poor or very poor: 39.0% and 37.2% respectively). There is a request for greater transparency, higher quality information, improved contact, and an increased understanding of the condition by others.
C_LI
C_LIO_LIHow might these results change the focus of research or clinical practice?
O_LIThere is a need to ensure equitable contact between healthcare teams and their patients, both for diabetes self-management and overall wellbeing.
C_LIO_LIA shift to remote consultations should include training practitioners to detect emotional distress in patients and the ability to refer patients to NHS or community-led mental health support.
C_LIO_LIA collective effort is needed to produce more stratified and consistent guidance, with clear messaging to minimise uncertainty and distress.
C_LIO_LIFurther research and policy are needed to help patients identify a support network outside their direct care team and equip them with the knowledge and skills to provide adequate support.
C_LIO_LIGreater understanding on how some individuals were able to adjust their self-management successfully could assist care teams, relevant charities and policy makers to provide better support for those individuals who are struggling.
C_LI
C_LI
C_TEXTBOX | health policy |
10.1101/2021.01.21.21249640 | Early detection of SARS-CoV-2 infection cases or outbreaks at nursing homes by targeted wastewater tracking | ObjectivesNear-source tracking of SARS-CoV-2 RNA in the sewage drains serving particular buildings may allow rapid identification of SARS-CoV-2 infection cases or local outbreaks. In this pilot study, we investigated whether this was the case for nursing homes (NH).
MethodsThe study involved five NH (from A to E) affiliated to the Clinico-Malvarrosa Health Department, Valencia (Spain). These were nursing or mixed nursing/care homes of different sizes, altogether providing care for 472 residents attended by a staff of 309. Near-source sewage samples were screened for presence of SARS-CoV-2 RNA by RT-qPCR at least 5 days per week during the study period. SARS-CoV-2 RNA testing in nasopharyngeal swabs from residents and staff was performed with the TaqPath COVID-19 Combo Kit (Thermo Fisher Scientific, Massachusetts, USA).
ResultsSARS-CoV-2 RNA was detected in wastewater samples from four of the five NH. SARS-CoV-2 infection cases were documented in three of these four NH. Of the two NH without SARS-CoV-2 infection cases, no SARS-CoV-2 RNA was detected in sewer samples from one facility, while it was repeatedly detected in samples from the other. Presence of SARS-CoV-2 RNA in sewage preceded identification of isolated cases among residents or staff or outbreak declaration in two NH, with lag times ranging from 5 to 19 days.
ConclusionOur study demonstrated that intermittent or persistent detection of SARS-CoV-2 RNA in NH sewers can provide an early warning of subsequent individual cases or outbreaks in these facilities. | infectious diseases |
10.1101/2021.01.13.20202200 | Extending influenza surveillance to detect non-influenza respiratory viruses of public health relevance: analysis of surveillance data, 2015-2019, Belgium | BACKGROUNDSeasonal influenza-like illness (ILI) affects millions of people yearly. Severe acute respiratory infections (SARI), mainly caused by influenza, are a leading cause of hospitalisation and mortality. Increasing evidence indicates that non-influenza respiratory viruses (NIRVs) also contribute to the burden of SARI. In Belgium, SARI surveillance by a network of sentinel hospitals is ongoing since 2011.
AIMHere, we report the results of using in-house multiplex PCRs for the detection of a flexible panel of viruses in respiratory ILI and SARI samples and the estimated incidence rates of SARI associated to each virus.
METHODSILI was defined as an infection with onset of fever and cough or dyspnoea. SARI was defined as an infection requiring hospitalization with onset of fever and cough or dyspnoea within the previous 10 days. Samples were collected during four winter seasons and tested by multiplex RT-qPCRs for influenza virus and NIRVs. Using catchment population estimates, incidence rates of SARI associated to each virus were calculated.
RESULTSOne third of the SARI cases were positive for NIRVs, reaching 49.4% among children under fifteen. In children under five, incidence rates of NIRV-associated SARI were double that of influenza (103.4 versus 57.6 per 100000 person-months), with NIRV co-infections, respiratory syncytial viruses, human metapneumoviruses and picornaviruses contributing the most (33.1, 13.6, 15.8 and 18.2 per 100000 person-months, respectively).
CONCLUSIONEarly testing for NIRVs could be beneficial to clinical management of SARI patients, especially in children under five, for whom the burden of NIRV-associated disease exceeds that of influenza. | infectious diseases |
10.1101/2021.01.20.21250158 | REACT-1 round 8 interim report: SARS-CoV-2 prevalence during the initial stages of the third national lockdown in England | BackgroundHigh prevalence of SARS-CoV-2 virus in many northern hemisphere populations is causing extreme pressure on healthcare services and leading to high numbers of fatalities. Even though safe and effective vaccines are being deployed in many populations, the majority of those most at-risk of severe COVID-19 will not be protected until late spring, even in countries already at a more advanced stage of vaccine deployment.
MethodsThe REal-time Assessment of Community Transmission study-1 (REACT-1) obtains throat and nose swabs from between 120,000 and 180,000 people in the community in England at approximately monthly intervals. Round 8a of REACT-1 mainly covers a period from 6th January 2021 to 15th January 2021. Swabs are tested for SARS-CoV-2 virus and patterns of swab-positivity are described over time, space and with respect to individual characteristics. We compare swab-positivity prevalence from REACT-1 with mobility data based on the GPS locations of individuals using the Facebook mobile phone app. We also compare results from round 8a with those from round 7 in which swabs were collected from 13th November to 24th November (round 7a) and 25th November to 3rd December 2020 (round 7b).
ResultsIn round 8a, we found 1,962 positives from 142,909 swabs giving a weighted prevalence of 1.58% (95% CI, 1.49%, 1.68%). Using a constant growth model, we found no strong evidence for either growth or decay averaged across the period; rather, based on data from a limited number of days, prevalence may have started to rise at the end of round 8a. Facebook mobility data showed a marked decrease in activity at the end of December 2020, followed by a rise at the start of the working year in January 2021. Between round 7b and round 8a, prevalence increased in all adult age groups, more than doubling to 0.94% (0.83%, 1.07%) in those aged 65 and over. Large household size, living in a deprived neighbourhood, and Black and Asian ethnicity were all associated with increased prevalence. Both healthcare and care home workers, and other key workers, had increased odds of swab-positivity compared to other workers.
ConclusionDuring the initial 10 days of the third COVID-19 lockdown in England in January 2021, prevalence of SARS-CoV-2 was very high with no evidence of decline. Until prevalence in the community is reduced substantially, health services will remain under extreme pressure and the cumulative number of lives lost during this pandemic will continue to increase rapidly. | infectious diseases |
10.1101/2021.01.21.21250230 | Redeployment and training of healthcare professionals to Intensive Care during COVID-19: a systemic review | BackgroundA rapid influx of patients to intensive care and infection control measures during the COVID-19 pandemic required the rapid development of innovative redeployment and training strategies.
MethodsWe conducted a systematic search of 9 databases including key terms related to intensive care AND training AND redeployment AND healthcare workers. Analysis consisted of a narrative synthesis of quantitative study outputs, and a framework-based thematic analysis of qualitative study outputs and grey literature. These results were then combined applying an interpretative synthesis.
ResultsTwenty papers were analysed. These took place primarily in the UK (N=8, 40%) and USA (N=5, 25%). Themes included in the results are Redeployment: Implementation strategies and learnings; Redeployed staff experience and strategies to address their needs; Redeployed staff learning needs; Training formats offered and training evaluations; and Future redeployment and training concerns. Some of the redeployment implementation and training strategies documented in this review are: Skills-based redeployment, buddy support systems, and agreeing on locally-specific principles, rather than strict procedures.
ConclusionThe COVID-19 pandemic presented unique challenges to deliver training promptly while following infection control recommendations and develop flexible redeployment strategies. This study synthesises original approaches to tackle these challenges which are relevant to inform the development of targeted and adaptative training and redeployment plans. | intensive care and critical care medicine |
10.1101/2021.01.21.21250230 | Redeployment and training of healthcare professionals to Intensive Care during COVID-19: a systematic review | BackgroundA rapid influx of patients to intensive care and infection control measures during the COVID-19 pandemic required the rapid development of innovative redeployment and training strategies.
MethodsWe conducted a systematic search of 9 databases including key terms related to intensive care AND training AND redeployment AND healthcare workers. Analysis consisted of a narrative synthesis of quantitative study outputs, and a framework-based thematic analysis of qualitative study outputs and grey literature. These results were then combined applying an interpretative synthesis.
ResultsTwenty papers were analysed. These took place primarily in the UK (N=8, 40%) and USA (N=5, 25%). Themes included in the results are Redeployment: Implementation strategies and learnings; Redeployed staff experience and strategies to address their needs; Redeployed staff learning needs; Training formats offered and training evaluations; and Future redeployment and training concerns. Some of the redeployment implementation and training strategies documented in this review are: Skills-based redeployment, buddy support systems, and agreeing on locally-specific principles, rather than strict procedures.
