title: Association between genes regulating neural pathways for quantitative traits of speech and language disorders

abstract: Speech sound disorders (SSD) manifest as difficulties in phonological memory and awareness, oral motor function, language, vocabulary, reading and spelling. Families enriched for SSD are rare, and typically display a cluster of deficits. We conducted a genome-wide association study (GWAS) in 435 children from 148 families in the Cleveland Family Speech and Reading study (CFSRS), examining 16 variables representing 6 domains. Replication was conducted using the Avon Longitudinal Study of Parents and Children (ALSPAC). We identified 18 significant loci (combined p<10-8) that we pursued bioinformatically. We prioritized 5 novel gene regions with likely functional repercussions on neural pathways, some which colocalized with differentially methylated regions in our sample. Polygenic risk scores for receptive language, expressive vocabulary, phonological awareness, phonological memory, spelling, and reading decoding associated with increasing clinical severity. In summary, neural genetic influence on SSD is primarily multigenic and acts on genomic regulatory elements, similar to other neurodevelopmental disorders.


title: Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases

abstract:
BackgroundClinical interpretation of genetic variants in the context of the patients phenotype is becoming the largest component of cost and time expenditure for genome-based diagnosis of rare genetic diseases. Artificial intelligence (AI) holds promise to greatly simplify and speed interpretation by comprehensively evaluating genetic variants for pathogenicity in the context of the growing knowledge of genetic disease. We assess the diagnostic performance of GEM, a new, AI-based, clinical decision support tool, compared with expert manual interpretation.

MethodsWe benchmarked GEM in a retrospective cohort of 119 probands, mostly NICU infants, diagnosed with rare genetic diseases, who received whole genome sequencing (WGS) at Rady Childrens Hospital. We also performed a replication study in a separate cohort of 60 cases diagnosed at five additional academic medical centers. For comparison, we also analyzed these cases with commonly used variant prioritization tools (Phevor, Exomiser, and VAAST). Included in the comparisons were WGS and whole exome sequencing (WES) as trios, duos, and singletons. Variants underpinning diagnoses spanned diverse modes of inheritance and types, including structural variants (SVs). Patient phenotypes were extracted either manually or by automated clinical natural language processing (CNLP) from clinical notes. Finally, 14 previously unsolved cases were re-analyzed.

ResultsGEM ranked >90% of causal genes among the top or second candidate, using manually curated or CNLP derived phenotypes, and prioritized a median of 3 genes for review per case. Ranking of trios and duos was unchanged when analyzed as singletons. In 17 of 20 cases with diagnostic SVs, GEM identified the causal SVs as the top or second candidate irrespective of whether SV calls where provided or inferred ab initio by GEM when absent. Analysis of 14 previously unsolved cases provided novel findings in one, candidates ultimately not advanced in 3, and no new findings in 10, demonstrating the utility of GEM for reanalysis.

ConclusionsGEM enables automated diagnostic interpretation of WES and WGS for all types of variants, including SVs, nominating a very short list of candidate genes and disorders for final review and reporting. In combination with deep phenotyping by CNLP, GEM enables substantial automation of genetic disease diagnosis, potentially decreasing the cost and speeding case review.

category: genetic and genomic medicine


title: Investigation of Autosomal Genetic Sex Differences in Parkinsons disease

abstract:
Parkinsons disease (PD) is a complex neurodegenerative disorder. Males are on average [~]1.5 times more likely to develop PD compared to females. Over the years genome-wide association studies (GWAS) have identified numerous genetic risk factors for PD, however it is unclear whether genetics contribute to disease etiology in a sex-specific manner.

In an effort to study sex-specific genetic factors associated with PD, we explored two large genetic datasets from the International Parkinsons Disease Genomics Consortium and the UK Biobank consisting of 13,020 male PD cases, 7,936 paternal proxy cases, 89,660 male controls, 7,947 female PD cases, 5,473 maternal proxy cases and 90,662 female controls. We performed GWAS meta-analyses to identify distinct patterns of genetic risk contributing to disease in male versus female PD cases.

In total 19 genome-wide significant regions were identified, and no sex-specific effects were observed. A high genetic correlation between the male and female PD GWASes was identified (rg=0.877) and heritability estimates were identical between male and female PD cases ([~]20%).

We did not detect any significant genetic differences between male or female PD cases. Our study does not support the notion that common genetic variation on the autosomes could explain the difference in prevalence of PD between males and females at least when considering the current sample size under study. Further studies are warranted to investigate the genetic architecture of PD explained by X and Y chromosomes and further evaluate environmental effects that could potentially contribute to PD etiology in male versus females.


title: LifeSim: A Lifecourse Dynamic Microsimulation Model of the Millennium Birth Cohort in England

abstract: We present a dynamic microsimulation model for childhood policy analysis that models developmental, economic, social and health outcomes from birth to death for each child in the Millennium Birth Cohort (MCS) in England, together with public costs and a summary wellbeing measure. The model is a discrete event simulation in discrete time (annual periods), implemented in R, which progresses 100,000 individuals through each year of their lives from birth in the year 2000 to death. From age 0 to 18 the model draws observational data from the MCS, with explicit modelling of only a few derived outcomes (mental health, conduct disorder, mortality, health-related quality of life, public costs and a general wellbeing metric). During adulthood, all outcomes are modelled dynamically using explicit networks of stochastic process equations, with separate networks for working age and retirement. Our equations are parameterised using effect estimates from existing studies combined with target outcome levels from up-to-date administrative and survey data. We present our baseline projections and a simple validation check against external data from the British Cohort Study 1970 and Understanding Society survey.

category: health economics


title: Learning Where to Look for COVID-19 Growth: Multivariate Analysis of COVID-19 Cases Over Time using Explainable Convolution-LSTM

abstract: Determinant factors which contribute to the prediction should take into account multivariate analysis for capturing coarse-to-fine contextual information. From the preliminary descriptive analysis, it shows that environmental factor such as UV (ultraviolet) is one of the essential factors that should be considered to observe the COVID-19 epidemic drivers, During summer, UV can inactivate viruses that live in the air and on the surface of the objects especially at noon in tropical or subtropical countries. However, it may not be significant in closed spaces like workspace and areas with the intensive human-to-human transmission, especially in densely populated areas. Different COVID-19 pandemic growth patterns in northern subtropical, southern subtropical and tropical countries occur over time. Moreover, there are education, government, morphological, health, economic, and behavioral factors contributing to the growth of COVID-19. Multivariate analysis via visual attribution of explainable Convolution-LSTM is utilized to see high contributing factors responsible for the growth of daily COVID-19 cases. For future works, data to be analyzed should be more detailed in terms of the region and the period where the time-series sample is acquired. The explainable Convolution-LSTM code is available here: https://github.com/cbasemaster/time-series-attribution


title: Economic evaluation of disease elimination: an extension to the net benefits framework and application to human African trypanosomiasis

abstract:
The global health community has earmarked a number of diseases for elimination or eradication, and these goals have often been praised on the premise of long-run cost-savings. However, decision-makers must contend with a multitude of demands on health budgets in the short- or medium-term, and costs-per-case often rise as the burden of a disease falls, rendering such efforts beyond the cost-effective use of scarce resources. In addition, these decisions must be made in the presence of substantial uncertainty regarding the feasibility and costs of elimination or eradication efforts. Therefore, analytical frameworks are necessary to consider the additional effort for reaching global goals, like elimination or eradication, that are beyond the cost-effective use of country resources. We propose a modification to the net-benefit framework to consider the implications of switching from an optimal strategy, in terms of cost-per-burden-averted, to a strategy with a higher likelihood of meeting the global target of elimination of transmission by a specified date. We illustrate the properties of our framework by considering the economic case of efforts to eliminate transmission of gambiense human African trypanosomiasis (gHAT), a vector-borne parasitic disease in West and Central Africa, by 2030.

Significance StatementVarious diseases are earmarked for elimination by the global health community. While the health economic implications of elimination have been discussed before, the combination of uncertainty, cost-effectiveness in terms of cases averted, and elimination in the face of rising per-case costs has not been tackled before. We propose an approach that considers the tension between the dual objectives of cost-effectiveness and elimination while incorporating uncertainty in these objectives. We apply our method to strategies against human African trypanosomiasis in three settings, but this method could be directly applied to simulation-based studies of the cost-effectiveness of other disease elimination efforts. The method yields common metrics of efficiency when stakeholders have different objectives.


title: Economic evaluation of disease elimination: an extension to the net-benefit framework and application to human African trypanosomiasis


title: Maternal depression and child human capital: A genetic instrumental-variable approach

abstract: We here address the causal relationship between maternal depression and child human capital using UK cohort data. We exploit the conditionally-exogenous variation in mothers genomes in an instrumental-variable approach, and describe the conditions under which mothers genetic variants can be used as valid instruments. An additional episode of maternal depression between the childs birth up to age nine reduces both their cognitive and non-cognitive skills by 20 to 45% of a SD throughout adolescence. Our results are robust to a battery of sensitivity tests addressing, among others, concerns about pleiotropy and the maternal transmission of genes to her child.


title: Home stay reflects symptoms severity in major depressive disorder: A multicenter observational study using geolocation data from smartphones.

abstract: Most smartphones and wearables are nowadays equipped with location sensing (using Global Positioning System and mobile network information) that enable continuous location tracking of their users. Several studies have reported that the amount of time an individual experiencing symptoms of Major Depressive Disorder (MDD) spends at home a day (i.e., home stay), as well as various mobility related metrics, are associated with symptom severity in MDD. Due to the use of small and homogeneous cohorts of participants, it is uncertain whether the findings reported in those studies generalize to a broader population of individuals with the MDD symptoms. In the present study, we examined the relationship between overall severity of the depressive symptoms, as assessed by the eight-item Patient Health Questionnaire (PHQ-8), and median daily home stay over the two weeks preceding the completion of a questionnaire in individuals with MDD. We used questionnaire and geolocation data of 164 participants collected in the observational Remote Assessment of Disease and Relapse - Major Depressive Disorder (RADAR-MDD) study. Participant age and severity of the MDD symptoms were found to be significantly related to home stay, with older and more severely affected individuals spending more time at home. The association between home stay and symptom severity appeared to be stronger on weekdays than on weekends. Furthermore, we found a significant modulation of home stay by occupational status, with employment reducing home stay. Our findings suggest that home stay is associated with symptom severity in MDD and demonstrate the importance of accounting for confounding factors in future MDD studies.

category: health informatics


title: Digital technologies for monitoring and improving treatment adherence in children and adolescents with asthma: A scoping review of randomised controlled trials

abstract:
BackgroundInadequate paediatric asthma care has resulted in potentially avoidable unplanned hospital admissions and morbidity. A wide variety of digital technologies have been developed to help monitor and support treatment adherence for children and adolescents with asthma. However, existing reviews need to be updated and expanded to provide an overview of the current state of research around these technologies and how they are being integrated into existing healthcare services and care pathways.

ObjectiveThe purpose of this scoping review is to provide an overview of the current research landscape and knowledge gaps regarding the use of digital technologies to support the care of children and adolescents with asthma.

MethodsThe review was structured according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks. Five databases (PubMed, the Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, EMBASE, and PsycINFO) were systematically searched for studies published in English from 2014 on. One reviewer screened references, selected studies for inclusion based on the eligibility criteria, and extracted the data, which were synthesised in a descriptive analysis.

ResultsA wide variety in study characteristics - including the number and age of participants, study duration, and type of digital intervention - was identified. There was mixed evidence for the effectiveness of the interventions; 6 of the 9 studies that evaluated treatment adherence found improvements, but the evidence was inconsistent for asthma control (4/9 found no evidence of effectiveness, and only one found significant evidence) and health outcome variables (4/7 found no evidence of effectiveness). The 5 studies that examined patient perceptions and assessments of acceptability and usability had generally positive findings.

ConclusionsDespite the range of different digital interventions being developed to support the monitoring and treatment adherence of children and adolescents with asthma, there is limited evidence to suggest that they achieve their range of intended outcomes. Stronger evidence of their effectiveness at achieving their specific aims is needed, as this will support decisions and research about their cost-effectiveness and how these technologies can best integrate with existing clinical care pathways. This research is necessary to determine which interventions are worth supporting and adopting in the clinical care pathways.


title: Analyzing Healthcare Safety Climate Through A Collaborative Filtering of Safety Attitudes Questionnaire for A Hospital Case Study

abstract:
BackgroundPatient safety climate in healthcare is an important element to improve quality of current healthcare system globally. Safety Attitudes Questionnaire (SAQ), one of measurable tools for patient safety climate, is applied as an effective research survey to collect opinions and information from medical workers in a long term.

MethodSAQ data in this study consists of medical employee scores to 46 questions in 8 aspects or dimensions and personal information during 2014 to 2017 from a teaching hospital. A quantitative analysis with a core user based collaborative filtering method is conducted to analyze the SAQ data for discovering the latent inter-related pattern among different SAQ aspects of sub-sectors in this hospital for four years.

ResultsThere are not interrelationships between these 8 independent aspects for wards at different level (A, B and C) consistently across 4 years. The correlation patterns of aspects are not strong consistent over years for wards.

ConclusionObservations in this study can be used to support understanding patient safety climate assessment. They are contributed to further study in this area and understand SAQ aspects dynamically in a real hospital case.


title: Addressing Extreme Imbalance for Detecting Medications Mentioned in Twitter User Timelines

abstract: Tweets mentioning medications are valuable for efforts in digital epidemiology to supplement traditional methods of monitoring public health. A major obstacle, however, is to differentiate them from the large majority of tweets on other topics posted in a users timeline: solving the infamous  needle in a haystack problem. While deep learning models have significantly improved classification, their performance and inference processing time remain low on extremely imbalanced corpora where the tweets of interest are less than 1% of all tweets. In this study, we empirically evaluate under-sampling, fine-tuning, and filtering heuristics to train such classifiers. Using a corpus of 212 Twitter timelines (181,607 tweets with only 0.2% tweets mentioning a medication), our results show that combining these heuristics is necessary to impact the classifiers performance. In our intrinsic evaluation, a classifier based on a lexicon and a BERT-base neural network achieved a 0.838 F1-score, a score similar to the ones of the best existing classifier, but it processed the corpus 28 times faster - a positive result, since processing speed is still a roadblock to deploying classifiers on large cohorts of Twitter users needed for pharmacovigilance. In our extrinsic evaluation, our classifier helped a labeler to extract the spans of medications more accurately and achieved a 0.76 Strict F1-score. To the best of our knowledge, this is the first evaluation of medications extraction in Twitter timelines and it establishes the first benchmark for future studies.


title: Demographic and Hygienic Factors as Predictors of Face Mask Wearing During Covid-19 Pandemic in Malaysia

abstract: Wearing a face mask has been recognised as an effective way of slowing down the spread of the Covid-19 pandemic. However, there is scarce evidence on predictors of face mask wearing during a pandemic. This research aims to investigate which demographic and hygienic factors could predict the compliance for face mask wearing in Malaysia. We employed a structured online survey of 708 Malaysian adult respondents. Among the factors examined, we found gender, hand washing and wearing of personal protective equipment significantly predicted face mask wearing.


title: SEED: Symptom Extraction from English Social Media Posts using Deep Learning and Transfer Learning

abstract: AO_SCPLOWBSTRACTC_SCPLOWThe increase of social media usage across the globe has fueled efforts in digital epidemiology for mining valuable information such as medication use, adverse drug effects and reports of viral infections that directly and indirectly affect population health. Such specific information can, however, be scarce, hard to find, and mostly expressed in very colloquial language. In this work, we focus on a fundamental problem that enables social media mining for disease monitoring. We present and make available SEED, a natural language processing approach to detect symptom and disease mentions from social media data obtained from platforms such as Twitter and DailyStrength and to normalize them into UMLS terminology. Using multi-corpus training and deep learning models, the tool achieves an overall F1 score of 0.86 and 0.72 on DailyStrength and balanced Twitter datasets, significantly improving over previous approaches on the same datasets. We apply the tool on Twitter posts that report COVID19 symptoms, particularly to quantify whether the SEED system can extract symptoms absent in the training data. The study results also draw attention to the potential of multi-corpus training for performance improvements and the need for continuous training on newly obtained data for consistent performance amidst the ever-changing nature of the social media vocabulary.


title: A Method for Machine Learning Generation of Realistic Synthetic Datasets for Validating Healthcare Applications

abstract:
BackgroundDigital health applications can improve quality and effectiveness of healthcare, by offering a number of tools to patients, professionals, and the healthcare system. Introduction of new technologies is not without risk, and digital health applications are often considered a medical device. Assuring their safe operation requires, amongst others, clinical validation, which needs large datasets to test their application in realistic clinical scenarios. Access to such datasets is challenging, due to concerns about patient privacy. Development of synthetic datasets, which will be sufficiently realistic to test digital applications, is seen as a potential alternative, enabling their deployment.

ObjectiveThe aim of work was to develop a method for the generation of realistic synthetic datasets, statistically equivalent to real clinical datasets, and demonstrate that Generative Adversarial Network based approach is fit for purpose.

MethodA generative adversarial network was implemented and trained, in a series of six experiments, using numerical and categorical variables from three clinically relevant datasets, including ICD-9 and laboratory codes from the MIMIC III dataset. A number of contextual steps provided the success criteria for the synthetic dataset.

ResultsThe approach created a synthetic dataset that exhibits very similar statistical characteristics with the real dataset. Pairwise association of variables is very similar. A high degree of Jaccard similarity and a successful K-S test further support this.

ConclusionsThe proof of concept of generating realistic synthetic datasets was successful, with the approach showing promise for further work.


title: Clinician Readiness to Adopt A.I. for Critical Care Prioritisation

abstract:
There is a wide chasm between what has been shown to be feasible in the application of artificial intelligence to data from the electronic medical record, and what is currently available. The reasons for this are complex and understudied, and vary across technical, ethical and sociocultural domains. This work addresses the gap in the literature for studies that determine the readiness of clinical end-users to adopt such tools and the way in which they are perceived to affect clinical practice itself.

In this study, we present a novel, credible AI system for predicting in-patient deterioration to likely end users. We gauge their readiness to adopt this technology using a modified version of the technology adoption model.

Users are found to be moderately positive towards the potential introduction of this technology in their workflow, although they demonstrate particular concern for the appropriateness of the clinical setting into which it is deployed.


title: Risk-taking behavior and sustained attention after a night shift: an observational study in healthcare professionals

abstract:
Study ObjectivesNight work plays an irreplaceable role in healthcare systems. However, sleep loss due to night shifts can negatively affect healthcare workers cognition. Identifying individual variables predicting night shift tolerance may help to mitigate the negative consequences of sleep loss on workers and patients safety. This study aims to explore, in a healthcare workers sample, which variables predict the possible impairment in sustained attention and increase in risk-taking behavior after a night shift.

Methods22 healthcare workers (avg. age 39.4 {+/-} 11.5 y, 63% females) participated in the experiment. Participants wore a wrist actigraph during a night shift and the preceding 6 days. At the beginning (t0) and at the end (t1) of the night shift, they underwent an assessment of sustained attention (Psychomotor Vigilance Task, PVT) and risk-taking behavior (Balloon Analogue Risk Task, BART). Questionnaires on risk propensity (Domain-Specific Risk Taking, DOSPERT) and on demographics were also administered. Linear regression models were estimated to disentangle the effect of age, risk propensity and actigraphically-defined sleep metrics on cognitive variables.

ResultsWake after sleep onset (WASO) significantly predicted t1-t0 PVT metric "major lapses" ({beta}=-0.11, p=0.0007) while age and DOSPERT significantly predicted t1-t0 BART score ({beta}=-0.26, p=0.023 and {beta}=-0.097, p=0.043, respectively).

ConclusionsSleep parameters predict the impairment in sustained attention, while the combination of age and risk propensity predicts an increase in risk-taking behavior. The implementation of measures to prevent cognitive decline during night shifts should be designed according to the type of tasks workers must accomplish.

category: health policy


title: A Comparative Analysis of COVID-19 Physical Distancing Policies in Botswana, India, Jamaica, Mozambique, Namibia, Ukraine, and the United States

abstract:
BackgroundUnderstanding the differences in timing and composition of physical distancing policies is important to evaluate the early global response to COVID-19. A physical distancing intensity framework comprising 16 domains was recently published to compare physical distancing approaches between U.S. States. We applied this framework to a diverse set of low and middle-income countries (LMICs) (Botswana, India, Jamaica, Mozambique, Namibia, and Ukraine) to test the appropriateness of this framework in the global context and to compare the policy responses in this set of LMICs and with a sample of U.S. States during the first 100-days of the epidemic.

ResultsAll six of the LMICs in our sample adopted wide ranging physical distancing policies. The highest peak daily physical distancing intensity in each country was: Botswana (4.60); India (4.40); Ukraine (4.40); Namibia (4.20); and Jamaica (3.80). The number of days each country stayed at peak intensity ranged from 12-days (Jamaica) to more than 67-days (Mozambique). We found some key similarities and differences, including substantial differences in whether and how countries expressly required certain groups to stay at home. We also found that the LMICs generally implemented physical distancing policies when there were few confirmed cases and the easing of physical distancing policies did not discernably correlate with change in COVID-19 incidence. The physical distancing responses in the LMIC sample were generally more intense than in a sample of U.S. States, but results vary depending on the U.S. State. For example, California had a peak intensity of 4.29, which would place California below the peak intensity for Botswana, India, and Ukraine but above Mozambique, Namibia and Jamaica. The U.S. State of Georgia had a peak intensity of 3.07, which would place it lower than all of the LMICs in this sample. The peak intensity for the U.S. 12-state average was 3.84, which would place it lower than every LMIC in this sample except Jamaica.

ConclusionThis analysis helps to highlight the differing paths taken by the countries in this sample and may provide lessons to other countries regarding options for structuring physical distancing policies in response to COVID-19 and future outbreaks.


title: Bereavement care for ethnic minority communities: A systematic review of access to, models of, outcomes from, and satisfaction with, service provision

abstract:
ObjectivesTo review and synthesize the existing evidence on bereavement care, within the United Kingdom (UK), for ethnic minority communities in terms of barriers and facilitators to access; models of care; outcomes from, and satisfaction with, service provision.

DesignA systematic review adopting a framework synthesis approach was conducted. An electronic search of the literature was undertaken in MEDLINE, Embase, PsycINFO, Social Work Abstract and CINAHL via EBSCO, Global Health, Cochrane library, the Trip database and ProQuest between 2000 and 2020. Search terms included bereavement care, ethnic minority populations and the UK setting.

ResultsFrom 3,185 initial records, following screening for eligibility, and full-text review of 164 articles, seven studies were identified. There was no research literature outlining the role of family, friends and existing networks; and a real absence of evidence about outcomes and levels of satisfaction for those from an ethnic minority background who receive bereavement care. From the limited literature, the overarching theme for barriers to bereavement care was  unfamiliarity and irregularities. Four identified subthemes were  lack of awareness;  variability in support;  type and format of support; and  culturally specific beliefs. The overarching theme for facilitators for bereavement care was  accessibility with the two subthemes being  readily available information and  inclusive approaches. Three studies reported on examples of different models of care provision.

ConclusionsThis review reveals a stark lack of evidence about bereavement care for ethnic minority populations. In particular, understanding more about the role of family, friends and existing support systems, alongside outcomes and satisfaction will begin to develop the evidence base underpinning current provision. Direct user-representation through proactive engagement and co-design approaches may begin to determine the most appropriate models and format of bereavement care for ethnic minority communities to inform service design and delivery.

category: health systems and quality improvement


title: Has the prevalence of cigarette smoking among HIV-positive patients in Poland changed over the last decade?

abstract:
IntroductionThe WHO report from 2016 estimates the prevalence of smoking as 22% worldwide and 28% in Poland. The prevalence of smoking in HIV-infected persons is 2-3 times higher than in the general population. The study conducted in 2009 in our department among n=116 HIV-infected patients showed 87.1% smoking cigarettes at least 2.5 pack-years (85.0% of males and 93.5% of females). The aim of the present study was to evaluate the change in the prevalence of cigarette smoking among HIV-infected patients over the last decade.

MethodsWe analyzed data from the survey conducted in n=204 HIV-infected patients hospitalized from November 2018 to November 2019 in our department. The survey included: age; sex, number of cigarettes smoked daily presently and in the past, the number of years as a smoker; the influence of HIV diagnosis on the number of cigarettes smoked.

ResultsAmong all n=204 patients current smokers n=78/204 (38.2%) with n=65/176 (36.9%) males and n=13/28 (46.4%) females. Among all n=115 current smokers and ex-smokers n=29 (25.2%) diagnosing the HIV infection had an impact on their smoking habits: n=26 (89.7%) increased and n=3 - all males (10.3%) decreased the number of smoked cigarettes.

ConclusionThe prevalence of smoking cigarettes among HIV-infected individuals in our department has decreased since 2009 but is still much higher than in the general population. The outcome indicates the need to improve smoking education provided by HIV care professionals. Smoking cessation guidance or treatment should become an integral part of HIV care for patients to fully benefit from antiretroviral therapy.

category: hiv aids


title: How has the prevalence of smoking cigarettes among HIV-infected patients changed over the last decade? Single-center analysis.


title: Recent SARS-CoV-2 seroconversion in a national, community-based prospective cohort of U.S. adults

abstract:
BackgroundEpidemiologic risk factors for incident SARS-CoV-2 infection as determined via prospective cohort studies greatly augment and complement information from case-based surveillance and cross-sectional seroprevalence surveys.

MethodsWe estimated the incidence of SARS-CoV-2 infection and risk factors in a well-characterized, national prospective cohort of 6,738 U.S. adults, enrolled March-August 2020, a subset of whom (n=4,510) underwent repeat serologic testing between May 2020 and January 2021. We examined the crude associations of sociodemographic factors, epidemiologic risk factors, and county-level community transmission with the incidence of seroconversion. In multivariable Poisson models we examined the association of social distancing and a composite score of several epidemiologic risk factors with the rate of seroconversion.

FindingsAmong the 4,510 individuals with at least one serologic test, 323 (7.3%, 95% confidence interval [CI] 6.5%-8.1%) seroconverted by January 2021. Among 3,422 participants seronegative in May-September 2020 and tested during November 2020-January 2021, we observed 161 seroconversions over 1,646 person-years of follow-up (incidence rate of 9.8 per 100 person-years [95%CI 8.3-11.5]). In adjusted models, participants who reported always or sometimes social distancing with people they knew (IRRalways vs. never 0.43, 95%CI 0.21-1.0; IRRsometimes vs. never 0.47, 95%CI 0.22-1.2) and people they did not know (IRRalways vs. never 0.64, 95%CI 0.39-1.1; IRRsometimes vs. never 0.60, 95%CI 0.38-0.97) had lower rates of seroconversion. The rate of seroconversion increased across tertiles of the composite score of epidemiologic risk (IRRmedium vs. low 1.5, 95%CI 0.92-2.4; IRRhigh vs. low 3.0, 95%CI 2.0-4.6). Among the 161 observed seroconversions, 28% reported no symptoms of COVID-like illness (i.e., were asymptomatic), and 27% reported a positive SARS-CoV-2 diagnostic test. Ultimately, only 29% reported isolating and 19% were asked about contacts.

InterpretationModifiable epidemiologic risk factors and poor reach of public health strategies drove SARS-CoV-2 transmission across the U.S during May 2020-January 2021.

FundingU.S. National Institutes of Allergy and Infectious Diseases (NIAID).

category: infectious diseases


title: SARS-CoV-2 incidence and risk factors in a national, community-based prospective cohort of U.S. adults


title: Detection of Antibiotic-Resistant Bacteria, Resistance Determinants, and Mobile Elements in Surface Waters in Lebanon

abstract: The prevalence of antibiotic-resistant bacteria in surface water in Lebanon is a growing concern and understanding the mechanisms of the spread of resistance determinants is essential. We aimed at studying the occurrence of resistant organisms and determinants in surface water sources in Lebanon and understanding their mobilization and transmission. Water samples were collected from five major rivers in Lebanon. 91 isolates were recovered out of which 25 were multidrug-resistant (MDR) and accordingly were further characterized. Escherichia coli and Klebsiella pneumoniae were the most commonly identified MDR isolates. Conjugation assays coupled with in silico plasmid analysis were performed and validated using PCR-based replicon typing (PBRT) to identify and confirm incompatibility groups and the localization of {beta}-lactamase encoding genes. E. coli EC23 carried a blaNDM-5 gene on a conjugative, multireplicon plasmid, while blaCTX-M-15 and blaTEM-1B were detected in the majority of the MDR isolates. Different ST types were identified including the highly virulent E. coli ST131. Our results showed a common occurrence of bacterial contaminants in surface water and an increase in the risk for the dissemination of resistance determinants exacerbated with the ongoing intensified population mobility in Lebanon and the widespread lack of wastewater treatment.


title: Biological attributes of age and gender variations in Indian COVID-19 cases: A retrospective data analysis

abstract:
BackgroundThe associated risk factors, co-morbid conditions and biological variations varying with gender and age might be the cause of higher COVID-19 infection and deaths among males and older persons. The objective of this study was to predict and specify the biological attributes of variation in age and gender-based on COVID-19 status (deceased/recovered).

MethodsIn this retrospective study, the data was extracted from a recognised web-based portal. A total of 112,860 patients record was filtered out and an additional 9,131 records were separately analyzed to examine age and gender relationship with patients COVID-19 status (recovered/deceased). Chi-square, t-test, binary logistic regression, and longitudinal regression analysis were conducted.

ResultsThe male COVID-19 cases (65.39%) were more than females (34.61%) and mean age of infected and recovered patients was 39.47{+/-}17.59 years and 36.85{+/-}18.51 years respectively. The odds for infection was significantly higher among females for lower age categories, which declines with age. The age-adjusted odds for recovery were significantly higher among females (O.R.=1.779) and odds for recovery was highest in 5-17 years age category (O.R.=88.286) independent of gender.

ConclusionThe chances of being COVID-19 infected was higher for females of lower age categories (<35 years) which decreases with age. The odds for recovery among females was significantly higher than males. The chances of recovery declines with increasing age and the variation could be attributed to the biological differences between age categories and gender.


title: Impact of January 2021 social distancing measures on SARS-CoV-2 B.1.1.7 circulation in France

abstract: Facing B.1.1.7 variant, social distancing was strengthened in France in January 2021. Using a 2-strain mathematical model calibrated on genomic surveillance, we estimated that curfew measures allowed hospitalizations to plateau, by decreasing transmission of the historical strain while B.1.1.7 continued to grow. School holidays appear to have further slowed down progression in February. Without progressively strengthened social distancing, a rapid surge of hospitalizations is expected, despite the foreseen increase in vaccination rhythm.


title: Impact of January 2021 curfew measures on SARS-CoV-2 B.1.1.7 circulation in France


title: SARS-CoV-2 antibody immunoassays in serial samples reveal earlier seroconversion in acutely ill COVID-19 patients developing ARDS

abstract:
ObjectivesDuring the COVID-19 pandemic, SARS-CoV-2 antibody testing has been suggested for (1) screening populations for disease prevalence, (2) diagnostics, and (3) guiding therapeutic applications. Here, we conducted a detailed clinical evaluation of four Anti-SARS-CoV-2 immunoassays in samples from acutely ill COVID-19 patients and in two negative cohorts.

