bluuebunny/crossref_metadata_2025 huggingface dataset:
Double attention recurrent convolution neural network for answer selection
Authors: Bao Ganchao , Wei Yuan , Sun Xin , Zhang Hongli
Published: May 2020

Answer selection is one of the key steps in many question answering (QA) applications. In this paper, a new deep model with two kinds of attention is proposed for answer selection: the double attention recurrent convolution neural network (DARCNN). Double attention means self-attention and cross-attention. The design inspiration of this model came from the transformer in the domain of machine translation. Self-attention can directly calculate dependencies between words regardless of the distance. However, self-attention ignores the distinction between its surrounding words and other words. Thus, we design a decay self-attention that prioritizes local words in a sentence. In addition, cross-attention is established to achieve interaction between question and candidate answer. With the outputs of self-attention and decay self-attention, we can get two kinds of interactive information via cross-attention. Finally, using the feature vectors of the question and answer, elementwise multiplication is used to combine with them and multilayer perceptron is used to predict the matching score. Experimental results on four QA datasets containing Chinese and English show that DARCNN performs better than other answer selection models, thereby demonstrating the effectiveness of self-attention, decay self-attention and cross-attention in answer selection tasks.
No evidence for neonicotinoid preferences in the bumblebeeBombus impatiens
Authors: Muth Felicity , Gaxiola Rebekah L. , Leonard Anne S.
Published: May 2020

Neonicotinoid pesticides can have a multitude of negative sublethal effects on bees. Understanding their impact on wild populations requires accurately estimating the dosages bees encounter under natural conditions. This is complicated by the possibility that bees might influence their own exposure: two recent studies found that bumblebees (Bombus terrestris) preferentially consumed neonicotinoid-contaminated nectar, even though these chemicals are thought to be tasteless and odourless. Here, we usedBombus impatiensto explore two elements of these reported preferences, with the aim of understanding their ecological implication and underlying mechanism. First, we asked whether preferences persisted across a range of realistic nectar sugar concentrations, when measured at a series of time points up until 24 h. Second, we tested whether bees' neonicotinoid preferences were driven by an ability to associate their post-ingestive consequences with floral stimuli such as colour, location or scent. We found no evidence that foragers preferred to consume neonicotinoid-containing solutions, despite finding effects on feeding motivation and locomotor activity in line with previous work. Bees also did not preferentially visit floral stimuli previously paired with a neonicotinoid-containing solution. These results highlight the need for further research into the mechanisms underlying bees’ responses to these pesticides, critical for determining how neonicotinoid-driven foraging preferences might operate in the real world for different bee species.
Chemo-mechanical characterization of carious dentine using Raman microscopy and Knoop microhardness
Authors: Alturki M. , Koller G. , Almhöjd U. , Banerjee A.
Published: May 2020

One of the aims in the clinical operative management of dental carious lesions is to remove selectively the highly infected and structurally denatured dentine tissue, while retaining the deeper, repairable affected and intact, healthy tissues for long-term mechanical strength. The present study examined the correlation of chemical functional groups and the microhardness through the different depths of a carious lesion using Raman spectroscopy and Knoop microhardness testing. The null hypothesis investigated was that there was no correlation between Raman peak ratios (amide I : phosphate

ν1

) and equivalent Knoop microhardness measurements. Ten freshly extracted human permanent teeth with carious dentine lesions were sectioned and examined using high-resolution Raman microscopy. The ratio of absorbency at the amide I and phosphate bands were calculated from 139 scan points through the depth of the lesions and correlated with 139 juxtaposed Knoop microhardness indentations. The results indicated a high correlation (
p
< 0.01) between the peak ratio and the equivalent Knoop hardness within carious dentine lesions. This study concluded that Raman spectroscopy can be used as a non-invasive analytical technology for
in vitro
studies to discriminate the hardness of carious dentine layers using the peak ratio as an alternative to the invasive, mechanical Knoop hardness test.
High prevalence and genomic characteristics of G6P[1] Bovine Rotavirus A in yak in China
Authors: Yan Nan , Li Ran , Wang Yuanwei , Zhang Bin , Yue Hua , Tang Cheng
Published: May 2020

Yak is an iconic species of the Qinghai–Tibet Plateau, which is the world's highest plateau. Here, a total of 541 yak diarrhoeic samples were collected from 69 farms in four provinces in the Qinghai–Tibet Plateau from April 2015 to June 2018, and 73.6 % of samples were detected as Bovine Rotavirus A (BRVA) positive by RT-PCR assay. Two G genotypes (G6, G10) and two P genotypes (P[1], P[11]) were determined, in which G6P[1] BRVA was the predominant strain. Moreover, VP7 and VP4 of these G6P[1] strains showed unique amino acid mutations, such that they clustered into an independent branch in the phylogenetic tree. A strain of BRVA designated as RVA/Yak-tc/CHN/QH-1/2015/G6P[1] was isolated successfully using MA104 cells, and the virus titre was determined as 105.84 TCID50 ml–1. The genome of strain QH-1 had a G6-P[1]-I2-R2-C2-M2-A3-N3-T6-E2-H3 genotype constellation. QH-1 was identified as a reassortment strain of BRVA, human RVA and ovine RVA based on the nucleotide identity and phylogenetic tree of 11 gene segments, indicating its public health significance. To the best of our knowledge, this is the first report on the molecular prevalence and genome characteristics of BRVA in yak, contributing to further understanding of the epidemic and genetic evolution of BRVA.
Suicide risk with selective serotonin reuptake inhibitors and new-generation serotonergic-noradrenergic antidepressants in adults: a systematic review and meta-analysis of observational studies
Authors: Hengartner Michael P , Amendola Simone , Kaminski Jakob A , Kindler Simone , Bschor Tom , Ploderl Martin
Published: May 2020