ConclusionThe COVID-19 pandemic presented unique challenges to deliver training promptly while following infection control recommendations and develop flexible redeployment strategies. This study synthesises original approaches to tackle these challenges which are relevant to inform the development of targeted and adaptative training and redeployment plans. | intensive care and critical care medicine |
10.1101/2021.01.20.21249656 | Clinical prediction rule for SARS-CoV-2 infection from 116 U.S. emergency departments | ObjectivesAccurate and reliable criteria to rapidly estimate the probability of infection with the novel coronavirus-2 that causes the severe acute respiratory syndrome (SARS-CoV-2) and associated disease (COVID-19) remain an urgent unmet need, especially in emergency care. The objective was to derive and validate a clinical prediction rule for SARS-CoV-2 infection that uses simple criteria widely available at the point of care.
MethodsData came from the Registry data from the national REgistry of suspected COVID-19 in EmeRgency care (RECOVER network) comprising 116 hospitals from 25 states in the US. Clinical predictors and 30-day outcomes were abstracted from medical records of 19,850 emergency department (ED) patients tested for SARS-CoV-2. The criterion standard for diagnosis of SARS-CoV-2 required a positive molecular test from a swabbed sample or positive antibody testing within 30 days. The prediction rule was derived from a 50% random sample (n=9,925) using unadjusted analysis of 107 candidate variables as a screening step, followed by stepwise forward logistic regression on 72 variables.
ResultsMultivariable regression yielded a 13-variable score, which was simplified to 13-point rule: +1 point each for age>50 years, measured temperature>37.5{degrees}C, oxygen saturation<95%, Black race, Hispanic or Latino ethnicity, household contact with known or suspected COVID-19, patient reported history of dry cough, anosmia/dysgeusia, myalgias or fever; and -1 point each for White race, no direct contact with infected person, or smoking. In the validation sample (n=9,975), the score produced an area under the receiver operating character curve of 0.80 (95% CI: 0.79-0.81), and this level of accuracy was retained across patients enrolled from the early spring to summer of 2020. In the simplified rule, a score of zero produced a sensitivity of 95.6% (94.8-96.3%), specificity of 20.0% (19.0-21.0%), likelihood ratio negative of 0.22 (0.19-0.26). Increasing points on the simplified rule predicted higher probability of infection (e.g., >75% probability with +5 or more points).
ConclusionCriteria that are available at the point of care can accurately predict the probability of SARS-CoV-2 infection. These criteria could assist with decision about isolation and testing at high throughput checkpoints.
Key pointsO_ST_ABSQuestionC_ST_ABSCan clinical criteria, derived solely from interview and vital signs accurately estimate the probability of infection from the novel coronavirus (SARS-CoV-2) that causes COVID-19?
FindingsFrom derivation sample (n=9,925), we derived a set of 13 clinical criteria that produced an area under the receiver operating characteristic curve of 0.80 (0.79-0.81) in a validation sample (n=9,925). At a score of zero, the simplified version of the criteria produced sensitivity of 95.6% (94.8 to 96.3%), and specificity of 20.0% (19.0 to 21.0%).
MeaningClinical criteria can estimate the probability of SARS-CoV-2 infection. | emergency medicine |
10.1101/2021.01.16.21249956 | Clinical effectiveness of convalescent plasma in hospitalized patients with COVID-19: a systematic review and meta-analysis | Given the variability of previously reported results, this systematic review aims to determine the clinical effectiveness of convalescent plasma employed in the treatment of hospitalized patients with diagnosis of COVID-19.
We conducted a systematic review of controlled clinical trials assessing treatment with convalescent plasma for hospitalized patients with a diagnosis of SARS-CoV-2 infection. The outcomes were mortality, clinical improvement, and ventilation requirement.
A total of 50 studies were retrieved from the databases. Four articles were finally included in the data extraction, qualitative and quantitative synthesis of results. The meta-analysis suggests that there is no benefit of convalescent plasma compared to standard care or placebo in the reduction of the overall mortality and in the ventilation requirement; but there could be a benefit for the clinical improvement in patients treated with plasma.
We can conclude that the convalescent plasma transfusion cannot reduce the mortality or ventilation requirement in hospitalized patients diagnosed with SARS-CoV-2 infection. More controlled clinical trials conducted with methodologies that ensure a low risk of bias are still needed. | epidemiology |
10.1101/2021.01.21.20245795 | Longitudinal trends and risk factors for depressed mood among Canadian adults during the first wave of COVID-19 | AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBO_SCPLOWACKGROUNDC_SCPLOWC_ST_ABSThe COVID-19 pandemic has raised serious concerns about the mental health impact of people directed and indirectly affected by the virus. Because this is a rapidly evolving situation, our goal was to explore potential risk factors and trends in feelings of anxiety and depression among the general population in Canada over the first five months of the pandemic.
MO_SCPLOWETHODSC_SCPLOWWe completed on-line surveys of 3,127 unique individuals representative of the Canadian general population at 4 discreet periods every 6 weeks from April 15th to July 28th 2020. We assessed feelings of anxiety, depression and loss of interest with the interRAI self-reported mood scale using a multivariable generalized estimating equation model to examine factors associated with having a 5+ score on the scale (indicating potentially depressed mood). We also investigated potential longitudinal trends to examine temporal changes in mood scores.
RO_SCPLOWESULTSC_SCPLOWMore than 30% of participants felt highly anxious, depressed, and disinterested in everyday activities in the first survey (April), but this number decreased to about 20% over 4 months. Feeling lonely, younger age, feeling overwhelmed by ones health needs, having financial concerns, and living outside of Quebec were significantly associated with depressed mood.
IO_SCPLOWNTERPRETATIONC_SCPLOWThe prevalence of depressed mood during the pandemic was between 2 and 3 times the pre-pandemic rate (especially among young people), but it can change rapidly in response to social changes. Thus, monitoring of psychological distress among vulnerable groups that may benefit from additional supports should be a priority. | epidemiology |
10.1101/2021.01.20.21249905 | A cross-sectional analysis of demographic and behavioral risk factors of SARS-CoV-2 antibody positivity among a sample of U.S. college students | BackgroundColleges and universities across the United States are developing and implementing data-driven prevention and containment measures against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Identifying risk factors for SARS-CoV-2 seropositivity could help to direct these efforts.
ObjectiveTo estimate the associations between demographic factors and social behaviors and SARS-CoV-2 seropositivity and self-reported positive SARS-CoV-2 diagnostic test.
MethodsIn September 2020, we randomly sampled Indiana University Bloomington (IUB) undergraduate students. Participants completed a cross-sectional, online survey about demographics, SARS-CoV-2 testing history, relationship status, and risk behaviors. Additionally, during a subsequent appointment, participants were tested for SARS-CoV-2 antibodies using a fingerstick procedure and SARS-CoV-2 IgM/IgG rapid assay kit. We used unadjusted modified Poisson regression models to evaluate the associations between predictors of both SARS-CoV-2 seropositivity and self-reported positive SARS-CoV-2 infection history.
ResultsOverall, 1,076 students were included in the serological testing analysis, and 1,239 students were included in the SARS-CoV-2 infection history analysis. Current seroprevalence of SARS-CoV-2 was 4.6% (95% CI: 3.3%, 5.8%). Prevalence of self-reported SARS-CoV-2 infection history was 10.3% (95% CI: 8.6%, 12.0%). Greek membership, having multiple romantic partners, knowing someone in ones immediate environment with SARS-CoV-2 infection, drinking alcohol more than 1 day per week, and hanging out with more than 4 people when drinking alcohol increased both the likelihood of seropositivity and SARS-CoV-2 infection history.
ConclusionOur findings have implications for American colleges and universities and could be used to inform SARS-C0V-2 prevention and control strategies on such campuses. | epidemiology |
10.1101/2021.01.21.21250252 | Age-dependent heterogeneity of lymph node metastases and survival: A population-based study. | BackgroundFor several cancers, including those of the breast, young age at diagnosis is associated with an adverse prognosis. Although this effect is often attributed to heritable mutations such as BRCA1/2, the relationship between pathologic features, young age of onset, and prognosis for breast cancer remains unclear. In the present study, we highlight links between age of onset and lymph node metastasis (NM) in US women with breast cancer.
MethodsCase listings from Surveillance, Epidemiology, and End Result (SEER) 18 registry data for women with breast cancer, which include information on race, were used. NM and its associated outcomes were evaluated for a subset of women with receptor subtype information and then compared against a larger, pre-subtype validation set of data from the same registry. Age of diagnosis was a 5-category variable; under 40 years, 40-49 years, 50-59 years, 60-69 years and 70+ years. Univariate and adjusted multivariate survival models were applied to both sets of data.
ResultsAs determined with adjusted logistic regression models, women under 40 years old at diagnosis had 1.55 times the odds of NM as women 60-69 years of age. The odds of NM for (HR = hormone receptor) HR+/HER2+, HR-/HER2+, and triple-negative breast cancer subtypes were significantly lower than those for HR+/HER2-. In subtype-stratified adjusted models, age of diagnosis had a consistent trend of decreasing odds of NM by age category, most noticeable for HR+ subtypes of luminal A and B. Univariate 5-year survival by age was worst for women under 40 years, with NM attributable for 49% of the hazard of death from cancer in adjusted multivariate models.