Methods443 serum specimens from serial sampling of 29 COVID-19 patients were used to determine clinical sensitivities. Patients were stratified for the presence of acute respiratory distress syndrome (ARDS). Individual serum specimens from a pre-COVID-19 cohort of 238 healthy subjects and from a PCR-negative clinical cohort of 257 patients were used to determine clinical specificities. All samples were measured side-by-side with the Anti-SARS-CoV-2-ELISA (IgG), Anti-SARS-CoV-2-ELISA (IgA) and Anti-SARS-CoV-2-NCP-ELISA (IgG) (Euroimmun AG, Lubeck, Germany) and the Elecsys Anti-SARS-CoV-2 ECLIA (Roche Diagnostics International, Rotkreuz, Switzerland).

ResultsMedian seroconversion occurred earlier in ARDS patients (8-9 days) than in non-ARDS patients (11-17 days), except for EUR N-IgG. Rates of positivity and mean signal ratios in the ARDS group were significantly higher than in the non-ARDS group. Sensitivities between the four tested immunoassays were equivalent. In the set of negative samples, the specificity of the Anti-SARS-CoV-2-ELISA (IgA) was lower (93.9 %) compared to all other assays ([≥]98.8 %) and the specificity of Anti-SARS-CoV-2-NCP-ELISA (IgG) was lower (98.8 %) than that of Elecsys Anti-SARS-CoV-2 (100 %).

ConclusionsSerial sampling in COVID-19 patients revealed earlier seroconversion and higher signal ratios of SARS-CoV-2 antibodies as a potential risk marker for the development of ARDS, suggesting a utility for antibody testing in acutely diseased patients.


title: Reinfection Rates among Patients who Previously Tested Positive for COVID-19: a Retrospective Cohort Study

abstract:
ObjectivesTo evaluate reinfection rates and protective effectiveness of prior disease among patients with coronavirus disease 2019 (COVID-19) infection in the United States.

DesignRetrospective cohort study

SettingOne multi-hospital health system in Ohio and Florida

ParticipantsAll 150,325 patients who were tested for COVID-19 infection via PCR from March 12, 2020 to August 30, 2020. Testing performed up to January 7, 2021 in these patients was included for analysis. Healthcare workers were excluded.

Main outcome measuresThe main outcome was reinfection, defined as infection [≥] 90 days after initial testing. Secondary outcomes were symptomatic infection and protective effectiveness of prior infection.

ResultsOf 150,325 patients tested for COVID-19 prior to August 30, 8,845 (5.9%) tested positive and 141,480 (94.1%) tested negative. 974 (11%) of the positive patients were retested after 90 days, and 56 had possible reinfection. Of those, 26 (46.4 %) were symptomatic. Of those with initial negative testing, 4,163 (12.9%) were subsequently positive and 2,460 of those (59.1%) were symptomatic. Protective effectiveness of prior infection was 78.5% (95% confidence interval 72.0 to 83.5), and against symptomatic infection was 83.1% (95% confidence interval 75.1 to 88.5). Protective effectiveness increased over time.

ConclusionsPrior infection in patients with COVID-19 was highly protective against reinfection and symptomatic disease. Protective effectiveness increased over time, suggesting that viral shedding or ongoing immune response may persist beyond 90 days and may not represent true reinfection. As vaccine supply is a limited resource around the world, patients with known history of COVID-19 could delay early vaccination to allow for the most vulnerable to access the vaccine and slow transmission.


title: Ruling out SARS-CoV-2 infection using exhaled breath analysis by electronic nose in a public health setting

abstract:
BackgroundRapid and accurate detection of SARS-CoV-2 infected individuals is crucial for taking timely measures and minimizing the risk of further SARS-CoV-2 spread. We aimed to assess the accuracy of exhaled breath analysis by electronic nose (eNose) for the discrimination between individuals with and without a SARS-CoV-2 infection.

MethodsThis was a prospective real-world study of individuals presenting to public test facility for SARS-CoV-2 detection by molecular amplification tests (TMA or RT-PCR). After sampling of a combined throat/nasopharyngeal swab, breath profiles were obtained using a cloud-connected eNose. Data-analysis involved advanced signal processing and statistics based on independent t-tests followed by linear discriminant and ROC analysis. Data from the training set were tested in a validation, a replication and an asymptomatic set.

FindingsFor the analysis 4510 individuals were available. In the training set (35 individuals with; 869 without SARS-CoV-2), the eNose sensors were combined into a composite biomarker with a ROC-AUC of 0.947 (CI:0.928-0.967). These results were confirmed in the validation set (0.957; CI:0.942-0.971, n=904) and externally validated in the replication set (0.937; CI:0.926-0.947, n=1948) and the asymptomatic set (0.909; CI:0.879-0.938, n=754). Selecting a cut-off value of 0.30 in the training set resulted in a sensitivity/specificity of 100/78, >99/84, 98/82% in the validation, replication and asymptomatic set, respectively.

InterpretationeNose represents a quick and non-invasive method to reliably rule out SARS-CoV-2 infection in public health test facilities and can be used as a screening test to define who needs an additional confirmation test.

FundingMinistry of Health, Welfare and Sport

Research in contextO_ST_ABSEvidence before this studyC_ST_ABSElectronic nose technology is an emerging diagnostic tool for diagnosis and phenotyping of a wide variety of diseases, including inflammatory respiratory diseases, lung cancer, and infections.

As of Feb 13, 2021, our search of PubMed using keywords "COVID-19" OR "SARS-CoV-2" AND "eNose" OR "electronic nose" OR "exhaled breath analysis" yielded 4 articles (1-4) that have assessed test characteristics of electronic nose to diagnose COVID-19. In these small studies the obtained signals using sensor-based technologies, two-dimensional gas chromatography and time-of-flight mass spectrometry, or proton transfer reaction time-of-flight mass spectrometry, provided adequate discrimination between patients with and without COVID-19.

Added value of this studyWe prospectively studied the accuracy of exhaled breath analysis by electronic nose (eNose) to diagnose or rule out a SARS-CoV-2 infection in individuals with and without symptoms presenting to a public test facility. In the training set with 904 individuals, the eNose sensors were combined into a composite biomarker with a ROC-AUC of 0.948. In three independent validation cohorts of 3606 individuals in total, eNose was able to reliably rule out SARS-CoV-2 infection in 70-75% of individuals, with a sensitivity ranging between 98-100%, and a specificity between 78-84%. No association was found between cycle thresholds values, as semi-quantitative measure of viral load, and eNose variables.

Implications of all the available evidenceThe available findings, including those from our study, support the use of eNose technology to distinguish between individuals with and without a SARS-CoV-2 infection with high accuracy. Exhaled breath analysis by eNose represents a quick and non-invasive method to reliably rule out a SARS-CoV-2 infection in public health test facilities. The results can be made available within seconds and can therefore be used as screening instrument. The eNose can reliably rule out a SARS-CoV-2 infection, eliminating the need for additional time-consuming, stressful, and expensive diagnostic tests in the majority of individuals.


title: A surrogate virus neutralization test to quantify antibody-mediated inhibition of SARS-CoV-2 in finger stick dried blood spot samples

abstract:
BackgroundThe spike protein of SARS-CoV-2 engages the human angiotensin-converting enzyme 2 (ACE2) receptor to enter host cells, and neutralizing antibodies are effective at blocking this interaction to prevent infection. Widespread application of this important marker of protective immunity is limited by logistical and technical challenges associated with live virus methods and venous blood collection. To address this gap, we validated an immunoassay-based method for quantifying neutralization of the spike-ACE2 interaction in a single drop of capillary whole blood, collected on filter paper as a dried blood spot (DBS) sample.

MethodsSamples are eluted overnight and incubated in the presence of spike antigen and ACE2 in a 96-well solid phase plate. Competitive immunoassay with electrochemiluminescent label is used to quantify neutralizing activity. The following measures of assay performance were evaluated: dilution series of confirmed positive and negative samples, agreement with results from matched DBS-serum samples, analysis of results from DBS samples with known COVID-19 status, and precision (intra-assay percent coefficient of variation; %CV) and reliability (inter-assay; %CV).

ResultsDilution series produced the expected pattern of dose-response. Agreement between results from serum and DBS samples was high, with concordance correlation = 0.991. Analysis of three control samples across the measurement range indicated acceptable levels of precision and reliability. Median % neutralization was 46.9 for PCR confirmed convalescent COVID-19 samples and 0.1 for negative samples.

ConclusionsLarge-scale testing is important for quantifying neutralizing antibodies that can provide protection against COVID-19 in order to estimate the level of immunity in the general population. DBS provides a minimally-invasive, low cost alternative to venous blood collection, and this scalable immunoassay-based method for quantifying neutralization of the spike-ACE2 interaction can be used as a surrogate for virus-based assays to expand testing across a wide range of settings and populations.


title: Comparison of SARS-CoV-2 viral load in saliva samples in symptomatic and asymptomatic cases

abstract: SARS-CoV-2 infections can be symptomatic as well as asymptomatic. In this study, we analyzed 460,814 saliva samples collected from July 2020 to January 2021 for a SARS-CoV-2-specific gene target using the FDA EUA test, CRL Rapid Response, based on reverse transcription polymerase chain reaction (RT-PCR). We measured SARS-CoV-2 viral loads using cycle threshold (Ct) values. A total of 17,813 samples tested positive for COVID-19 using self-collected saliva samples. The Ct values ranged from 11 to 40, 91.3% distributed between 22 to 38 Ct. We then compared Ct values for symptomatic and asymptomatic cases for all positive saliva samples. A total of 8,706 cases were symptomatic with an average Ct value of 29.24, and 9,107 cases were asymptomatic with an average Ct value of 30.99. Hence, SARS-CoV-2 viral loads (Ct) in saliva samples for both symptomatic and asymptomatic cases are similar.


title: Treatment of irritant contact dermatitis in healthcare settings during the COVID19 pandemic: The emollient Dermol 500 exhibits virucidal activity against influenza A virus and SARS-CoV-2.

abstract:
ObjectivesTo investigate whether the antimicrobial emollient Dermol 500 and its active components, benzalkonium chloride (BAK) and chlorhexidine dihydrochloride (CD), exhibit virucidal activity thus informing whether Dermol 500 is a suitable soap substitute for use during the COVID19 pandemic, to combat the increased incidence of work-related contact dermatitis in clinical settings that we report here.

MethodsInactivation of influenza A virus and SARS-CoV-2 by Dermol 500 and the independent and combined virucidal activity of the Dermol 500 components BAK and CD was assessed by influenza A virus and SARS-CoV-2 infectivity assays. Viruses were treated with concentrations of BAK and CD comparable to Dermol 500, and lower, and infectivity of the viruses assessed by titration.

ResultsDermol 500 exhibits comparable virucidal activity to alcohol-based sanitisers against influenza A virus and SARS-CoV-2. In addition, the Dermol 500 components BAK and CD exhibit independent and synergistic virucidal activity against influenza A virus and SARS-CoV-2, the causative agent of COVID19.

ConclusionsThe synergistic virucidal activity of the Dermol 500 components BAK and CD makes Dermol 500 suitable as a soap substitute to treat and prevent work-related contact dermatitis in healthcare settings.

KEY MESSAGESO_LIWhat is already known about this subject?
O_LIWork-related contact dermatitis is a prominent issue among healthcare workers, and likely exacerbated by the enhanced hand hygiene and personal protective equipment required to control infection during the COVID19 pandemic.
C_LIO_LIThe antimicrobial lotion Dermol 500 is frequently prescribed as an emollient and soap substitute to help prevent and treat dermatitis, but its use during the COVID19 pandemic was not advised as its capacity to inactivate viruses was unknown.
C_LI
C_LIO_LIWhat are the new findings?
O_LIIncreased incidence of irritant contact dermatitis was recorded amongst healthcare workers at Kings College Hospital NHS Foundation Trust in 2020 compared to 2019.
C_LIO_LIDermol 500 lotion and its antimicrobial components, benzalkonium chloride (BAK) and chlorhexidine dihydrochloride (CD), exhibit virucidal activity against influenza A virus and SARS-CoV-2, the virus responsible for COVID19 pandemic.
C_LI
C_LIO_LIHow might this impact policy or clinical practice in the foreseeable future?
O_LIOur results demonstrate that Dermol 500 can be safely used as a soap substitute to treat work-related contact dermatitis in clinical care settings during the COVID19 pandemic.
C_LIO_LIEmployers can meet their obligations under COSHH to eliminate workplace exposure to a harmful substance and substitute with an alternative product for hand hygiene.
C_LI
C_LI


title: Confirmation of an Inverse Relationship between Bioaerosol Count and Influenza-like Illnesses, Including COVID-19. On the Contribution of Mold Spores

abstract: Data from Chicago confirm the end of flu season coincides with the beginning of pollen season. The end of flu season also coincides with onset of seasonal aerosolization of mold spores. Overall, the data suggest bioaerosols, especially mold spores, compete with viruses for a shared receptor, with the periodicity of influenza-like illnesses, including COVID-19, a consequence of seasonal factors that influence aerosolization of competing species.


title: SARS-CoV2- infection as a trigger of humoral response against apolipoprotein A-1

abstract:
AimsUnravelling autoimmune targets triggered by SARS-CoV-2 infection may provide crucial insights in the physiopathology of the disease and foster the development of potential therapeutic candidate targets and prognostic tools. We aimed at determining i) the association between anti-SARS-CoV-2 and anti-apoA-1 humoral response, ii) their relationship to prognosis, and iii) the degree of linear homology between SARS-CoV-2, apoA-1, and Toll-like receptor-2 (TLR2) epitopes.

Methods and ResultsImmunoreactivity against different engineered peptides as well as cytokines were assessed by immunoassays, on a case-control (n=101), an intensive care unit (ICU; n=126) with a 28-days follow-up, and a general population cohort (n=663) with available samples in the pre and post-pandemic period. Using bioinformatics modelling a linear sequence homologies between apoA-1, TLR2, and Spike epitopes were identified. Overall, anti-apoA-1IgG levels were higher in COVID-19 patients or anti-SARS-CoV-2 seropositive individuals than in healthy donors or anti-SARS-CoV-2 seronegative individuals (p<0.0001). Significant and similar associations were noted between anti-apoA-1, anti-SARS-CoV-2IgG, cytokines, and lipid profile. In ICU patients, anti-SARS-CoV-2 and anti-apoA-1 seroconversion rates displayed similar 7-days kinetics, reaching 82% for anti-apoA-1 seropositivity. C-statistics (CS) indicated that anti-Spike/TLR2 mimic-peptide IgGs displayed a significant prognostic accuracy for overall mortality at 28 days (CS: 0.64; p=0.02). In the general population, SARS-CoV-2 exposure increased baseline anti-apoA-1 IgG levels.

ConclusionCOVID-19 induces a marked humoral response against the major protein of high-density lipoproteins. As a correlate of poorer prognosis in other clinical settings, such autoimmunity signatures may relate to long-term COVID-19 prognosis assessment and warrant further scrutiny in the current COVID-19 pandemic.


title: Cytokine response following perturbation of the cervicovaginal milieu during HPV genital infection

abstract:
Human papillomaviruses (HPVs) are the most oncogenic viruses known to human, causing nearly all cervical cancers worldwide. Highly prevalent in young, sexually active women, most HPV infections are cleared within 3 years, and only a minority of those infections persist and lead to cancer later in life. To better characterize the immuno-modulatory impact of early HPV infection and more generally perturbations of the cervicovaginal milieu, we measured changes in a panel of 20 cytokines, known as highly dynamic effector molecules implicated in cell signaling. We analyzed 92 cervicovaginal samples collected from young, sexually active women who were tested for or diagnosed with HPV, chlamydia, and bacterial vaginosis. Also, symptoms associated with genital inflammation and infection were collected through self-reporting.

Following a parsimonious multi-factor modeling approach, our statistical analyses revealed that increased IL-1Alpha and IL-12/IL-23p40 concentrations were associated with HPV infection. Cytokine network analysis further highlighted the role of IL-1Alpha and macrophage inflammatory proteins (MIP-3Alpha) in HPV-associated immuno-modulation.


title: Anterior nasal versus nasal mid-turbinate sampling for a SARS-CoV-2 antigen-detecting rapid test: does localisation or professional collection matter?

abstract:
ObjectivesThe aim of this diagnostic accuracy study was direct comparison of two different nasal sampling methods for an antigen-based rapid diagnostic test (Ag-RDT) that detects severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Furthermore, the accuracy and feasibility of self-sampling was evaluated.

MethodsThis manufacturer-independent, prospective diagnostic accuracy study, compared professional anterior nasal (AN) and nasal mid-turbinate (NMT) sampling for a WHO-listed SARS-CoV-2 Ag-RDT. A second group of participants collected a NMT sample themselves and underwent a professional nasopharyngeal swab for comparison. The reference standard was real-time polymerase chain reaction (RT-PCR) using combined oro-/nasopharyngeal sampling. Individuals with high suspicion of SARS-CoV-2 infection were tested. Sensitivity, specificity, and percent agreement were calculated. Self-sampling was observed without intervention. Feasibility was evaluated by observer and participant questionnaires.

ResultsAmong 132 symptomatic adults, both professional AN- and NMT-sampling yielded a sensitivity of 86.1% (31/36 RT-PCR positives detected; 95%CI: 71.3-93.9) and a specificity of 100.0% (95%CI: 95.7-100). The positive percent agreement (PPA) was 100% (95%CI: 89.0-100). Among 96 additional adults, self NMT- and professional NP-sampling yielded an identical sensitivity of 91.2% (31/34; 95%CI 77.0-97.0). Specificity was 98.4% (95%CI: 91.4-99.9) with NMT- and 100.0% (95%CI: 94.2-100) with NP-sampling. The PPA was 96.8% (95%CI: 83.8-99.8). Most participants (85.3%) considered self-sampling as easy to perform.

ConclusionProfessional AN- and NMT-sampling are of equivalent accuracy for an Ag-RDT in ambulatory symptomatic adults. Participants were able to reliably perform the NMT-sampling themselves, following written and illustrated instructions. Nasal self-sampling will likely facilitate scaling of SARS-CoV-2 antigen testing.


title: An analysis of school absences in England during the Covid-19 pandemic

abstract:
The introduction of SARS-CoV-2, the virus that causes COVID-19 infection, in the UK in early 2020, resulted in the UK government introducing several control policies in order to reduce the spread of disease. As part of these restrictions, schools were closed to all pupils in March (except for vulnerable and key worker children), before re-opening to certain year groups in June. Finally all school children returned to the classroom in September. In this paper, we analyse the data on school absences from September 2020 to December 2020 as a result of COVID-19 infection and how that varied through time as other measures in the community were introduced. We utilise data from the Educational Settings database compiled by the Department for Education and examine how pupil and teacher absences change in both primary and secondary schools.

Our results show that absences as a result of COVID-19 infection rose steadily following the re-opening of schools in September. Cases in teachers were seen to decline during the November lockdown, particularly in those regions that had previously been in tier 3, the highest level of control at the time. Cases in secondary school pupils increased for the first two weeks of the November lockdown, before decreasing. Since the introduction of the tier system, the number of absences owing to confirmed infection in primary schools was observed to be significantly lower than in secondary schools across all regions and tiers.

In December, we observed a large rise in the number of absences per school in secondary school settings in the South East and Greater London, but such rises were not observed in other regions or in primary school settings. We conjecture that the increased transmissibility of the new variant in these regions may have contributed to this rise in cases in secondary schools. Finally, we observe a positive correlation between cases in the community and cases in schools in most regions, with weak evidence suggesting that cases in schools lag behind cases in the surrounding community. We conclude that there is not significant evidence to suggest that schools are playing a significant role in driving spread in the community and that careful monitoring may be required as schools re-open to determine the effect associated with open schools upon community incidence.


title: Severe COVID-19 pneumonia and barotrauma: From the frying pan into the fire.

abstract:
AimCOVID-19 pneumonia with ARDS (C-ARDS) has a high mortality. Preliminary reports indicate a higher incidence of barotrauma in patients with C-ARDS[1] both on invasive mechanical ventilation (iMV) and non-invasive ventilation (NIV) This study examines the incidence and risk factors for barotrauma and change in outcomes after barotrauma in patients with severe C-ARDS on positive pressure respiratory support (PPRS).

Methods and materialsThis is a retrospective study of C-ARDS associated barotrauma over 5 months in patients on PPRS in a tertiary COVID care center. The type of barotrauma, intervention, related factors, such as type of respiratory support (iMV vs NIV), airway pressure prior to the occurrence of barotrauma, and post-barotrauma outcomes were analyzed.

ResultsA total of 38/410 (9.3%) C-ARDS patients on PPRS [mean age 57.82 {+/-} 13.3 years, 32 males (84.2%)] developed barotrauma. Of these, 20 patients (52.6%) were on NIV and 18 (47.4%) patients were iMV on standard recommended settings. The median P/F ratio of patients on MV at the time of barotrauma was 116.4 (IQR 72.4, 193.25). The details of barotrauma were as follows: 24 patients had pneumothorax (PTX), 2 had pneumo-mediastinum and 12 had subcutaneous emphysema. Overall, 24/38 (63.2%) patients, including 15/18 (83.3%) on MV succumbed to their illness. The barotrauma happened a median of 6.5 days (IQR 4.75,13) after admission and 15 days (IQR 10.25,18.0) from symptom onset. The median duration from barotrauma to death was 7 days (IQR 2.25, 8.0) and barotrauma to discharge (for survivors) was 12.5 days (IQR 8.0, 21.25). All patients received steroids and 11/38 (28.9%) received additional immunosuppression with tocilizumab.

ConclusionA high incidence of barotrauma was seen in this large series of severe C-ARDS patients on PPRS. Barotrauma led to further deterioration in the clinical status leading to a fatal outcome in the majority of the MV patients, despite prompt treatment.

category: intensive care and critical care medicine


title: CATALYST trial protocol: A multicentre, open-label, phase II, multi-arm trial for an early and accelerated evaluation of the potential treatments for COVID-19 in hospitalised adults

abstract:
IntroductionSevere SARS-CoV-2 infection is associated with a dysregulated immune response. Inflammatory monocytes and macrophages are crucial, promoting injurious, pro-inflammatory sequelae. Immunomodulation is, therefore, an attractive therapeutic strategy and we sought to test licensed and novel candidate drugs.

Methods and analysisThe CATALYST trial is a multi-arm, open-label, multi-centre, phase II platform trial designed to identify candidate novel treatments to improve outcomes of patients hospitalised with COVID-19 compared with usual care. Treatments with evidence of biomarker improvements will be put forward for larger-scale testing by current national phase III platform trials. Hospitalised patients >16 years with a clinical picture strongly suggestive of SARS-CoV-2 pneumonia (confirmed by chest X-ray or CT scan, with or without a positive reverse transcription polymerase chain reaction (RT-PCR) assay) and a C-Reactive Protein (CRP) [≥]40 mg/L are eligible. The primary outcome measure is CRP, measured serially from admission to day 14, hospital discharge or death. Secondary outcomes include the WHO Clinical Progression Improvement Scale as a principal efficacy assessment.

Ethics and disseminationThe protocol was approved by the East Midlands - Nottingham 2 Research Ethics Committee (20/EM/0115) and given Urgent Public Health status; initial approval was received on 05-May-2020, current protocol version (v6.0) approval on 12-Oct-2020. The MHRA also approved all protocol versions. The results of this trial will be disseminated through national and international presentations and peer-reviewed publications.

Trial registration numberEudraCT Number: 2020-001684-89

ISRCTN Number: 40580903

Strengths and limitations of this trialO_LICATALYST will provide a rapid readout on the safety and proof-of-concept of candidate novel treatments
C_LIO_LICATALYST will enable phase III trial resources to be focussed and allocated for agents with a high likelihood of success
C_LIO_LICATALYST uses Bayesian multi-level models to allow for nesting of repeated measures data, with factors for each individual patient and treatment arm, and allowing for non-linear responses
C_LIO_LICATALYST is not designed to provide a definitive signal on clinical outcomes
C_LI


title: A genetically-informed study disentangling the relationships between tobacco smoking, cannabis use, alcohol consumption, substance use disorders and respiratory infections, including COVID-19

abstract:
BackgroundObservational studies suggest smoking, cannabis use, alcohol consumption, cannabis use, and substance use disorders (SUDs) may play a role in the susceptibility for respiratory infections and disease, including coronavirus 2019 (COVID-2019). However, causal inference is challenging due to comorbid substance use.

MethodsUsing genome-wide association study data of European ancestry (data from >1.7 million individuals), we performed single-variable and multivariable Mendelian randomization to evaluate relationships between smoking, cannabis use, alcohol consumption, SUDs, and respiratory infections.

ResultsGenetically predicted lifetime smoking was found to be associated with increased risk for hospitalized COVID-19 (odds ratio (OR)=4.039, 95% CI 2.335-6.985, P-value=5.93x10-7) and very severe hospitalized COVID-19 (OR=3.091, 95% CI, 1.883-5.092, P-value=8.40x10-6). Genetically predicted lifetime smoking was also associated with increased risk pneumoniae (OR=1.589, 95% CI, 1.214-2.078, P-value=7.33x10-4), lower respiratory infections (OR=2.303, 95% CI, 1.713-3.097, P-value=3.40x10-8), and several others. Genetically predicted cannabis use disorder (CUD) was associated with increased bronchitis risk (OR=1.078, 95% CI, 1.020-1.128, P-value=0.007).

ConclusionsWe provide strong genetic evidence showing smoking increases the risk for respiratory infections and diseases even after accounting for other substance use and abuse. Additionally, we provide find CUD may increase the risk for bronchitis, which taken together, may guide future research SUDs and respiratory outcomes.

category: addiction medicine


title: CD8+ T cell responses in COVID-19 convalescent individuals target conserved epitopes from multiple prominent SARS-CoV-2 circulating variants

abstract: This study examined whether CD8+ T-cell responses from COVID-19 convalescent individuals(n=30) potentially maintain recognition of the major SARS-CoV-2 variants. Out of 45 mutations assessed, only one from the B.1.351 Spike overlapped with a low-prevalence CD8+ epitope, suggesting that virtually all anti-SARS-CoV-2 CD8+ T-cell responses should recognize these newly described variants.

category: allergy and immunology


title: Analysis of 200,000 exome-sequenced UK Biobank subjects implicates genes involved in increased and decreased risk of hypertension

abstract:
BackgroundPrevious analyses have identified common variants along with some specific genes and rare variants which are associated with risk of hypertension but much remains to be discovered.

Methods and ResultsExome-sequenced UK Biobank participants were phenotyped based on having a diagnosis of hypertension or taking anti-hypertensive medication to produce a sample of 66,123 cases and 134,504 controls. Variants with minor allele frequency (MAF) < 0.01 were subjected to a gene-wise weighted burden analysis, with higher weights assigned to variants which are rarer and/or predicted to have more severe effects. Of 20,384 genes analysed, two genes were exome-wide significant, DNMT3A and FES. Also strongly implicated were GUCY1A1 and GUCY1B1, which code for the subunits of soluble guanylate cyclase. There was further support for the previously reported effects of variants in NPR1 and protective effects of variants in DBH. An inframe deletion in CACNA1D with MAF = 0.005, rs72556363, is associated with modestly increased risk of hypertension. Other biologically plausible genes highlighted consist of CSK, AGTR1, ZYX and PREP. All variants implicated were rare and cumulatively they are not predicted to make a large contribution to the population risk of hypertension.

ConclusionsThis approach confirms and clarifies previously reported findings and also offers novel insights into biological processes influencing hypertension risk, potentially facilitating the development of improved therapeutic interventions. This research has been conducted using the UK Biobank Resource.

category: cardiovascular medicine


title: Score for Emergency Risk Prediction (SERP): An Interpretable Machine Learning AutoScore-Derived Triage Tool for Predicting Mortality after Emergency Admissions

abstract:
ImportanceTriage in the emergency department (ED) for admission and appropriate level of hospital care is a complex clinical judgment based on the tacit understanding of the patients likely acute course, availability of medical resources, and local practices. While a scoring tool could be valuable in triage, currently available tools have demonstrated limitations.

ObjectiveTo develop a tool based on a parsimonious list of predictors available early at ED triage, to provide a simple, early, and accurate estimate of short-term mortality risk, the Score for Emergency Risk Prediction (SERP), and evaluate its predictive accuracy relative to published tools.

Design, Setting, and ParticipantsWe performed a single-site, retrospective study for all emergency department (ED) patients between January 2009 and December 2016 admitted in a tertiary hospital in Singapore. SERP was derived using the machine learning framework for developing predictive models, AutoScore, based on six variables easily available early in the ED care process. Using internal validation, the SERP was compared to the current triage system, Patient Acuity Category Scale (PACS), Modified Early Warning Score (MEWS), National Early Warning Score (NEWS), Cardiac Arrest Risk Triage (CART), and Charlson Comorbidity Index (CCI) in predicting both primary and secondary outcomes in the study.

Main Outcomes and MeasuresThe primary outcome of interest was 30-day mortality. Secondary outcomes include 2-day mortality, inpatient mortality, 30-day post-discharge mortality, and 1-year mortality. The SERPs predictive power was measured using the area under the curve (AUC) in the receiver operating characteristic (ROC) analysis. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated under the optimal threshold, defined as the point nearest to the upper-left corner of the ROC curve.

ResultsWe included 224,666 ED episodes in the model training cohort, 56,167 episodes in the validation cohort, and 42,676 episodes in the testing cohort. 18,797 (5.8%) of them died in 30 days after their ED visits. Evaluated on the testing set, SERP outperformed several benchmark scores in predicting 30-day mortality and other mortality-related outcomes. Under cut-off score of 27, SERP achieved a sensitivity of 72.6% (95% confidence interval [CI]: 70.7-74.3%), a specificity of 77.8% (95% CI: 77.5-78.2), a positive predictive value of 15.8% (15.4-16.2%) and a negative predictive value of 98% (97.9-98.1%).

ConclusionsSERP showed better prediction performance than existing triage scores while maintaining easy implementation and ease of ascertainment at the ED. It has the potential to be widely applied and validated in different circumstances and healthcare settings.

Key pointsO_ST_ABSQuestionC_ST_ABSHow does a tool for predicting hospital outcomes based on a machine learning-based automatic clinical score generator, AutoScore, perform in a cohort of individuals admitted to hospital from the emergency department (ED) compared to other published clinical tools?

FindingsThe new tool, the Score for Emergency Risk Prediction (SERP), is parsimonious and point-based. SERP was more accurate in identifying patients who died during short or long-term care, compared with other point-based clinical tools.

MeaningSERP, a tool based on AutoScore is promising for triaging patients admitted from the ED according to mortality risk.

category: emergency medicine


title: AIBx, Artificial Intelligence Model to Risk Stratify Thyroid Nodules

abstract:
BackgroundCurrent classification systems for thyroid nodules are very subjective. Artificial intelligence (AI) algorithms have been used to decrease subjectivity in medical image interpretation. 1 out of 2 women over the age of 50 may have a thyroid nodule and at present the only way to exclude malignancy is through invasive procedures. Hence, there exists a need for noninvasive objective classification of thyroid nodules. Some cancers have benign appearance on ultrasonogram. Hence, we decided to create an image similarity algorithm rather than image classification algorithm.

MethodsUltrasound images of thyroid nodules from patients who underwent either biopsy or thyroid surgery from February of 2012 through February of 2017 in our institution were used to create AI models. Nodules were excluded if there was no definitive diagnosis of benignity or malignancy. 482 nodules met the inclusion criteria and all available images from these nodules were used to create the AI models. Later, these AI models were used to test 103 thyroid nodules which underwent biopsy or surgery from March of 2017 through July of 2018.

ResultsNegative predictive value of the image similarity model was 93.2%. Sensitivity, specificity, positive predictive value and accuracy of the model was 87.8%, 78.5%, 65.9% and 81.5% respectively.

ConclusionWhen compared to published results of ACR TIRADS and ATA classification system, our image similarity model had comparable negative predictive value with better sensitivity specificity and positive predictive value. By using image similarity AI models, we can eliminate subjectivity and decrease the number of unnecessary biopsies. Using image similarity AI model, we were able to create an explainable AI model which increases physicians confidence in the predictions.

category: endocrinology


title: Quantitative genome-scale analysis of human liver reveals dysregulation of glycosphingolipid pathways in progressive nonalcoholic fatty liver disease

abstract: Nonalcoholic fatty liver disease (NAFLD) is an increasingly prevalent disease that is associated with multiple metabolic disturbances, yet the metabolic pathways underlying its progression are poorly understood. Here we studied metabolic pathways of the human liver across the full histological spectrum of NAFLD. We analyzed whole liver tissue transcriptomics and serum metabolomics data obtained from a large, prospectively enrolled cohort of 206 histologically characterized patients derived from the European NAFLD Registry and developed genome-scale metabolic models (GEMs) of human hepatocytes at different stages of NAFLD. We identified several metabolic signatures in the liver and blood of these patients, specifically highlighting the alteration of vitamins (A, E) and glycosphingolipids, and their link with complex glycosaminoglycans in advanced fibrosis. Furthermore, we derived GEMs and identified metabolic signatures of three common NAFLD-associated gene variants (PNPLA3, TM6SF2 and HSD17B13). The study demonstrates dysregulated liver metabolic pathways which may contribute to the progression of NAFLD.


title: Blood and skeletal muscle ageing determined by epigenetic clocks and their associations with physical activity and functioning

abstract:
The aim of this study was to investigate the correspondence of different biological ageing estimates (i.e. epigenetic age) in blood and muscle tissue and their associations with physical activity (PA), physical function and body composition.

Two independent cohorts were included, whose age span covered adulthood (23-69 years). Whole blood and m. vastus lateralis samples were collected, and DNA methylation analysed. Four different DNA methylation age (DNAmAge) estimates were calculated using genome-wide methylation data and publicly available online tools. A novel muscle-specific methylation age was estimated using the R-package  MEAT. PA was measured with questionnaires and accelerometers. Several tests were conducted to estimate cardiorespiratory fitness and muscle strength. Body composition was estimated by dual-energy X-ray absorptiometry.

DNAmAge estimates from blood and muscle were highly correlated with chronological age, but different age acceleration estimates were weakly associated with each other. The monozygotic twin within-pair similarity of ageing pace was higher in blood (r=0.617-0.824) than in muscle (r=0.523-0.585). Associations of age acceleration estimates with PA, physical function and body composition were weak in both tissues and mostly explained by smoking and sex. The muscle-specific epigenetic clock MEAT was developed to predict chronological age, which may explain why it did not associate with functional phenotypes. The Horvaths clock and GrimAge were weakly associated with PA and related phenotypes, suggesting that higher PA would be linked to accelerated biological ageing in muscle. This may, however, be more reflective of the low capacity of epigenetic clock algorithms to measure functional muscle ageing than of actual age acceleration.

Based our results, the investigated epigenetic clocks have rather low value in estimating muscle ageing with respect to the physiological adaptations that typically occur due to ageing or PA. Thus, further development of methods is needed to gain further insight into muscle tissue-specific ageing and the underlying biological pathways.

category: epidemiology


title: An early assessment of the epidemiological effects of SARS-CoV-2 variants of concern in Germany

abstract: Growing evidence on higher transmissibility of novel variants of the SARS-CoV-2 coronavirus is raising alarm in many countries. We provide near-time estimates of the statistical association between reported cases of SARS-CoV-2 variants of concern (VOC) and epidemiological indicators at the local area level in Germany. Our findings indicate that the 7-day incidence rates in regions with confirmed VOC cases increased by up to 35%, on average, after VOC reporting compared to regions without confirmed cases by February 4. The hospitalization rate for COVID-19 patients in intensive care increased by up to 40%, but only for regions with most reported VOC cases. Both indicators further show a clear upward trend in regions with reported VOC cases vis-a-vis those without cases.


title: Early assessment of epidemiological trends associated with SARS-CoV-2 variants of concern in Germany


title: Changes in health behaviors, mental and physical health among older adults under severe lockdown restrictions during the COVID-19 pandemic in Spain

abstract:
BackgroundWe aimed to examine main changes in health behaviors, mental and physical health among older adults under severe lockdown restrictions during the COVID-19.

MethodsWe used prospective data from 3041 participants in four cohorts of community-dwelling individuals aged [≥]65 years in Spain. Data were obtained using validated questionnaires through a pre-pandemic face-to-face interview and a telephone interview conducted between weeks 7 to 15 after the beginning the COVID-19 lockdown. Lineal or multinomial, as appropriate, regression models with adjustment for the main confounders were used to assess changes in the outcome variables from the pre-pandemic to the confinement period, and to identify their associated factors.

ResultsOn average, the confinement was not associated with a deterioration in lifestyle risk factors (smoking, alcohol intake, diet or weight), except for a decreased physical activity and increased sedentary time, which reversed with the end of confinement. However, chronic pain worsened, and moderate declines in mental health, that did not seem to reverse after restrictions were lifted, were observed. Several subgroups of individuals were at increased risk of developing unhealthier lifestyles or mental health decline with confinement: (i)-males (for physical activity and sedentariness), (ii)-those with greater social isolation (for diet, physical activity, mental health), (iii)-feelings of loneliness (for diet, sleep quality, mental health), (iv)-poor housing conditions (for diet, physical activity, TV viewing time), (v)-unhealthy sleep duration (for physical activity and sedentariness), and (vi-worse overall health or chronic morbidities (for physical activity, screen time, mental health). On the other hand, previously having a greater adherence to the Mediterranean diet and doing more physical activity protected older adults from developing unhealthier lifestyles with confinement.

ConclusionsThe lockdown during the first wave of the COVID-19 in Spain, which was one of the most restrictive in Europe, only led to minor average changes in health behaviors among older adults. However, mental health was moderately affected. If another lockdown were imposed on this or future pandemics, public health programs should specially address the needs of older individuals with male sex, greater social isolation, poor housing conditions and chronic morbidities, because of their greater vulnerability to the enacted movement restrictions


title: Mortality from injury, overdose and suicide during the 2020 COVID-19 pandemic, March-July, 2020

abstract:
Introduction

The COVID-19 pandemic has been associated with substantial rates of all-cause excess mortality. The contribution of external causes of death to excess mortality including drug overdose, homicide, suicide, and unintentional injuries during the initial outbreak in the United States is less well documented.

MethodsUsing public data published by the National Center for Health Statistics on February 10, 2021, we measured monthly excess mortality (the gap between observed and expected deaths) from five external causes using national-level data published by National Center for Health Statistics; assault (homicide); intentional self-harm (suicide); accidents (unintentional injuries); and motor vehicle accidents. We used seasonal autoregressive integrated moving average (sARIMA) models developed with cause-specific monthly mortality counts and US population data from 2015-2019 and estimated the contribution of individual cause-specific mortality to all-cause excess mortality from March-July 2020.

ResultsFrom March-July, 2020, 212,825 (95% CI 136,236-290,776) all-cause excess deaths occurred in the US). There were 8,540 excess drug overdoses (all intents) (95% CI 5,106 to 11,975), accounting for 4% of all excess mortality; 1,455 excess homicide deaths (95% CI 708 to 2202, accounting for 0.7% of excess mortality; 5,492 excess deaths due to unintentional accidents occurred (95% CI 85 to 10,899, accounting for 2.6% of excess mortality. Though a non-significantly 135 (95% CI -1361 to 1,630) more MVA deaths were recorded during the study period, a significant decrease in April (525; 95% CI -817 to -233) and significant increases in June-July (965; 95% CI 348 to 1,587) were observed. Suicide deaths were statistically lower than projected by 2,067 (95% CI 941-3,193 fewer deaths).

MeaningExcess deaths from drug overdoses, homicide, and addicents occurred during the pandemic but represented a small fraction of all-cause excess mortality. The excess external causes of death, however, still represent thousands of lives lost. Notably, deaths from suicide were lower than expected and therefore did not contribute to excess mortality.


title: The impact of armed conflict on the epidemiological situation of Coronavirus disease (COVID-19) in Libya, Syria, and Yemen.

abstract:
BackgroundSince the Arab uprising 2011, Libya, Syria, and Yemen have gone through a major armed conflict. This resulted in a high rate of mortality, injury, and population displacement with a collapse of the health care system. Furthermore, it was complicated by the emergence of, COVID-19 as a global pandemic which made the population of these countries strive under unusual conditions to tackle both the pandemic and the ongoing wars. The objectives of this study were to determine the impacts and influence of armed conflicts on the epidemiology of Novel Coronavirus (SARS-CoV-2) within these war-torn countries and outline the needed strategies to combat the spread of the pandemic and its upcoming consequences.

MethodsThe official and public data regarding the dynamics of armed conflict and the spread, of SARS-COV-19 in Libya, Syria, and Yemen were collected from all available sources. Starting from the early emergence of the COVID-19 in each country until the end of December 2020. Datasets were analyzed through a set of statistical techniques and the weekly resolved data were used to probe the link between the intensity levels of the armed conflict and the spread of the pandemic.

ResultsData indicated that there is an increase in the intensity of violence levels at an early stage from March to August reached up to two folds in the three countries particularly in Libya. In this violent period, few cases of COVID-19 were reported ranging from 5-53 cases/day. From September to December, a significant decline in the level of the armed conflict was accompanied by steep upsurges in the number of reported COVID-19 cases reached up to 500 cases/day. The highest accumulative cases of COVID-19 were reported in Libya, Syria, and Yemen respectively.

ConclusionsOur analysis demonstrates that the armed conflict has provided an opportunity for SARS-COV-19 to spread. At the early weeks of the pandemic that coincided with high levels of the armed conflict few cases were officially reported indicating a vast undercount, which may suggest a hidden mitigating spread at an early stage. Then the pandemic increased immensely as the armed conflict decline to reach the highest by December. A full-blown transmission of the COVID-19 pandemic in these countries is expected. Therefore, urgent national and international strategies should be implemented to combat the pandemic and its upcoming consequences.


title: Human liver organoid derived intra-hepatic bile duct cells support SARS-CoV-2 infection and replication and its comparison with SARS-CoV

abstract:
BackgroundAlthough the main route of infection for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the respiratory tract, liver injury is also commonly seen in many patients, as evidenced by deranged parenchymal liver enzymes. Furthermore, patients with severe liver disease have been shown to have higher mortality. Overall, the mechanism behind the liver injury remains unclear.

Approach and resultsWe showed that intra-hepatic bile duct cells could be grown using a human liver organoid platform. The cholangiocytes were not only susceptible to SARS-CoV-2 infection, they also supported efficient viral replication. We also showed that SARS-CoV-2 replication was much higher than SARS-CoV.

ConclusionOur findings suggested direct cytopathic viral damage being a mechanism for SARS-CoV-2 liver injury.

category: gastroenterology


title: Moderators of changes in smoking, drinking, and quitting behaviour associated with the first Covid-19 lockdown in England

abstract:
AimTo estimate changes in smoking, drinking, and quitting behaviour from before to during the first Covid-19 lockdown in England, and whether changes differed by age, sex, or social grade.

DesignRepresentative cross-sectional surveys of adults, collected monthly between August 2018 and July 2020.

SettingEngland.

Participants36,980 adults ([≥]18y).

MeasurementsIndependent variables were survey month (pre-lockdown: August-February vs. lockdown months: April-July) and year (pandemic: 2019/20 vs. comparator: 2018/19). Smoking outcomes were smoking prevalence, cessation, quit attempts, quit success, and use of evidence-based or remote cessation support. Drinking outcomes were high-risk drinking prevalence, alcohol reduction attempts, and use of evidence-based or remote support. Moderators were age, sex, and occupational social grade (ABC1=more advantaged/C2DE=less advantaged).

FindingsRelative to changes over the same time period in 2018/19, lockdown was associated with significant increases in smoking prevalence (+24.7% in 2019/20 vs. 0.0% in 2018/19, ORadj=1.35[95%CI=1.12-1.63]) and quit attempts (+39.9% vs. -22.2%, ORadj=2.48[1.76-3.50]) among 18-34 year-olds, but not older groups. Increases in cessation (+156.4% vs. -12.5%, ORadj=3.08[1.86-5.09]) and the success rate of quit attempts (+99.2% vs. +0.8%, ORadj=2.29[1.31-3.98]) were also observed, and did not differ significantly by age, sex, or social grade. Lockdown was associated with a significant increase in high-risk drinking prevalence across all sociodemographic groups (+39.5% vs. -7.8%, ORadj=1.80[1.64-1.98]), with particularly high increases among women (ORadj=2.17[1.87-2.53]) and social grades C2DE (ORadj=2.34[2.00-2.74]). Alcohol reduction attempts increased significantly among high-risk drinkers from social grades ABC1 (ORadj=2.31[1.78-3.00]) but not C2DE (ORadj=1.25[0.83-1.88]), with larger increases among those aged 18-34 (ORadj=2.56[1.72-3.81]) and [≥]60 (ORadj=1.43[1.05-1.95]) than 35-59 (ORadj=2.51[1.51-4.18]). There were few significant changes in use of support for smoking cessation or alcohol reduction, although samples were small.

ConclusionsIn England, the first Covid-19 lockdown was associated with increased smoking prevalence among younger adults, and increased high-risk drinking prevalence among all adults. Smoking cessation activity also increased: more younger smokers made quit attempts during lockdown and more smokers quit successfully. Socioeconomic disparities in drinking behaviour were evident: high-risk drinking increased by more among women and those from less advantaged social grades (C2DE) but the rate of reduction attempts increased only among the more advantaged social grades (ABC1).


title: Effectiveness of Influenza Vaccines in the HIVE household cohort over 8 years: is there evidence of indirect protection?

abstract:
BackgroundThe evidence that influenza vaccination programs regularly provide protection to unvaccinated individuals (i.e. indirect effects) of a community is lacking. We sought to determine the direct, indirect, and total effects of influenza vaccine in the Household Influenza Vaccine Evaluation (HIVE) cohort.

MethodsUsing longitudinal data from the HIVE cohort from 2010-11 through 2017-18, we estimated direct, indirect, and total influenza vaccine effectiveness (VE) and the incidence rate ratio of influenza virus infection using adjusted mixed-effect Poisson regression models. Total effectiveness was determined through comparison of vaccinated members of full or partially vaccinated households to unvaccinated individuals in completely unvaccinated households.

ResultsThe pooled, direct VE against any influenza was 30.2% (14.0-43.4). Direct VE was higher for influenza A/H1N1 43.9% (3.9 to 63.5) and B 46.7% (17.2 to 57.5) than A/H3N2 31.7% (10.5 to 47.8); and was higher for young children 42.4% (10.1 to 63.0) than adults 18.6% (-6.3 to 37.7). Influenza incidence was highest in completely unvaccinated households (10.6 per 100 person-seasons) and lower at all other levels of household vaccine coverage. We found little evidence of indirect VE after adjusting for potential confounders. Total VET was 56.4% (30.1-72.9) in low coverage, 43.2% (19.5-59.9) in moderate coverage, and 33.0% (12.1 to 49.0) in fully vaccinated households.

ConclusionInfluenza vaccines may have a benefit above and beyond the direct effect but that effect in this study was small. While there may be exceptions, the goal of global vaccine recommendations should remain focused on provision of documented, direct protection to those vaccinated.


title: Epidemiological, Clinical Characteristics and Risk Factors for Severe Condition and ICU Admission of COVID-19 Patients of Early Stage in China: A review

abstract:
ObjectiveSome retrospective studies reporting epidemiological, clinical characteristics of COVID-19 patients of early stage were published. We aim to provide an overview of epidemiological and clinical characteristics of the COVID-19 patients, and identification, treatment of early stage, especially for the patients with poor prognosis.

Data SourcesPubMed, CNKI and Google Scholar.

Study SelectionWe searched for published retrospective studies that described epidemiological and clinical characteristics of confirmed COVID-19 patients in China by April 14th, 2020 with search terms. Some studies were excluded according to criteria. Finally, 53 studies were included.

Data ExtractionCharacteristics of the COVID-19 patients available from included articles were extracted, reorganized and recorded into electronic data forms.

Data SynthesisCharacteristics of patients in the included studies were summarized and analyzed for median-interquartile ranges and univariable odds ratio.

ConclusionThis study summarized, analyzed and compared epidemiological, clinical characteristics and estimated univariable risk factors among confirmed COVID-19 patients either in former epicenter, in severe condition, with ICU admission or not of early stage. Higher proportions of patients were found to have older age and more comorbidities, typical characteristics on admission and complications either in former epicenter, with severe condition or ICU admission. No evidence showed that patients who were male or had smoking history had higher susceptibility, but they were significant risk factors for severe condition. Some self-implementable traditional Chinese medicine therapies conducted for immunity improvement, control of comorbidities and reduction of some medicine intake. Limited evidence revealed that some characteristics of the disease might be changing with human-to-human transmission, and more research, especially international collaboration, is needed.

Copyright form disclosureThe authors have disclosed that they do not have any potential conflicts of interest.


title: Interrogating structural inequalities in COVID-19 Mortality in England and Wales

abstract:
BackgroundNumerous observational studies have highlighted structural inequalities in COVID-19 mortality in the UK. Such studies often fail to consider the complex spatial nature of such inequalities in their analysis, leading to the potential for bias and an inability to reach conclusions about the most appropriate structural levels for policy intervention.

MethodsWe use publicly available population data on COVID-19 related- and all-cause mortality between March and July 2020 in England and Wales to investigate the spatial scale of such inequalities. We propose a multiscale approach to simultaneously consider four spatial scales at which processes driving inequality may act and apportion inequality between these.

ResultsAdjusting for population age structure, number of care homes and residing in the North we find highest regional inequality in March and June/July. We find finer-grained within-region increased steadily from March until July. The importance of spatial context increases over the study period. No analogous pattern is visible for non-COVID mortality. Higher relative deprivation is associated with increased COVID-19 mortality at all stages of the pandemic but does not explain structural inequalities.

ConclusionsResults support initial stochastic viral introduction in the South, with initially high inequality decreasing before the establishment of regional trends by June and July, prior to reported regionality of the "second-wave". We outline how this framework can help identify structural factors driving such processes, and offer suggestions for a long-term, locally-targeted model of pandemic relief in tandem with regional support to buffer the social context of the area.

Key MessagesO_LIRegional inequality in COVID-19 mortality declined from an initial peak in April, before increasing again in June/July.
C_LIO_LIWithin-region inequality increased steadily from March until July.
C_LIO_LIStrong regional trends are evident in COVID-19 mortality in June/July, prior to wider reporting of regional differences in "second wave".
C_LIO_LIAnalogous spatial inequalities are not present in non-COVID related mortality over the study period.
C_LIO_LIThese inequalities are not explained by age structure, care homes, or deprivation.
C_LI