title: No Clear Benefit to the Use of Corticosteroid as Treatment in Adult Patients with Coronavirus Disease 2019 : A Retrospective Cohort Study

text: Background Coronavirus disease 2019 (COVID-19) is becoming an increasing global health issue which has spread across the globe. We aimed to study the effect of corticosteroids in the treatment of adult inpatients with COVID-19. Methods A retrospective cohort of 115 consecutive adult COVID-19 patients admitted to The Third Peoples Hospital of Hubei Province between Jan 18, 2020, and Feb 28, 2020 was analysed to study the effectiveness of corticosteroid. They were categorized according to whether or not corticosteroid therapy was given, and compared in terms of demographic characteristics, clinical features, laboratory indicators and clinical outcomes. The primary endpoint was defined as either mortality or intensive care unit (ICU) admission. Known adverse prognostic factors were used as covariates in multiple logistic regressions to adjust for their confounding effects on outcomes. Results Among 115 patients, 73 patients (63.5%) received corticosteroid. The levels of age, C-reactive protein, D-dimer and albumin were similar in both groups. The corticosteroid group had more adverse outcomes (32.9% vs. 11.9%) and statistically significant differences were observed (p=0.013). In multivariate analysis, corticosteroid treatment was associated with a 2.155-fold increase in risk of either mortality or ICU admission, although not statistically significant. Conclusion No evidence suggests that adult patients with COVID-19 will benefit from corticosteroids, and they might be more likely to be harmed with such treatment.


title: Data-driven discovery of clinical routes for severity detection in COVID-19 pediatric cases

text: The outbreak of COVID-19 epidemic has caused worldwide health concerns since Nov., 2019. A previous study described the demographic, epidemiologic, and clinical features for infected infants. However, compared with adult cases, little attention has been paid to the infected pediatric cases. Severity detection is challenging for children since most of children patients have mild symptoms no matter they are moderately or critically ill therein.


title: A Scalable Method of Applying Heat and Humidity for Decontamination of N95 Respirators During the COVID-19 Crisis

text: A lack of N95 respirators during the COVID-19 crisis has placed healthcare workers at risk. It is important for any N95 reuse strategy to determine the effects that proposed protocols would have on the physical functioning of the mask, as well as the practical aspects of implementation. Here we propose and implement a method of heating N95 respirators with moisture (85{degrees}C, 60-85% humidity). We test both mask filtration efficiency and fit to validate this process. Our tests focus on the 3M 1860 and 3M 8210 Plus N95 models. After five cycles of the heating procedure, both respirators pass quantitative fit testing (score of >100) and show no degradation of mask filtration efficiency. We also test the Chen Heng V9501 KN95 and HKYQ N95 finding no degradation of mask filtration efficiency, however even for unheated masks these scored <50 for every fit test. The heating method presented here is scalable from individual masks to over a thousand a day with a single industrial convection oven, making this method practical for local application inside health-care facilities.


title: Whole genome sequencing of SARS-CoV-2 isolated in Guangdong Province and factors influencing the sequencing/ 广东省新型冠状病毒全基因组序列测定及其影响因素分析

text: Objective: To obtain the genome sequences of SARS-CoV-2 in respiratory specimens in Guangdong Province with next-generation sequencing (NGS) and analyze the factors influencing sequencing. Methods: Eight upper and lower respiratory tract specimens were collected from patients with SARS-CoV-2 infection in Guangdong Province in January 2020. RNA library construction was used to obtain the genome sequences of SARS-CoV-2. A bio-informatics software package (CLC Genomics Workbench 12.0) was used to analyze and compare the genomic sequences. Results: Five SARS-CoV-2 genome sequences were obtained from the eight specimens and two were obtained from lower respiratory tract specimens. The nucleotide homology to SARS-CoV-2 was 97.74%-99.90%. The Ct values were lower, while the sequencing depth, coverage, relative abundance and genome integrity were higher in sequencing the SARS-CoV-2 in lower respiratory tract specimens. Conclusions: The low Ct value of SARS-CoV-2 in the samples was good for sequencing.


title: COVID-19: Why SOLIDARITY and DisCoVeRy trials may fail to bring informative and timely results

text: Objective: The SOLIDARITY and DisCoVeRy trials were launched to facilitate the rapid worldwide comparison of the efficacy and safety of treatments against COVID-19. This study aimed to review the trial designs of SOLIDARITY and DisCoVeRy and their feasibility to generate high-quality evidence. Method: A systematic search of the European Clinical trial registry, the U.S. National Library of Medicine ClinicalTrials.gov, and the International Clinical Trials Registry Platform (ICTRP) created by the World Health Organization (WHO) was conducted on May 10th, 2020 to identify the study details of the SOLIDARITY and DisCoVeRy trials. A supplementary search of PubMed, the websites of the WHO and French authorities, and Google search engine was conducted. A critical review was performed on the findings. Results: The DisCoVeRy trial design was detailed consistently in both the European and the US clinical rial registries. SOLIDARITY was registered on ICTRP, with country-specific information reported on country-level registry platforms. The design of DisCoVeRy trial appears to be ideal from the methodological perspective. Both trials appear difficult to implement, impractical, and disconnected from the pandemic reality. This is consistent with the apparent failure of the trials to deliver conclusions before the end of the pandemic. Conclusion: Both trials constitute an interesting initiative yet may lack the resources to support a high-quality implementation. The authors call for a pandemic task force, with various experts on the front-line of COVID-19, to inform policy-makers to make effective decisions that may not be based on traditional, methodological state-of-the-art evidence, but rather pragmatic and revisable decisions reflecting emerging evidence for the benefit of patients and society.


title: Susceptibility of ferrets, cats, dogs, and different domestic animals to SARS-coronavirus-2

text: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the infectious disease COVID-19, which was first reported in Wuhan, China in December, 2019. Despite the tremendous efforts to control the disease, COVID-19 has now spread to over 100 countries and caused a global pandemic. SARS-CoV-2 is thought to have originated in bats; however, the intermediate animal sources of the virus are completely unknown. Here, we investigated the susceptibility of ferrets and animals in close contact with humans to SARS-CoV-2. We found that SARS-CoV-2 replicates poorly in dogs, pigs, chickens, and ducks, but efficiently in ferrets and cats. We found that the virus transmits in cats via respiratory droplets. Our study provides important insights into the animal reservoirs of SARS-CoV-2 and animal management for COVID-19 control.


title: COVID-19 Outbreak, Social Response, and Early Economic Effects: A Global VAR Analysis of Cross-Country Interdependencies

text: The COVID-19 pandemic underscored the importance of countries' interconnections in understanding and reacting to the spread of the virus. This paper uses a global model with a sample of 41 countries to study the interdependencies between COVID-19 health shocks, populations' risk perceptions about the disease, and their social distancing responses; it also provides some early evidence about potential economic effects. Social networks are a central component in understanding the international transmission. We exploit a dataset on existing social connections across country borders, made available by Facebook, and show that social networks help explain not only the spread of the disease, but also cross-country spillovers in risk perceptions and in social behavior. Social distancing responses across countries are measured based on aggregated mobility tracking indicators, obtained from Google Mobility Reports. We estimate a Global VAR (GVAR) model, which allows for endogeneity of each health, social, and economic, domestic variable, and for a dependence of domestic variables on country-specific foreign aggregates, which depend in turn on the matrix of social connections. Our empirical results highlight the importance of cross-country interdependencies and social networks. Risk perceptions and social responses are affected by experiences abroad, with Italy and the U.S. playing large roles in our sample. The social distancing responses to domestic health shocks are heterogeneous across countries, but they share some similarities: they adjust only gradually and with delay, hence displaying adaptive behavior. Early indicators are suggestive of unemployment consequences that vary widely across countries, depending on their labor market characteristics. Unemployment is particularly responsive to health shocks in the U.S. and Spain, while the fluctuations are attenuated almost everywhere else.


title: Impacts of remdesivir on dynamics and efficacy stratified by the severity of COVID-19: a simulated two-arm controlled study

text: Background: The impact of remdesivir on length of stay of hospitalization, high-risk state, and death stratified by the severity of COVID-19 at enrollment is controversial. Methods: We applied a simulated two-arm controlled study design to the data on compassionate use of remdesivir as a secondary analysis. Dynamics of risk states and death from COVID-19 patients defined by the six-point disease severity recommended by the WHO R&D and the time to discharge from hospital were used to evaluate the efficacy of remdesivir treatment compared with standard care. Results: Stratified by the risk state at enrollment, low-risk patients exhibited the highest efficacy of remdesivir in reducing subsequent progression to high-risk state by 67% (relative risk (RR)=0.33,95% CI: 0.30-0.35) and further to death by 55% (RR=0.45, 95%CI: 0.39-0.50). For the medium-risk patients, less but still statistically significant efficacy results were noted in reducing progression to high-risk state by 52% (RR=0.48, 95% CI: 0.45-0.51) and further to death by 40% (RR=0.60, 95% CI:0.54-0.66). High-risk state patients treated with remdesivir led to a 25% statistically significant reduction in death (RR=0.75, 95% CI: 0.69-0.82). Regarding the outcome of discharge, remdesivir treatment was most effective for medium-risk patients at enrollment (RR: 1.41, 95% CI: 1.35-1.47) followed by high- (RR=1.34, 95% CI: 1.27-1.42) and low-risk patients (RR=1.28, 95% CI: 1.25-1.31). Conclusion: Our results with a simulated two-arm controlled study have provided a new insight into the precision treatment of remdesivir for COVID-19 patients based on risk-stratified efficacy.