ConclusionsLymph node metastasis is age-dependent, yet not all molecular subtypes are clearly affected by this relationship. For <40-yr-old women, NM is a major cause for shorter survival. When stratified by subtype, the strongest associations were in HR+ groups, suggesting a possible hormonal connection between young age of breast cancer onset and NM. | epidemiology |
10.1101/2021.01.21.21250252 | Age-dependent heterogeneity of lymph node metastases and survival in breast cancer: A population-based study. | BackgroundFor several cancers, including those of the breast, young age at diagnosis is associated with an adverse prognosis. Although this effect is often attributed to heritable mutations such as BRCA1/2, the relationship between pathologic features, young age of onset, and prognosis for breast cancer remains unclear. In the present study, we highlight links between age of onset and lymph node metastasis (NM) in US women with breast cancer.
MethodsCase listings from Surveillance, Epidemiology, and End Result (SEER) 18 registry data for women with breast cancer, which include information on race, were used. NM and its associated outcomes were evaluated for a subset of women with receptor subtype information and then compared against a larger, pre-subtype validation set of data from the same registry. Age of diagnosis was a 5-category variable; under 40 years, 40-49 years, 50-59 years, 60-69 years and 70+ years. Univariate and adjusted multivariate survival models were applied to both sets of data.
ResultsAs determined with adjusted logistic regression models, women under 40 years old at diagnosis had 1.55 times the odds of NM as women 60-69 years of age. The odds of NM for (HR = hormone receptor) HR+/HER2+, HR-/HER2+, and triple-negative breast cancer subtypes were significantly lower than those for HR+/HER2-. In subtype-stratified adjusted models, age of diagnosis had a consistent trend of decreasing odds of NM by age category, most noticeable for HR+ subtypes of luminal A and B. Univariate 5-year survival by age was worst for women under 40 years, with NM attributable for 49% of the hazard of death from cancer in adjusted multivariate models.
ConclusionsLymph node metastasis is age-dependent, yet not all molecular subtypes are clearly affected by this relationship. For <40-yr-old women, NM is a major cause for shorter survival. When stratified by subtype, the strongest associations were in HR+ groups, suggesting a possible hormonal connection between young age of breast cancer onset and NM. | epidemiology |
10.1101/2021.01.21.21250245 | Incentivizing Multiple Objectives in Active Surveillance for Urban Disease Vectors | Large-scale vector control campaigns have successfully reduced infectious disease incidence around the world. In addition to preventing new infections, these campaigns produce a wealth of information about the distribution and density of insect vectors, which can be incorporated into risk maps. These maps can effectively communicate risk map data to technicians on the ground, although encouraging them to use the data remains a challenge. We carried out a series of rolling trials in which we evaluated risk map use under different incentive schemes. Participants in the studies were trained field technicians tasked with house-to-house surveillance for insect vectors of Chagas disease in Arequipa, Peru. A novel incentive scheme based on poker best achieved a dual objective: to encourage technicians to preferentially visit higher-risk houses while surveilling evenly across the search zone. The poker incentive structure may be well-suited to improve entomological surveillance activities and other complex multi-objective tasks. | epidemiology |
10.1101/2021.01.21.21250251 | Air passenger travel and international surveillance data predict spatiotemporal variation in measles importations to the United States | Measles incidence in the United States has grown dramatically, as vaccination rates are declining and transmission internationally is on the rise. Measles virus is highly infectious and can cause severe symptoms and even death. Because imported cases are necessary drivers of outbreaks in non-endemic settings, predicting measles outbreaks in the US depends on predicting imported cases. To assess the predictability of imported measles cases, we performed a regression of imported measles cases in the US against an inflow variable that combines air travel data with international measles surveillance data. To understand the contribution of each data type to these predictions, we repeated the regression analysis with alternative versions of the inflow variable that replaced each data type with averaged values and with versions of the inflow variable that used modeled inputs. We assessed the performance of these regression models using correlation, coverage probability, and area under the curve statistics, including with resampling and cross-validation. Our regression model had good predictive ability with respect to the presence or absence of imported cases in a given state in a given year (AUC = 0.78) and the magnitude of imported cases (Pearson correlation = 0.84). By comparing alternative versions of the inflow variable averaging over different inputs, we found that both air travel data and international surveillance data contribute to the models ability to predict numbers of imported cases, and individually contribute to its ability to predict the presence or absence of imported cases. Predicted sources of imported measles cases varied considerably across years and US states, depending on which countries had high measles activity in a given year. Our results emphasize the importance of the relationship between global connectedness and the spread of measles. | epidemiology |
10.1101/2021.01.21.20228569 | Improving Fabric Face Masks: Impact of Design Features on the Protection Offered by Fabric Face Masks | ObjectiveWith much of the public around the world depending on fabric face masks to protect themselves and others, it is essential to understand how the protective ability of fabric masks can be enhanced. This study evaluated the protection offered by eighteen fabric masks designs. In addition, it assessed the benefit of including three design features: insert filters, surgical mask underlayers, and nose wires.
MethodsQuantitative fit tests were conducted on different masks and with some additional design features. An array of fabric masks were tested on a single participant to account for variability in face shapes. The effects of insert filters, surgical mask underlayers and nose wires were also assessed.
ResultsAs expected, the fabric masks offered low degrees of protection; however, alterations in design showed significant increase in their protective ability. The most effective designs were multi-layered masks that fit tightly to the face and lacked dead space between the user and mask. Also, low air-resistance insert filters and surgical mask underlays provided the greatest increase in protection.
ConclusionsOur findings indicate substantial heterogeneity in the protection offered by various fabric face masks. We also note some design features which may enhance the protection these masks offer. | public and global health |
10.1101/2021.01.21.21250228 | Simulating the impact of different vaccination policies on the COVID-19 pandemic in New York City | PurposeTo analyze potential COVID-19 epidemic outcomes in New York City under different SARS-CoV-2 virus circulation scenarios and vaccine rollout policies from early Jan 2021 to end of June 2021.
Key findingsIn anticipation of the potential arrival and dominance of the more infectious SARS-CoV-2 variant:
O_LIMass-vaccination would be critical to mitigating epidemic severity (26-52% reduction in infections, hospitalizations, and deaths, compared to no vaccination, provided the new UK variant supplants currently circulating variants).
C_LIO_LIPrioritizing key risk groups for earlier vaccination would lead to greater reductions in hospitalizations and deaths than infections. Thus, in general this would be a good strategy.
C_LIO_LICurrent vaccination prioritization policy is suboptimal. To avert more hospitalizations and deaths, mass-vaccination of all individuals 65 years or older should be done as soon as possible. For groups listed in the same phase, 65+ year-olds should be given first priority ahead of others.
C_LIO_LIAvailable vaccine doses should be given to the next priority groups as soon as possible without awaiting hesitant up-stream groups.
C_LIO_LIWhile efficacy of vaccination off-protocol is unknown, provided immune response following a first vaccine dose persists, delaying the 2nd vaccine dose by [~]1 month (i.e. administer the two doses 8 weeks apart) can substantially reduce infections, hospitalizations, and deaths compared to the 3-week apart regimen. Across all scenarios tested here, delaying the 2nd vaccine dose leads to the largest reduction in severe epidemic outcomes (e.g. hospitalizations and deaths). Therefore, to protect as many people as possible, this strategy should be considered if rapid increases in infections, hospitalization or deaths and/or shortages in vaccines were to occur.
C_LI | public and global health |
10.1101/2021.01.20.21250005 | Apolipoprotein E genotype and MRI-detected brain alterations pertaining to neurodegeneration: A systematic review | IntroductionThe effect of apolipoprotein E (APOE) genotype, particularly APOE {varepsilon}4, the main genetic risk factor for late-onset Alzheimers disease (LOAD), has been widely explored in neuroimaging studies pertaining to older adults. The goal of this systematic review was to review the literature on the relationship between carriage of the APOE {varepsilon}4 allele and grey matter (GM) changes across various age groups and its influence on neurodegeneration as evidenced by structural magnetic resonance imaging (MRI).
MethodsA search of the electronic databases Pubmed, Scopus, Ovid and Cochrane was carried out till March 2020. Only studies published in English were included. Risk of bias of each study was assessed using the modified Newcastle-Ottawa Scale.
ResultsA total of 115 articles met the inclusion criteria. Methodological quality varied from poor to good. There is moderate evidence of reduced GM volume in the middle frontal gyrus, precuneus, hippocampus, hippocampal subfields, amygdala, parahippocampal gyrus, middle temporal lobe, whole temporal lobe, temporal pole, and posterior cingulate cortex in APOE {varepsilon}4 carriers.
ConclusionThe present data supports the utility of the hippocampal GM volume to evaluate early structural neurodegenerative changes that occurs in APOE {varepsilon}4 positive elderly individuals who are at increased risk of developing LOAD. Furthermore, the evidence supports serial measurements and comparison of hippocampal volume based on age group, to track the progression of neurodegeneration in APOE {varepsilon}4 carriers. Additional longitudinal studies are necessary to confirm whether the combination of MRI-detected hippocampal atrophy with APOE {varepsilon}4 carrier status, can better predict the development of LOAD in cognitively normal individuals. | radiology and imaging |
10.1101/2021.01.22.21250293 | Plasma biomarkers of Alzheimer's disease predict cognitive decline and could improve clinical trials in the cognitively unimpaired elderly | Plasma biomarkers of amyloid, tau, and neurodegeneration (ATN) need to be characterized in cognitively unimpaired (CU) elderly indviduals. We therefore tested if plasma measurements of amyloid-{beta} (A{beta})42/40, phospho-tau217 (P-tau217), and neurofilament light (NfL) together predict clinical deterioration in 435 CU individuals followed for an average of 4.8 {+/-}1.7 years in the BioFINDER study. A combination of all three plasma biomarkers and basic demographics best predicted change in the cognition (Pre-Alzheimers Clinical Composite; R2=0.14, 95% CI [0.12-0.17]; P<0.0001) and subsequent AD dementia (AUC=0.82, 95% CI [0.77-0.91], P<0.0001). In a simulated clinical trial, a screening algorithm combining all three plasma biomarkers would reduce the required sample size by 70% (95% CI [54-81]; P<0.001) with cognition as trial endpoint, and by 63% (95% CI [53-70], P<0.001) with subsequent AD dementia as trial endpoint. Plasma ATN biomarkers show usefulness in cognitively unimpaired populations and could make large clinical trials more feasible and cost-effective. | neurology |
10.1101/2021.01.21.21250266 | Excess mortality associated with the COVID-19 pandemic among Californians 18-65 years of age, by occupational sector and occupation: March through October 2020 | BackgroundThough SARS-CoV-2 outbreaks have been documented in occupational settings and though there is speculation that essential workers face heightened risks for COVID-19, occupational differences in excess mortality have, to date, not been examined. Such information could point to opportunities for intervention, such as workplace modifications and prioritization of vaccine distribution.
Methods and findingsUsing death records from the California Department of Public Health, we estimated excess mortality among Californians 18-65 years of age by occupational sector and occupation, with additional stratification of the sector analysis by race/ethnicity. During the COVID-19 pandemic, working age adults experienced a 22% increase in mortality compared to historical periods. Relative excess mortality was highest in food/agriculture workers (39% increase), transportation/logistics workers (28% increase), facilities (27%) and manufacturing workers (23% increase). Latino Californians experienced a 36% increase in mortality, with a 59% increase among Latino food/agriculture workers. Black Californians experienced a 28% increase in mortality, with a 36% increase for Black retail workers. Asian Californians experienced an 18% increase, with a 40% increase among Asian healthcare workers. Excess mortality among White working-age Californians increased by 6%, with a 16% increase among White food/agriculture workers.
ConclusionsCertain occupational sectors have been associated with high excess mortality during the pandemic, particularly among racial and ethnic groups also disproportionately affected by COVID-19. In-person essential work is a likely venue of transmission of coronavirus infection and must be addressed through strict enforcement of health orders in workplace settings and protection of in-person workers. Vaccine distribution prioritizing in-person essential workers will be important for reducing excess COVID mortality. | occupational and environmental health |
10.1101/2021.01.21.21250231 | Potential contribution of climate conditions on COVID-19 pandemic transmission over West and North African countries | The COVID-19 disease, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is a very contagious disease that has killed many people around the world. According to the World Health Organization (WHO) data, the spread of the disease appears to be slower in Africa. Although a number of studies have been published on the relationship between meteorological parameters and COVID-19 transmission, the effects of climate conditions on COVID-19 remain largely unexplored and without consensus following the main research finding over Africa (often based on a single country or city). Here, using available epidemiological data over 275 days (i.e., from March 1 to November 30, 2020) taken from the European Center for Disease Prevention and Control of the European Union database and daily data of surface air temperature and humidity from the National Center for Environmental Prediction (NCEP), this paper investigates the potential contributions of climate conditions on COVID-19 transmission over 16 countries selected from three bioclimatic regions of Africa (i.e., Sahel, Maghreb and Gulf of Guinea). On average, our main findings highlight statistically significant inverse correlations between COVID-19 cases and temperature over the Maghreb and the Gulf of Guinea regions, whereas positive correlations are found in the Sahel, especially over the central part including Niger and Mali. Correlations with specific humidity and water vapor parameters display significant and positive values over the Sahelian and the Gulf of Guinean countries and negative values over the Maghreb countries. In other word, results imply that the COVID-19 pandemic transmission is influenced differently across the three bioclimatic regions: i) cold and dry environmental conditions over the Maghreb; ii) warm and humid conditions over the Sahel iii) cold and humid conditions over the Gulf of Guinea. These findings could be useful for decision-makers who plan public health and control measures in affected African countries and would have substantial implications for directing respiratory disease surveillance activities. | occupational and environmental health |
10.1101/2021.01.21.21250199 | Associations between indicators of socioeconomic position and DNA methylation: A systematic review | Socioeconomic position (SEP) is a major determinant of health across the life course. Yet, little is known about the biological mechanisms explaining this relationship. One possible explanation is through an epigenetic process called DNA methylation (DNAm), wherein the socioeconomic environment causes no alteration in the DNA sequence but modifies gene activity, gene expression, and therefore long-term health. To understand the evidence supporting a potential SEP-DNAm link, we performed a systematic review of published empirical findings on the association between SEP (from prenatal development to adulthood) and DNAm measured across the life course, with an eye toward evaluating how the timing, duration, and type of SEP exposure influenced DNAm. Across the 37 studies we identified, there was some evidence for the effect of SEP timing and duration on DNAm, with early-life SEP and persistently low SEP being particularly strong indicators of DNAm. Different indicators of SEP also had some unique associations with DNAm profiles, suggesting that SEP is not a singular concept, but rather that different aspects of the socioeconomic environment can shift DNAm patterns through distinct pathways. These differences with respect to SEP timing, duration, and type were notable because they were detected even among heterogenous study designs. Overall, findings from this review underscore the importance of analyzing SEP timing, duration, and type, given the complex relationship between SEP and DNAm across the lifespan. To guide future research, we highlight current limitations in the literature and propose recommendations for overcoming some of these challenges. | genetic and genomic medicine |
10.1101/2021.01.21.21250243 | Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic strength of methods review | IntroductionAssessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature.
MethodsWe included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26, 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation, assessing what impact evaluation method was used, graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating.
ResultsAfter 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes.
DiscussionThe reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigor to be actionable by policy-makers. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible. | health policy |
10.1101/2021.01.21.21250243 | Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic strength of methods review | IntroductionAssessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature.
MethodsWe included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26, 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation, assessing what impact evaluation method was used, graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating.
ResultsAfter 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes.
DiscussionThe reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigor to be actionable by policy-makers. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible. | health policy |
10.1101/2021.01.21.21250243 | Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic review of evidence strength | IntroductionAssessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature.
MethodsWe included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26, 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation, assessing what impact evaluation method was used, graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating.
ResultsAfter 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes.
DiscussionThe reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigor to be actionable by policy-makers. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible. | health policy |
10.1101/2021.01.21.21250243 | Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic review of study design and evidence strength | IntroductionAssessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature.
MethodsWe included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26, 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation, assessing what impact evaluation method was used, graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating.
ResultsAfter 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes.
DiscussionThe reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigor to be actionable by policy-makers. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible. | health policy |
10.1101/2021.01.21.21250243 | Problems with Evidence Assessment in COVID-19 Health Policy Impact Evaluation (PEACHPIE): A systematic review of study design and evidence strength | IntroductionAssessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature.
MethodsWe included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26, 2020 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and released review guidance for COVID-19 policy impact evaluation, assessing what impact evaluation method was used, graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating.
ResultsAfter 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes.
DiscussionThe reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for inference of sufficient rigor to be actionable by policy-makers. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible. | health policy |
10.1101/2021.01.21.21250240 | Assessing the efficacy of interventions to control indoor SARS-Cov-2 transmission: an agent-based modeling approach | Intervention strategies for minimizing indoor SARS-CoV-2 transmission are often based on anecdotal evidence because there is little evidence-based research to support them. We developed a spatially-explicit agent-based model for simulating indoor respiratory pathogen transmission, and used it to compare effects of four interventions on reducing individual-level SARS-CoV-2 transmission risk by simulating a well-known case study. We found that imposing movement restrictions and efficacious mask usage appear to have the greatest effects on reducing infection risk, but multiple concurrent interventions are required to minimize the proportion of susceptible individuals infected. Social distancing had little effect on reducing transmission if individuals move during the gathering. Furthermore, our results suggest that there is potential for ventilation airflow to expose susceptible people to aerosolized pathogens even if they are relatively far from infectious individuals. Maximizing rates of aerosol removal is the key to successful transmission-risk reduction when using ventilation systems as intervention tools.
Article Summary LineImposing mask usage requirements, group size restrictions, duration limits, and social distancing policies can have additive, and in some cases multiplicative protective effects on SARS-CoV-2 infection risk during indoor events. | infectious diseases |
10.1101/2021.01.21.21250273 | Do Pandemics Obey the Elliott Wave Principle of Financial Markets? | The Elliott Wave principle is a time-honored, oft-used method for predicting variations in the financial markets. It is based on the notion that human emotions drive financial decisions. In the fight against COVID-19, human emotions are similarly decisive, for instance in that they determine ones willingness to be vaccinated, and/or to follow preventive measures including the wearing of masks, the application of social distancing protocols, and frequent handwashing. On this basis, we postulated that the Elliott Wave Principle may similarly be used to predict the future evolution of the COVID-19 pandemic. We demonstrated that this method reproduces the data pattern especially well for USA (daily new cases). Potential scenarios were then extrapolated, from the best-case corresponding to a rapid, full vaccination of the population, to the utterly disastrous case of slow vaccination, and poor adherence to preventive protocols. | infectious diseases |
10.1101/2021.01.21.21250268 | Personalized Virus Load Curves of SARS-CoV-2 Infection | We introduce an explicit function that describes virus-load curves on a patient-specific level. This function is based on simple and intuitive model parameters. It allows virus load analysis without solving a full virus load dynamic model. We validate our model on data from influenza A as well as SARS-CoV-2 infection data for Macaque monkeys and humans. Further, we compare the virus load function to an established target model of virus dynamics, which shows an excellent fit. Our virus-load function offers a new way to analyse patient virus load data, and it can be used as input to higher level models for the physiological effects of a virus infection, for models of tissue damage, and to estimate patient risks. | infectious diseases |
10.1101/2021.01.22.21250289 | Development and validation of a predictive model for critical illness in adult patients requiring hospitalization for COVID-19 | BackgroundIdentifying factors that can predict severe disease in patients needing hospitalization for COVID-19 is crucial for early recognition of patients at greatest risk.
Objective1) Identify factors predicting intensive care unit (ICU) transfer and (2) develop a simple calculator for clinicians managing patients hospitalized with COVID-19.
MethodsA total of 2,685 patients with laboratory-confirmed COVID-19 admitted to a large metropolitan health system in Georgia, USA between March and July 2020 were included in the study. Seventy-five percent of patients were included in the training dataset (admitted March 1 to July 10). Through multivariable logistic regression, we developed a prediction model (probability score) for ICU transfer. Then, we validated the model by estimating its performance accuracy (area under the curve [AUC]) using data from the remaining 25% of patients (admitted July 11 to July 31).
ResultsWe included 2,014 and 671 patients in the training and validation datasets, respectively. Diabetes mellitus, coronary artery disease, chronic kidney disease, serum C-reactive protein, and serum lactate dehydrogenase were identified as significant risk factors for ICU transfer, and a prediction model was developed. The AUC was 0.752 for the training dataset and 0.769 for the validation dataset. We developed a free, web-based calculator to facilitate use of the prediction model (https://icucovid19.shinyapps.io/ICUCOVID19/).
ConclusionOur validated, simple, and accessible prediction model and web-based calculator for ICU transfer may be useful in assisting healthcare providers in identifying hospitalized patients with COVID-19, who are at high risk for clinical deterioration.
Triage of such patients for early aggressive treatment can impact clinical outcomes for this potentially deadly disease. | intensive care and critical care medicine |
10.1101/2021.01.21.21250234 | The Generalizability of Clinical Prediction Models for Patients with Acute Coronary Syndromes: Results from Independent External Validations | PurposeIt is increasingly recognized that clinical prediction models (CPMs) often do not perform as expected when they are tested on new databases. Independent external validations of CPMs are recommended but often not performed. Here we conduct independent external validations of acute coronary syndrome (ACS) CPMs.
MethodsA systematic review identified CPMs predicting outcomes for patients with ACS. Independent external validations were performed by evaluating model performance using individual patient data from 5 large clinical trials. CPM performance with and without various recalibration techniques was evaluated with a focus on CPM discrimination (c-statistic, % relative change in c-statistic) as well as calibration (Harrells Eavg, E90, Net Benefit).
ResultsOf 269 ACS CPMs screened, 23 (8.5%) were compatible with at least one of the trials and 28 clinically appropriate external validations were performed. The median c statistic of the CPMs in the derivation cohorts was 0.76 (IQR, 0.74 to 0.78). The median c-statistic in these external validations was 0.70 (IQR, 0.66 to 0.71) reflecting a 24% decrement in discrimination. However, this decrement in discrimination was due mostly to narrower case-mix in the validation cohorts compared to derivation cohorts, as reflected in the median model based c-statistic [0.71 (IQR 0.66 to 0.75). The median calibration slope in external validations was 0.84 (IQR, 0.72 to 0.98) and the median Eavg (standardized by the outcome rate) was 0.4 (IQR, 0.3 to 0.8). Net benefit indicates that most CPMs had a high risk of causing net harm when not recalibrated, particularly for decision thresholds not near the overall outcome rate.
ConclusionIndependent external validations of published ACS CPMs demonstrate that models tested in our sample had relatively well-preserved discrimination but poor calibration when externally validated. Applying off-the-shelf CPMs often risks net harm unless models are recalibrated to the populations on which they are used. | cardiovascular medicine |
10.1101/2021.01.21.21250278 | Detection and removal of pacing artifacts prior to automated analysis of 12-lead ECG | BackgroundPacing artifacts must be excluded from the analysis of paced ECG waveform. This study aimed to develop and validate an algorithm to identify and remove the pacing artifacts on ECG.
MethodsWe developed a semi-automatic algorithm that identifies the onset and offset of a pacing artifact based on the ECG signal slope steepness and designed a graphical user interface that permits quality control and fine-tuning the constraining threshold values. We used 1,054 ECGs from the retrospective, multicenter cohort study "Global Electrical Heterogeneity and Clinical Outcomes," including 3,825 atrial and 10,031 ventricular pacing artifacts for the algorithm development and 22 ECGs including 108 atrial and 241 ventricular pacing artifacts for validation. Validation was performed per digital sample. We used the kappa-statistic of interrater agreement between manually labeled sample (ground-truth) and automated detection.
ResultsThe constraining parameter values were for onset threshold 13.06{+/-}6.21 V/ms, offset threshold 34.77{+/-}17.80 V/ms, and maximum window size 27.23 {+/-} 3.53 ms. The automated algorithm detected a digital sample belonging to pacing artifact with a sensitivity of 74.5% and specificity of 99.6% and classified correctly 98.8% of digital samples (ROC AUC 0.871; 95%CI 0.853-0.878). The kappa-statistic was 0.785, indicating substantial agreement. The agreement was on 98.81% digital samples, significantly (P<0.00001) larger than the random agreement on 94.43% of digital samples.
ConclusionsThe semi-automated algorithm can detect and remove ECG pacing artifacts with high accuracy and provide a user-friendly interface for quality control.
HighlightsO_LIWe developed and validated a semi-automated algorithm to detect and remove pacing spike artifacts from a digital ECG signal.
C_LIO_LIThe semi-automated algorithm can detect and remove pacing spike artifacts with high accuracy and provide a user-friendly interface for quality control.
C_LI | cardiovascular medicine |
10.1101/2021.01.21.21250255 | Comparative Effects of E-cigarette Aerosol on Periodontium | IntroductionTobacco use is one of the main causes of periodontitis. E-cigarettes are gaining in popularity, and studies are needed to better understand the impact of e-cigarettes on oral health. Objective: To perform a longitudinal study to evaluate the adverse effects of e-cigarettes on periodontal health.
MethodsNaive e-cigarette users, cigarette smokers, and non-smokers were recruited using newspaper and social media. Demographics, age, gender, and ethnicity, were recorded. Participants were scheduled for two visits 6 months apart. At each visit, we collected data on the daily frequency puffs of an e-cigarette, the number of cigarettes smokes, and other parameters, such as alcohol consumption. Carbon monoxide levels, cotinine levels, salivary flow rate, probing depth, and bleeding on probing were determined at both baseline and follow-up visits. P-values less than 0.05 were considered statistically significant.
ResultsWe screened 159 subjects and recruited 140 subjects. One-hundred-one subjects (31 cigarette smokers, 32 e-cigarette smokers, and 38 non-smokers) completed every assessment in both visits. The retention and compliance rate of subjects was 84.1%. The use of social media and craigslist was significant in recruiting e-cigarette subjects. Ethnicity and race differed between cohorts, as did average age in the male subjects. Carbon monoxide and salivary cotinine levels were highest among cigarette smokers. Bleeding on probing and average probing depths similarly increased over time in all three cohorts. Increase in the rates of severe periodontal disease were significantly higher in cigarette smokers and e-cigarette users than non-smokers. Confounding factors were subjects age as most of the e-cigarette group were much younger than cigarette smokers.
ConclusionAmong the recruited participants, periodontal severity status after 6 month was significantly worse in cigarette smokers and e-cigarette smokers than non-smokers. This study design and protocol will assist in future larger studies on e-cigarette and oral health. | dentistry and oral medicine |
10.1101/2021.01.21.21250261 | Using body temperature and variables commonly available in the EHR to predict acute infection: A proof-of-concept study showing improved pretest probability estimates for acute COVID-19 infection among discharged emergency department patients | ObjectivesObtaining body temperature is a quick and easy method to screen for acute infection such as COVID-19. Currently, the predictive value of body temperature for acute infection is inhibited by failure to account for other readily available variables that affect temperature values. In this proof-of-concept study, we sought to improve COVID-19 pretest probability estimation by incorporating covariates known to be associated with body temperature, including patient age, sex, comorbidities, month, time of day.
MethodsFor patients discharged from an academic hospital emergency department after testing for COVID-19 in March and April of 2020, we abstracted clinical data. We reviewed physician documentation to retrospectively generate estimates of pretest probability for COVID-19. Using patients COVID-19 PCR test results as a gold standard, we compared AUCs of logistic regression models predicting COVID-19 positivity that used: 1) body temperature alone; 2) body temperature and pretest probability; 3) body temperature, pretest probability, and body temperature-relevant covariates. Calibration plots and bootstrap validation were used to assess predictive performance for model #3.
ResultsData from 117 patients were included. The models AUCs were: 1) 0.69 2) 0.72, and 3) 0.76, respectively. The absolute difference in AUC was 0.029 (95%CI -0.057 to 0.114, p=0.25) between model 2 and 1 and 0.038 (95%CI -0.021 to 0.097, p=0.10) between model 3 and 2.
ConclusionsBy incorporating covariates known to affect body temperature, we demonstrated improved pretest probability estimates of acute COVID-19 infection. Future work should be undertaken to further develop and validate our model in a larger, multi-institutional sample. | emergency medicine |
10.1101/2021.01.21.21250264 | Abrupt increase in the UK coronavirus death-case ratio in December 2020 | 1Objectiveto determine the statistical relationship between reported deaths and infections in the UK coronavirus outbreak
DesignPublicly available UK government data is used to determine a relationship between reported cases and deaths, taking into account various UK regions, age profiles and prevalence of the variant of concern (VOC) B.1.1.7.
Main Outcome MeasuresEstablishing a simple statistical relationship between detected cases and subsequent mortality.
ResultsThroughout October and November 2020, deaths in England are well described as 1/55th of detected cases from 12 days previously. After that, the relationship no longer holds and deaths are significantly higher. This is especially true in regions affected by the VOC B.1.1.7
ConclusionsIn early December, some new factor emerged to increase the case-fatality rate in the UK.
Summary BoxO_ST_ABSWhat is already known on this topicC_ST_ABSThe infection-mortality ratio enables one to predict future deaths based on current infections. Incomplete monitoring of infection may be sufficient to predict future trends.
What the study addsFor the specific case of the second wave of coronavirus infection in the UK, we show a clear mathematical relationship between detected infections (positive tests) and subsequent deaths. This relationship begins to fail in December, with unexpectedly high death rates. This may be correlated in time and region with the emergence of the Variant of Concern B 1.1.7. | epidemiology |
10.1101/2021.01.21.21250258 | Theoretical framework for retrospective studies of the effectiveness of SARS-CoV-2 vaccines | Observational studies of the effectiveness of vaccines to prevent COVID-19 are needed to inform real-world use. These are now in planning amid the ongoing rollout of SARS-CoV-2 vaccines globally. While traditional case-control (TCC) and test-negative design (TND) studies feature prominently among strategies used to assess vaccine effectiveness, such studies may encounter important threats to validity. Here we review the theoretical basis for estimation of vaccine direct effects under TCC and TND frameworks, addressing specific natural history parameters of SARS-CoV-2 infection and COVID-19 relevant to these designs. Bias may be introduced by misclassification of cases and controls, particularly when clinical case criteria include common, non-specific indicators of COVID-19. When using diagnostic assays with high analytical sensitivity for SARS-CoV-2 detection, individuals testing positive may be counted as cases even if their symptoms are due to other causes. The TCC may be particularly prone to confounding due to associations of vaccination with healthcare-seeking behavior or risk of infection. The TND reduces but may not eliminate this confounding, for instance if individuals who receive vaccination seek care or testing for less-severe infection. These circumstances indicate the two study designs cannot be applied naively to datasets gathered through public health surveillance or administrative sources. We suggest practical strategies to reduce bias in vaccine effectiveness estimates at the study design and analysis stages. | epidemiology |
10.1101/2021.01.21.21250237 | Agent-Based Simulation of Covid-19 Vaccination Policies in CovidSIMVL | An agent-based infectious disease modeling tool (CovidSIMVL) is employed in this paper to explore outcomes associated with MRNA two-dose vaccination regimens set out in Emergency Use Authorization (EUA) documents submitted by Pfizer and Moderna to the US Department of Health & Human Services. As well, the paper explores outcomes associated with a third "Hybrid" policy that reflects ranges of expected levels of protection according to Pfizer and Moderna EUAs, but entails a 35 day separation between first and second dose, which exceeds the 21 days set out in Pfizer documentation or the 28 days in Moderna documentation.
Four CovidSIMVL parameters are varied in the course of 75 simulated clinical trials. Two relate directly to the vaccines and their impacts (duration between doses; degree of expected protection conferred by different vaccines following first or second dose). Two relate to the simulation contexts to which the vaccines are applied (degree of infectivity; duration of infectivity). The simulated trials demonstrate expected effects for timing of second dose, and for degree of protection associated with first and second dose of Pfizer and Moderna vaccines, and the effects are consistent with an assumed value of 75% for degree of protection after first and second doses for the Hybrid vaccine. However, the simulated trials suggest a more complex interaction between expected level of protection following first dose, timing of second dose and degree of infectivity. These results suggest that policy options should not be considered independent of the transmission dynamics that are manifested in the contexts in which the policies could be applied.
CovidSIMVL embodies stochasticity in the mechanisms that govern viral transmission, and it treats the basic reproduction number (R0)as an emergent characteristic of transmission dynamics, not as a pre-set value that determines those dynamics. As such, results reported in this paper reflect outcomes that could happen, but do not necessarily reflect what is more or less likely to happen, given different configurations of parameters. The discussion section goes into some measure of detail regarding next steps that could be pursued to enhance the potential for agent-based models such as CovidSIMVL to inform exploration of possible vaccination policies, and to project outcomes that are possible or likely in local contexts, where stochasticity and heterogeneity of transmission must be featured in models that are intended to reflect local realism. | epidemiology |
10.1101/2021.01.22.21250292 | Ready-to-drink beverage (RTD) consumption in Thai population: trend and associated factors | ObjectivesTo examine ready-to-drink beverage (RTD) consumption and to investigate the effects of gender and age on RTD consumption by using data 2011 and 2014 waves of a national alcohol survey.
DesignAnalysis of data from Smoking and Drinking Behavior Survey (SADBeS) 2011 and 2014, a nationally representative survey.
SettingThailand
Participants177,350 (2011 survey) and 25,758 (2014 survey) samples of Thais aged 15 years or older who were randomly selected using multistage-sampling technique.
Primary outcomeRTD consumption in past 12 months (yes/no) as stated by survey participants
ResultsThe prevalence of RTD drinkers increased from 0.5% (95% CI, 0.5-0.5%) in 2011 to 2.4% (95% CI, 2.1-2.6%) in 2014. Female drinkers were 5.1 (95% CI, 4.1-6.4) times more likely to consume RTDs than male drinkers. The likelihood of drinking RTDs decreased with age. Drinking initiation before the legal purchasing age (20 years old) was associated with 1.5 (95% CI, 1.1-1.9) times likelihood of RTDs consumption.
ConclusionsA substantial increase in RTD consumption was observed in Thailand, a middle-income country, during 2011-2014. The consumption was notable in youths and females. Given that RTDs have been introduced into the Thai market relatively recently, this may be a part of the alcohol industry strategies to boost their sales in middle-income countries. Growth in RTD consumption could pose a challenge for health authorities to control alcohol-related harms in the future especially among youths and females.
Article SummaryO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIA reliable estimate of prevalence of RTD consumption was obtained by using data from two waves of a large national representative survey.
C_LIO_LIThe lack of information about pattern of RTD consumption including quantity and drinking frequency limited further analysis.
C_LI
FundingThis work was supported by the Center for Alcohol Studies, Thailand, grant number 62-02029-0043.
Competing interests statementNone declared. | public and global health |
10.1101/2021.01.22.21250283 | Negative Excess Mortality in Pneumonia Death caused by COVID-19 in Japan | BackgroundSince the emergence of COVID-19, cases of excess mortality from all causes have been very few in Japan.
ObjectTo evaluate COVID-19 effects precisely, we specifically examine deaths caused by pneumonia and examine excess mortality attributable to pneumonia in Japan.
MethodWe applied the NIID model to pneumonia deaths from 2005 up through November, 2020 for the whole of Japan. Introduction of routine pneumococcal vaccination for elderly people and revision in ICD10 were incorporated into the estimation model.
ResultsNo excess mortality was found for 2020. However, negative excess mortality was observed as 178 in May, 314 in June, and 75 in July. No negative excess mortality was not found between August and November.
Discussion and ConclusionSignificantly negative excess mortality might reflect precautions taken by people including wearing masks, washing hands with alcohol, and maintaining social distance. They reduced the infection risk not only of for COVID-19 but also of other infectious diseases causing pneumonia. | public and global health |
10.1101/2021.01.22.21250283 | Negative Excess Mortality in Pneumonia Death caused by COVID-19 in Japan | BackgroundSince the emergence of COVID-19, cases of excess mortality from all causes have been very few in Japan.
ObjectTo evaluate COVID-19 effects precisely, we specifically examine deaths caused by pneumonia and examine excess mortality attributable to pneumonia in Japan.
MethodWe applied the NIID model to pneumonia deaths from 2005 up through November, 2020 for the whole of Japan. Introduction of routine pneumococcal vaccination for elderly people and revision in ICD10 were incorporated into the estimation model.
ResultsNo excess mortality was found for 2020. However, negative excess mortality was observed as 178 in May, 314 in June, and 75 in July. No negative excess mortality was not found between August and November.
Discussion and ConclusionSignificantly negative excess mortality might reflect precautions taken by people including wearing masks, washing hands with alcohol, and maintaining social distance. They reduced the infection risk not only of for COVID-19 but also of other infectious diseases causing pneumonia. | public and global health |
10.1101/2021.01.22.21250283 | Negative Excess Mortality in Pneumonia Death caused by COVID-19 in Japan | BackgroundSince the emergence of COVID-19, cases of excess mortality from all causes have been very few in Japan.
ObjectTo evaluate COVID-19 effects precisely, we specifically examine deaths caused by pneumonia and examine excess mortality attributable to pneumonia in Japan.
MethodWe applied the NIID model to pneumonia deaths from 2005 up through November, 2020 for the whole of Japan. Introduction of routine pneumococcal vaccination for elderly people and revision in ICD10 were incorporated into the estimation model.
ResultsNo excess mortality was found for 2020. However, negative excess mortality was observed as 178 in May, 314 in June, and 75 in July. No negative excess mortality was not found between August and November.
Discussion and ConclusionSignificantly negative excess mortality might reflect precautions taken by people including wearing masks, washing hands with alcohol, and maintaining social distance. They reduced the infection risk not only of for COVID-19 but also of other infectious diseases causing pneumonia. | public and global health |
10.1101/2021.01.22.21250283 | Negative Excess Mortality in Pneumonia Death caused by COVID-19 in Japan | BackgroundSince the emergence of COVID-19, cases of excess mortality from all causes have been very few in Japan.
ObjectTo evaluate COVID-19 effects precisely, we specifically examine deaths caused by pneumonia and examine excess mortality attributable to pneumonia in Japan.
MethodWe applied the NIID model to pneumonia deaths from 2005 up through November, 2020 for the whole of Japan. Introduction of routine pneumococcal vaccination for elderly people and revision in ICD10 were incorporated into the estimation model.
ResultsNo excess mortality was found for 2020. However, negative excess mortality was observed as 178 in May, 314 in June, and 75 in July. No negative excess mortality was not found between August and November.
Discussion and ConclusionSignificantly negative excess mortality might reflect precautions taken by people including wearing masks, washing hands with alcohol, and maintaining social distance. They reduced the infection risk not only of for COVID-19 but also of other infectious diseases causing pneumonia. | public and global health |
10.1101/2021.01.21.21250241 | Predicting Prognosis and IDH Mutation Status for Patients with Lower-Grade Gliomas Using Whole Slide Images | We developed end-to-end deep learning models using whole slide images of adults diagnosed with diffusely infiltrating, World Health Organization (WHO) grade 2 gliomas to predict prognosis and the mutation status of a somatic biomarker, isocitrate dehydrogenase (IDH) 1/2. The models, which utilize ResNet-18 as a backbone, were developed and validated on 296 patients from The Cancer Genome Atlas (TCGA) database. To account for the small sample size, repeated random train/test splits were performed for hyperparameter tuning, and the out-of-sample predictions were pooled for evaluation. Our models achieved a concordance- (C-) index of 0.715 (95% CI: 0.569, 0.830) for predicting prognosis and an area under the curve (AUC) of 0.667 (0.532, 0.784) for predicting IDH mutations. When combined with additional clinical information, the performance metrics increased to 0.784 (95% CI: 0.655, 0.880) and 0.739 (95% CI: 0.613, 0.856), respectively. When evaluated on the grade 3 gliomas TCGA dataset, which was not used for training, our models were able to predict survival with a C-index of 0.654 (95% CI: 0.537, 0.768) and IDH mutations with an AUC of 0.814 (95% CI: 0.721, 0.897). If validated in a prospective study, our method could potentially assist clinicians in managing and treating patients with diffusely infiltrating gliomas. | health informatics |
10.1101/2021.01.21.20202119 | Effects of Diabetes and Blood Glucose on COVID-19 Mortality: A Retrospective Observational Study | OBJECTIVETo investigate the association of diabetes and blood glucose on mortality of patients with Coronavirus Disease 2019 (COVID-19).
RESEARCH DESIGN AND METHODSThis was a retrospective observational study of all patients with COVID-19 admitted to Huo-Shen-Shan Hospital, Wuhan, China. The hospital was built only for treating COVID-19 and opened on February 5, 2020. The primary endpoint was all-cause mortality during hospitalization.
RESULTSAmong 2877 hospitalized patients, 13.5% (387/2877) had a history of diabetes and 1.9% (56/2877) died in hospital. After adjustment for confounders, patients with diabetes had a 2-fold increase in the hazard of mortality as compared to patients without diabetes (adjusted HR 2.11, 95%CI: 1.16-3.83, P=0.014). The on-admission glucose (per mmol/L[≥]4mmol/L) was significantly associated with subsequent mortality on COVID-19 (adjusted HR 1.17, 95%CI: 1.10-1.24, P<0.001).
CONCLUSIONSDiabetes and on-admission glucose (per mmol/L[≥]4mmol/L) are associated with increased mortality in patients with COVID-19. These data support that blood glucose should be properly controlled for possibly better survival outcome in patients with COVID-19. | public and global health |
10.1101/2021.01.14.21249587 | Two-sample Mendelian randomization analysis of associations between periodontal disease and risk of colorectal, lung, and pancreatic cancers | Observational studies indicate that periodontal disease may increase the risk of colorectal, lung, and pancreatic cancers. We tested these associations using two-sample Mendelian randomization to emulate a randomized study with observational data. We developed an instrument including single nucleotide polymorphisms with strong genome-wide association study evidence for associations with aggressive and/or advanced periodontal disease. We used this instrument to assess associations with summary-level genetic data for colorectal cancer (n=58,131 cases), lung cancer (n=18,082 cases), and pancreatic cancer (n=9254 cases). The genetic predisposition index for periodontitis was significantly associated with an increased risk of colorectal cancer (p=0.026), colon cancer (p=0.021), proximal colon cancer (p=0.013), and colorectal cancer among females (p=0.039); however, it was not significantly associated with the risk of lung cancer or pancreatic cancer, overall or within most subgroups. Further research should determine whether increased periodontitis prevention and increased cancer surveillance of patients with periodontitis is warranted. | epidemiology |
10.1101/2021.01.16.21249939 | Tool for estimating the probability of having COVID-19 with one or more negative RT-PCR results | Early case detection and isolation of infected individuals are critical to controlling COVID-19. RT-PCR is considered the diagnosis gold standard, but false-negatives occur. Based on previous work, we built a user-friendly online tool to estimate the probability of having COVID-19 with negative RT-PCR results and thus avoid preventable SARS-CoV-2 transmission. | public and global health |
10.1101/2021.01.15.21249747 | New Role of Red Blood Cells in Absorption of DNA Bearing Tumorigenic Mutations from Lung Cancer Tissue | Red blood cells (RBC) are commonly assumed to be vehicles for oxygen, carbon dioxide, and cells metabolic byproducts. In this study, we investigated whether RBC may contain cancer-cell derived DNA and whether such cargo may be used as a biomarker for detecting cancer. Using an in vitro co-culture system, we showed that RBC could absorb DNA bearing tumorigenic mutations from cancer cell lines. Next, we demonstrated that we could detect common genetic mutations, including EGFR 19 deletion, L858R, and KRAS G12 in RBC collected from early-stage non-small cell lung cancer patients. We were able to repeat our finding using both next-generation sequencing and droplet digital PCR. Our study highlights a new biological phenomenon involving RBC and their translational potential as a novel liquid biopsy technology platform that can be used for early cancer screening. | oncology |
10.1101/2021.01.16.21249943 | Artificial Intelligence for Emotion-Semantic Trending and People Emotion Detection During COVID-19 Social Isolation | Taking advantage of social media platforms, such as Twitter, this paper provides an effective framework for emotion detection among those who are quarantined. Early detection of emotional feelings and their trends help implement timely intervention strategies. Given the limitations of medical diagnosis of early emotional change signs during the quarantine period, artificial intelligence models provide effective mechanisms in uncovering early signs, symptoms and escalating trends. Novelty of the approach presented herein is a multitask methodological framework of text data processing, implemented as a pipeline for meaningful emotion detection and analysis, based on the Plutchik/Ekman approach to emotion detection and trend detection. We present an evaluation of the framework and a pilot system. Results of confirm the effectiveness of the proposed framework for topic trends and emotion detection of COVID-19 tweets. Our findings revealed Stay-At-Home restrictions result in people expressing on twitter both negative and positive emotional semantics (feelings), where negatives are "Anger" (8.5% of tweets), followed by "Fear" (5.2%), "Anticipation" (53.6%) and positive emotional semantics are "Joy" (14.7%) and "Trust" (11.7%). Semantic trends of safety issues related to staying at home rapidly decreased within the 28 days and also negative feelings related to friends dying and quarantined life increased in some days. These findings have potential to impact public health policy decisions through monitoring trends of emotional feelings of those who are quarantined. The framework presented here has potential to assist in such monitoring by using as an online emotion detection tool kit. | health informatics |
10.1101/2021.01.16.21249950 | Six-month Neurological and Psychiatric Outcomes in 236,379 Survivors of COVID-19 | BackgroundNeurological and psychiatric sequelae of COVID-19 have been reported, but there are limited data on incidence rates and relative risks.
MethodsUsing retrospective cohort studies and time-to-event analysis, we estimated the incidence of ICD-10 diagnoses in the 6 months after a confirmed diagnosis of COVID-19: intracranial haemorrhage; ischaemic stroke; Parkinsonism; Guillain-Barre syndrome; nerve/nerve root/plexus disorders; myoneural/muscle disease; encephalitis; dementia; mood, anxiety, and psychotic disorders; substance misuse; and insomnia. Data were obtained from the TriNetX electronic health records network (over 81 million patients). We compared incidences with those in propensity score-matched cohorts of patients with influenza or other respiratory infections using a Cox model. We investigated the effect on incidence estimates of COVID-19 severity, as proxied by hospitalization and encephalopathy (including delirium and related disorders).
Findings236,379 patients survived a confirmed diagnosis of COVID-19. Among them, the estimated incidence of neurological or psychiatric sequelae at 6 months was 33.6%, with 12.8% receiving their first such diagnosis. Most diagnostic categories were commoner after COVID-19 than after influenza or other respiratory infections (hazard ratios from 1.21 to 5.28), including stroke, intracranial haemorrhage, dementia, and psychotic disorders. Findings were equivocal for Parkinsonism and Guillain-Barre syndrome. Amongst COVID-19 cases, incidences and hazard ratios for most disorders were higher in patients who had been hospitalized, and markedly so in those who had experienced encephalopathy. Results were robust to sensitivity analyses, including comparisons against an additional four index health events.
InterpretationThe study provides evidence for substantial neurological and psychiatric morbidity following COVID-19 infection. Risks were greatest in, but not limited to, those who had severe COVID-19. The information can help in service planning and identification of research priorities.
FundingNational Institute for Health Research (NIHR) Oxford Health Biomedical Research Centre. | neurology |
10.1101/2021.01.17.21249994 | The "throwaways". Conflicts of interest in dermatology publications. | ImportanceConflict of interest as it relates to medical education is a topic of concern. Dermatology journals, periodicals, editorials, and news magazines are influential resources that are not uniformly regulated and subject to influence from the pharmaceutical industry.
ObjectiveThis study evaluates industry payments to physician editorial board members of common dermatology publications, including "throwaway" publications.
DesignA list of editorial board members was compiled from a collection of clinical dermatology publications received over a 3-month period. To analyze the nature and extent of industry payments to this cohort, payments data from the Open Payments database from 2013 to 2019 were collected. Analysis of the total payments, number of transactions, categories of payments, payment sources, and physician specific characteristics was performed.
ResultsTen publications were evaluated, and payments data for 466 physicians were analyzed. The total compensation across all years was $75,622,369.64. Services other than consulting, consulting, and travel/lodging payments comprised most of the payments. A faction of dermatologists received the majority of payments. The top payers were manufacturers of biologic medications. Payment amounts were higher for throwaway publications compared to peer-reviewed journals.
ConclusionsEditorial board members of dermatology publications received substantial payments from the pharmaceutical industry. A minority of physicians receive the lions share of payments from industry. "Throwaway" publications have more financial conflict of interest than peer-reviewed journals. The impact of these conflicts of interest on patient care, physicians practice patterns, and patient perception of physicians is noteworthy. | dermatology |
10.1101/2021.01.20.21249647 | Genome-wide analysis of 102,084 migraine cases identifies 123 risk loci and subtype-specific risk alleles | Migraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. This genome-wide association study (GWAS) of 102,084 migraine cases and 771,257 controls identified 123 loci of which 86 are novel. The loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. A stratification of the risk loci using 29,679 cases with subtype information, of which approximately half have never been used in a GWAS before, indicated three risk variants that appear specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that appear specific for migraine without aura (near SPINK2 and near FECH), and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology. | genetic and genomic medicine |
10.1101/2021.01.19.21249296 | Diagnosing pulmonary tuberculosis using sequence-specific purification of urine cell-free DNA | Transrenal urine cell-free DNA (cfDNA) is a promising tuberculosis (TB) biomarker, but is challenging to detect because of the short length (<100 bp) and low concentration of TB-specific fragments. We aimed to improve the diagnostic sensitivity of TB urine cfDNA by increasing recovery of short fragments during sample preparation. We developed a highly sensitive sequence-specific purification method that uses hybridization probes immobilized on magnetic beads to capture short TB cfDNA (50 bp) with 91.8% average efficiency. Combined with short-target PCR, the assay limit of detection was [≤]5 copies of cfDNA in 10 mL urine. In a clinical cohort study in South Africa, our urine cfDNA assay had 83.7% sensitivity (95% CI: 71.0- 91.5%) and 100% specificity (95% CI: 86.2-100%) for diagnosis of active pulmonary TB when using sputum Xpert MTB/RIF as the reference standard. The detected cfDNA concentration was 0.14-2804 copies/mL (median 14.6 copies/mL) and was inversely correlated with CD4 count and days to culture positivity. Sensitivity was non-significantly higher in HIV-positive (88.2%) compared to HIV-negative patients (73.3%), and was not dependent on CD4 count. Sensitivity remained high in sputum smear-negative (76.0%) and urine LAM-negative (76.5%) patients. With improved sample preparation, urine cfDNA is a viable biomarker for TB diagnosis. Our assay has the highest reported accuracy of any TB urine cfDNA test to date and has the potential to enable rapid non-sputum-based TB diagnosis across key underserved patient populations. | infectious diseases |
10.1101/2021.01.21.21249920 | Survey of contaminated percutaneous injuries in anesthesiologists | BackgroundAnesthesia practitioners are at inherent risk for percutaneous injuries by blood-contaminated needles and sharp objects. These exposures may result in transmission of HIV and hepatitis viruses. Data about this occupational hazard from contaminated needles and sharp devices is limited and decades old. We conducted a web-based survey to assess the occurrence, reporting, characteristics, and outcome of contaminated percutaneous injuries (CPI) in anesthesia residents, fellows, and attendings.
MethodsAfter institutional research board approval, an email was sent to 217 anesthesia practitioners requesting their participation in an online survey about contaminated percutaneous injuries. Responses were collected from February through March 2020. Results are reported as absolute numbers and proportions with 95% confidence interval (CI).
ResultsThe overall survey response rate was 51% (110/217). 59% (65/110) (95% CI, 50-68) of participants reported having one or more contaminated percutaneous injury during their years of anesthesia practice (42% (21/50) of residents, 50% (4/8) of fellows, 77% (40/52) of anesthesia attendings). Prevalence of injuries related to attendings years of anesthesia practice was 69% (95% CI, 44-94) for 5-10 years, 62.5% (95% CI, 29-96) for 10-15 years, and 79% (95% CI, 63- 95) for greater than 15 years of practice.
35% (95% CI, 26-44) of participants reported having one or more CPI within the last 5 years (40% of residents, 50% of fellows, 29% of attendings). Occurrence of CPI within the last 5 years based on attending anesthesiologist years of practice was 57% for less than 5 years, 37.5% for 10-15 years, and 20% for 15-20 years of practice. 75% (95% CI, 65-85) reported the incident at the time of injury. 59% (95% CI, 48-70) of injuries were due to hollow bore needles. 50% (95% CI, 39-61) of total injuries were high risk. 26% of injured anesthesia practitioners received post-exposure prophylaxis and there were zero seroconversions.
ConclusionMost anesthesiologists will sustain a contaminated percutaneous injury during their careers. Incidence of these injuries decreases with years of practice. Occurrence of these injuries is high among anesthesia residents, with the majority reporting their injuries. Half of the injuries are high risk with a quarter requiring postexposure prophylaxis. More education and interventions are needed to reduce percutaneous injuries and improve reporting. | anesthesia |