Background: There is ongoing controversy whether antidepressant use alters the suicide risk in adult routine-care patients with depression and other treatment indications. The aim of this study was thus to examine the suicide risk with antidepressants in observational studies, considering financial conflicts of interest (fCOI) and publication bias.
Design: Systematic review and meta-analysis.
Main outcome measures: Risk of suicide, suicide attempt and/or intentional self-harm.
Data sources: We searched MEDLINE, PsycINFO, Web of Science, PsycARTICLES and SCOPUS for case-control and cohort studies published 1990-2020.
Eligibility criteria for study selection: Cohort and case-control studies in adults (aged >=18 years) with depression and any unspecified condition reporting suicide risk for patients exposed to selective serotonin reuptake inhibitors (SSRI) or new-generation serotonergic-noradrenergic antidepressants (SNA) relative to unexposed patients.
Data extraction and analysis: Effects were aggregated with a random-effects model and reported as relative risk estimates (RE) with 95%-confidence-intervals. We assessed heterogeneity via I2-statistics and publication bias via funnel-plot asymmetry and trim-and-fill method. Study fCOI was defined present when lead-authors' professorship was industry-sponsored, they received payments from the industry, or when the study was industry-sponsored.
Results: We included 27 original studies in the meta-analysis; 19 on depression (including other affective and anxiety disorders) and 8 on any unspecified condition. Use of SSRI or SNA for depression was associated with increased suicide risk (comprising both suicide and suicide attempt), RE=1.29, 1.06-1.57. Risk estimates were significantly lower in studies with fCOI (Q=21.87, p<0.001) and the trim-and-fill method estimated that 12 studies were missing due to publication bias; the result with missing studies imputed was RE=1.61, 1.31-1.99. Use of SSRI or SNA for all conditions (including depression and any unspecified condition) was associated with increased suicide risk, RE=1.43, 1.21-1.68. Studies with fCOI reported significantly lower risk estimates (Q=34.19, p<0.001) and the trim-fill method estimated that 13 studies were missing; after imputation of missing studies the result was RE=1.72, 1.44-2.05. Quality of evidence was rated very low due to substantial inconsistency of between-study results (I2>85%).
Conclusions: Exposure to new-generation antidepressants is associated with increased suicide risk in adult routine-care patients with depression and other conditions. Publication bias and fCOI contribute to systematic underestimation of risk estimates in the published literature.
Registration: Open Science Framework, https://osf.io/eaqwn/
Manifestations of mortality based global data of COVID-19; unifying global model through single parameter
Authors: Jindal V.K.
Published: May 2020

Critical inspection of the world data of COVID-19 mortality rates per population number has been made and used to express extensive variations in mortality over the globe in terms of a powered parameter λ varying from 0 to 1.2 expressed as a measure of strength of primary infection, originating from China source. The copying process is degenerating successively while infection is passed on to secondary subjects. We have been able to correlate global data through this parameter; any value close to or less than 1 shows significant impact of diluted multiple secondary effect. Further, the scatter diagram shows no effect of temperature of the geographical location and so is likely as the virus is only being spread from either contact or close proximity – the virus does not need to face highs and lows of temperatures of the environment. It stays only in the range of human body temperature and appears to be stable in 36–40°C range. If it faces the environmental temperatures it is possible for its quicker deactivation but that situation never arises for this virus except when it spreads from surfaces.
Mortality rates from COVID-19 in Spain and Italy, Lessons for the UK!
Authors: Davis Adrian , Stratton Irene , Quinton Richard , O'Donoghue Gerard , Roberts Graham
Published: May 2020

The Covid-19 pandemic brings major new challenges to health services resulting from the lack of a
vaccine and from the enormous resources it can consume over a prolonged period. The available
control measures are currently limited to quarantining, contact tracking-and-tracing and social distancing. Disease transmission to health care workers is common and deaths among clinical and
nursing staff have been reported in the UK (where serious concerns about the availability of personal protective equipment - PPE - have been raised) and elsewhere; particularly in Lombardy, where General Practitioners (Medici di Base) have died in disproportionate numbers.
Can we use these masks? Rapid Assessment of the Inhalation Resistance Performance of Uncertified Medical Face Masks in the Context of Restricted Resources Imposed during a Public Health Emergency
Authors: Begg Steven , Emekwuru Nwabueze G , Miche Nicolas , Whitney Bill , Ejohwomu Obuks
Published: May 2020