title: A novel deterministic forecast model for COVID-19 epidemic based on a single ordinary integro-differential equation

text: In this paper, we present a new approach to deterministic modelling of COVID-19 epidemic. Our model dynamics is expressed by a single prognostic variable in an integro-differential equation. All unknown parameters are described with a single, timedependent variable {kappa}(t). We show that our model has similarities to classic compartmental models, such as SIR, and that the variable {kappa}(t) can be interpreted as the effective reproduction number Reff. The advantages of our approach are the simplicity of having only one equation, the numerical stability due to an integral formulation and the reliability because the model is formulated with the most trustable statistical data variable: the number of cumulative diagnosed positive cases of COVID-19. Once this dynamic variable is calculated, other non-dynamic variables, such as the number of heavy cases (hospital beds), the number of intensive-care cases (ICUs) and the fatalities, can be derived from it using a similarly stable, integral approach. The formulation with a single equation allows us to calculate from real data the values of the effective reproduction number, which can then be fitted. The extrapolated values of {kappa} can be used in the model to make a reliable forecasts, though under the assumption that measures for reducing infections are maintained. We have applied our model to more than 15 countries and results are available via a web-based platform. In this paper we focus on the data for two exemplary countries, Italy and Germany, and show that the model is capable of reproducing the course of the epidemic in the past and forecasting its course for a period of two to three weeks with a reasonable numerical stability.


title: A stochastic model for COVID-19 spread and the effects of Alert Level 4 in Aotearoa New Zealand

text: While case numbers remain low, population-wide control methods combined with efficient tracing, testing, and case isolation, offer the opportunity for New Zealand to contain and eliminate COVID-19. We use a stochastic model to investigate containment and elimination scenarios for COVID-19 in New Zealand, as the country considers the exit from its four week period of strong Level 4 population-wide control measures. In particular we consider how the effectiveness of its case isolation operations influence the outcome of lifting these strong population-wide controls. The model is parameterised for New Zealand and is initialised using current case data, although we do not make use of information concerning the geographic dispersion of cases and the model is not stratified for age or co-morbidities. We find that fast tracing and case isolation (i.e. operations that are sustained at rates comparable to that at the early stages of New Zealand's response) can lead to containment or elimination, as long as strong population-wide controls remain in place. Slow case isolation can lead to containment (but not elimination) as long as strong Level 4 population-wide controls remain in place. However, we find that relaxing strong population-wide controls after four weeks will most likely lead to a further outbreak, although the speed of growth of this outbreak can be reduced by fast case isolation, by tracing, testing, or otherwise. We find that elimination is only likely if case isolation is combined with strong population-wide controls that are maintained for longer than four weeks. Further versions of this model will include an age-structured population as well as considering the effects of geographic dispersion and contact network structure, the possibility of regional containment combined with inter-regional travel restrictions, and the potential for harm to at risk communities and essential workers.


title: Effect of in-process laser interface heating on strength isotropy of extrusion-based additively manufactured PEEK

text: Abstract Fused Filament Fabrication (FFF) 3D printing provides an effective solution for fabrication of custom components at affordable cost and in short time. Nevertheless, relative to the conventional methods, the anisotropic properties exhibited by FFF 3D printed parts cause the mechanical strength to be less satisfactory. In order to resolve the problem, we propose an in-process laser local pre-deposition heating (LLPH) method, which is capable of enhancing thermal relaxation at inter-layer interface and reinforcing inter-layer adhesion, that ultimately resulted in an increase in tensile strength along the build direction. This improvement in tensile strength of the build parts with in-process laser power has been demonstrated in this manuscript. Besides, the subsequent relevance with polymer relaxation, reptation and entanglement has been discussed. As verified by mechanical testing, tensile strength was improved by 350% compared to control sample and 99.5% isotropy was achieved (build-direction strength divided by in-plane strength) with the application of laser. Scanning Electron Microscope was used to make observation of isotropic behavior at inter-layer interface.


title: Clinical characteristics and outcomes in diabetes patients admitted with COVID-19 in Dubai: a cross-sectional single centre study.

text: Aim: To describe the clinical characteristics and outcomes of hospitalised Coronavirus Disease 2019 (COVID-19) patients with diabetes. Methods: A cross-sectional observational study was conducted in patients with diabetes admitted with COVID-19 to Mediclinic Parkview Hospital in Dubai, United Arab Emirates (UAE) from 30th March to 7th June 2020. They had laboratory and/or radiologically confirmed severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), known as COVID-19. Variation in characteristics, length of stay in hospital, diabetes status, comorbidities and outcomes were examined. Results: A total of 103 patients with confirmed COVID-19 presentations had diabetes. During the same timeframe, 410 patients overall were admitted with COVID-19 infection. This gives a total proportion of persons admitted with COVID-19 infection and coexistent diabetes/prediabetes of 25%. 67% (n=69) of the COVID-19 diabetes cohort were male. Patients admitted with COVID-19 and diabetes represented 17 different ethnicities. Of these, 59.2% (n=61) were Asians and 35% (n=36) were from Arab countries. Mean age (SD) was 54 (12.5) years. 85.4% (n=88) were known to have diabetes prior to admission, while 14.6% (n=15) were newly diagnosed with either diabetes or prediabetes during admission. Most patients in the study cohort had type 2 diabetes or prediabetes, with only 3% overall having type 1 diabetes (n=3). 46.9% of patients had evidence of good glycaemic control of their diabetes during the preceding 4-12 weeks prior to admission as defined arbitrarily by admission HbA1c <7.5%. 73.8% (n=76) had other comorbidities including hypertension, ischaemic heart disease, and dyslipidaemia. Laboratory data Mean(SD) on admission for those who needed ward-based care versus those needing intensive care unit (ICU) care: Fibrinogen 462.75 (125.16) mg/dl vs 660 (187.58) mg/dl ; D-dimer 0.66 (0.55) mcg/ml vs 2.3 (3.48) mcg/ml; Ferritin 358.08 (442.05) mg/dl vs 1762.38 (2586.38) mg/dl; and CRP 33.9 (38.62) mg/L vs 137 (111.72) mg/L were all statistically significantly higher for the ICU cohort (p<0.05). Average length of stay in hospital was 14.55 days. 28.2% of patients needed ICU admission. 4.9% (n=5) overall died during hospitalisation (all in ICU). Conclusions: In this single-centre study in Dubai, 25% of patients admitted with COVID-19 also had diabetes/prediabetes. Most diabetes patients admitted to hospital with COVID-19 disease were males of Asian origin. 14.6% had new diagnosis of diabetes/prediabetes on admission. The majority of patients with diabetes/prediabetes and COVID-19 infection had other important comorbidities (n=76; 73.8%). Only 4 patients had negative COVID-19 RT-PCR but had pathognomonic changes of COVID-19 radiologically. Our comprehensive laboratory analysis revealed distinct abnormal patterns of biomarkers that are associated with poor prognosis: Fibrinogen, D-dimer, Ferritin and CRP levels were all statistically significantly higher (p<0.05) at presentation in patients who subsequently needed ICU care compared with those patients who remained ward-based. 28.2% overall needed ICU admission, out of which 5 patients died. More studies with larger sample sizes are needed to compare data of COVID-19 patients admitted with and without diabetes within the UAE region.


title: Nicotinic receptors atlas in the adult human lung

text: Nicotinic acetylcholine receptors (nAChRs) are pentameric ligand-gated ion channels responsible for the rapid neural and neuromuscular signal transmission. Although it is well documented that 16 subunits are encoded by the human genome, their presence in airway epithelial cells (AEC) remains poorly understood, and contribution to pathology is mainly discussed in the context of cancer. We analysed nAChR subunit expression in the human lung of smokers and non-smokers using transcriptomic data for whole lung tissues, isolated large AEC, and isolated small AEC. We identified differential expressions of nAChRs in terms of detection and repartition in the three modalities. Smoking-associated alterations were also unveiled. Then, we identified a nAChR transcriptomic print at a single cell level. Finally, we reported the localizations of detectable nAChRs in bronchi and large bronchioles. Thus, we compiled the first complete atlas of pulmonary nAChRs to open new avenues to further unravel the involvement of these receptors in lung homeostasis and respiratory diseases.


title: Epidemiological and clinical features of 291 cases with coronavirus disease 2019 in areas adjacent to Hubei, China: a double-center observational study

text: Abstract Background: The clinical outcomes of COVID-19 patients in Hubei and other areas are different. We aim to investigate the epidemiological and clinical characteristics of patient with COVID-19 in Hunan which is adjacent to Hubei. Methods: In this double-center, observational study, we recruited all consecutive patients with laboratory confirmed COVID-19 from January 23 to February 14, 2020 in two designated hospitals in Hunan province, China. Epidemiological and clinical data from patients' electronic medical records were collected and compared between mild, moderate and severe/critical group in detail. Clinical outcomes were followed up to February 20, 2020. Findings: 291 patients with COVID-19 were categorized into mild group (10.0%), moderate group (72.8%) and severe/critical group (17.2%). The median age of all patients was 46 years (49.8% were male). 86.6% patients had an indirect exposure history. The proportion of patients that had been to Wuhan in severe/critical group (48.0% vs 17.2%, p=0.006) and moderate group (43.4% vs 17.2%, p=0.007) were higher than mild group. Fever (68.7%), cough (60.5%), and fatigue (31.6%) were common symptoms especially for severe and critical patients. Typical lung imaging finding were bilateral and unilateral ground glass opacity or consolidation. Leukopenia, lymphopenia and eosinopenia occurred in 36.1%, 22.7% and 50.2% patients respectively. Increased fibrinogen was detected in 45 of 58 (77.6%) patients with available results. 29 of 44 (65.9%) or 22 of 40 (55.0%) patients were positive in Mycoplasma pneumonia or Chlamydia pneumonia antibody test respectively. Compared with mild or moderate group, severe/critical group had a relative higher level of neutrophil, Neutrophil-to-Lymphocyte Ratio, h-CRP, ESR, CK, CK-MB, LDH, D-dimer, and a lower level of lymphocyte, eosinophils, platelet, HDL and sodium (all p<0.01). Most patients received antiviral therapy and Chinese Medicine therapy. As of February 20, 2020, 159 (54.6%) patients were discharged and 2 (0.7%) patients died during hospitalization. The median length of hospital stay in discharged patients was 12 days (IQR: 10-15). Interpretation: The epidemiological and clinical characteristics of COVID-19 patients in Hunan is different from patients in Wuhan. The proportion of patients that had been to Wuhan in severe/critical group and moderate group were higher than mild group. Laboratory and imaging examination can assist in the diagnosis and classification of COVID-19 patients.


title: Ocular infection and detection of coronavirus/ 冠状病毒眼部感染及检测

text: •Since the outbreak of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV), the study of coronavirus pathogens and the identification of host organisms has been an important task in the medical domain. New coronavirus SARS-CoV-2 appeared in 2019 was more contagious and pathogenic, which quickly attracted a global attention. So far, there have been clinical reports that patients with coronavirus infection can develop ocular symptoms mainly conjunctivitis, and ocular nucleic acid detection has been proposed as an assistant method for early coronavirus identification. This paper reviewed the ocular manifestations and detection of coronavirus to provide references for further research.


title: Evaluation of a genetic risk score for severity of COVID-19 using human chromosomal-scale length variation.

text: The course of COVID-19 varies from asymptomatic to severe in patients. The basis for this range in symptoms is unknown. One possibility is that genetic variation is partly responsible for the highly variable response. We evaluated how well a genetic risk score based on chromosomal-scale length variation and machine learning classification algorithms could predict severity of response to SARS-CoV-2 infection. We compared 981 patients from the UK Biobank dataset who had a severe reaction to SARS-CoV-2 infection before 27 April 2020 to a similar number of age matched patients drawn for the general UK Biobank population. For each patient, we built a profile of 88 numbers characterizing the chromosomal-scale length variability of their germ line DNA. Each number represented one quarter of the 22 autosomes. We used the machine learning algorithm XGBoost to build a classifier that could predict whether a person would have a severe reaction to COVID-19 based only on their 88-number classification. We found that the XGBoost classifier could differentiate between the two classes at a significant level (p=2*10^(-11)) as measured against a randomized control and (p=3*10^(-14)) as measured against the expected value of a random guessing algorithm (AUC=0.5). However, we found that the AUC of the classifier was only 0.51, too low for a clinically useful test. Genetics play a role in the severity of COVID-19, but we cannot yet develop a useful genetic test to predict severity.


title: Comparison of primer-probe sets among different master mixes for laboratory screening of Severe Acute Respiratory Syndrome - Coronavirus 2 (SARS-CoV-2)

text: Background: The shortage of chemical reagents for severe acute respiratory syndrome - coronavirus 2 (SARS-CoV-2) diagnosis and the surge of SARS-CoV-2 cases, especially in limited-resource settings. Therefore, the combination of an optimal assay kit is necessary. Methods: We compared the ability to screen SARS-CoV-2 among three primer-probe sets added into two different master mixes (Invitrogen SuperScript III One-Step RT-PCR, and LightCycler Multiplex RNA Virus Master). Results: The assay with TIB-Molbiol, IDT, and Phu Sa sets for LightCycler Multiplex RNA Virus Master or Invitrogen SuperScript III One-Step RT-PCR showed positive results from a single reaction of triplicate in the three days of 4.8 copies per reaction, with R-square and amplification efficiently (AE) were 0.97 and ranged from 107 to 108%, respectively. Conclusions: Our findings indicated TIB-Molbiol, IDT, and Phu Sa primer-probe sets could be beneficial for the laboratory screening of SARS-CoV-2 by Realtime RT-PCR assay of E gene. There is a need for considering the combination of these reagent sets as a new strategy to increase testing capacity for screening programs for COVID-19.


title: Inhaled corticosteroids downregulate the SARS-CoV-2 receptor ACE2 in COPD through suppression of type I interferon

text: Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 is a new rapidly spreading infectious disease. Early reports of hospitalised COVID-19 cases have shown relatively low frequency of chronic lung diseases such as chronic obstructive pulmonary disease (COPD) but increased risk of adverse outcome. The mechanisms of altered susceptibility to viral acquisition and/or severe disease in at-risk groups are poorly understood. Inhaled corticosteroids (ICS) are widely used in the treatment of COPD but the extent to which these therapies protect or expose patients with a COPD to risk of increased COVID-19 severity is unknown. Here, using a combination of human and animal in vitro and in vivo disease models, we show that ICS administration attenuates pulmonary expression of the SARS-CoV-2 viral entry receptor angiotensin-converting enzyme (ACE)-2. This effect was mechanistically driven by suppression of type I interferon as exogenous interferon-β reversed ACE2 downregulation by ICS. Mice deficient in the type I interferon-α/β receptor (Ifnar1−/−) also had reduced expression of ACE2. Collectively, these data suggest that use of ICS therapies in COPD reduces expression of the SARS-CoV-2 entry receptor ACE2 and this effect may thus contribute to altered susceptibility to COVID-19 in patients with COPD.


title: Cardiovascular medications and regulation of COVID-19 receptors expression

text: Introduction: Emerging epidemiological studies suggested that Renin–Angiotensin–Aldosterone system (RAAS) inhibitors may increase infectivity and severity of COVID-19 by modulating the expression of ACE2. Methods: In silico analysis was conducted to compare the blood expression levels of SARS-CoV-2 entry genes between age and gender matched cohort of hypertensive patients versus control, and to determine the effect of common cardiovascular medications on the expression of COVID-19 receptors in vitro using primary human hepatocytes. Results: The transcriptomic analysis revealed a significant increase of ACE2 and TMPRSS2 in the blood of patients with hypertension. Treatment of primary human hepatocytes with captopril, but not enalapril, significantly increased ACE2 expression. A similar pattern of ACE2 expression was found following the in vitro treatments of rat primary cells with captopril and enalapril. Telmisartan, a second class RAAS inhibitors, did not affect ACE2 levels. We have also tested other cardiovascular medications that may be used alone, or in combination with RAAS inhibitors. Some of these medications increased TMPRSS2, while others, like furosemide, significantly reduced COVID-19 receptors. Conclusions: The increase in ACE2 expression levels could be due to chronic use of RAAS inhibitors or alternatively caused by other hypertension-related factors or presence of other comorbidities. Treatment of common co-morbidities often require chronic use of multiple medications, which may result in an additive increase in the expression of ACE2 and TMPRSS2. Our data suggest that more research is needed to determine the effect of different medications, as well as medication combinations, on COVID-19 receptors.


title: Effects of latency and age structure on the dynamics and containment of COVID-19

text: In this paper we develop an SEIR-type model of COVID-19, with account for two particular aspects: non-exponential distribution of incubation and recovery periods, as well as age structure of the population. For the mean-field model, which does not distinguish between different age groups, we demonstrate that including a more realistic Gamma distribution of incubation and recovery periods may not have an effect on the total number of deaths and the overall size of an epidemic, but it has a major effect in terms of increasing the peak numbers of infected and critical care cases, as well as on changing the timescales of an epidemic, both in terms of time to reach the peak, and the overall duration of an outbreak. In order to obtain more accurate estimates of disease progression and investigate different strategies for introducing and lifting the lockdown, we have also considered an age-structured version of the model, which has allowed us to include more accurate data on age-specific rates of hospitalisation and COVID-19 related mortality. Applying this model to three comparable neighbouring regions in the UK has delivered some fascinating insights regarding the effect of quarantine in regions with different population structure. We have discovered that for a fixed quarantine duration, the timing of its start is very important in the sense that the second epidemic wave after lifting the quarantine can be significantly smaller or larger depending on the specific population structure. Also, the later the fixed-duration quarantine is introduced, the smaller is the resulting final number of deaths at the end of the outbreak. When the quarantine is introduced simultaneously for all regions, increasing quarantine duration postpones and slightly reduces the epidemic peak, though without noticeable differences in peak magnitude between different quarantine durations.


title: Virtual screening of small molecular inhibitors of SARS-CoV-2 3CL hydrolase based on high-throughput molecular docking and prediction of Chinese materia medica and its compound against COVID-19/ 基于高通量分子对接虚拟筛选SARS-CoV-2 3CL水解酶中药小分子抑制剂及抗新型冠状病毒肺炎（COVID-19）的中药及其复方预测

text: Objective: Based on the systematic pharmacological database of traditional Chinese medicine (TCM) and the analysis platform TCMSP, the computer virtual screening technique was used to screen the small molecule inhibitors of SARS-CoV-2 3CL hydrolase from Chinese materia medica (CMM), and speculate the potential anti-COVID-19 novel coronavirus pneumonia TCMs and its compounds. Methods: SARS-CoV-2 3CL hydrolase protein was targeted in this study. Autodock Vina software and Python script were used to realize high-throughput molecular docking. Combined with “ADME-Lipinski” rules, the re-screening was carried out to optimize the active ingredients and speculate the key TCMs and compound prescriptions. Based on the perspective of network pharmacology, a component-target-pathway network was constructed to infer the mechanism of action of core drug pairs. Results: Taking the reference ligand as positive control, 66 natural micromolecule compounds with good pharmacokinetic properties were obtained. Twelve single TCMs, two Chinese medicine pairs of Glycyrrhizae Radix et Rhizoma-Mori Cortex and Lonicerae Japonicae Flos-Forsythiae Fructus, and 12 TCM prescriptions including Sangju Drink and modified Sangju Drink and Yinqiao Powder were selected as candidate schemes to fight against novel coronavirus pneumonia. Conclusion: This study is based on high-throughput molecular docking technology to virtually screen small molecule inhibitors of SARS-CoV-2 3CL hydrolase of CMM and Chinese medicines, innovatively analyze the potential molecular mechanism in combination with network pharmacology, and provide scientific guidance and theoretical basis for TCM to resist novel coronavirus pneumonia.


title: A new system in qualitative RT-PCR detecting SARS-CoV-2 in biological samples: an Italian experience.

text: In the last moths the world was faced with the pandemic of a new severe acute respiratory syndrome coronavirus (SARS-CoV) and the majority of the Nations have yet to come out of it. Numerous assays have emerged to meet SARS-CoV-2 diagnostic needs. A clear knowledge of these assays parameters is essential to choose the proper test by clinical microbiologists. Unfortunately, the latter cannot be the unique criterion that guides test selection as - given the great demand - shortcomings of commercial kits is also a great issue. Aimed by the intention of overcoming both difficulties we have developed a new qualitative RT-PCR probe based for COVID-19 detection. The system detects three genes of SARS-CoV-2: RNA-dependent RNA polymerase (RdRp), envelope (E) and nucleocapsid (N) and {beta}-actin gene used as endogenous internal control. The results of our assay show a total agreement with those obtained using a commercially available kit, with the exception of two specimens which did not pass the endogenous internal control. Moreover, our kit was designed to be open either for nucleic acid extraction step or on the RT-PCR assay to be carried out on several instruments. Thus, it is free from the industrial production logics of closed systems and conversely it is hypothetically available for distribution on large numbers in any microbiological laboratories. Presently, the kit is currently distributed worldwide


title: Comparative assessment of multiple COVID-19 serological technologies supports continued evaluation of point-of-care lateral flow assays in hospital and community healthcare settings

text: There is a clear requirement for an accurate SARS-CoV-2 antibody test, both as a complement to existing diagnostic capabilities and for determining community seroprevalence. We therefore evaluated the performance of a variety of antibody testing technologies and their potential as diagnostic tools. A highly specific in-house ELISA was developed for the detection of anti-spike (S), -receptor binding domain (RBD) and -nucleocapsid (N) antibodies and used for the cross-comparison of ten commercial serological assays - a chemiluminescence-based platform, two ELISAs and seven colloidal gold lateral flow immunoassays (LFIAs) - on an identical panel of 110 SARS-CoV-2-positive samples and 50 pre-pandemic negatives. There was a wide variation in the performance of the different platforms, with specificity ranging from 82% to 100%, and overall sensitivity from 60.9% to 87.3%. However, the head to head comparison of multiple serodiagnostic assays on identical sample sets revealed that performance is highly dependent on the time of sampling, with sensitivities of over 95% seen in several tests when assessing samples from more than 20 days post onset of symptoms. Furthermore, these analyses identified clear outlying samples that were negative in all tests, but were later shown to be from individuals with mildest disease presentation. Rigorous comparison of antibody testing platforms will inform the deployment of point of care technologies in healthcare settings and their use in the monitoring of SARS-CoV-2 infections.


title: As COVID-19 forces conferences online, scientists discover upsides of virtual format

text: But when COVID-19 caused organizers to cancel a series of local chemistry meetings across Canada—called Inorganic Discussion Weekends—and offer a virtual alternative, she signed up to give a talk Altman’s institute had planned an inperson conference this month, but COVID-19 forced organizers to scuttle it ”For some societies, the COVID-19 crisis hasn’t so much started discussions about virtual conferences as accelerated them


title: Fully human single-domain antibodies against SARS-CoV-2

text: The COVID-19 pandemic is spreading rapidly, highlighting the urgent need for an efficient approach to rapidly develop therapeutics and prophylactics against SARS-CoV-2. We describe here the development of a phage-displayed single-domain antibody library by grafting naïve CDRs into framework regions of an identified human germline IGHV allele. This enabled the isolation of high-affinity single-domain antibodies of fully human origin. The panning using SARS-CoV-2 RBD and S1 as antigens resulted in the identification of antibodies targeting five types of neutralizing or non-neutralizing epitopes on SARS-CoV-2 RBD. These fully human single-domain antibodies bound specifically to SARS-CoV-2 RBD with subnanomolar to low nanomolar affinities. Some of them were found to potently neutralize pseudotyped and live virus, and therefore may represent promising candidates for prophylaxis and therapy of COVID-19. This study also reports unique immunogenic profile of SARS-CoV-2 RBD compared to that of SARS-CoV and MERS-CoV, which may have important implications for the development of effective vaccines against SARS-CoV-2.


title: Cytokine biomarkers of COVID-19

text: We used a new strategy to screen cytokines associated with SARS-CoV-2 infection. Cytokines that can classify populations in different states of SARS-CoV-2 infection were first screened in cross-sectional serum samples from 184 subjects by 2 statistical analyses. The resultant cytokines were then analyzed for their interrelationships and fluctuating features in sequential samples from 38 COVID-19 patients. Three cytokines, M-CSF, IL-8 and SCF, which were clustered into 3 different correlation groups and had relatively small fluctuations during SARS-CoV-2 infection, were selected for the construction of a multiclass classification model. This model discriminated healthy individuals and asymptomatic and nonsevere patients with accuracy of 77.4% but was not successful in classifying severe patients. Further searching led to a single cytokine, hepatocyte growth factor (HGF), which classified severe from nonsevere COVID-19 patients with a sensitivity of 84.6% and a specificity of 97.9% under a cutoff value of 1128 pg/ml. The level of this cytokine did not increase in nonsevere patients but was significantly elevated in severe patients. Considering its potent antiinflammatory function, we suggest that HGF might be a new candidate therapy for critical COVID-19. In addition, our new strategy provides not only a rational and effective way to focus on certain cytokine biomarkers for infectious diseases but also a new opportunity to probe the modulation of cytokines in the immune response.


What is required to prevent a second major outbreak of SARS-CoV-2 upon lifting the quarantine of Wuhan city, China


Ventilators may not be best for severe covid-19


title: Projected ICU and Mortuary load due to COVID-19 in Sydney

text: The spread of COVID-19 is expected to put a large strain on many hospital resources, including ICU bed space, and mortuary capacity. In this report we study the possible demands on ICU and mortuary capacity in Sydney, Australia, using an adapted SEIR epidemiological model.


title: Nrf2 Activator PB125(®) as a Potential Therapeutic Agent against COVID-19

text: Nrf2 is a transcription factor that regulates cellular redox balance and the expression of a wide array of genes involved in immunity and inflammation, including antiviral actions. Nrf2 activity declines with age, making the elderly more susceptible to oxidative stress-mediated diseases, which include type 2 diabetes, chronic inflammation, and viral infections. Published evidence suggests that Nrf2 activity may regulate important mechanisms affecting viral susceptibility and replication. We examined gene expression levels by GeneChip microarray and by RNA-seq assays. We found that the potent Nrf2-activating composition PB125(®) downregulates ACE2 and TMPRSS2 mRNA expression in human liver-derived HepG2 cells. ACE2 is a surface receptor and TMPRSS2 activates the spike protein for SARS-CoV-2 entry into host cells. Furthermore, in endotoxin-stimulated primary human pulmonary artery endothelial cells, we report the marked downregulation by PB125 of 36 genes encoding cytokines. These include IL-1-beta, IL-6, TNF-α, the cell adhesion molecules ICAM-1, VCAM-1, and E-selectin, and a group of IFN-γ-induced genes. Many of these cytokines have been specifically identified in the “cytokine storm” observed in fatal cases of COVID-19, suggesting that Nrf2 activation may significantly decrease the intensity of the storm.


title: For Brazil’s Indigenous communities, pandemic revives memories of earlier plagues

text: To the older generation of the Paiter Surui, the COVID-19 pandemic looks familiar The Indigenous people who inhabit the border of the Brazilian states of Rondônia and Mato Grosso suffered hundreds of deaths from measles and other infectious diseases in the decades after they first made contact with non-Indigenous people in 1969 The survivors “already experienced what is happening in the world today with the coronavirus,” says Rubens Naraikoe Surui, a young Indigenous leader Now, as the number of coronavirus cases ramps up in Brazil, the Pater Surui and other Indigenous people worry that they could be hard hit So far, 16 members of such groups are known to have had COVID-19 infections, and three have died: a 15-year-old Yanomami boy, a 78-year-old Tikuna man, and a 44-year-old Kokama woman


title: Combining fine-scale social contact data with epidemic modelling reveals interactions between contact tracing, quarantine, testing and physical distancing for controlling COVID-19

text: Case isolation and contact tracing can contribute to the control of COVID-19 outbreaks. However, it remains unclear how real-world networks could influence the effectiveness and efficiency of such approaches. To address this issue, we simulated control strategies for SARS-CoV-2 in a real-world social network generated from high resolution GPS data. We found that tracing contacts-of-contacts reduced the size of simulated outbreaks more than tracing of only contacts, but resulted in almost one third of the local population being quarantined at a single point in time. Testing and releasing non-infectious individuals reduced the numbers of quarantined individuals without large increases in outbreak size, but high testing rates were required for this to be effective. Finally, if testing availability is constrained, we estimated that combining physical distancing with contact tracing could enable epidemic control while reducing the number of quarantined individuals. Our approach highlights the importance of network structure and social dynamics in evaluating the potential impact of SARS-CoV-2 control.


title: Analyzing hCov genome sequences: Applying Machine Intelligence and beyond

text: Covid-19 pandemic, caused by the sars-cov-2 strain of coronavirus, has affected millions of people all over the world and taken thousands of lives. It is of utmost importance that the character of this deadly virus be studied and its nature be analysed. We present here an analysis pipeline comprising phylogenetic analysis on strains of this novel virus to track its evolutionary history among the countries uncovering several interesting relationships, followed by a classification exercise to identify the virulence of the strains and extraction of important features from its genetic material that are used subsequently to predict mutation at those interesting sites using deep learning techniques. In a nutshell, we have prepared an analysis pipeline for hCov genome sequences leveraging the power of machine intelligence and uncovered what remained apparently shrouded by raw data.


title: Scalable and Resilient SARS-CoV2 testing in an Academic Centre

text: The emergence of the novel coronavirus SARS-CoV-2 has led to a pandemic infecting more than two million people worldwide in less than four months, posing a major threat to healthcare systems. This is compounded by the shortage of available tests causing numerous healthcare workers to unnecessarily self-isolate. We provide a roadmap instructing how a research institute can be repurposed in the midst of this crisis, in collaboration with partner hospitals and an established diagnostic laboratory, harnessing existing expertise in virus handling, robotics, PCR, and data science to derive a rapid, high throughput diagnostic testing pipeline for detecting SARS-CoV-2 in patients with suspected COVID-19. The pipeline is used to detect SARS-CoV-2 from combined nose-throat swabs and endotracheal secretions/ bronchoalveolar lavage fluid. Notably, it relies on a series of in-house buffers for virus inactivation and the extraction of viral RNA, thereby reducing the dependency on commercial suppliers at times of global shortage. We use a commercial RT-PCR assay, from BGI, and results are reported with a bespoke online web application that integrates with the healthcare digital system. This strategy facilitates the remote reporting of thousands of samples a day with a turnaround time of under 24 hours, universally applicable to laboratories worldwide.


title: Is the impact of social distancing on coronavirus growth rates effective across different settings? A non-parametric and local regression approach to test and compare the growth rate

text: Epidemiologists use mathematical models to predict epidemic trends, and these results are inherently uncertain when parameters are unknown or changing. In other contexts, such as climate, modellers use multi-model ensembles to inform their decision-making: when forecasts align, modellers can be more certain. This paper looks at a sub-set of alternative epidemiological models that focus on the growth rate, and it cautions against relying on the method proposed in (Pike & Saini, 2020): relying on the data for China to calculate future trajectories is likely to be subject to overfitting, a common problem in financial and economic modelling. This paper finds, surprisingly, that the data for China are double-exponential, not exponential; and that different countries are showing a range of different trajectories. The paper proposes using non-parametric and local regression methods to support epidemiologists and policymakers in assessing the relative effectiveness of social distancing policies. All works contained herein are provided free to use worldwide by the author under CC BY 2.0.


title: Lung Ultrasound Findings in Patients Hospitalized with Covid-19

text: Introduction: Point-of-care ultrasound (POCUS) has the potential to transform healthcare delivery in the era of COVID-19 with its diagnostic and therapeutic expediency. It can be performed by clinicians already at the bedside, which permits an immediate and augmented assessment of a patient. Although lung ultrasound can be used to accurately diagnose a variety of disease states such as pneumothorax, pleural effusions, pneumonia and interstitial lung disease2, there are limited reports on the sonographic manifestations of COVID-19. There is an urgent need to identify alternative diagnostic modalities that can be immediately employed at the bedside of COVID-19 patients. Methods: This study was conducted at two medical centers in the United States from 3/21/2020-6/01/2020. Any adult who was hospitalized with COVID-19 (based on symptomatology and a confirmatory RT-PCR for SARS-CoV-2) and received a pulmonary POCUS examination was included. Providers were instructed to use a 12-zone scanning protocol for pulmonary views and save 6 second clips of each lung zone. This study utilized several POCUS devices, including Butterfly IQ, Vave, Lumify, and Sonosite. The collected images were interpreted by the study researchers based on a consensus document developed by the study authors and previously accepted definitions of lung POCUS findings. Results: A total of 22 eligible patients who received 36 lung scans were included in our study. Eleven (50%) patients experienced clinical deterioration (defined as either ICU admission, invasive mechanical ventilation, or death within 28 days from the initial symptom onset). Among the 36 lung scans collected, only 3 (8%) were classified as normal. The remaining scans had the following abnormalities: presence of B-lines (n=32, 89%), consolidations (n=20, 56%), pleural thickening (n=17, 47%), and pleural effusion (n=4, 11%). Out of 20 scans with consolidations, 14 (70%) were subpleural and 5 (25%) were translobar. A-lines were present in 26 (72%) of patients, although they were only observed in the majority of the collected lung zones in 5 (14%) of patients. Ultrasound findings were stratified by time from symptom onset to the scan based on the following time periods: early (0-6 days), middle (7-13 days), and late (14-28 days). B-lines appeared early after symptom onset and persisted well into the late disease course. In contrast, pleural thickening increased in frequency over time (early: 25%, middle: 47%, late: 67%). Subpleural consolidations also appeared in higher frequency later in the disease course (early: 13%, middle 42%, late: 56%). Discussion: certain lung ultrasound findings may be common in Covid-19, while others may appear later in the disease course or only occur in patients who experience clinical deterioration. Future efforts should investigate the predictive utility of consolidations, pleural thickening and B-lines for clinical deterioration and compare them to traditional radiological studies such as X-rays or CTs.


title: A Combined Deep CNN-LSTM Network for the Detection of Novel Coronavirus (COVID-19) Using X-ray Images

text: Nowadays automatic disease detection has become a crucial issue in medical science with the rapid growth of population. Coronavirus (COVID-19) has become one of the most severe and acute diseases in very recent times that has been spread globally. Automatic disease detection framework assists the doctors in the diagnosis of disease and provides exact, consistent, and fast reply as well as reduces the death rate. Therefore, an automated detection system should be implemented as the fastest way of diagnostic option to impede COVID-19 from spreading. This paper aims to introduce a deep learning technique based on the combination of a convolutional neural network (CNN) and long short -term memory (LSTM) to diagnose COVID-19 automatically from X-ray images. In this system, CNN is used for deep feature extraction and LSTM is used for detection using the extracted feature. A collection of 421 X -ray images including 141 images of COVID-19 is used as a dataset in this system. The experimental results show that our proposed system has achieved 97% accuracy, 91% specificity, and 100% sensitivity. The system achieved desired results on a small dataset which can be further improved when more COVID-19 images become available. The proposed system can assist doctors to diagnose and treatment the COVID-19 patients easily.


title: Short-term forecasts and long-term mitigation evaluations for the COVID-19 epidemic in Hubei Province, China

text: As an emerging infectious disease, the 2019 coronavirus disease (COVID-19) has developed into a global pandemic. During the initial spreading of the virus in China, we demonstrated the ensemble Kalman filter performed well as a short-term predictor of the daily cases reported in Wuhan City. Second, we used an individual-level network-based model to reconstruct the epidemic dynamics in Hubei Province at its early stage and examine the effectiveness of non-pharmaceutical interventions on the epidemic spreading with various scenarios. Our simulation results show that without continued control measures, the epidemic in Hubei Province could have become persistent. Only by continuing to decrease the infection rate through 1) protective measures and 2) social distancing can the actual epidemic trajectory that happened in Hubei Province be reconstructed in simulation. Finally, we simulate the COVID-19 transmission with non-Markovian processes and show how these models produce different epidemic trajectories, compared to those obtained with Markov processes. Since recent studies show that COVID-19 epidemiological parameters do not follow exponential distributions leading to Markov processes, future works need to focus on non-Markovian models to better capture the COVID-19 spreading trajectories. In addition, shortening the infectious period via early case identification and isolation can slow the epidemic spreading significantly.


title: Isogrid lattice structure for armouring applications

text: Abstract Isogrid structure is a grid stiffening structure formed by partially hollowing out triangular shapes to produce rib features on the surface of the plate. These features are widely used in the aerospace industry for producing lightweight with efficient structures. These structures are usually expensive to manufacture using conventional subtractive manufacturing processes. Therefore, this work involves checking the feasibility of design optimization for additive manufacturing(AM) of Isogrid and Non-Isogrid structure-based structural components subjected to impact loads. Izod impact test, as per ASTM D256, on seven specimens, were performed to check the energy that the material is capable of withstanding for the samples made using various AM parameters(layer height=0.2mm, feed rate 1800mm/min, bed temperature=70◦C, Nozzle temperature= 210 ◦C). Analysing the results of Izod impact test, the projectile velocity of impact for a trivial plate such as of 5mm thickness was used. The results from a trivial case impact test were used to predict the velocity of impact on the identical volume samples. The identical volume samples such as plate, plate stiffened by Isogrid without H-ribs, plate stiffened by Isogrid with H-ribs were used. Also, these results were correlated with simulations, and it was found that Isogrid stiffened plate with H-ribs was more stable.


title: The Impact of Host-Based Early Warning on Disease Outbreaks

text: Objective: The detection of communicable pathogens responsible for major outbreaks relies on health care professionals recognition of symptoms manifesting in infectious individuals. Early warning of such communicable diseases before the onset of symptoms could improve both patient care and public health responses. However, the potential impact of such a host-based early warning system on containing the spread of an outbreak and in steering public health response is unknown. Methods: We extend the deterministic SEIR (Susceptible, Exposed, Infectious, Recovered) model to simulate disease outbreak scenarios and to quantify the potential impact of a host-based early warning capability to mitigate pathogen transmission during an outbreak. In particular, we compare and contrast the performance of five different policies: Self-monitoring and reporting (baseline SEIR model), Quarantining the entire population, Quarantine-on-alert (with high sensitivity early warning), Quarantine-on-alert (with high specificity early warning), and Quarantine-on-alert (ideal early warning). We further evaluate these five policy options against four different outbreak scenarios with high or low disease transmission and high or low initial population exposures. Results: For all scenarios, a quarantine-on-alert policy coupled with the near-ideal early warning capability reduces quarantine needs with only a small increase in the number of additional infections. The cost of a highly specific early detection system (i.e., a reduction in false alarms and thus quarantine costs) is an increase in additional infections relative to the near-ideal system. Conversely, a highly sensitive early detection system increases the percentage of the population in quarantine compared to both the ideal and high-specificity early detection system while also reducing the number of additional infections to nearly the numbers seen by quarantining the entire population a priori. Conclusions: Our simulations demonstrate the utility of host-based early warning systems in controlling an outbreak under various outbreak conditions. Our tools also provide a simulation capability for evaluating public health policies enabling quantitative evaluation of their impacts prior to implementation.


title: Appendix 2 Glossary of Terms

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title: Repositioned chloroquine and hydroxychloroquine as antiviral prophylaxis for COVID-19: A protocol for rapid systematic review of randomized controlled trials

text: Since the SARS-CoV-2 outbreak rapidly evolved into a pandemic, there is an urgent need for rapid development, identification and confirmation of efficacious antiviral prophylaxis. In this setting, the existing drugs chloroquine (CQ) and hydroxychloroquine (HCQ) which has suggestive evidence of efficacy against SARS-CoV-2 infection and COVID-19 disease has become prime candidates to be repositioned as therapeutic and preventative agents, and a growing number of clinical trials have been registered to study their preventative potential for at-risk populations using a range of dosing schemes and outcome measures. This rapid systematic review protocol aims to provide streamlined and timely synthesis on methodologies and results of randomized controlled trials assessing the efficacy of CQ and HCQ in hopes that this will constructively inform further research as well as public health policy.


title: A Brief Theory of Epidemic Kinetics

text: In the context of the COVID-19 epidemic, and on the basis of the Theory of Dynamical Systems, we propose a simple theoretical approach for the expansion of contagious diseases, with a particular focus on viral respiratory tracts. The infection develops through contacts between contagious and exposed people, with a rate proportional to the number of contagious and of non-immune individuals, to contact duration and turnover, inversely proportional to the efficiency of protection measures, and balanced by the average individual recovery response. The obvious initial exponential increase is readily hindered by the growing recovery rate, and also by the size reduction of the exposed population. The system converges towards a stable attractor whose value is expressed in terms of the “reproductive rate” R(0), depending on contamination and recovery factors. Various properties of the attractor are examined, and particularly its relations with R(0). Decreasing this ratio below a critical value leads to a tipping threshold beyond which the epidemic is over. By contrast, significant values of the above ratio may bring the system through a bifurcating hierarchy of stable cycles up to a chaotic behaviour.


title: Delaying the COVID-19 epidemic in Australia: Evaluating the effectiveness of international travel bans

text: Following the outbreak of novel Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) or COVID-19 in Wuhan, China late 2019, different countries have put in place interventions such as travel ban, proper hygiene, and social distancing to slow the spread of this novel virus. We evaluated the effects of travel bans in the Australia context and projected the epidemic until May 2020. Our modelling results closely align with observed cases in Australia indicating the need for maintaining or improving on the control measures to slow down the virus.


Severe COVID-19 Pneumonia and Very Late Stent Thrombosis: a Trigger or Innocent Bystander?


title: Social Media Data Analytics on Telehealth During the COVID-19 Pandemic

text: Introduction: Physical distancing during the coronavirus Covid-19 pandemic has brought telehealth to the forefront to keep up with patient care amidst an international crisis that is exhausting healthcare resources. Understanding and managing health-related concerns resulting from physical distancing measures are of utmost importance. Objectives: To describe and analyze the volume, content, and geospatial distribution of tweets associated with telehealth during the Covid-19 pandemic. Methods: We inquired Twitter public data to access tweets related to telehealth from March 30, 2020 to April 6, 2020. We analyzed tweets using natural language processing (NLP) and unsupervised learning methods. Clustering analysis was performed to classify tweets. Geographic tweet distribution was correlated with Covid-19 confirmed cases in the United States. All analyses were carried on the Google Cloud computing service “Google Colab” using Python libraries (Python Software Foundation). Results: A total of 41,329 tweets containing the term “telehealth” were retrieved. The most common terms appearing alongside ‘telehealth’ were “covid”, “health”, “care”, “services”, “patients”, and “pandemic”. Mental health was the most common health-related topic that appeared in our search reflecting a high need for mental healthcare during the pandemic. Similarly, Medicare was the most common appearing health plan mirroring the accelerated access to telehealth and change in coverage policies. The geographic distribution of tweets related to telehealth and having a specific location within the United States (n=19,367) was significantly associated with the number of confirmed Covid-19 cases reported in each state (p<0.001). Conclusion: Social media activity is an accurate reflection of disease burden during the Covid-19 pandemic. Widespread adoption of telehealth-favoring policies is necessary and mostly needed to address mental health problems that may arise in areas of high infection and death rates.


title: Immunization with the receptor–binding domain of SARS-CoV-2 elicits antibodies cross-neutralizing SARS-CoV-2 and SARS-CoV without antibody-dependent enhancement

text: Recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the ongoing coronavirus disease 2019 (COVID-19) pandemic. Currently, there is no vaccine available for preventing SARS-CoV-2 infection. Like closely related severe acute respiratory syndrome coronavirus (SARS-CoV), SARS-CoV-2 also uses its receptor-binding domain (RBD) on the spike (S) protein to engage the host receptor, human angiotensin-converting enzyme 2 (ACE2), facilitating subsequent viral entry. Here we report the immunogenicity and vaccine potential of SARS-CoV-2 RBD (SARS2-RBD)-based recombinant proteins. Immunization with SARS2-RBD recombinant proteins potently induced a multi-functional antibody response in mice. The resulting antisera could efficiently block the interaction between SARS2-RBD and ACE2, inhibit S-mediated cell-cell fusion, and neutralize both SARS-CoV-2 pseudovirus entry and authentic SARS-CoV-2 infection. In addition, the anti-RBD sera also exhibited cross binding, ACE2-blockade, and neutralization effects towards SARS-CoV. More importantly, we found that the anti-RBD sera did not promote antibody-dependent enhancement of either SARS-CoV-2 pseudovirus entry or authentic virus infection of Fc receptor-bearing cells. These findings provide a solid foundation for developing RBD-based subunit vaccines for SARS-CoV2.


COVID-19: Changing the Landscape of Treatment of Patients With Psoriatic Disease


title: COVID-19 Confirmed Case Incidence Age Shift to Young Persons Age 0-19 and 20-39 Years Over Time: Washington State March - April 2020

text: Background: As the coronavirus (COVID-19) epidemic passes the peak infection rate in some states and counties a phased re-opening with changes of stay-at-home restrictions and social distancing recommendations may lead to an increase of non-essential work, social activities and gathering, especially among younger persons. Methods: A longitudinal cohort analysis of Washington State Department of Health COVID-19 confirmed case age distribution March 1-April 19 2020 for proportional change over time using chi square tests for significance (N = 13,934). Results: From March 1st to April 19, 2020 age distribution shifted with a 10% decline in cases age 60 years and older and a 20% increase in age 0-19/20-39 years (chi-square = 223.10, p <.001). Number of cases over the eight-week analysis period were 0-19 years n = 515, 20-39 years n = 4078, 40-59 years n =4788, 60-79 years n = 3221, 80+ years n = 1332. New cases increased steadily among 0-19 and 20-39-year olds. After the peak (March 22, 2020), there was no decline among age 0-19 and a lesser decline among age 20-39 than older groups. As incidence declined in older age groups, the combined percentage of cases age 0-19 and 20-39 increased from 20% to 40% of total cases. Conclusions: Increased COVID-19 infection among children and young adults is not without serious morbidity and mortality risk to them and others they may come in contact with, indicating a targeted approach for awareness and safety measures is advisable to reduce incidence among the supposedly less vulnerable but more mobile young population age 0-19 and 20-39 years.


title: Psychological Impact of COVID-19 on Pakistani University Students and How They Are Coping

text: Background: COVID-19 is spreading quickly, causing great deal of fear and unrest in the public. Methods: This web-based, cross-sectional study was conducted among students of four renowned Pakistani education institutions. Google forms were used to disseminate the online questionnaire to assess anxiety (generalized anxiety disorder 7-item scale), depression (9-item patient health questionnaire), sources of distress (14-items) and the coping strategies (Brief-COPE). Results: A total of 1134 responses (age 21.7 {+/-} 3.5 years, 70.5% females) were included. The frequency of students having moderate-severe anxiety and depression (score [≥] 10) were {approx} 34% and 45%, respectively. The respondents aged [≥] 31 years had significantly lower depression score than those below 30 years. Males had significantly less anxiety and depression scores than females. Additionally, those having a family member, friend or acquaintance infected with disease had significantly higher anxiety score. The main sources of distress were related to adverse effects of ongoing pandemic on daily life followed by the rapid disease spread. Regarding coping strategies, majority of respondents were found to have adopted religious/spiritual coping followed by acceptance. Conclusions: COVID-19 have significant adverse impact on students' mental health. The most frequent coping strategy adopted by them are religious/spiritual coping, acceptance, self-distraction and active coping. It is suggested that mental health of students should not be neglected during epidemics.


title: Design of an Epitope-Based Peptide Vaccine against the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2): A Vaccine Informatics Approach

text: The recurrent and recent global outbreak of SARS-COV-2 has turned into a global concern which has infected more than one million people all over the globe, and this number is increasing in hours. Unfortunate no vaccine or specific treatment is available, which make it more deadly. An immunoinformatics approach has shown significant breakthrough in peptide-based epitope mapping and opens the new horizon in vaccine development. In this study, we have identified a total of 15 antigenic peptides (including T and B Cells) in the surface glycoprotein of SARS-CoV-2 which found to be 100% conserved with other SARS coronaviruses. Furthermore, the population coverage analysis has found that CD4+ T-cell peptides showed higher cumulative population coverage over to CD8+ peptides in the 16 different geographical regions in the world. Notably, only 09 out of 15 peptides (LTDEMIAQY, IRASANLAA, FGAISSVLN, VKQLSSNFG, FAMQMAYRF, FGAGAALQ, VITPGTNTS, WTAGAAAYY and QTQTNSPRRARS) that have 80% - 90% identity with experimentally identified epitopes of different organisms including SARS-CoV and this will likely be beneficial for a quick progression of the vaccine design. Moreover, docking analysis suggested that these peptides are tightly bound in the groove of HLA molecules which can induce the T-cell response. Overall this study allows us to determine potent peptide antigen targets in surface glycoprotein on intuitive grounds which open up a new horizon in COVID-19 research. However, this study needs experimental validation by in vitro and in vivo.


The Borders around Us: Forced Migration and the Politics of Border Control


title: Hijacking SARS-Cov-2/ACE2 receptor interaction by natural and semi-synthetic steroidal agents acting on functional pockets on receptor binding region

text: The coronavirus disease 2019 (COVID-19) is a respiratory tract infection caused by the severe acute respiratory syndrome coronavirus (SARS)-CoV-2. In the light of the urgent need to identify novel approaches to be used in the emergency phase, a largely explored strategy has been the repurpose of clinically available drugs as new antivirals, by targeting different viral proteins. In this paper, we describe a drug repurposing strategy based on a virtual screening of druggable pockets located in the central β-sheet core of the SARS-CoV-2 Spike protein RBD supported by in vitro tests identifying several steroidal derivatives as SARS-CoV-2 entry inhibitors. Our results demonstrate that several potential binding sites exist in the SARS CoV-2 S protein, and that the occupancy of these pockets reduces the ability of the S protein RBD to bind to the ACE2 consensus in vitro. In particular, natural occurring and clinically available steroids as glycyrrhetinic and oleanolic acids, as well as the bile acids derivatives glyco-UDCA and obeticholic acid have been shown to be effective in preventing virus entry in the case of low viral load. All together, these results might help to define novel approaches to reduce the viral load by using SARS-CoV-2 entry inhibitors.


title: Effect of hydroxychloroquine on SARS-CoV-2 viral load in patients with COVID-19

text: Background: Some studies have shown that hydroxychloroquine (HCQ) is an effective drug in reducing the in vitro replication of SARS-CoV-2. However, the in vivo effect of HCQ still unclear. This study aims to evaluate viral load clearance in patients with COVID-19 who underwent HCQ treatment in comparison with a control group that did not receive the drug. Methods: This prospective study comprised consecutive viral load measurements in patients with COVID-19 hospitalized with a moderate illness. Patients received 400 mg of HCQ every 12 hours for 10 days according to the medical decision. Nasal swab samples were collected at the 1st, 7th, and 14th days of the admission. Results: 155 samples were collected from 66 patients with COVID-19 (60% female), with a median age of 58 years. The viral load between studied groups, assumed as a semiquantitative measure of cycle threshold (Ct) values, presented no significant difference within the three consecutive measures ({Delta}Ct) (p>0.05). We also analyzed the {Delta}Ct viral load at different intervals of sample collection ({Delta}t <7; 7-12 and >12 days) without significant differences at any {Delta}Ct (p>0.05). Conclusion: In this study, we did not observe any change in viral load in vivo with the use of HCQ.


title: Antibody profiling of COVID-19 patients in an urban low-incidence region in Northern Germany

text: This explorative monocentric study shows IgA and IgG antibody profiles from 110 patients with self-reported mild to moderate, or no COVID-19 related symptoms after laboratory-confirmed infection with SARS-CoV-2. The study region is in an urban and well-defined environment in a low-incidence region in Northern Germany. We found that approx. 70 % of the patients developed sustainable antibodies 3 weeks or later after the infection. In about 30 % of the patients with mild to moderate symptoms, no significant antibodies could be detected in two consecutive analyses. Conversely, out of ten patients without symptoms, four were repeatedly positive. Expectedly, six had no specific antibodies. The data indicate that antibody-positivity is a useful indicator of a previous SARS-CoV-2 infection. Negative antibodies do not rule out SARS-CoV-2 infection. Future studies need to determine the functionality of the antibodies in terms of personal protection and ability to transmit the virus.


title: Estimating the Growth Rate and Doubling Time for Short-Term Prediction and Monitoring Trend During the COVID-19 Pandemic with a SAS Macro

text: Coronavirus disease (COVID-19) has spread around the world and it causes tremendous stress to the US health care system. Knowing the trend of the COVID-19 pandemic is critical for the federal and local governments and health care system to prepare plans. Our aim was to develop an approach and create a SAS macro to estimate the growth rate and doubling time in days. We fit a series of growth curves using a rolling approach to estimate the growth rates and the doubling times. This approach was applied to the death data of New York State during March 14th and 31st. The growth rate was 0.48 (95% CI, 0.39-0.57) and the doubling time was 2.77 days (95% CI, 2.49-3.04) for the period of March 14th-March 20th; the growth rate decreased to 0.25 (95% CI, 0.22-0.28) and the doubling time increased to 4.09 days (95% CI, 3.73-4.44) for the period of March 25th-March 31st. This approach can be used for short-term prediction and monitoring the trend of the COVID-19 pandemic.


CT imaging of one extended family cluster of corona virus disease 2019 (COVID-19) including adolescent patients and "silent infection"


COVID-19 Prevention: Model Shows Physical Distancing Highly Effective


title: Are men dying more than women by COVID-19?

text: We aimed to clarify if the infection and death rate by COVID-19 differ among gender in the top 50 countries with the highest death rates. Also, we investigated if secondary variables such as HDI, number of hospital beds, average age, temperature, percentage of elderly, smoker and obesity are contributing to the variability observed among countries. Meta-analyses and meta-regressions approaches were applied to official public data reported by the Word Health Organization and governments until May, 2020. A random effect model was used for the meta-analysis and heterogeneity was calculated by I2 statistic. There was not significative difference between men and women to be infected by COVID-19 (P = 0.42), though a significative difference was observed for death rate (P < 0.0001). High heterogeneity was observed among countries. For both infection and death rates this variability was mainly explained by the HDI (42.3% and 54.2%), average age (40.9% and 40.3%) and temperature (30.1% and 39.3%). Man are dying more than women around the word by COVID-19. Countries with highest HDI present less difference between sexes. These results reinforce that public politics promoting social isolation, health care and general well-being of the population are key factors in combating COVID-19.


title: Trends of SARS-CoV-2 infection worldwide: Role of population density, age structure, and climate on transmission and case fatality

text: Introduction The disease transmission pattern of COVID19 is highly heterogeneous, which suggests that the pandemic maybe driven by complex factors, which may include habitat suitability, region specific human mobility, and transmission related to susceptibility. The purpose of this study was to examine the effects of different spatial and demographic factors on COVID19 transmission and case fatality worldwide. Methods We assessed SARS CoV2 virus transmission and COVID19 related fatalities in 50 countries in all continents of the globe. Data from the COVID19 data repository of the Johns Hopkins Center for Systems Science and Engineering, the European center for disease control and prevention, and the World Health Organization were used to obtain the daily number of cases and organize the incidence data. Disease spread, was assessed using the reproduction number of the disease across the sampled countries. R0 package of R statistical software was used to estimate the reproduction number of the COVID19 using the exponential growth method. After computing the reproductive number of each country in the study, a multiple linear regression model was fitted by taking the R0 value as dependent variable, and latitude and population density as an independent variable. Disease severity was analyzed using the case fatality ratio of COVID19. The proportion of deaths to the total numbers of cases was meta analyzed using metaphor package of R statistical software using random effect inverse variance weighting to come up with the case fatality ratio. Results We found no statistically significant association between disease spread and latitude or population density. The regression model analysis that accounted for age, population density and latitude showed that age distribution remains an important driver shaping the current distribution of COVID19 cases. The relative frequency of people above 65 years old was positively correlated with the cumulative numbers of COVID19 cases as well as case fatality ratio in each country. The multiple linear regression model fitted between CFR and the three major covariates showed that, the demographic distribution of the sampled countries is strongly associated with the case fatality ratio. An increase in the elderly population proportion by 1 percent was associated with an increase in CFR by 0.32. Correlation with proportion of populations over 65 years old is concordant with the previous findings relationship between case fatality ratio and patient age. Conclusion This analysis provides important information that can inform the decisions of local and global health authorities. Particularly, as our study confirms that death and severity of COVID19 are associated with age, in countries with the biggest outbreaks, strategies must be employed to ensure that high risk groups, such as old people received adequate protection from COVID19.


title: Coronavirus PPE: a positive pressure hood assembled from ubiquitous,low-cost materials

text: A positive pressure protective hood system was purposefully constructed only from materials commonly found worldwide, including bendable aluminum mesh, elastic head straps, velcro tape, a plastic sheet, a furnace filter and two computer central processing unit (CPU) cooling fans. The practical advantages of this system are that the materials are readily available in the inventories of most electronics and hardware outlets, ease of assembly (particularly if choosing to employ 3D printing for the fan enclosure and/or making several units at once with a defined workflow), and high probability of the materials being available in current or prospective personal protective equipment (PPE)-deplete regions. An experiment with identical fire detectors showed adequate inner isolation of the hood prototype from paper combustion particulates, which have a size range slightly smaller than putative coronavirus aerosols, for at least 90 seconds. The theoretical advantages of this system include significant reduction in healthcare provider exposure to coronavirus-containing respiratory fomites, respiratory droplets and aerosols (vs. traditional static masks and shields) during high risk procedures such as endotracheal intubation or routine care of an upright and coughing patient. Additionally, the assembly eliminates contact exposure to coronavirus fomites due to whole-head coverage from a hood system.


title: AI-assisted CT imaging analysis for COVID-19 screening: Building and deploying a medical AI system in four weeks

text: The sudden outbreak of novel coronavirus 2019 (COVID-19) increased the diagnostic burden of radiologists. In the time of an epidemic crisis, we hoped artificial intelligence (AI) to help reduce physician workload in regions with the outbreak, and improve the diagnosis accuracy for physicians before they could acquire enough experience with the new disease. Here, we present our experience in building and deploying an AI system that automatically analyzes CT images to detect COVID-19 pneumonia features. Different from conventional medical AI, we were dealing with an epidemic crisis. Working in an interdisciplinary team of over 30 people with medical and / or AI background, geographically distributed in Beijing and Wuhan, we were able to overcome a series of challenges in this particular situation and deploy the system in four weeks. Using 1,136 training cases (723 positives for COVID-19) from five hospitals, we were able to achieve a sensitivity of 0.974 and specificity of 0.922 on the test dataset, which included a variety of pulmonary diseases. Besides, the system automatically highlighted all lesion regions for faster examination. As of today, we have deployed the system in 16 hospitals, and it is performing over 1,300 screenings per day.


title: Fit-for-purpose urban wastewater reuse: Analysis of issues and available technologies for sustainable multiple barrier approaches

text: A selective approach for multiple wastewater recovery is nowadays desirable and technologically feasible, to provide water at specific quality standards for each reuse objective. This “fit-for-purpose” approach to water reuse could both save water and would reduce production cost and energy demand by eliminating unnecessary treatment and long-range conveyance, as it typically aims at local reuses. The appropriate choice of technologies for such approaches is perhaps the most critical planning and design decision when evaluating systems for implementation or refurbishing. This article examines wastewater reuse goals (direct potable use, indirect potable use, non-potable uses and industrial uses) and related requirements as relevant case studies, and issues that may arise during implementation. It then proposes an overview of current conventional and advanced technologies and their possible combination to meet foreseen uses under a multiple barrier treatment (MBT) approach, which implies a sequence of complementary processes at an increasing level of protection for both conventional and emerging pollutants according to reuse goals. (Figure presented.).


title: Incidence and risk factors of kidney impairment on patients with COVID-19: a systematic review and meta-analysis

text: Background: The novel coronavirus is pandemic around the world. Several researchers have given the evidence of impacts of COVID-19 on the respiratory, cardiovascular and gastrointestinal system. Studies still have debated on kidney injury of COVID-19 patients. The purpose of the meta-analysis was to evaluate the association of kidney impairment with the development of COVID-19. Methods: The PubMed, Embase and MedRxiv databases were searched until April 1, 2020. We extracted data from eligible studies to summarize the clinical manifestations and laboratory indexes of kidney injury on COVID-19 infection patients and further compared the prevalence of acute kidney injury (AKI) and the mean differences of three biomarkers between in ICU/severe and non-ICU/non-severe cases. Heterogeneity was evaluated using the I2 method. Results: In the sum of 19 studies with 4375 patients were included in this analysis. The pooled prevalence of AKI, increased serum creatinine (Scr), increased blood urea nitrogen (BUN), increased D-dimer, proteinuria and hematuria in patients with COVID-19 were 7.7%, 6.6%, 6.2%, 49.8%, 42% and 30.3% respectively. Moreover, the means of Scr, BUN and D-dimer were shown 6-folds, 1.8-folds and 0.68-folds, respectively, higher in ICU/severe cases than in corresponding non-ICU/non-severe patients. The prevalence of AKI was about 17 folds higher in ICU/severe patients compared with the non-ICU/non-severe cases. Conclusions: Overall, we assessed the incidences of the clinic and laboratory features of kidney injury in COVID-19 patients. And kidney dysfunction may be a risk factor for COVID-19 patients developing into the severe condition. In reverse, COVID-19 can also cause damage to the kidney.


title: ‘It’s heartbreaking.’ Labs are euthanizing thousands of mice in response to coronavirus pandemic

text: Faced with her lab’s imminent closure, Sunny Shin had already begun to fear she would have to euthanize large numbers of the mice she works on Then, last Tuesday, the email came from her school’s vice provost of research “In response to the public health crisis caused by COVID-19,” it read, “mouse/rodent users should cull their colonies as much as possible ”


title: Demand for hospitalization services for COVID-19 patients in Brazil

text: COVID-19 is now a pandemic and many of the affected countries face severe shortages of hospital resources. In Brazil, the first case was reported on February 26. As the number of cases grows in the country, there is a concern that the health system may become overwhelmed, resulting in shortages of hospital beds, intensive care unit beds, and mechanical ventilators. The timing of shortage is likely to vary geographically depending on the observed onset and pace of transmission observed, on the availability of resources, and on the actions implemented. Here we consider the daily number of cases reported in municipalities in Brazil to simulate twelve alternative scenarios of the likely timing of shortage, based on parameters consistently reported for China and Italy, on rates of hospital occupancy for other health conditions observed in Brazil in 2019, and on assumptions of allocation of patients in public and private facilities. Results show that hospital services could start to experience shortages of hospital beds, ICU beds, and ventilators in early April, the most critical situation observed for ICU beds. Increasing the allocation of beds for COVID-19 (in lieu of other conditions) or temporarily placing all resources under the administration of the state delays the anticipated start of shortages by a week. This suggests that solutions adopted by the Brazilian government must aim at expanding the available capacity (e.g., makeshift hospitals), and not simply prioritizing the allocation of available resources to COVID-19.


title: The COVID-19 pandemic and its impact on mental health

text: Similarities exist between our past experience of viral diseases and COVID-19 concerning the mental health issues of sufferers of an epidemic, frontline health workers and the social and psychological impact on society. There is significant evidence that a novel illness such as COVID-19 can cause widespread fear, panic, anxiety and xenophobia. Dr Chakraborty explores the latest literature and what it means for mental health.


title: China's fight against COVID-19: What we have done and what we should do next?

text: Background: On 12 March, the World Health Organization Director-General declared that "the threat of a global pandemic has become a reality", and the disease caused by the novel coronavirus, known as COVID-19, has become a global concern. Chinese efforts in curbing the virus have widely been recognized. Even the WHO has lauded the efforts of the Chinese government and advised the world to learn from China in fighting the disease. Since the outbreak of COVID-19, to curb the spread of the epidemic, the Chinese government has implemented unprecedented prevention interventions at the nationwide level. Currently, the outbreak in Wuhan is changing in a positive direction and has been effectively controlled. However, it is not clear what these measures were and how these measures changed to curb the outbreak of COVID-19 quickly. This study explored the characteristics and identified that China's control strategies have changed the epidemiological curve of rapidly rising new confirmed cases of COVID-19. This study also seeks to expand the experiences and lessons from this outbreak. Methods: We collected public health interventions measures from Jan 20, 2020, to 5 March 2020, and data from COVID-19 daily newly confirmed cases and daily cumulates cases to compare the control effects and changing trends. We performed a retrospective description of these intervention strategies from three stages. Besides, from the perspective of public health, the experiences and lessons exposed by this outbreak were roughly summarized. Results: These non-pharmacology interventions measures adopted by the Chinese government by the instruction and spirit of President Xi Jinping were timely and efficient. Conclusions: The present study was conducted to comprehensively analyze from a social epidemiology context. The results confirmed that these radical interventions taken by the Chinese government were effective, ambitious, and agile. However, we must be aware that the epidemic situation in Wuhan is still challenging. Keywords: China; COVID-19; intervention measures; change features, lessons


title: A minimal and adaptive prediction strategy for critical resource planning in a pandemic

text: Current epidemiological models can in principle model the temporal evolution of a pandemic. However, any such model will rely on parameters that are unknown, which in practice are estimated using stochastic and poorly measured quantities. As a result, an early prediction of the long-term evolution of a pandemic will quickly lose relevance, while a late model will be too late to be useful for disaster management. Unless a model is designed to be adaptive, it is bound either to lose relevance over time, or lose trust and thus not have a second-chance for retraining. We propose a strategy for estimating the number of infections and the number of deaths, that does away with time-series modeling, and instead makes use of a 'phase portrait approach'. We demonstrate that, with this approach, there is a universality to the evolution of the disease across countries, that can then be usedto make reliable predictions. These same models can also be used to plan the requirements for critical resources during the pandemic. The approach is designed for simplicity of interpretation, and adaptivity over time. Using our model, we predict the number of infections and deaths in Italy and New York State, based on an adaptive algorithm which uses early available data, and show that our predictions closely match the actual outcomes. We also carry out a similar exercise for India, where in addition to projecting the number of infections and deaths, we also project the expected range of critical resource requirements for hospitalizations in a location.


title: Excess mortality during COVID-19 in five European countries and a critique of mortality analysis data

text: INTRODUCTION The COVID-19 pandemic is an ongoing event disrupting lives, health systems, and economies worldwide. Clear data about the pandemic's impact is lacking, namely regarding mortality. This work aims to study the impact of COVID-19 through the analysis of all-cause mortality data made available by different European countries, and to critique their mortality surveillance data. METHODS European countries that had publicly available data about the number of deaths per day/week were selected (England and Wales, France, Italy, Netherlands and Portugal). