title: Disentangling post-vaccination symptoms from early COVID-19

abstract:
BackgroundIdentifying and testing individuals likely to have SARS-CoV-2 is critical for infection control, including post-vaccination. Vaccination is a major public health strategy to reduce SARS-CoV-2 infection globally. Some individuals experience systemic symptoms post-vaccination, which overlap with COVID-19 symptoms. This study compared early post-vaccination symptoms in individuals who subsequently tested positive or negative for SARS-CoV-2, using data from the COVID Symptom Study (CSS) app.

DesignWe conducted a prospective observational study in UK CSS participants who were asymptomatic when vaccinated with Pfizer-BioNTech mRNA vaccine (BNT162b2) or Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19) between 8 December 2020 and 17 May 2021, who subsequently reported symptoms within seven days (other than local symptoms at injection site) and were tested for SARS-CoV-2, aiming to differentiate vaccination side-effects per se from superimposed SARS-CoV-2 infection. The post-vaccination symptoms and SARS-CoV-2 test results were contemporaneously logged by participants. Demographic and clinical information (including comorbidities) were also recorded. Symptom profiles in individuals testing positive were compared with a 1:1 matched population testing negative, including using machine learning and multiple models including UK testing criteria.

FindingsDifferentiating post-vaccination side-effects alone from early COVID-19 was challenging, with a sensitivity in identification of individuals testing positive of 0.6 at best. A majority of these individuals did not have fever, persistent cough, or anosmia/dysosmia, requisite symptoms for accessing UK testing; and many only had systemic symptoms commonly seen post-vaccination in individuals negative for SARS-CoV-2 (headache, myalgia, and fatigue).

InterpretationPost-vaccination side-effects per se cannot be differentiated from COVID-19 with clinical robustness, either using symptom profiles or machine-derived models. Individuals presenting with systemic symptoms post-vaccination should be tested for SARS-CoV-2, to prevent community spread.

FundingZoe Limited, UK Government Department of Health and Social Care, Wellcome Trust, UK Engineering and Physical Sciences Research Council, UK National Institute for Health Research, UK Medical Research Council and British Heart Foundation, Alzheimers Society, Chronic Disease Research Foundation, Massachusetts Consortium on Pathogen Readiness (MassCPR).

Research in contextO_ST_ABSEvidence before this studyC_ST_ABSThere are now multiple surveillance platforms internationally interrogating COVID-19 and/or post-vaccination side-effects. We designed a study to examine for differences between vaccination side-effects and early symptoms of COVID-19. We searched PubMed for peer-reviewed articles published between 1 January 2020 and 21 June 2021, using keywords: "COVID-19" AND "Vaccination" AND ("mobile application" OR "web tool" OR "digital survey" OR "early detection" OR "Self-reported symptoms" OR "side-effects"). Of 185 results, 25 studies attempted to differentiate symptoms of COVID-19 vs. post-vaccination side-effects; however, none used artificial intelligence (AI) technologies ("machine learning") coupled with real-time data collection that also included comprehensive and systematic symptom assessment. Additionally, none of these studies attempt to discriminate the early signs of infection from side-effects of vaccination (specifically here: Pfizer-BioNTech mRNA vaccine (BNT162b2) and Oxford-AstraZeneca adenovirus-vectored vaccine (ChAdOx1 nCoV-19)). Further, none of these studies sought to provide comparisons with current testing criteria used by healthcare services.

Added value of this studyThis study, in a uniquely large community-based cohort, uses prospective data capture in a novel effort to identify individuals with COVID-19 in the immediate post-vaccination period. Our results show that early symptoms of SARS-CoV-2 cannot be differentiated from vaccination side-effects robustly. Thus, post-vaccination systemic symptoms should not be ignored, and testing should be considered to prevent COVID-19 dissemination by vaccinated individuals.

Implications of all the available evidenceOur study demonstrates the critical importance of testing symptomatic individuals - even if vaccinated - to ensure early detection of SARS-CoV-2 infection, helping to prevent future pandemic waves in the UK and elsewhere.

category: respiratory medicine


title: The Remote Assessment of Parkinsonism Supporting Ongoing Development of Interventions in Gaucher Disease - Study Protocol

abstract:
Mutations in GBA which are causative of Gaucher disease in their biallelic form, are the most common genetic risk factor for Parkinson disease. The diagnosis of Parkinson disease relies upon clinically defined motor features which appear after irreversible neurodegeneration. Prodromal symptoms of Parkinson disease may provide a means to predict latent pathology, years before the onset of motor features. Previous work has reported prodromal features of Parkinson disease in GBA mutation carriers, however this has been insufficiently sensitive to identify those that will develop Parkinson disease. The Remote Assessment of Parkinsonism Supporting Ongoing Development of Interventions in Gaucher Disease (RAPSODI) study assesses a large cohort of GBA mutation carriers, to aid development of procedures for earlier diagnosis of Parkinson disease.

Summary PointsO_LIThe therapeutic focus for Parkinson disease is currently symptomatic, rather than disease-modifying or neuroprotective.
C_LIO_LINon-motor prodromal features of Parkinson disease may precede the motor symptoms required for clinical diagnosis by several years.
C_LIO_LIGBA mutations, which are associated with Gaucher disease in their biallelic form, have emerged as the most common genetic risk factor for Parkinson Disease.
C_LIO_LIGBA associated PD displays a slightly exaggerated phenotype, including earlier age of onset, enhanced cognitive decline, more severe affective disturbances, and a greater likelihood of manifesting REM Sleep Behaviour Disorder, hyposmia and autonomic dysfunction.
C_LIO_LIThe RAPSODI GD study is an annual remote assessment which aims to define the clinical prodrome of PD in a large cohort of GBA mutation carriers, to accurately predict clinical diagnosis.
C_LIO_LIThe secondary objectives of RAPSODI GD are to risk stratify homozygote and heterozygote GBA mutation carriers for PD risk, understand the variable penetrance of the GBA associated PD phenotype, and create a platform for the future evaluation of biomarkers of disease.
C_LIO_LIThe putative implication of the RAPSODI GD study is to contribute towards earlier diagnosis of GBA associated PD, to provide a timeframe for delivering neuroprotective interventions.
C_LIO_LIDefining prodromal PD in GBA carriers may have wider implications for sporadic PD.
C_LI

category: neurology


title: Workplace risk management for SARS-CoV-2: a three-step early in-tervention strategy for effective containment of infection chains with special regards to virus variants with increased infectivity

abstract:
BackgroundPriority during the SARS-CoV2 pandemic is that employees need to be protected from infection risks and business activities need to be ensured. New virus variants with increased infection risks require an evolved risk strategy.

Material and methodsSeveral standard measures such as testing, isolation and quarantine are combined to a novel risk strategy. Epidemiological model calculations and scientific knowledge about the course of SARS-CoV2 infectivity are used to optimize this strategy. The procedure is implemented in an easy-to-use calculator based on Excel.

Layout in practice and resultsAlternative combinations of measures and practical aspects are discussed. Example calculations are used to demonstrate the effect of the discussed measures.

ConclusionThat quarantine calculator derived from these principles enables even non-specialists to perform a differentiated risk analysis and to introduce optimized measures. Targeted testing routines and alternative measures ensure staff availability.

category: occupational and environmental health


title: The effect of singers masks on the impulse dispersion of aerosols during singing

abstract:
BackgroundDuring the Covid-19 pandemic, singing activities were restricted due to several super-spreading events that have been observed during rehearsals and vocal performances. However, it has not been clarified how the aerosol dispersion, which has been assumed to be the leading transmission factor, could be reduced by masks which are specially designed for singers.

Material and Methods12 professional singers (10 of the Bavarian Radio-Chorus and two freelancers, 7 females and 5 males) were asked to sing the melody of the ode of joy of Beethovens 9th symphony "Freude schoner Gotterfunken, Tochter aus Elysium" in D-major without masks and afterwards with five different singers masks, all distinctive in their material and proportions. Every task was conducted after inhaling the basic liquid from an e-cigarette. The aerosol dispersion was recorded by three high-definition video cameras during and after the task. The cloud was segmented and the dispersion was analyzed for all three spatial dimensions. Further, the subjects were asked to rate the practicability of wearing the tested masks during singing activities using a questionnaire.

ResultsConcerning the median distances of dispersion, all masks were able to decrease the impulse dispersion of the aerosols to the front. In contrast, the dispersion to the sides and to the top was increased. The evaluation revealed that most of the subjects would reject performing a concert with any of the masks.

ConclusionAlthough, the results exhibit that the tested masks could be able to reduce the radius of aerosol expulsion for virus-laden aerosol particles, there are more improvements necessary to enable the practical implementations for professional singing.

category: otolaryngology


title: Longitudinal analysis of antibody responses to the Pfizer BNT162b2 vaccine in Patients Undergoing Maintenance Hemodialysis

abstract:
BackgroundHemodialyzed patients are at higher risk for COVID-19 and were prioritized in the Portuguese vaccination campaign

MethodsWe performed a prospective, longitudinal, cohort analysis of 143 patients on hemodialysis and 143 age-matched controls along BTN162b2 vaccination. ELISA quantified anti-full-length Spike IgG, IgM and IgA levels prior to the first vaccine dose (t0); 3 weeks later (second dose, t1); and 3 weeks later (t2); 127 patients were re-evaluated140 (t3) and 180 days (t4) after the first dose.

ResultsSeroconversion at t1 was remarkably low in patients, with positivity for anti-spike IgG, IgM and IgA antibodies of 29.4%, 12% and 41%, respectively, increasing to 90.9% (IgG) and 83.9% (IgA) in t2, (IgM remained unchanged). Below 70 years of age anti-spike IgG levels at t1 were significantly lower compared to age-matched controls and showed a profile similar to older individuals. Immunosuppression was associated with lower antibody responses (p=0.005 at t1; p=0.008 at t2). Previous unresponsiveness to hepatitis B vaccination (75/129, 58% of patients negative for anti-HBs antibodies) did not correlate with humoral unresponsiveness to BTN162b2. Anti-spike IgG, IgM and IgA positivity and antibody levels significantly decay at t3, with IgG levels showing further waning at t4.

ConclusionsThe large majority of hemodialyzed patients showed IgG seroconversion upon BNT162b2 mRNA vaccination, albeit a sizable proportion of patients presented poor responses. Follow-up of antibody responses 180 days post vaccination unveiled significant decay of anti-spike antibodies and warrant close monitoring of COVID-19 infection and further studies on reinforced vaccination schedules in patients undergoing maintenance hemodialysis.

category: infectious diseases


title: MIXTURE of human expertise and deep learning - Developing an explainable model for predicting pathological diagnosis and survival in patients with interstitial lung disease

abstract:
Interstitial pneumonia is a heterogeneous disease with a progressive course and poor prognosis, at times even worse than those in the main cancer types. Histopathological examination is crucial for its diagnosis and estimation of prognosis. However, the evaluation strongly depends on the experience of pathologists, and the reproducibility of diagnosis is low.

Herein, we propose MIXTURE (huMan-In-the-loop eXplainable artificial intelligence Through the Use of REcurrent training), a method to develop deep learning models for extracting pathologically significant findings based on an expert pathologists perspective with a small annotation effort. The procedure of MIXTURE consists of three steps as follows. First, we created feature extractors for tiles from whole slide images using self-supervised learning. The similar looking tiles were clustered based on the output features and then pathologists integrated the pathologically synonymous clusters. Using the integrated clusters as labeled data, deep learning models to classify the tiles into pathological findings were created by transfer-learning the feature extractors. We developed three models for different magnifications.

Using these extracted findings, our model was able to predict the diagnosis of usual interstitial pneumonia, a finding suggestive of progressive disease, with high accuracy (AUC 0.90). This high accuracy could not be achieved without the integration of findings by pathologists. The patients predicted as UIP had significantly poorer prognosis (five-year overall survival [OS]: 55.4%) than those predicted as non-UIP (OS: 95.2%). The Cox proportional hazards model for each microscopic finding and prognosis pointed out dense fibrosis, fibroblastic foci, elastosis, and lymphocyte aggregation as independent risk factors. We suggest that MIXTURE may serve as a model approach to different diseases evaluated by medical imaging, including pathology and radiology, and be the prototype for artificial intelligence that can collaborate with humans.

category: pathology


title: The Effect of Increasing Women's Autonomy on Primary and Repeated Caesarean Sections in Brazil

abstract: Caesarean section (C-section) rates continue to rise globally. Yet, there is little consensus about the key determinants of rising C-section rates and the sources of variation in C-section rates across the world. While C-sections can save lives when medically justified, unnecessary surgical procedures can be harmful for women and babies. We show that a state-wide law passed in Sao Paulo (Brazil), which increased women's autonomy to choose to deliver via C-sections even when not medically necessary, is associated with a 3% increase in overall C-section rates. This association was driven by a 5% increase in primary C-sections, rather than repeated C-sections. These findings are notable given the already high C-section rate in Brazil (>55%) and given the likelihood of primary C-section leading to future births being delivered via C-section.

category: obstetrics and gynecology


title: Autosomal recessive SLC30A9 Mutations in a Proband with a Cerebro-Renal Syndrome and No Parental Consanguinity

abstract: An SLC30A9-associated cerebro-renal syndrome was first reported in consanguineous Bedouin kindred by Perez et al. in 2017. While the function of the gene has not yet been fully elucidated, it may be implicated in Wnt signaling, nuclear regulation, as well as cell and mitochondrial zinc regulation. In this research report, we present a female proband with two distinct, inherited autosomal recessive loss-of-function SLC30A9 variants from unrelated parents. To our knowledge, this is the first reported case of a possible SLC30A9-associated cerebro-renal syndrome in a non-consanguineous family. Furthermore, a limited statistical analysis was conducted to identify possible allele frequency differences between populations. Our findings provide further support for an SLC30A9-associated cerebro-renal syndrome and may help further clarify the genes function.

category: genetic and genomic medicine


title: An Explainable Artificial Intelligence Approach for Predicting Cardiovascular Outcomes using Electronic Health Records

abstract: Understanding the conditionally-dependent clinical variables that drive cardiovascular health outcomes is a major challenge for precision medicine. Here, we deploy a recently developed massively scalable comorbidity discovery method called Poisson Binomial based Comorbidity discovery (PBC), to analyze Electronic Health Records (EHRs) from the University of Utah and Primary Childrens Hospital (over 1.6 million patients and 77 million visits) for comorbid diagnoses, procedures, and medications. Using explainable Artificial Intelligence (AI) methodologies, we then tease apart the intertwined, conditionally-dependent impacts of comorbid conditions and demography upon cardiovascular health, focusing on the key areas of heart transplant, sinoatrial node dysfunction and various forms of congenital heart disease. The resulting multimorbidity networks make possible wide-ranging explorations of the comorbid and demographic landscapes surrounding these cardiovascular outcomes, and can be distributed as web-based tools for further community-based outcomes research. The ability to transform enormous collections of EHRs into compact, portable tools devoid of Protected Health Information solves many of the legal, technological, and data-scientific challenges associated with large-scale EHR analyzes.

category: health informatics


title: Role of Multi-resolution Vulnerability Indices in COVID-19 spread: A Case Study in India

abstract:
IntroductionThe outbreak of COVID-19 has differentially affected countries in the world, with health infrastructure and other related vulnerability indicators playing a role in determining the extent of the COVID-19 spread. Vulnerability of a geographical region/country to COVID-19 has been a topic of interest, particularly in low- and middle-income countries like India to assess the multi-factorial impact of COVID-19 on the incidence, prevalence or mortality data.

Datasets and MethodsBased on publicly reported socio-economic, demographic, health-based and epidemiological data from national surveys in India, we compute contextual, COVID-19 Vulnerability Indices (cVIs) across multiple thematic resolutions for different geographical and spatial administrative regions. These multi-resolution cVIs were used in regression models to assess their impact on indicators of the spread of COVID-19 such as the average time-varying instantaneous reproduction number.

ResultsOur observational study was focused on 30 districts of the eastern Indian state of Odisha. It is an agrarian state, prone to natural disasters and one of the largest contributors of an unprotected migrant workforce. Our analyses identified housing and hygiene conditions, availability of health care and COVID preparedness as important spatial indicators.

ConclusionOdisha has demonstrated success in containing the COVID-19 infection to a reasonable level with proactive measures to contain the spread of the virus during the first wave. However, with the onset of the second wave of COVID, the virus has been making inroads into the hinterlands and peripheral districts of the state, burdening the already deficient public health system in these areas. The vulnerability index presented in this paper identified vulnerable districts in Odisha. While some of them may not have a large number of COVID-19 cases at a given point of time, they could experience repercussions of the pandemic. Improved understanding of the factors driving COVID-19 vulnerability will help policy makers prioritise resources and regions leading to more effective mitigation strategies for the COVID-19 pandemic and beyond.

O_TEXTBOXWHAT IS ALREADY KNOWNMeasuring vulnerability to COVID-19 and other pandemics is a complex and layered subject. In Low-to-Middle-Income Country (LMIC) like India, complete reliance on incidence, prevalence or mortality data of the disease may not be the best measure since this data from the health system and DHS in public domain is limited.

ADDED VALUE OF THIS STUDYTo our knowledge, this is the first study at the district level concerning the COVID-19 situation in Odisha, characterized by a large tribal and migrant population. We defined vulnerability through relevant socio-economic domains that have an influence on mitigation strategies. Although we applied our methods to the districts of Odisha, we believe they can be used in other LMIC regions.

IMPLICATIONS OF THE FINDINGSRegions with higher overall or theme-specific vulnerability index might experience potentially severe consequences of the COVID-19 outbreak demanding precise, dynamic and nimble policy decisions to prevent a potentially dire situation.

C_TEXTBOX


title: Variation in SARS-CoV-2 bioaerosol production in exhaled breath

abstract: Using face mask bioaerosol sampling, we found substantial variation between individuals in SARS-CoV-2 copies exhaled over a 15-minute period, which moderately correlated with nasal swab viral load. Talking was associated with a median of 2 log10 greater exhaled viral copies. Exposure varies substantially between individuals but may be risk stratified by nasal swab viral load and whether the exposure involved conversation.


title: Asthma and the Risk of SARS-CoV-2 Infection Among Children and Adolescents

abstract: Importance: More than 4 million SARS-COV-2 infections have occurred among children and adolescents in the United States. Risk factors for SARS-CoV-2 infection among children remain poorly defined. Objective: To evaluate the association between asthma and the risk of SARS-CoV-2 infection among children. Design: Retrospective cohort study Setting: A large, integrated health system in central North Carolina. Participants: Children 5 to 17 years of age with a Durham County address and at least one health care encounter in the Duke University Health System between March 1, 2017, and February 28, 2020. Exposure: Diagnosis of asthma Main Outcomes and Measures: The primary outcome was SARS-CoV-2 infection identified by PCR testing of a respiratory sample collected between March 1, 2020, and October 31, 2020. We matched children with asthma 1:1 to children without asthma using propensity scores and used Poisson regression to evaluate the association between asthma and the risk of SARS-CoV-2 infection. We assessed for effect modification of this association by inhaled corticosteroid prescription and comorbid atopic diseases. Results: Of 49,455 children, 6,515 (13%) met criteria for a diagnosis of asthma; all children with asthma were matched to a control child without asthma for a final cohort of 13,030 children. Median (interquartile range) age was 11.0 (8.0, 14.0) years, 56% were male, and 78% were non-White. A diagnosis of asthma was associated with a decreased risk of SARS-CoV-2 infection [risk ratio (RR): 0.67, 95% confidence interval (CI): 0.49-0.92]. This association tended to be stronger in children with asthma who were prescribed inhaled corticosteroids (RR: 0.60, 95% CI: 0.38-0.94) or who had comorbid atopic diseases (RR: 0.59, 95% CI: 0.39-0.88). Of the 66 children with asthma who developed SARS-CoV-2 infection, none required hospitalization for COVID-19. Conclusions and Relevance: Children with asthma had a lower risk of SARS-CoV-2 infection, particularly children prescribed an inhaled corticosteroid or with comorbid atopic diseases. Further studies are needed to explore the complex relationship between asthma, inhaled corticosteroids, and SARS-CoV-2.


title: Optimal vaccine allocation for COVID-19 in the Netherlands: a data-driven prioritization

abstract:
For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to find an optimal distribution of vaccines, there is an excessively large number of possible schemes to be simulated.

Here, we propose an algorithm to find a near-optimal allocation scheme given an intervention objective such as minimization of new infections, hospitalizations, or deaths, where multiple vaccines are available. The proposed principle for allocating vaccines is to target subgroups with the largest reduction in the outcome of interest, such as new infections, due to vaccination that fully immunizes a single individual. We express the expected impact of vaccinating each subgroup in terms of the observed incidence of infection and force of infection. The proposed approach is firstly evaluated with a simulated epidemic and then applied to the epidemiological data on COVID-19 in the Netherlands.

Our results reveal how the optimal allocation depends on the objective of infection control. In the case of COVID-19, if we wish to minimize deaths, the optimal allocation strategy is not efficient for minimizing other outcomes, such as infections. In simulated epidemics, an allocation strategy optimized for an outcome outperforms other strategies such as the allocation from young to old, from old to young, and at random. Our simulations clarify that the current policy in the Netherlands (i.e., allocation from old to young) was concordant with the allocation scheme that minimizes deaths.

The proposed method provides an optimal allocation scheme, given routine surveillance data that reflect ongoing transmissions. The principle of allocation is useful for providing plausible simulation scenarios for complex models, which give a more robust basis to determine intervention strategies.

Author summaryVaccination is the key to controlling the ongoing COVID-19 pandemic. In the early stages of an epidemic, there is shortage of vaccine stocks. Here, we propose an algorithm that computes an optimal vaccine distribution among groups for each intervention objective (e.g., minimizing new infections, hospitalizations, or deaths). Unlike existing approaches that use detailed information on at-risk contacts between and among groups, the proposed algorithm requires only routine surveillance data on the number of cases. This method is applicable even when multiple vaccines are available. Simulation results show that the allocation scheme optimized by our algorithm performed the best compared with other strategies such as allocating vaccines at random and in the order of age. Our results also reveal that an allocation scheme optimized for one specific objective is not necessarily efficient for another, indicating the importance of the decision-making at the early phase of distributions.


title: The evaluation of the insertion parameters and complications of the i-gel Plus airway device for maintaining patent airway during planned procedures under general anaesthesia: a protocol for a prospective multi-center cohort study.

abstract:
IntroductionSupraglottic airway devices represent a less invasive method of airway management than tracheal intubation during general anaesthesia. Their continued development is focused mainly on improvements in the insertion success rate and minimalization of perioperative and postoperative complications. The i-gel Plus is a novel, anatomically preshaped supraglottic airway device which achieves a perilaryngeal seal due to a non-inflatable cuff made of a soft thermoplastic elastomer. The purpose of this trial is to assess the success rate of the i-gel Plus use during elective procedures under general anaesthesia, its intraoperative performance, and the degree of postoperative complications.

Methods and analysisThis is a multicenter, prospective, interventional cohort study. The enrolment will take place in seven centers in four European countries. We plan to enrol 2000 adult patients in total, who are scheduled for elective surgery under general anaesthesia, and with an indication for use of a supraglottic airway device for management of their airway. The study is projected to run over a period of 18 months. The primary outcome of the study is the total success rate of the i-gel Plus insertion in terms of successful ventilation and oxygenation through the device. Secondary outcomes include perioperative parameters, such as insertion time, seal/leak pressures, number of insertion attempts, and postoperative adverse events and complications. Postoperative follow-up will be performed at 1 hour, 24 hours in all patients, and for selected patients at 3 and 6 months.

Ethics and disseminationThe trial has received the following ethical approvals: General University Hospital Prague, University Hospital Olomouc, University Military Hospital Prague, University Hospital Barcelona, University Hospital Lodz, Antrim Area Hospital, Craigavon Area Hospital, Office for Research Ethics Committees Northern Ireland. The results will be published in peer-reviewed journals and presented at relevant anaesthesia conferences.

Trial registration numberISRCTN86233693

ARTICLE SUMMARYO_ST_ABSStrengths and limitations of this studyC_ST_ABS- The study will provide the first data about the use of the novel supraglottic airway device, the i-gel Plus for maintaining ventilation and oxygenation during anaesthesia.
- Broad inclusion criteria and the multicenter, multinational design of the study will allow study of a wide spectrum of populations of different age, gender and ethnicity and thus provide more generalisable results.
- Patients showing significant postoperative adverse effects will be followed up for up to 6 months which will provide information about the long-term complication rates of the device.
- The main limitation of the study is that the device will be trialled only in selected elective procedures and not as a rescue device or in difficult airway management scenarios.

category: anesthesia


title: Local Exhaust Ventilation to Control Dental Aerosols and Droplets

abstract: Dental procedures produce aerosols which may remain suspended and travel significant distances from the source. Dental aerosols and droplets contain oral microbes and there is potential for infectious disease transmission and major disruption to dental services during infectious disease outbreaks. One method to control hazardous aerosols often used in industry is Local Exhaust Ventilation (LEV). The aim of this study was to investigate the effect of LEV on aerosols and droplets produced during dental procedures. Experiments were conducted on dental mannequins in an 825.4 m3 open plan clinic, and a 49.3 m3 single surgery. 10-minute crown preparations were performed with an air-turbine handpiece in the open plan clinic, and 10-minute full mouth ultrasonic scaling in the single surgery. Fluorescein was added to instrument irrigation reservoirs as a tracer. In both settings, Optical Particle Counters (OPCs) were used to measure aerosol particles between 0.3 - 10.0 m and liquid cyclone air samplers were used to capture aerosolised fluorescein tracer. Additionally, in the open plan setting fluorescein tracer was captured by passive settling onto filter papers in the environment. Tracer was quantified fluorometrically. An LEV device with High Efficiency Particulate Air (HEPA) filtration and a flow rate of 5,000 L/min was used. LEV reduced aerosol production from the air-turbine handpiece by 90% within 0.5 m, and this was 99% for the ultrasonic scaler. OPC particle counts were substantially reduced for both procedures, and air-turbine settled droplet detection reduced by 95% within 0.5 m. The effect of LEV was substantially greater than suction alone for the air-turbine and was similar to the effect of suction for the ultrasonic scaler. LEV reduces aerosol and droplet contamination from dental procedures by at least 90% in the breathing zone of the operator and it is therefore a valuable tool to reduce the dispersion of dental aerosols.

category: dentistry and oral medicine


title: How an election can be safely planned and conducted during a pandemic: Decision support based on a discrete event model

abstract:
In 2020, the ongoing COVID-19 pandemic caused major limitations for any aspect of social life and in specific for all events that require a gathering of people. While most events of this kind can be postponed or cancelled, democratic elections are key elements of any democratic regime and should be upheld if at all possible. Consequently, proper planning is required to establish the highest possible level of safety to both voters and scrutineers. In this paper, we present the novel and innovative way how the municipal council and district council elections in Vienna were planned and conducted using an discrete event simulation model. Key target of this process was to avoid queues in front of polling stations to reduce the risk of related infection clusters. In cooperation with a hygiene expert, we defined necessary precautions that should be met during the election in order to avoid the spread of COVID-19. In a next step, a simulation model was established and parametrized and validated using data from previous elections. Furthermore, the planned conditions were simulated to see whether excessive queues in front of any polling stations could form, as these could on the one hand act as an infection herd, and on the other hand, turn voters away. Our simulation identified some polling stations where long queues could emerge. However, splitting up these electoral branches resulted in a smooth election across all of Vienna. Looking back, the election did not lead to a significant increase of COVID-19 incidences. Therefore, it can be concluded that careful planning led to a safe election, despite the pandemic.

Author summaryO_ST_ABSWhy was this study done?C_ST_ABSO_LIThe ongoing COVID-19-Pandemic poses a risk for elections, as these could lead to another spread of the disease.
C_LIO_LIAdditional hygiene measures, which are inevitable if the election is conducted, could lead to long queues in front of the polling stations on election day.
C_LI

What did the researchers do and find?O_LIWe describe the defined additional hygiene measures.
C_LIO_LIWe modeled the whole election process, including the new hygiene concept, to show where extensive queues could form on the election day.
C_LIO_LIWe show that thanks to the additional hygiene measures, the election actually did not cause a temporary upswing of the epidemic.
C_LI

What do these findings mean?O_LIThanks to careful planning, it is possible to safely hold an election during such a pandemic.
C_LIO_LIOur simulation contributed to a safe and smooth election.
C_LIO_LIHowever, it should be stated, that these findings hold for elections in Austria, where long queues in front of polling stations are comparably rare and short.
C_LI

category: epidemiology


title: Will a natural collective immunity of Ukrainians restrain new COVID-19 waves?

abstract: The visible and real sizes the COVID-19 epidemic in Ukraine were estimated with the use of the number of laboratory-confirmed cases (accumulated in May and June 2021), the generalized SIR-model and the parameter identification procedure taking into account the difference between registered and real number of cases. The calculated optimal value of the visibility coefficient shows that most Ukrainians have already been infected with the coronavirus, and some more than once, i.e., Ukrainians have probably achieved a natural collective immunity. Nevertheless, a large number of new strains and short-lived antibodies can cause new pandemic waves. In particular, the beginning of such a wave, we probably see in Ukraine in mid-July 2021. The further dynamics of the epidemic and its comparison with the results of mathematical modeling will be able to answer many important questions about the natural immunity and effectiveness of vaccines.


title: Characterization of SARS CoV-2 Antibodies in Breast Milk from 21 Women with Confirmed COVID-19 Infection

abstract:
One potential mechanism for protection from SARS-CoV-2 in infants and young children is through passive immunity via breast milk from a mother previously infected with the novel coronavirus. The primary objectives of this study were to establish the presence of SARS-CoV-2 specific IgA and IgG and to characterize the specific antigenic regions of SARS-CoV-2 proteins that were reactive with antibodies in breast milk from women with confirmed SARS-CoV-2 infection.

Between March 2020 and September 2020, 21 women with confirmed SARS-CoV-2 infection were enrolled into Mommys Milk at the University of California, San Diego. Women donated serial breast milk samples. Breast milk samples were used to probe a multi-coronavirus protein microarray containing full-length proteins and variable length overlapping fragments of SARS-CoV-2 spike (S), envelope (E), membrane (M), nucleocapsid (N), and open reading frame (ORF) proteins.

The breast milk samples contained IgA reactive with a variety of SARS-CoV-2 antigens. The most IgA-reactive SARS-CoV-2 proteins were N (42.9% of women responded to 1 [≥] N fragment) and S proteins (23.9% of women responded to [≥] 1 fragment of S1 or S2). Overall, individual COVID-19 cases had diverse and unique milk IgA profiles over the course of follow-up since onset of SARS-CoV-2 symptoms.

category: pediatrics


title: Uptake of infant and pre-school immunisations in Scotland and England during the COVID-19 pandemic: an observational study of routinely collected data

abstract:
BackgroundIn 2020, the COVID-19 pandemic and control measures such as national lockdowns threatened to disrupt routine childhood immunisation programmes. Initial reports from the early weeks of lockdown in the UK and worldwide suggested that uptake could fall putting children at risk from multiple other infectious diseases. In Scotland and England, enhanced surveillance of national data for childhood immunisations was established to inform and rapidly assess the impact of the pandemic on infant and preschool immunisation uptake rates.

Methods and findingsWe undertook an observational study using routinely collected data for the year prior to the pandemic (2019), and immediately before, during and after the first period of the UK  lockdown in 2020. Data were obtained for Scotland from the Public Health Scotland "COVID19 wider impacts on the health care system" dashboard (https://scotland.shinyapps.io/phs-covid-wider-impact/) and for England from ImmForm.

Five vaccinations delivered at different ages were evaluated; three doses of the  6-in-1 DTaP/IPV/Hib/HepB vaccine and two doses of MMR. Uptake in the periods in 2020 compared to that in the baseline year of 2019 using binary logistic regression analysis. For Scotland, we analysed timely uptake of immunisations, defined as uptake within four weeks of the child becoming eligible by age for each immunisation and data were also analysed by geographical region and indices of deprivation. For both Scotland and England, we assessed whether immunisations were up to date at approximately 6 months (all doses 6-in-1) and 16-18 months (first MMR) of age.

We found that uptake rates within four weeks of eligibility in Scotland for all the five vaccine visits were higher during the 2020 lockdown period than in 2019. The difference ranged from 1.3% for the first dose of the 6-in-1 vaccine (95.3 vs 94%, OR 1.28, CI 1.18-1.39) to 14.3% for the second MMR dose (66.1 vs 51.8 %, OR 1.8, CI 1.74-1.87). Significant increases in uptake were seen across all deprivation levels, though, for MMR, there was evidence of greater improvement for children living in the least deprived areas.

In England, fewer children who had been due to receive their immunisations during the lockdown period were up to date at 6 months (6-in-1) or 18 months (first dose MMR). The fall in percentage uptake ranged from 0.5% for first 6-in1 (95.8 vs 96.3%, OR 0.89, CI 0.86-0.91) to 2.1% for third 6-in-1 (86.6 vs 88.7%, OR 0.82, CI 0.81-0.83).

ConclusionsThis study suggests that the national lockdown in Scotland was associated with a positive effect on timely childhood immunisation uptake, however in England a lower percentage of children were up to date at 6 and 18 months. Reason for the improve uptake in Scotland may include active measures taken to promote immunisation at local and national level during this period. Promoting immunisation uptake and addressing potential vaccine hesitancy is particularly important given the ongoing pandemic and COVID-19 vaccination campaigns.


title: Association Between Ultrasonography Fetal Anomalies and Autism Spectrum Disorder

abstract:
AbstractsO_ST_ABSBackgroundC_ST_ABSPrenatal ultrasound is frequently used to monitor fetal growth and identify fetal anomalies that may suggest genetic or developmental abnormalities which may develop into congenital anomalies and diseases. Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder, associated with a wide range of congenital anomalies. Nevertheless, very little has been done to investigate organ development using prenatal ultrasound as a means to identify fetuses with ASD susceptibility.

MethodsA retrospective matched case-sibling-control study. ASD cases were matched to two control groups: typically developing sibling (TDS) closest in age to ASD child; and typically developing population (TDP), matched for age, sex, and ethnicity. The study comprised 659 children: 229 ASD, 201 TDS, and 229 TDP; 471 (71.5%) males.

ResultsUltrasonography fetal anomalies (UFAs) were found in 29.3% of ASD cases vs. only 15.9% and 9.6% in the TDS and TDP groups (aOR=2.23, 95%CI=1.32-3.78, and OR=3.50, 95%CI=2.07-5.91, respectively). Also, multiple co-occurring UFAs were significantly more prevalent among ASD cases. UFAs in the urinary system, heart, and head&brain were the most significantly associated with ASD diagnosis (aORUrinary =2.08, 95%CI=0.96-4.50 and aORUrinary=2.90, 95%CI=1.41-5.95; aORHeart=3.72, 95%CI=1.50-9.24 and aORHeart=8.67, 95%CI=2.62-28.63; and aORHead&Brain=1.96, 95%CI=0.72-5.30 and aORHead&Brain=4.67, 95%CI=1.34-16.24; vs. TDS and TDP, respectively). ASD females had significantly more UFAs than ASD males (43.1% vs. 25.3%, p=0.013) as well as higher prevalence of multiple co-occurring UFAs (15.7% vs. 4.5%, p=0.011), while no sex differences were seen among TDS and TDP controls. ASD fetuses were characterized by a narrower head and a relatively wider ocular-distance vs. TDP fetuses (aORBPD=0.81, 95%CI=0.70-0.94, and aOROcular-Distance=1.29, 95%CI=1.06-1.57). Finally, UFAs were associated with more severe ASD symptoms.

ConclusionsOur findings shed important light on the abnormal multiorgan embryonic development of ASD and suggest fetal ultrasonography biomarkers for ASD.


category: psychiatry and clinical psychology


title: Cognitive profile of mild behavioral impairment in Brain Health Registry participants

abstract:
INTRODUCTIONDementia assessment includes cognitive and behavioral testing with informant validation. Conventional testing is resource intensive, with uneven access. Online unsupervised assessments could reduce barriers to risk assessment. We interrogated the relationship between informant-rated behavioral changes and neuropsychological test performance in older adults in the Brain Health Registry.

METHODSParticipants completed online unsupervised cognitive tests, and informants completed the Mild Behavioral Impairment Checklist via a Study Partner portal. Cognitive performance was evaluated in MBI+/- individuals, as was the association between cognitive scores and MBI symptom severity.

RESULTSMean age of the 499 participants was 67, 61% of which were female. MBI+ participants had lower working memory and executive function test scores. Lower cognitive test scores associated with greater MBI burden.

DISCUSSIONOur findings support the feasibility of remote, informant-reported behavioral assessment and support its validity by demonstrating a relationship to cognitive test performance using online unsupervised assessments for dementia risk assessment.

RESEARCH IN CONTEXTO_ST_ABSSystematic reviewC_ST_ABSThe authors searched MEDLINE and Google Scholar for studies linking Mild Behavioral Impairment (MBI) and cognition in non-demented older adults. Most studies have utilized transformed Neuropsychiatric Inventory scores to assess MBI, and relatively few using the novel MBI-checklist (MBI-C), with the largest study using self-report. Exploration of informant reports of MBI is important due to impaired insight that may accompany neuropsychiatric symptoms.

InterpretationOlder adults with online, informant reported MBI had poorer performance in memory and executive function measured using online neuropsychological testing compared to those without MBI. These findings are consistent with the current literature and suggest that the MBI-C may serve as a marker for poorer cognitive performance.

Future directionsOur data support the role of online testing of cognition and behavior for risk assessment. This approach to evaluate behavior and cognition can be explored further, to determine if it is a scalable, online approach to detection of neurodegenerative disease.


title: Digital Health Tools for the Passive Monitoring of Depression: A Systematic Review of Methods

abstract: Background: The use of digital tools to measure physiological and behavioural variables of potential relevance to mental health is a growing field sitting at the intersection between computer science, engineering and clinical science. We aim to summarise the literature on remote measuring technologies, mapping methodological challenges and threats to reproducibility, and to identify leading digital signals for depression. Methods: Medical and computer science databases were searched between January 2007 to November 2019. Published studies linking depression and objective behavioural data obtained from smartphone and wearable device sensors in adults with unipolar depression and healthy subjects were included (PROSPERO registration: 2019 CRD42019159929). A descriptive approach was taken to synthesise study methodologies. Results We included 52 studies and found threats to reproducibility and transparency arising from failure to provide comprehensive descriptions of recruitment strategies, sample information, feature construction and the determination and handling of missing data. The literature is characterised by small sample sizes, short follow-up duration and great variability in quality of reporting, limiting the interpretability of pooled results. Bivariate analyses show some consistency in statistically significant associations between depression and digital features from sleep, physical activity, location, and phone use data. Regression and classification machine learning models found predictive value of aggregated features. Interpretation: Recommendations are put forward to improve aspects of generalisability and reproducibility, such as wider diversity of samples, thorough reporting methodology and the potential for reporting bias in studies with numerous features. Funding: National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London.


title: Determinants of SARS-CoV-2 Vaccine Engagement in Algeria: A Population-based Study with Systematic Review of Studies from Arab Countries of the MENA Region

abstract:
BackgroundThe Algerian COVID-19 vaccination campaign, which started by the end of January 2021, is marked by a slowly ascending curve despite the deployed resources. To tackle the issue, we assessed the levels and explored determinants of engagement towards the COVID-19 vaccine among the Algerian population.

MethodsA nationwide, online-based cross-sectional study was conducted between March 27 and April 30, 2021. A two-stage stratified snowball sampling method was used to include an equivalent number of participants from the four cardinal regions of the country. A vaccine engagement scale was developed, defining vaccine engagement as a multidimensional parameter (5 items) that combined self-stated acceptance and willingness with perceived safety and efficacy of the vaccine. An Engagement score was calculated and the median was used to define engagement versus nonengagement. Sociodemographic and clinical data, perceptions about COVID-19 and levels of adherence to preventive measures were analyzed as predictors for nonengagement.

ResultsWe included 1,019 participants, 54% were female and 64% were aged 18-29 years. Overall, there were low rates of self-declared acceptance (26%) and willingness (21%) to take the vaccine, as well as low levels of agreement regarding vaccine safety (21%) and efficacy (30%). Thus, vaccine engagement rate was estimated at 33.5%, and ranged between 29.6-38.5% depending on the region (p>0.05). Nonengagement was independently associated with female gender (OR=2.31, p<0.001), low adherence level to preventive measures (OR=6.93p<0.001), private sector jobs (OR=0.53, p=0.038), perceived COVID-19 severity (OR=0.66, p=0.014), and fear from contracting the disease (OR=0.56, p=0.018). Concern about vaccine side effects (72.0%) and exigence for more efficacy and safety studies (48.3%) were the most commonly reported barrier and enabler for vaccine acceptance respectively; whereas beliefs in the conspiracy theory were reported by 23.4%.

ConclusionsThe very low rates of vaccine engagement among the Algerian population probably explain the slow ascension of the vaccination curve in the country. Vaccine awareness campaigns should be implemented to address the multiple misconceptions and enhance the levels of knowledge and perception both about the disease and the vaccine, by prioritizing target populations and engaging both healthcare workers and the general population.

category: public and global health


title: Effects of COVID-19 2021 lockdown on the sleep quality and mental health of undergraduate medical and dental students of Pakistan: A cross-sectional study.

abstract:
Background and objectivesThe COVID-19 pandemic has been recognized as a cause of direct and indirect psychological consequences that impact mental health such as acute stress disorders, anxiety, irritability, poor concentration, and insomnia. This study was planned to evaluate the sleep quality and mental health of undergraduate students amidst the COVID-19 lockdown of 2021.

Materials and MethodsThis observational cross-sectional study was conducted in Lahore, Pakistan, where 261 undergraduate medical and dental students enrolled at a private medical and dental school were approached from March to May 2021. The Pittsburg Sleep Quality Index (PSQI) was used to identify the sleep quality along with the Generalized Anxiety Disorder Scale (GAD-7) to establish anxiety symptoms and the Physical Health Questionnaire (PHQ-9) for depression symptoms.

ResultsThe results show that 212 (81.2%) female and 49 (18.8%) male students participated in the study. Of the participants 75.1% experienced poor sleep quality, 90% had symptoms of depression, and 85.4% had symptoms of anxiety. The mean score on the PSQI scale was 8.59{+/-}4.10, on the GAD-7 scale was 11.36{+/-}5.94 and on the PHQ-9 scale was 13.70{+/-}6.81. Multiple regression analysis showed that anxiety symptoms ({beta} = 0.315, p = 0.000) and depression symptoms ({beta} = 0.398, p = 0.000) were significant predictors of sleep quality amongst the undergraduate medical and dental students.

ConclusionA high majority of the study participants are experiencing poor sleep quality along with suffering from depression and anxiety amidst the COVID-19 lockdown. It is concluded from the analysis that anxiety and depression symptoms are significant predictors of sleep quality. Relevant authorities need to set up systems that help undergraduate medical students in alleviating and coping with these symptoms midst the COVID-19 pandemic.


title: Spanish Version of the Attitude Towards COVID-19 Vaccines Scale: Reliability and Validity Assessment

abstract: Background and purpose: The negative attitude to vaccines for coronavirus disease (COVID-19) has motivated the adaptation of instruments for this specific purpose. However, details of the reliability and validity of these scales are unknown. The study aimed to evaluate some indicators of the reliability and validity of the Spanish version of the Attitude towards COVID-19 Vaccines Scale. Methods: A validation study was carried out with 1,136 students of emerging age (18 and 29 years) from a Colombian university; 65.5% were female. Cronbach's alpha and McDonald's omega were calculated for reliability, and exploratory and confirmatory factor analyzes for validity. Additionally, the gender differential item functioning (DIF) was estimated with Kendall's tau b. Results: The Spanish version of Attitude towards COVID-19 Vaccines Scale showed high internal consistency (Cronbach's alpha of 0.94 and McDonald's omega of 0.95), a one-dimensional structure with acceptable goodness-of-fit indicators (CFI=0.94, TLI=0.91, and SRMR=0.04), and non-gender DIF (Kendall's tau b between 0.02 and 0.06). Conclusions: The Spanish version of the Attitude towards COVID-19 Vaccines Scale presents some appropriate reliability and validity indicators among university emerging adults. These findings should be explored in samples with other characteristics.


title: Predicting Managers' Mental Health Across Countries Using Country-Level COVID-19 Statistics

abstract:
BackgroundThere is limited research focusing on publicly available statistics on the Coronavirus disease 2019 (COVID-19) pandemic as predictors of mental health across countries. Managers are at risk of suffering from mental disorders during the pandemic because they face particular hardship.

ObjectiveWe aim to predict mental disorder (anxiety and depression) symptoms of managers across countries using country-level COVID-19 statistics.

MethodsA two-wave online survey of 406 managers from 26 countries was finished in May and July 2020. We used logistic panel regression models for our main analyses and performed robustness checks using ordinary least squares regressions. In the sample of 406 managers from 26 countries, 26.5% of managers reached the cut-off levels for anxiety (General Anxiety Disorder-7; GAD-7) and 43.5% did so for depression (Patient Health Questionnaire-9; PHQ-9) symptoms.

FindingsWe found that cumulative COVID-19 statistics (e.g., cumulative cases, cumulative cases per million, cumulative deaths, and cumulative deaths per million) predicted managers anxiety and depression symptoms positively, whereas daily COVID-19 statistics (daily new cases, smoothed daily new cases, daily new deaths, smoothed daily new deaths, daily new cases per million, and smoothed daily new cases per million) predicted anxiety and depression symptoms negatively. In addition, the reproduction rate was a positive predictor, while stringency of governmental lockdown measures was a negative predictor. Individually, we found that the cumulative count of deaths is the best single predictor of both anxiety and depression symptoms.

ConclusionsCumulative COVID-19 statistics predicted managers anxiety and depression symptoms positively, while non-cumulative daily COVID-19 statistics predicted anxiety and depression symptoms negatively. Cumulative count of deaths is the best single predictor of both anxiety and depression symptoms. Reproduction rate was a positive predictor, while stringency of governmental lockdown measures was a negative predictor.


title: Understanding COVID-19 Vaccine Early Skepticism and Misinformation

abstract: Recent polls report that approximately 18% of healthcare workers are still skeptical about getting vaccinated. These professionals play a key role as communicators to their patients and community members. Understanding their concerns and informational needs, as well as those of other essential workers, is important for building an effective communication strategy for the whole population. This study presents the results of a survey of 1,591 hesitant U.S. essential workers, conducted in December 2020, when they were the only group eligible for the vaccine, aiming to describe their concerns regarding the COVID-19 vaccine and related policies. Results show that freedom of choice, concerns about equal access to the vaccine and being able to live a life with no restrictions once vaccinated, were important issues since the early days of the distribution campaign. Vaccine communication campaigns and distribution policies should address both non-medical and medical concerns with the same relevance.


title: Class dependency based learning using Bi-LSTM coupled with the transfer learning of VGG16 for the diagnosis of Tuberculosis from chest x-rays

abstract: Tuberculosis is an infectious disease that is leadingto the death of millions of people across the world. The mortalityrate of this disease is high in patients suffering from immuno-compromised disorders. The early diagnosis of this disease cansave lives and can avoid further complications. But the diagnosisof TB is a very complex task. The standard diagnostic tests stillrely on traditional procedures developed in the last century. Theseprocedures are slow and expensive. So this paper presents anautomatic approach for the diagnosis of TB from posteroanteriorchest x-rays. This is a two-step approach, where in the first stepthe lung regions are segmented from the chest x-rays using thegraph cut method, and then in the second step the transfer learn-ing of VGG16 combined with Bi-directional LSTM is used forextracting high-level discriminative features from the segmentedlung regions and then classification is performed using a fullyconnected layer. The proposed model is evaluated using data fromtwo publicly available databases namely Montgomery Countryset and Schezien set. The proposed model achieved accuracy andsensitivity of 97.76%, 97.01%and 96.42%, 94.11%on Schezienand Montgomery county datasets. This model enhanced thediagnostic accuracy of TB by 0.7%and 11.68%on Schezien andMontgomery county datasets.

category: radiology and imaging


title: Protocol for systematic review of measurement of fatigue in people with cerebral palsy

abstract:
BackgroundFatigue is a common problem for people with cerebral palsy (CP), which adversely affects health-related outcomes. The emerging body of literature on fatigue in people with CP is characterised by substantial heterogeneity in assessment methods. To date, a systematic analysis of the measurement methods, and appraisal of the tools used to measure fatigue in people with CP has not been carried out. The aim of this review is to use The International Classification of Functioning, Disability and Health (ICF) as a framework to categorise and appraise current methods for measuring fatigue in people with CP.

Methods and DesignLiterature searches will be conducted in MEDLINE, PsycInfo, CINAHL, Web of Science and Cochrane databases. Studies will be included in this systematic review if they purport to measure any type of fatigue in people with CP of any age through original research, are written in English and are published in peer-reviewed literature since 1980. From included studies we will extract the assessment methods used to measure fatigue, and demographic and clinical characteristics of the sample of people with CP. We will then provide a narrative synthesis of the type and ICF domain of fatigue purportedly measured and critical appraisal of the assessment methods used.

DiscussionThis review will summarise current methods for measuring fatigue in people with CP. Critical appraisal and systematic categorisation of assessment methods will allow us to identify areas for further research on the domains in which fatigue occurs, and the role of fatigue in relation to clustering with other symptoms. Findings are expected to guide future assessment of fatigue in people with CP.

category: rehabilitation medicine and physical therapy


title: Investigating the causal relationship between physical activity and chronic back pain: a bidirectional two-sample Mendelian randomization study

abstract:
BackgroundRecent observational studies have reported a negative association between physical activity and chronic back pain (CBP), but the causality of the association remains unknown. We introduce bidirectional Mendelian randomization (MR) to assess potential causal inference between physical activity and CBP.

MethodsThe two-sample MR was used with independent genetic variants associated with physical activity phenotypes and CBP as genetic instruments from large genome-wide association studies (GWASs) on individuals of European ancestry. The effects of both directions (physical activity to CBP and CBP to physical activity) were examined. Inverse variance-weighted meta-analysis and alternate methods (weighted median and MR-Egger) were used to combine the MR estimates of the genetic instruments. Multiple sensitivity analyses were conducted to examine the robustness of the results.

ResultsFor primary analysis, instrumental variables were extracted from 337,234 participants for physical activity (the same as the outcome cohort) and 158,025 participants (29,531 cases) for CBP, while the outcome cohort for CBP included 117,404 participants (80,588 cases). No evidence of a causal relationship was found in the direction of physical activity to CBP (odds ratio [OR], 0.98; 95% CI, 0.85-1.13; P = 0.81). In contrast, a negative causal relationship in the direction of CBP to physical activity was detected ({beta} = -0.07; 95% CI, -0.12 to -0.01; P = 0.02), implying a reduction in moderate-vigorous physical activity (approximately 146 MET-minutes/week) for participants with CBP relative to controls.

ConclusionsThe negative relationship between physical activity and CBP is probably derived from the reduced physical activity of patients experiencing CBP rather than the protective effect of physical activity on CBP.

Highlights[tpltrtarr] Previous studies found a negative relationship between physical activity and chronic back pain, but the causal inference behind the relationship is lacking in evidences.
[tpltrtarr]We applied Mendelian randomization and revealed that the negative relationship probably derived from the fact that patients experiencing CBP tend to reduce their physical activities.
[tpltrtarr]If the negative relationship between physical activity and CBP is truly a reverse causality, the concept that patients with CBP should be engaging in activity, which is recommended by current guidelines, may need to be reconsidered.

category: sports medicine


title: Structural changes to primary visual cortex in the congenital absence of cone input in achromatopsia

abstract:
Autosomal recessive Achromatopsia (ACHM) is a rare inherited disorder associated with dysfunctional cone photoreceptors resulting in a congenital absence of cone input to visual cortex. This might lead to distinct changes in cortical architecture with a negative impact on the success of gene augmentation therapies. To investigate the status of the visual cortex in these patients, we performed a multi-centre study focusing on the cortical structure of regions that normally receive predominantly cone input. Using high-resolution T1-weighted MRI scans and surface-based morphometry, we compared cortical thickness, surface area and grey matter volume in foveal, parafoveal and paracentral representations of primary visual cortex in 15 individuals with ACHM and 42 normally sighted, healthy controls (HC). In ACHM, surface area was reduced in all tested representations, while thickening of the cortex was found highly localized to the most central representation. These results were comparable to more widespread changes in brain structure reported in congenitally blind individuals, suggesting similar developmental processes, i.e., irrespective of the underlying cause and extent of vision loss. Our findings indicate that there may be an optimum time window for gene therapy to counteract developmental cortical changes related to the absence of sensory input.

HighlightsO_LIWe assessed cortical anatomy of a large cohort of patients with genetically confirmed cone photoreceptor dysfunction (achromatopsia) using surface-based morphometry.
C_LIO_LIWe found widespread reduction in cortical surface area across foveal, parafoveal and paracentral proportions of primary visual cortex in participants with achromatopsia.
C_LIO_LIhighly localized cortical thickening in participants with achromatopsia at the region of visual cortex that lacked inputs from the retinal region occupied solely by cones.
C_LIO_LIFurther evidence that the visual cortex is unlikely to take on normal properties if vision were restored after the developmental plastic period.
C_LIO_LIEarly intervention is preferable when considering vision restoration treatment in achromatopsia.
C_LI

category: neurology


title: Altered functional connectome hierarchy with gene expression signatures in newly-diagnosed focal epilepsy

abstract:
ObjectiveNeuroimaging research is providing insights into epilepsy as a disorder of brain connectivity linked to functional impairments which may have an identifiable genetic component. This case-control study aims to identify imbalances in a functional connectome dimension spanning from unimodal to transmodal networks and explore the potential genetic basis of such alterations in patients with newly diagnosed focal epilepsy (NDfE).

MethodsWe used gradient-based analysis of resting-sate fMRI data comparing cortical gradient maps in patients with NDfE (n = 27) to age and sex-matched controls (n = 36). Using a brain-wide gene expression dataset, gene combinations associated with altered brain regions were then entered into an enrichment analysis.

ResultsWe found an increased differentiation of connectivity profiles between unimodal and transmodal networks in NDfE, which was particularly pronounced in the patients with persistent seizures at 12-months follow-up (n=10). Differences corresponded to gradient score reductions in a visual network and increases in limbic and default mode systems which subserve higher-level cognition. Cortical difference maps were spatially correlated with regional expression of a weighted gene combination. These genes were enriched for disease and ontology terms and pathways previously associated with epilepsy and seizure susceptibility.

InterpretationsLarge-scale functional hierarchy may be altered from in focal epilepsy from diagnosis and correlate with response to treatment. Combining functional neuroimaging and transcriptional data analysis may provide a framework for understanding the wide-ranging impairments associated with the disorder and mechanistic insight into how gene processes may drive alterations in brain function mediating the genetic risk of epilepsy.


title: A Cross Sectional Study to Assess Perception and Behavior towards COVID-19 Vaccine Among Students and Faculties of Nursing Colleges at Anand and Kheda Districts, Gujarat

abstract: Background On 11 March 2020 World Health Organization (WHO) announce that COVID-19 as a pandemic health problem2. According to report on 25 January 2021, worldwide cases reached to 100 million.3 The first confirmed case of COVID-19 in India was reported on 30 January 2020 in Kerala and affected individual had come from Wuhan china.4 Corona virus is spread over 220 countries across the world. In order to prevent corona virus all the countries are taken initiative to prepare effective vaccine against corona virus. There is not any effective treatment is available for corona so far vaccine is the key preventive aspect against corona virus. There are presently above 125 vaccines go through pre-clinical investigation for covid-19. India has develop two types of vaccine (Covaxin and covidshield) in primary phase and from 01 January 2021 Indian government started vaccination namely Covidshield to health workers (front line workers). So in primary stage target set to cover 30 million health workers followed by policeman and old age peoples to be vaccinated against corona. During primary phase of corona vaccine we dont have appropriate research and literature about side effects and how far vaccine is reliable that why due so some miner side effect and negative media publicity peoples are very scared to take vaccine. So few peoples were started denial get vaccinated. Aims The current study is aimed to assess the perception and behavior towards Covid-19 vaccine among students and faculties of nursing colleges those who have taken vaccine against corona. The researcher wan to explore the positivity through the research result to reduce the negative mindset of the peoples toward corona vaccine Because in India few peoples has fear to take vaccine against corona due to negative media publicity and scared of side effect. Objective 1. To assess the existing level of perception toward COVID 19 vaccine among students and faculties of Nursing colleges at Anand and Kheda Districts. 2. To assess the behavior towards COVID 19 vaccine among students and faculties of Nursing colleges at Anand and Kheda Districts. 3. To find out the association between selected socio-demographic variables and perceptions towards COVID 19 vaccine. Methodology Design and Setting Descriptive cross sectional survey research design was used and non-probability (snowball) sampling method was used to drawn samples through online Google form. Due to Covid-19 pandemic situation research has adopted online snowball sampling method where after tool validation from various subject experts all questions were plots on Google form and inform consent form also has been conducted online prior to data collection from the samples. Prior to data collection written setting permission obtain from nursing colleges principals for the data collection researcher were selected total 03 nursing institutes which were namely Dinsha Patel College of Nursing Vinayaka College of Nursing Nadiad Vinayaka College of Nursing Anand, and Zydus College of nursing Anand. The total sample size was 254 nursing college students and faculties. The tool consist of following Section-01 Demographic variables section-02 Nursing students and faculties information related to covid-19 vaccination during 1st and 2nd dose and Section-3 Questions related to perception and behaviour towards COVID 19 vaccine. Statistical Analysis used Descriptive statistics applied where data were analyzed by using SPSS software and Frequency percentage tables etc. were used to represent the statistical data in the tables and graph and figure. Chi-square test was used to assess the significant association between the demographic and level of perception to test the hypothesis. Results Out of 254, 245(96.45%) were belong age 17-25 years 219(86.22%) were females 53(20.87%) were study Diploma course and 178(70.08%) were study degree course 223(87.79%) belong to Hindu religion, 227(89.37%) were Unmarried 134(52.75%) were from urban area and rest 120 (47.24%) belongs to Rural area. Sources of information about COVID 19 vaccine 109(42.92%) got from online media 44(17.32%) from television 243(95.67%) received free of cost corona vaccine 199(78.35%) mindset was not influenced by negative media publicity about vaccine 248(97.63%) do not have any co-morbidities. 219(86.22%) taken Covid-19 vaccine empty stomach. 221(87%) of samples were taken willingly vaccine 205(80.71%) of samples were received covidshield vaccine and others 49(19.29%) were taken Covaxin 109(42.91%) samples noticed mild fever 53(20.87%) samples noticed moderate fever 18(7.08%) noticed severe fever and rest 74(29.13%) didnt noticed fever. Conclusions Regarding perception and behaviour towards COVID 19 vaccine the majority of samples has good perception and behaviour, 74.00% has good perception and only 23.00 had moderate to poor perception, majority of participant were willingly taken vaccine and agree to recommend to others not evidence any serious side effect due to vaccination. KEYWORDS Covaxin Covidshield DPCN WHO Nursing College Fever.

category: nursing


title: Seroprevalence of the SARS-CoV-2 antibody in healthcare workers: a multicenter cross-sectional study in ten Colombian cities.

abstract: Background: SARS-CoV-2 affects mainly occupational health populations. Healthcare workers are at constant risk of infection. The objective of this study was to determine the seroprevalence of SARS-CoV-2 in healthcare workers in Colombia. Methods: This study is a cross-sectional study focused on estimating the seroprevalence of SARS-CoV-2 antibodies in healthcare workers from 65 hospitals in 10 cities of Colombia during the second semester of 2020. The seroprevalence was determined using an automated immunoassay (Abbott SARS-CoV-2 CLIA IgG). The study included a survey to establish the sociodemographic variables and the risk of infection. Results: The global seroprevalence of antibodies against SARS-CoV-2 was 35% (95% Bayesian Confidence Interval 33%-37%). All the personnel reported the use of protective equipment. General services personnel and nurses presented the highest rates of seroprevalence among the healthcare workers. Low socioeconomic strata have shown a strong association with seropositivity. Conclusion: This study shows the occupational risk for SARS-CoV-2 infection among healthcare workers. Even though, all the personnel reported the use of protective equipment, the seroprevalence in the general services personnel and nurses was high. Also, it was observed a significant difference by city. The results could be used to perform prevention and control in this exposed population. However, further investigation of these is required to inform sources of infection to improve the control and occupational health practices.

category: occupational and environmental health


title: Reprogramming of pro-tumor macrophages by hydroxychloroquine in an abdominally metastasized diffuse midline glioma

abstract: Macrophage (M{phi}) repolarization from a pro-tumor, immunosuppressive phenotype towards an anti-tumor, pro-inflammatory state represents a promising therapeutic strategy in patients with cancer1. Successful reprogramming of M{phi} in a clinical setting has not been documented. Here, we traced the evolution at single-cell resolution of a diffuse midline glioma (DMG) with H3K27M mutation which metastasized in the abdomen after placing a ventriculoperitoneal (VP) shunt and exploited this information for therapeutic decision-making. The primary tumor showed a complex cellular and genomic landscape characterized by heterogeneous cancer cells and a tumor-supportive immune microenvironment. Upon metastasis, malignant cells populated the peritoneum and triggered a massive anti-inflammatory immune cell infiltration and expansion of myeloid-derived suppressor cells (MDSCs) in peripheral blood. Hydroxychloroquine adjuvant treatment started to overcome the immunosuppressive milieu, which resulted in a decrease in peritoneal cancer cells and pro-tumor innate immune cells. Importantly, an emergence of anti-tumor, pro-inflammatory macrophages and cytotoxic T-cells was observed, accompanied by the activation of monocytes in the blood. Our study advocates the employment of single-cell technologies to better understand and inspire therapeutic regimens in patients with cancer.

category: oncology


title: Real-world Evidence for Preventive Effects of Statins on Cancer Incidence: A Trans-Atlantic Analysis

abstract:
BackgroundNumerous clinical trials have considered the potential linkages between statins and cancer. Despite some evidence for reduced mortality associated with statin use, the results thus far have been somewhat inconclusive and not easily comparable, thus hampering the emergence of a consensus. We suspect that this uncertainty would be reduced, and greater clarity achieved (e.g. regarding clinical best practices and standards-of-care), were we to have a reliable, causal biomarker that could help identify those individual patients who might benefit from statin use during cancer treatment.

Methods and FindingsIn the joint experimental and statistical analysis reported here, we assessed the inhibitory potential of various statins on the expression of a tumor enhancer known as MACC1, taking into account the molecular functions of this key metastasis-associated protein. To assess any effects of statins in cancer prevention (observationally), we also performed a retrospective, two-center, nested case-control study, focusing on medical centers in Berlin, Germany and Virginia, USA. Among nearly a half-million patient visits, over a decade-long period, cancer patients were identified and analyzed in comparison to patients without cancer diagnoses. Odds ratios (OR) and hazard ratios (HR) for cancer were computed for patients with and without statin intake, accounting for potential confounders. Finally, we also extended these analyses of our trans-Atlantic cohort by utilizing real-world data from 132,072 cancer patients with statins available on the TriNetX platform.

Experimental work revealed that statins inhibit MACC1 mRNA levels and protein expression, resulting in reduced MACC1-induced phenotypic functions, such as motility and proliferation. Moreover, we found that statins restrict colorectal cancer (CRC) growth and metastasis in xenografted mice. The cohort data that we gathered at the German and U.S. centers enabled analysis of 53,113 cancer patients and matched controls. These were extracted, aggregated, and 1:1 matched (by age/gender) in order to build propensity-score matched sub-cohorts, to mitigate confounder bias. Based on this real-world evidence (RWE), we found that atorvastatin, fluvastatin, lovastatin, pravastatin, rosuvastatin and simvastatin were associated with a 50% reduced overall risk for developing cancer (OR 0.5, CI 0.48-0.51). The strongest association of reduced cancer risk was found for (i) liver cancer (OR 0.35, 0.29-0.43), (ii) secondary neoplasms of respiratory and digestive organs (OR 0.42, 0.34-0.45), and (iii) colorectal cancer (OR 0.44, 0.39-0.5). The effect of atorvastatin (OR 0.3, 0.28-0.32) exceeded other considered statins, even after exclusion of aspirin as the strongest confounder (OR 0.63, CI 0.57-0.7). Additionally, we note that those patients taking statins have a 38% decreased risk of death (HR 0.64, 0.48-0.86).

ConclusionsOur data, which offer evidence for cancer-preventative and anti-metastatic effects of statins, lead us to suggest that these medications should be considered in treating some types of cancers. In addition, MACC1 may serve as a potentially helpful biomarker for purposes of patient stratification (and personalized treatment). A more definitive test of these proposed ideas could come from prospective, randomized clinical trials.


title: Visual and refractive status of children with Down's syndrome and nystagmus

abstract:
Background/AimsChildren with Downs syndrome (DS) are known to have poorer visual acuity that neurotypical children. One report has shown that children with DS and nystagmus also have poor acuity when compared to typical children with nystagmus. What has not been established, is the extent of any acuity deficit due to nystagmus and whether nystagmus impacts on refractive error is within a population with DS.

MethodsClinical records from The Cardiff University Downs Syndrome Vision Research Unit were examined retrospectively. Binocular visual acuity and refraction data were available for 50 children who had DS and nystagmus (DSN) and 176 children who had DS but no nystagmus. Data were compared between the two groups, and with published data for neurotypical children with nystagmus.

ResultsThe study confirms the deficit in acuity in DS, compared to neurotypical children, of approximately 0.2 LogMAR and shows a further deficit attributable to nystagmus of a further 0.2 logMAR beyond the first year of life. Children with DS and no nystagmus appear to have acuity that mirrors that of typical children with nystagmus, while children with both DS and nystagmus have a significant additional impairment. Children with DS have a wide range of refractive errors, but nystagmus increases the likelihood of myopia. Prevalence and axis direction of astigmatism, on the other hand appears unaffected by nystagmus.

ConclusionNystagmus confers an additional visual impairment on children with Downs syndrome and must be recognised as such by families and educators. Children with both DS and nystagmus clearly need targeted support.

category: ophthalmology


title: Identification and validation of novel candidate risk genes in endocytic vesicular trafficking associated with esophageal atresia and tracheoesophageal fistulas

abstract: Esophageal atresias/tracheoesophageal fistulas (EA/TEF) are rare congenital anomalies caused by aberrant development of the foregut. Previous studies indicate that rare or de novo genetic variants significantly contribute to EA/TEF risk, and most individuals with EA/TEF do not have pathogenic genetic variants in established risk genes. To identify novel genetic contributions to EA/TEF, we performed whole genome sequencing of 185 trios (probands and parents) with EA/TEF, including 59 isolated and 126 complex cases with additional congenital anomalies and/or neurodevelopmental disorders. There was a significant burden of protein altering de novo coding variants in complex cases (p=3.3e-4), especially in genes that are intolerant of loss of function variants in the population. We performed simulation analysis of pathway enrichment based on background mutation rate and identified a number of pathways related to endocytosis and intracellular trafficking that as a group have a significant burden of protein altering de novo variants. We assessed 18 variants for disease causality using CRISPR-Cas9 mutagenesis in Xenopus and confirmed 13 with tracheoesophageal phenotypes. Our results implicate disruption of endosome-mediated epithelial remodeling as a potential mechanism of foregut developmental defects. This research may have implications for the mechanisms of other rare congenital anomalies.


title: Deep learning-based identification of genetic variants: Application to Alzheimer's disease classification

abstract: Deep learning is a promising tool that uses nonlinear transformations to extract features from high-dimensional data. Deep learning is challenging in genome-wide association studies (GWAS) with high-dimensional genomic data. Here we propose a novel three-step approach (SWAT-CNN) for identification of genetic variants using deep learning to identify phenotype-related single nucleotide polymorphisms (SNPs) that can be applied to develop accurate disease classification models. In the first step, we divided the whole genome into non-overlapping fragments of an optimal size and then ran Convolutional Neural Network (CNN) on each fragment to select phenotype-associated fragments. In the second step, using a Sliding Window Association Test (SWAT), we ran CNN on the selected fragments to calculate phenotype influence scores (PIS) and identify phenotype-associated SNPs based on PIS. In the third step, we ran CNN on all identified SNPs to develop a classification model. We tested our approach using GWAS data from the Alzheimers Disease Neuroimaging Initiative (ADNI) including (N=981; cognitively normal older adults (CN) =650 and AD=331). Our approach identified the well-known APOE region as the most significant genetic locus for AD. Our classification model achieved an area under the curve (AUC) of 0.82, which was compatible with traditional machine learning approaches, Random Forest, and XGBoost. SWAT-CNN, a novel deep learning-based genome-wide approach, identified AD-associated SNPs and a classification model for AD and may hold promise for a range of biomedical applications.


title: Fine-mapping of melanoma-associated genomic regions identifies novel causal SNPs in the MTAP/CDKN2A and CASP8 loci

abstract: A number of genomic regions have been associated with melanoma risk through genome-wide association studies, however, the causal variants underlying the majority of these associations remain unknown. Here, we sequenced either the full locus or the functional regions including exons of 19 melanoma-associated loci in 1,977 British melanoma cases and 754 controls. Variant filtering followed by Fisher's exact test analyses identified 88 variants associated with melanoma risk. Sequential conditional logistic regressions identified the distinct haplotypes on which variants lie, and massively parallel reporter assays (MPRA) provided biological insights into how these variants influence gene function. We performed further analyses to link variants to melanoma risk phenotypes and assess their association with melanoma-specific survival. Our analyses replicate previously known associations in the MC1R and TYR loci, while identifying novel potentially causal variants at the MTAP/CDKN2A and CASP8 loci. These results increase our understanding of the architecture of melanoma risk and outcome.


title: Population risk stratification for health systems via accretive predictive modeling

abstract:
ObjectiveHealth systems rely on multiple approaches for population-level risk stratification/management. However, they can under-represent members with rising risk and complex treatment needs. To address these gaps and broaden the coverage of members at risk, we present an accretive framework of six predictive models across complementary risk measures for population-level stratification/management.

Materials and MethodsLogistic regression models were trained/tested for six outcomes across cost (rising and elevated cost), utilization (rising and elevated utilization), and chronic-disease related (multimorbidities and polypharmacy) risk measures in 2016 using claims-based features from 2015 for [~]8.97 million members in a nation-wide administrative claims database. Model performances were validated against a holdout cohort of [~]2.99 million members. The presence/absence of each outcome prediction for members was summed into an accretive predictive risk index (aPRI) for population-level risk stratification evaluation.

ResultsIntegrating predictions from the six models enabled member stratification across risk measures including future costs, utilizations, and comorbidities. Each of the risk predictions is represented in aPRI levels 0- 6, and their underlying model probabilities/risk measures increase with increasing aPRI levels. [~]83% of members grouped into a "low risk" (aPRI = 0) or "rising risk" category (aPRI = 1 - 2) and [~]17% into a "high risk" (aPRI = 3 - 6) category. Overlap/correlation analyses of risk predictions and comparison of their drivers further support the complementarity of predictions within aPRI and its enhanced coverage of members at risk.

DiscussionBy integrating targeted and complementary risk predictions, aPRI enhances current population-level risk stratification approaches.

ConclusionWe have developed an accretive predictive modeling framework for enhanced population-level risk stratification/management.


title: The role of IT ambidexterity, digital dynamic capability and knowledge processes as enablers of patient agility: an empirical study

abstract: There is a limited understanding of ITs role as a crucial enabler of patient agility and the departments ability to respond to patients needs and wishes adequately. This studys objective is to contribute to the insights of the validity of the hypothesized relationship between IT resources, practices and capabilities, and hospital departments knowledge processes and the departments ability to adequately sense and respond to patient needs and wishes, i.e., patient agility. This study conveniently sampled data from 107 clinical hospital departments in the Netherlands and uses structural equation modeling for model assessment. IT ambidexterity positively enhances the development of a digital dynamic capability. Likewise, IT ambidexterity also positively impacts the hospital departments knowledge processes. Both digital dynamic capability and knowledge processes positively influence patient agility. IT ambidexterity promotes taking advantage of IT resources and experiments to reshape patient services and enhance patient agility.

category: health systems and quality improvement


title: Sociodemographic differences in patient experience with virtual care during COVID-19

abstract:
PurposeWe sought to understand patients care-seeking behaviours during the pandemic, their use and views of different virtual care modalities, and whether these differed by sociodemographic factors.

MethodsWe conducted a multi-site cross-sectional patient experience survey at thirteen academic primary care teaching practices between May and June of 2020. An anonymized link to an electronic survey was sent to a subset of patients with a valid email address on file; sampling was based on birth month. For each question, the proportion of respondents who selected each response was calculated, followed by a comparison by sociodemographic characteristics using chi-squared tests.

ResultsIn total, 7482 participants responded to the survey. Most received care from their primary care clinic during the pandemic (67.7%, 5068/7482), the majority via phone (82.5%, 4195/5086). Among those who received care, 30.53% (1509/4943) stated that they delayed seeking care because of the pandemic. Most participants reported a high degree of comfort with phone (92.4%, 3824/4139), video (95.2%, 238/250) and email or messaging (91.3%, 794/870). However, those reporting difficulty making ends meet, poor or fair health, and arriving in Canada in the last 10 years reported lower levels of comfort with virtual care and fewer wanted their practice to continue offering virtual options after the pandemic.

ConclusionsOur study suggest that newcomers, people living with a lower income, and those reporting poor or fair health have a stronger preference and comfort for in-person primary care. Further research should explore potential barriers to virtual care and how these could be addressed.


title: Validation and performance evaluation of a novel interferon-γ release assay for the detection of SARS-CoV-2 specific T-cell response

abstract:
BackgroundThe reliable detection of the T-cell mediated response to COVID-19 or COVID-19 vaccination is important for individual patient care and for monitoring the immune response e.g. in COVID-19 vaccine trials in a standardized fashion.

MethodsWe used blood samples from health care workers (HCW) with or without history of COVID-19 to define test accuracy of a novel interferon-release assay. Usefulness of qualitative and quantitative results after COVID-19 vaccination was examined in HCW receiving homologous or heterologous vaccination regimens. For a real-life performance evaluation, we analysed interferon-response to complete vaccination in 149 patients receiving immunosuppressive or immune modulating therapies.

ResultsUsing a double-cut-off strategy integrating the result of background stimulation the assay had a specificity of 100%. Sensitivity of the IGRA was 83.5 and 100% in HCW after SARS-CoV-2 infection more or less than 6 months ago. Quantitative results showed significant differences between first and second vaccine dose, but no difference between homologous and heterologous vaccination regimen. The majority of immunocompromised patients showed no immune response or isolated T-cell or antibody response to complete vaccination.

ConclusionsThe novel IGRA proved to be a highly specific and sensitive tool to detect the SARS-CoV-2 specific T-cell response to COVID-19 as well as COVID-19 vaccination. In perspective, it may serve as a standardized tool in COVID-19 vaccine trials and in clinical care of immunosuppressed patients.

category: infectious diseases


title: Surveillance of seasonal respiratory viruses among Chilean patients during the COVID-19 pandemic

abstract: The StudySARS-CoV-2 has generated over 122 million cases worldwide. Non-pharmaceuticals interventions such as confinements and lockdowns started in Chile on March 18th 2020. In Europe, confinements and lockdowns have been accompanied by a decrease in the circulation of other respiratory viruses such as Influenza A virus(IAV), Influenza B virus(IBV) or respiratory syncytial virus(RSV) (1). Although changes in circulation patterns of respiratory viruses have been reported, limited information regarding the southern hemisphere is available where the SARS-CoV-2 pandemic merged with the winter season. We conducted viral surveillance of respiratory viruses and we evaluated their presence and establishing whether they were co-circulating with SARS-CoV-2.


title: Estimation of COVID-19 recovery and decease periods in Canada using machine learning algorithms

abstract: We derive a novel model escorted by large scale compartments, based on a set of coupled delay differential equations with extensive delays, in order to estimate the incubation, recovery and decease periods of COVID-19, and more generally any infectious disease. This is possible thanks to machine learning algorithms applied to publicly available database of confirmed corona cases, recovered cases and death toll. In this purpose, we separate i) the total cases into 14 groups corresponding to 14 incubation periods, ii) the recovered cases into 406 groups corresponding to a combination of incubation and recovery periods, and iii) the death toll into 406 groups corresponding to a combination of incubation and decease periods. In this paper, we focus on recovery and decease periods and their correlation with the incubation period. The estimated mean recovery period we obtain is 22.14 days (95% Confidence Interval(CI): 22.00 to 22.27), and the 90th percentile is 28.91 days (95% CI: 28.71 to 29.13), which is in agreement with statistical supported studies. The bimodal gamma distribution reveals that there are two groups of recovered individuals with a short recovery period, mean 21.02 days (95% CI: 20.92 to 21.12), and a long recovery period, mean 38.88 days (95% CI 38.61 to 39.15). Our study shows that the characteristic of the decease period and the recovery period are alike. From the bivariate analysis, we observe a high probability domain for recovered individuals with respect to incubation and recovery periods. A similar domain is obtained for deaths analyzing bivariate distribution of incubation and decease periods.


title: Increasing SARS-CoV-2 antibody prevalence in England at the start of the second wave: REACT-2 Round 4 cross-sectional study in 160,000 adults

abstract:
BackgroundREACT-2 Study 5 is a population survey of the prevalence of SARS-CoV-2 antibodies in the community in England.

MethodsWe contacted a random sample of the population by sending a letter to named individuals aged 18 or over from the NHS GP registrations list. We then sent respondents a lateral flow immunoassay (LFIA) kit for SARS-CoV-2 antibody self-testing and asked them to perform the test at home and complete a questionnaire, including reporting of their test result. Overall, 161,537 adults completed questionnaires and self-administered LFIA tests for IgG against SARS-CoV-2 between 27 October and 10 November 2020.

ResultsThe overall adjusted and weighted prevalence was 5.6% (95% CI 5.4-5.7). This was an increase from 4.4% (4.3-4.5) in round 3 (September), a relative increase of 26.9% (24.0-29.9).The largest increase by age was in the 18 to 24 year old age group, which increased (adjusted and weighted) from 6.7% (6.3-7.2) to 9.9% (9.3-10.4), and in students, (adjusted, unweighted) from 5.9% (4.8-7.1) to 12.1% (10.8-13.5). Prevalence increased most in Yorkshire and The Humber, from 3.4% (3.0-3.8) to 6.3% (5.9-6.8) and the North West from 4.5% (4.2-4.9) to 7.7% (7.2-8.1). In contrast, the prevalence in London was stable, at 9.5% (9.0-9.9) and 9.5% (9.1-10.0) in rounds 3 and 4 respectively. We found the highest prevalence in people of Bangladeshi 15.1% (10.9-20.5), Pakistani 13.9% (11.2-17.2) and African 13.5% (10.7-16.8) ethnicity, and lowest in those of white British ethnicity at 4.2% (4.0-4.3).

InterpretationThe second wave of infection in England is apparent in increasing antibody prevalence, particularly in younger people, students, and in the Northern Regions. By late October a large proportion of the population remained susceptible to SARS-CoV-2 infection in England based on naturally acquired immunity from the first and early second wave.


title: A Combinatorial Approach towards Adaptability of 22 Functional Cas12a Orthologs for Nucleic Acid Detection in Clinical Samples

abstract: Reliable, efficient, and cheap detection of infectious diseases, especially in the wake of the SARS-CoV-2 pandemic, is of increasing importance. CRISPR/Cas systems have the capabilities to be optimized for this purpose. There is a broad diversity among Cas12a nucleases with immense detection capability, but only a few have been purified and studied biochemically. Here we present the investigation of 22 Cas12a orthologs, with a focus on their cis- and trans-cleavage activity, and thermal stability in combination with non-canonical crRNAs. We noticed that some non-canonical crRNA:Cas12a effector complexes outperformed its corresponding wild-type crRNA:Cas12a complex in trans-cleavage assays. In particular, TsCas12a, ErCas12a, and ArCas12a showed an increase in thermal stability in binary complex compared to its wild-type structure and apo form. Moreover, Cas12a was observed to have the ability to recruit segments of truncated crRNAs providing insights into crRNA:Cas12a catalytic complex with potential for further applications. We also discovered that ErCas12a, BsCas12a, BoCas12a, and TsCas12a possess robust trans-cleavage activity with a shorter PAM sequence requirement. Finally, we applied these effector complexes to discriminately detect SARS-CoV-2 and its B.1.1.7 lineage in clinical nasopharyngeal swabs, saliva samples, and tracheal aspirates. Our findings further expand the toolbox for next-generation CRISPR-based diagnostics.