In the case of a public health emergency such as the COVID-19 pandemic, access to large quantities of appropriate personal protection equipment (PPE) has presented a significant problem. A shortage of face masks and respirators has been widely reported across the world. A concerted effort to manufacture high volumes has not unsurprisingly put pressure on the supply chain and the important certification processes. PPE procured or donated as uncertified stock requires rigorous, expedient and scientifically informed evidence before decisions can be made regarding suitable deployment, expensive certification, return or possible destruction of stock. This paper reports a series of experiments devised in reaction to this situation. In this study, an experimental methodology for the assessment of the filtration performance of samples of real-world, uncertified, fluid resistant surgical masks (FRSM type IIR) was evaluated in the resource limited (lockdown) environment of the COVID-19 pandemic. A steady-state flow rig was adapted to incorporate a bespoke filter flow chamber for mounting face masks in order to evaluate the resistance to air flow as an indicator of mask inhalation performance. Pure air was drawn through a specified control surface area at known flow rate conditions; the resistance to the air flow through the masks was measured as the resulting pressure drop. Over 60 tests were performed from 4 different, randomly sampled batches and compared to a control sample of EN Type IIR certified FRSM masks. Steady-state volumetric airflow rates of 30 and 95 lmin-1 were chosen to represent deep breathing and vigorous exercise conditions respectively. The results showed that the sample masks produced a pressure drop of between 26% to 58% compared to the control batch at the lower flow rate and 22% to 55% at the higher rate. The results for each sample were consistent across both flow rates. Within the group of masks tested, two sets (between 48% and 58% of the reference set) showed the potential to be professionally assessed for appropriate deployment in a suitable setting. Although the absolute values of pressure drop measured by this method are unlikely to correlate with other testing approaches, the observed, indicative trends and relative performance of the masks is key to this approach. Critically, this method does not replace certification but it has enabled a public body to quickly make decisions; certify, re-assign, refund, thus saving time and resources. The total time spent conducting the tests was less than 8 hours and the low cost method proposed can be repurposed for low resource regions.
Making sense of publicly available data on COVID-19 in Ireland
Authors: Mills Gerald , Cullen Walter , Moore Niamh , Foley Ronan
Published: May 2020

This paper reports on the management of the COVID19 pandemic in Ireland over the period March to May 2020. During this period the Irish government implemented a series of policies designed to delay the spread of the pandemic culminating in a stay-at-home order that greatly restricted mobility for the majority of the population. In this paper we evaluate the policies enacted using evidence obtained from a number of novel sources, including census and real-time traffic data. The evidence suggests that the policies have impeded the spread of the virus, which has mostly been confined to Dublin and its commuter belt. At the same time, the virus has become concentrated in a number of clusters associated with nursing homes and workplaces that remained open during the delay phase. This evidence is used to hypothesise on the likely impact of the pandemic on high density and poor neighbourhoods in Dublin.
The infection fatality rate of COVID-19 inferred from seroprevalence data
Authors: Ioannidis John P.A.
Published: May 2020

Objective

To estimate the infection fatality rate of coronavirus disease 2019 (COVID-19) from data of seroprevalence studies.

Methods

Population studies with sample size of at least 500 and published as peer-reviewed papers or preprints as of July 11, 2020 were retrieved from PubMed, preprint servers, and communications with experts. Studies on blood donors were included, but studies on healthcare workers were excluded. The studies were assessed for design features and seroprevalence estimates. Infection fatality rate was estimated from each study dividing the number of COVID-19 deaths at a relevant time point by the number of estimated people infected in each relevant region. Correction was also attempted accounting for the types of antibodies assessed. Secondarily, results from national studies were also examined from preliminary press releases and reports whenever a country had no other data presented in full papers of preprints.

Results

36 studies (43 estimates) were identified with usable data to enter into calculations and another 7 preliminary national estimates were also considered for a total of 50 estimates. Seroprevalence estimates ranged from 0.222% to 47%. Infection fatality rates ranged from 0.00% to 1.63% and corrected values ranged from 0.00% to 1.31%. Across 32 different locations, the median infection fatality rate was 0.27% (corrected 0.24%). Most studies were done in pandemic epicenters with high death tolls. Median corrected IFR was 0.10% in locations with COVID-19 population mortality rate less than the global average (<73 deaths per million as of July 12, 2020), 0.27% in locations with 73-500 COVID-19 deaths per million, and 0.90% in locations exceeding 500 COVID-19 deaths per million. Among people <70 years old, infection fatality rates ranged from 0.00% to 0.57% with median of 0.05% across the different locations (corrected median of 0.04%).

Conclusions

The infection fatality rate of COVID-19 can vary substantially across different locations and this may reflect differences in population age structure and case-mix of infected and deceased patients as well as multiple other factors. Estimates of infection fatality rates inferred from seroprevalence studies tend to be much lower than original speculations made in the early days of the pandemic.
COVID-19 management in a UK NHS Foundation Trust with a High Consequence Infectious Diseases centre: a detailed descriptive analysis
Authors: Baker Kenneth F. , Hanrath Aidan T. , Schim van der Loeff Ina , Tee Su Ann , Capstick Richard , Marchitelli Gabriella , Li Ang , Barr Andrew , Eid Alsafi , Ahmed Sajeel , Bajwa Dalvir , Mohammed Omer , Alderson Neil , Lendrem Clare , Lendrem Dennis ,   COVID-19 Control Group,   COVID-19 Clinical Group, Pareja-Cebrian Lucia , Welch Andrew , Field Joanne , Payne Brendan A.I. , Taha Yusri , Price David A. , Gibbins Christopher , Schmid Matthias L. , Hunter Ewan , Duncan Christopher J.A.
Published: May 2020

Background: Recent large national and international cohorts describe the baseline characteristics and outcome of hospitalised patients with COVID-19, however there is little granularity to these reports. We aimed to provide a detailed description of a UK COVID-19 cohort, focusing on clinical decisions and patient journeys.

Methods: We retrospectively analysed the management and 28-day outcomes of 316 consecutive adult patients with SARS-CoV-2 PCR-confirmed COVID-19 admitted to a large NHS Foundation Trust with a tertiary High Consequence Infectious Diseases centre in the North of England.

Findings: Most patients were elderly (median age 75) with multiple comorbidities. One quarter were admitted from residential or nursing care. Symptoms were consistent with COVID-19, with cough, fever and/or breathlessness in 90.5% of patients. Two thirds of patients had severe disease on admission. Mortality was 81/291 (27.8%). Most deaths were anticipated; decisions to initiate respiratory support were individualised after consideration of patient wishes, premorbid frailty and comorbidities, with specialist palliative care input where appropriate. 22/291 (7.6%) patients were intubated and 11/22 (50%) survived beyond discharge. Multiple logistic regression identified age as the most significant risk factor for death (OR 1.09 [95% CI 1.06 - 1.12] per year increase, p < 0.001).

Interpretation: These findings provide important clinical context to outcome data. Deaths were anticipated, occurring in patients with advance decisions on ceilings of treatment. Age was the most significant risk factor for death, confirming that demographic factors in the population are a major influence on hospital mortality rates.

Funding: Funding was not required.
Automated Prediction of Ischemic Brain Tissue Fate from Multi-Phase CT-Angiography in Patients with Acute Ischemic Stroke Using Machine Learning
Authors: Qiu Wu , Kuang Hulin , Ospel Johanna , Hill Michael D , Demchuk Andrew , Goyal Mayank , Menon Bijoy
Published: May 2020

Background: Multiphase CT-Angiography (mCTA) provides time variant images of the pial vasculature supplying brain in patients with acute ischemic stroke (AIS). To develop a machine learning (ML) technique to predict infarct, penumbra and tissue perfusion from mCTA source images.
Methods: 284 patients with AIS were included from the PRoveIT study. All patients had non-contrast CT, mCTA and CTP imaging at baseline and follow up MRI/NCCT imaging. Of the 284 patient images, 140 patient images were randomly selected to train and validate three ML models to predict infarct, penumbra, and perfusion parameter on CTP, respectively. The remaining unseen 144 patient images independent of the derivation cohort were used to test the derived ML models. The predicted infarct, penumbra, and perfusion volume from ML models was spatially and volumetrically compared to manually contoured follow up infarct and time-dependent Tmax thresholded volume (CTP volume), using Bland-Altman plots, concordance correlation coefficient (CCC), intra-class correlation coefficient (ICC), and Dice similarity coefficient (DSC).
Results: Within the test cohort, Bland-Altman plots showed that the mean difference between the mCTA predicted infarct and follow up infarct was 21.7 mL (limit of agreement (LoA): -41.0 to 84.3mL) in the 100 patients who had acute reperfusion (mTICI 2b/2c/3), and 3.4mL (LoA: -66 to 72.9mL) in the 44 patients who did not achieve reperfusion (mTICI 0/1). Amongst reperfused subjects, CCC was 0.4 [95%CI: 0.15-0.55, P<.01] and ICC 0.42 [95% CI: 0.18-0.50, P<.01]; in non-reperfused subjects CCC was 0.52 [95%CI: 0.2-0.6, P<.001] and ICC 0.6 [95% CI: 0.37-0.76, P<.001]. No difference was observed between the mCTA and CTP predicted infarct volume for the overall test cohort (P=.67).
Conclusion: Multiphase CT Angiography is able to predict infarct, penumbra and tissue perfusion, comparable to CT perfusion imaging.
Exploring alternative medicine options for the prevention or treatment of coronavirus disease 2019 (COVID-19)- A systematic scoping review
Authors: Nandan Amrita , Tiwari Santosh , Sharma Vishwas
Published: May 2020

Background: Coronavirus disease 2019 (COVID-19) is caused by coronavirus 2 (SARS-CoV-2). Symptoms include fever, cough, shortness of breath, muscle pain, pneumonia, and multi-organ failure. The infection spreads from one person to another via respiratory droplets. Alternative medicine (AMs) viz., Ayurveda, Homeopathy, Unani, and Traditional Chinese Medicine (TCM), are being promoted for the prevention of COVID-19. The aim of this systematic scoping review was to identify and summarize the scientific evidences promoting the use of AMs for the prevention of COVID-19.

Methods: A comprehensive search of electronic search engines (PubMed and Web of Science) was performed. In addition, freewheeling searches of the government health ministries and government websites was done to retrieve the available information. Records available until 12th March 2020 were considered. Reports proposing the use of AMs for prevention or treatment of COVID-19 across all countries were included. Screening (primary and secondary) of the records and data extraction from the eligible studies were done by a single reviewer followed by a random quality check (10%) by the second reviewer.

Results: Overall, 8 records (7 from China and 1 from India) exploring the use of AMs for the prevention or treatment of COVID-19 were identified. Different medicines were explored by different AM systems.

Conclusions: Several AMs options are proposed for the prevention or treatment of COVID-19. However, their efficacy and safety still needs scientific validation through rigorous randomized controlled trials. This review may help inform decisions about the importance of research and development of AMs for COVID-19 prevention and treatment.
COVID-19 FATALITY RISK: WHY IS AUSTRALIA’S LOWER THAN SOUTH KOREA?
Authors: Collignon Peter , Beggs John J.
Published: May 2020

Background

As the Covid-19 virus epidemic spreads, it is important to establish reliable estimates of fatality hazard rates. Australia and South Korea are ideal candidates for detailed consideration. Both have completed the first wave of the epidemic, they have extensive Covid-19 testing and tracking programs so that confirmed case load data are reliable, and neither country has had any significant case load stress in their hospital systems.

Methods

For each country, mortality hazard models were estimated using a parameterized distributed lag model where the number of daily deaths was dependent on the number of confirmed cases in each of the preceding six weeks. Age cohort CFRs were also examined.

Findings

We observed major difference in the mortality rates when comparing South Korea to Australia in both the simple age adjusted fatality rates and in the disease hazard curve. On a like-for-like basis, the CFR for South Korea appears to be close to double the Australian rate (aggregate; 2.4% vs 1.4%).

Interpretation

Neither differences in the time pattern of the peaking of the case load of confirmed cases, nor differences in the size of age cohorts of confirmed cases explain the difference in mortality observed. We discuss possible explanations that point the way for further investigation.

Funding

nil.
A semi-supervised approach for rapidly creating clinical biomarker phenotypes in the UK Biobank using different primary care EHR and clinical terminology systems
Authors: Denaxas Spiros , Shah Anoop D. , Mateen Bilal A. , Kuan Valerie , Quint Jennifer K. , Fitzpatrick Natalie , Torralbo Ana , Fatemifar Ghazaleh , Hemingway Harry
Published: May 2020

Objectives

The UK Biobank (UKB) is making primary care Electronic Health Records (EHR) for 500,000 participants available for COVID-19-related research. Data are extracted from four sources, recorded using five clinical terminologies and stored in different schemas. The aims of our research were to: a) develop a semi-supervised approach for bootstrapping EHR phenotyping algorithms in UKB EHR, and b) to evaluate our approach by implementing and evaluating phenotypes for 31 common biomarkers.

Materials and Methods

We describe an algorithmic approach to phenotyping biomarkers in primary care EHR involving a) bootstrapping definitions using existing phenotypes, b) excluding generic, rare or semantically distant terms, c) forward-mapping terminology terms, d) expert review, and e) data extraction. We evaluated the phenotypes by assessing the ability to reproduce known epidemiological associations with all-cause mortality using Cox proportional hazards models.

Results

We created and evaluated phenotyping algorithms for 31 biomarkers many of which are directly related to COVID–19 complications e.g. diabetes, cardiovascular disease, respiratory disease. Our algorithm identified 1651 Read v2 and Clinical Terms Version 3 terms and automatically excluded 1228 terms. Clinical review excluded 103 terms and included 44 terms, resulting in 364 terms for data extraction (sensitivity 0.89, specificity 0.92). We extracted 38,190,682 events and identified 220,978 participants with at least one biomarker measured.

Discussion and conclusion

Bootstrapping phenotyping algorithms from similar EHR can potentially address pre-existing methodological concerns that undermine the outputs of biomarker discovery pipelines and provide research-quality phenotyping algorithms.
Medical Doctors Awareness, Perception, and Attitude towards COVID-19 in Bangladesh: A Cross sectional study
Authors: Mumu Sadia Biswas , Aktar Most Nasrin , Nahar Zabun , Sharmin Shahana , Mostaid Md Shaki
Published: May 2020

Objective: COVID-19 has emerged as a pandemic and during the first week of May Bangladesh has reported more than 10,000 cases. A lack of awareness and poor understanding of the disease may result in rapid transmission of the disease in Bangladesh. This study aimed to investigate the awareness, perception, and attitude towards COVID-19 among Bangladeshi medical doctors.
Method: This cross sectional, web-based study was conducted with the help of an online questionnaire and sent to the doctors which comprised of a series of questions regarding demographics of the participants, symptoms and incubation period of COVID-19, mode of transmission, measures to prevent transmission, availability of training and personal protective equipment in Bangladeshi hospitals, and attitude of doctors towards the treatment of suspected patients with COVID-19.
Results: Of 800 medical doctors, a total 545 completed the survey (response 68.13%). Among the participants, 52.3% were females, 72.8% were below 30 years of age, and majority (52.8%) were working outside the cities in the villages and rural areas. A total of 404 (74.1%) doctors reported the correct incubation period of COVID-19. Majority doctors were aware of the symptoms with mode of transmission of COVID-19, measures to prevent hospital transmission, along with ways of identifying suspected patients with COVID-19. However, more than 90% of the doctors reported of inadequate intensive care unit and ventilator facilities along with extreme scarcity of personal protective equipment in the hospitals. 65.7% doctors prefer avoid working with a COVID-19 patient and more than 50% doctors have expressed that they would send the suspected COVID-19 patients to designated hospitals without providing treatment.
Conclusion: The health authorities should take appropriate training measures to increase the awareness of the medical doctors along with providing sufficient amount of personal protective equipment for the medical doctors and supporting staff before deploying them in hospitals.
Flatten the Curve! Modeling SARS-CoV-2/COVID-19 Growth in Germany at the County Level
Authors: Wieland Thomas
Published: May 2020

Since the emerging of the “novel coronavirus” SARS-CoV-2 and the corresponding respiratory disease COVID-19, the virus has spread all over the world. Being one of the most affected countries in Europe, in March 2020, Germany established several nonpharmaceutical interventions to contain the virus spread, including the closure of schools and child day care facilities (March 16-18, 2020) as well as a full “lockdown” with forced social distancing and closures of “nonessential” services (March 23, 2020). The present study attempts to analyze whether these governmental interventions had an impact on the declared aim of ‘’flattening the curve”, referring to the epidemic curve of new infections. This analysis is conducted from a regional perspective. On the level of the 412 German counties, logistic growth models were estimated based on daily infections (estimated from reported cases), aiming at determining the regional growth rate of infections and the point of inflection where infection rates begin to decrease and the curve flattens. All German counties exceeded the peak of new infections between the beginning of March and the middle of April. In a large majority of German counties, the epidemic curve has flattened before the “lockdown” was established. In a minority of counties, the peak was already exceeded before school closures. The growth rates of infections vary spatially depending on the time the virus emerged. Counties belonging to states which established an additional curfew show no significant improvement with respect to growth rates and mortality. Furthermore, mortality varies strongly across German counties, which can be attributed to infections of people belonging to the “risk group”, especially residents of retirement homes. The results raise the question whether social ban measures and curfews really contribute to curve flattening within a pandemic.
COVID Faster R-CNN: A Novel Framework to Diagnose Novel Coronavirus Disease (COVID-19) in X-Ray Images
Authors: Shibly Kabid Hassan , Dey Samrat Kumar , Islam Md. Tahzib Ul , Rahman Md. Mahbubur
Published: May 2020

COVID-19 or novel coronavirus disease, which has already been declared as a worldwide pandemic, at first had an outbreak in a small town of China, named Wuhan. More than two hundred countries around the world have already been affected by this severe virus as it spreads by human interaction. Moreover, the symptoms of novel coronavirus are quite similar to the general flu. Screening of infected patients is considered as a critical step in the fight against COVID-19. Therefore, it is highly relevant to recognize positive cases as early as possible to avoid further spreading of this epidemic. However, there are several methods to detect COVID-19 positive patients, which are typically performed based on respiratory samples and among them one of the critical approach which is treated as radiology imaging or X-Ray imaging. Recent findings from X-Ray imaging techniques suggest that such images contain relevant information about the SARS-CoV-2 virus. In this article, we have introduced a Deep Neural Network (DNN) based Faster Regions with Convolutional Neural Networks (Faster R-CNN) framework to detect COVID-19 patients from chest X-Ray images using available open-source dataset. Our proposed approach provides a classification accuracy of 97.36%, 97.65% of sensitivity, and a precision of 99.28%. Therefore, we believe this proposed method might be of assistance for health professionals to validate their initial assessment towards COVID-19 patients.
Development of a Predictive Score for COVID-19 Diagnosis based on Demographics and Symptoms in Patients Attended at a Dedicated Screening Unit
Authors: Zavascki Alexandre P , Gazzana Marcelo B , Bidart Joao Pedro , Fernandes Patricia S , Galiotto Aline , Kawski Cristiane T , Nasi Luiz A , Falci Diego R
Published: May 2020

Background: The diagnosis of COVID-19 based on clinical evaluation is difficult because symptoms often overlap with other respiratory diseases. A clinical score predictive of COVID-19 based on readily assessed variables may be useful in settings with restricted or no access to molecular diagnostic tests.
Methods: A score based on demographics and symptoms was developed in a cross-sectional study including patients attended in a dedicated COVID-19 screening unit. A backward stepwise logistic regression model was constructed and values for each variable were assigned according to their β coefficient values in the final model. Receiver operating characteristic (ROC) curve was constructed and its area under the curve (AUC) was calculated.
Results: A total of 464 patients were included: 98 (21.1%) COVID-19 and 366 (78.9%) non-COVID-19 patients. The score included variables independently associated with COVID-19 in the final model: age equal or above 60 years (2 points), fever (2), dyspnea (1), fatigue (1 point) and coryza (-1). Score values were significantly higher in COVID-19 than non-COVID-19 patients: median (Interquartile Range), 3 (2-4), and 1 (0-2), respectively; P<0.001. The score had an AUC of 0.80 (95% Confidence Interval [CI], 0.76-0.86). The specificity of scores equal or greater than 4 and 5 points were 90.4 (95%CI, 87.0-93.3) and 96.2 (95%CI, 93.7-97.9), respectively.
Conclusions: This preliminary score based on patients symptoms is a feasible tool that may be useful in setting with restricted or no access to molecular tests in a pandemic period, owing to the high specificity. Further studies are required to validate the score in other populations.
International Journal of Epidemiology peer reviewers: global and gender distribution
Authors: Masukume Gwinyai , Gonzalez-Alvarez Julio , Grech Victor
Published: May 2020

The science of epidemiology studies and analyses the patterns, distributions and determinants of health-related entities. Peer review is crucial to the biomedical journal ecosystem. Furthermore, gender inequality persists in science and improving gender representation is a key international goal. For these reasons, we evaluated the geographical location and gender distribution of the International Journal of Epidemiology peer reviewers for 2018.
There were 695 peer reviewers hailing from 41 countries. 77% (533) of the reviewers were from 20% (8) of these countries, a classical 80:20 Pareto distrubution.
41% (282) of peer reviewers were female. Although in line with the general underrepresentation of females reported in the literature, this proportion was much closer to parity than in other fields.
Our investigation of peer reviewer 'epidemiology' demonstrates geographical and gender inequalities that can be further improved since diversity promotes innovation and a greater possibility for solving complex problems.
AI-based multi-modal integration (ScanCov scores) of clinical characteristics, lab tests and chest CTs improves COVID-19 outcome prediction of hospitalized patients
Authors: Lassau Nathalie , Ammari Samy , Chouzenoux Emilie , Gortais Hugo , Herent Paul , Devilder Matthieu , Soliman Samer , Meyrignac Olivier , Talabard Marie-Pauline , Lamarque Jean-Philippe , Dubois Remy , Loiseau Nicolas , Trichelair Paul , Bendjebbar Etienne , Garcia Gabriel , Balleyguier Corinne , Merad Mansouria , Stoclin Annabelle , Jegou Simon , Griscelli Franck , Tetelboum Nicolas , Li Yingping , Verma Sagar , Terris Matthieu , Dardouri Tasnim , Gupta Kavya , Neacsu Ana , Chemouni Frank , Sefta Meriem , Jehanno Paul , Bousaid Imad , Boursin Yannick , Planchet Emmanuel , Azoulay Mikael , Dachary Jocelyn , Brulport Fabien , Gonzalez Adrian , Dehaene Olivier , Schiratti Jean-Baptiste , Schutte Kathryn , Pesquet Jean-Christophe , Talbot Hugues , Pronier Elodie , Wainrib Gilles , Clozel Thomas , Barlesi Fabrice , Bellin Marie-France , Blum Michael G. B.
Published: May 2020

The SARS-COV-2 pandemic has put pressure on Intensive Care Units, and made the identification of early predictors of disease severity a priority. We collected clinical, biological, chest CT scan data, and radiology reports from 1,003 coronavirus-infected patients from two French hospitals. Among 58 variables measured at admission, 11 clinical and 3 radiological variables were associated with severity. Next, using 506,341 chest CT images, we trained and evaluated deep learning models to segment the scans and reproduce radiologists’ annotations. We also built CT image-based deep learning models that predicted severity better than models based on the radiologists’ reports. Finally, we showed that adding CT scan information—either through radiologist lesion quantification or through deep learning—to clinical and biological data, improves prediction of severity. These findings show that CT scans contain novel and unique prognostic information, which we included in a 6-variable ScanCov severity score.
Ostavimir is ineffective against COVID-19: in silico assessment, in vitro and retrospective study
Authors: Tan Qi , Jin Yang
Published: May 2020

As a neuraminidase inhibitor, oseltamivir has effectively combated the pandemic influenza A and B, so it is a first-line commonly used antiviral drug, especially in primary hospitals. At the same time, oseltamivir, as an over-the-counter drug, is also a popular antiviral drug. As healthcare workers fighting against coronavirus disease 2019 (COVID-19), we have found that many patients experiencing discomfort or considered to be infected with a virus take oseltamivir. From severe acute respiratory syndrome coronavirus (SARS-CoV) in 2003 to middle east respiratory syndrome coronavirus (MERS-CoV) in 2012, and now the current COVID-19 epidemic, there is not plenty of evidence showing that oseltamivir is effective against coronavirus. Still, there is also no sufficient evidence to refute its ineffectiveness. We cannot predict whether there will be a pandemic of respiratory coronavirus in the future, so we hope to initiate such research and preliminarily explore whether oseltamivir is effective for COVID-19, which can better guide healthcare workers in the selection of appropriate antiviral drugs in the face of coronavirus epidemics. If oseltamivir is effective, then a wide promotion of its application often can achieve a double effect with half the effort. If it is not effective, then considering the side effects of oseltamivir, it is not necessary to use unreasonable drugs that will not slow the progression of the disease but can cause adverse reactions. We found that oseltamivir is not suitable for fighting against COVID-19 through the method of computer aided drug design and in vitro study and retrospective case study. Meanwhile it was high-occurrence seasons for the influenza, COVID-19 should be highly suspected in patients who did not benefit from oseltamivir. We hope that the result of our study could be shared with the frontline physicians in fighting against COVID-19.
Super spreader cohorts and covid-19
Authors: Van Esch Patrick
Published: May 2020

A simple two-cohort SIR like model can explain the qualitative behaviour of the logarithmic derivative estimations of the covid-19 epidemic evolution as observed in several countries. The model consists of a general population in which the R_0 value is slightly below 1, but in which a super-spreading small subgroup with high R_0, coupled to the general population, is contaminating a significant fraction of the population. The epidemic starts to slow down when herd immunity is reached in this subgroup. The dynamics of this system is quite robust against non-pharmaceutical measures.
A Model-Based Approach for Pulse Selection from Electrodermal Activity
Authors: Subramanian Sandya , Purdon Patrick L. , Barbieri Riccardo , Brown Emery N.
Published: May 2020

Objective

The goal of this work was to develop a physiology-based paradigm for pulse selection from electrodermal activity (EDA) data.

Methods

We aimed to use insight about the integrate-and-fire physiology of sweat gland bursts, which predicts inverse Gaussian inter-pulse interval structure. At the core of our paradigm is a subject-specific amplitude threshold selection process for pulses based on the statistical properties of four right-skewed models including the inverse Gaussian. These four models differ in their tail behavior, which reflects sweat gland physiology to varying degrees. By screening across thresholds and fitting all four models, we selected for heavier tails that reflect inverse Gaussian-like structure and verified the pulse selection with a goodness-of-fit analysis.

Results

We tested our paradigm on two different subject cohorts recorded during different experimental conditions and using different equipment. In both cohorts, our method robustly and consistently recovered pulses that captured the inverse Gaussian-like structure predicted by physiology, despite large differences in noise level of the data. In contrast, an established EDA analysis paradigm, which assumes a constant amplitude threshold across all data, was unable to separate pulses from noise.

Conclusion

We present a computationally efficient, statistically rigorous, and physiology-informed paradigm for pulse selection from EDA data that is robust across individuals and experimental conditions yet adaptable to changes in noise level.

Significance

The robustness of our paradigm and its basis in physiology move EDA closer to serving as a clinical marker for sympathetic activity in diverse conditions such as pain, anxiety, depression, and sleep.
Does chronic systemic injection of the DREADD agonists clozapine-N-oxide or compound 21 change behavior relevant to locomotion, exploration, anxiety, and depression in male non-DREADD-expressing mice?
Authors: Tran Fionya H. , Spears Stella L. , Ahn Kyung J. , Eisch Amelia J. , Yun Sanghee
Published: May 2020

Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) are chemogenetic tools commonly-used to manipulate brain activity. The most widely-used synthetic DREADD ligand, clozapine-N-oxide (CNO), is back-metabolized to clozapine which can itself activate endogenous receptors. Studies in non-DREADD-expressing rodents suggest CNO or a DREADD agonist that lacks active metabolites, such as Compound 21 (C21), change rodent behavior (e.g. decrease locomotion), but chronic injection of CNO does not change locomotion. However, it is unknown if chronic CNO changes behaviors relevant to locomotion, exploration, anxiety, and depression, or if chronic C21 changes any aspect of mouse behavior. Here non-DREADD-expressing mice received i.p. Vehicle (Veh), CNO, or C21 (1mg/kg) 5 days/week for 16 weeks and behaviors were assessed over time. Veh, CNO, and C21 mice had similar weight gain over the 16-week-experiment. During the 3rd injection week, CNO and C21 mice explored more than Veh mice in a novel context and had more open field center entries; however, groups were similar in other measures of locomotion and anxiety. During the 14th-16th injection weeks, Veh, CNO, and C21 mice had similar locomotion and anxiety-like behaviors. We interpret these data as showing chronic Veh, CNO, and C21 injections given to male non-DREADD-expressing mice largely lack behavioral effects. These data may be helpful for behavioral neuroscientists when study design requires repeated injection of these DREADD agonists.

Highlights

Acute injection of CNO changes behavior of non-DREADD-expressing mice

It’s not known if chronic CNO or alternative agonist C21 also changes mouse behavior

DREADD agonists or Veh were given chronically to non-DREADD-expressing mice

CNO and C21 don’t change locomotion and have a mixed effect on anxiety-like behavior

1 mg/kg CNO and C21 can be injected repeatedly without non-specific behavior effects
Endocannabinoids and dopamine balance basal ganglia output
Authors: Gorodetski Lilach , Loewenstern Yocheved , Faynveitz Anna , Bar-Gad Izhar , Blackwell Kim T. , Korngreen Alon
Published: May 2020

The entopeduncular nucleus is one of the basal ganglia’s output nuclei, thereby controlling basal ganglia information processing. Entopeduncular nucleus neurons integrate GABAergic inputs from the striatum and the globus pallidus and glutamatergic inputs from the subthalamic nucleus. We show that endocannabinoids and dopamine interact to modulate the long-term plasticity of all the primary afferents to the entopeduncular nucleus. Our results suggest that dopamine-endocannabinoids interplay determines the balance of the direct or indirect dominance of entopeduncular nucleus output. Furthermore, we demonstrate that, despite the lack of axon collaterals, information is transferred between neighboring neurons in the entopeduncular nucleus via endocannabinoids diffusion. These results transform the prevailing view of the entopeduncular nucleus as a feedforward “relay” nucleus to an intricate control unit, which may play a vital role in the process of action selection.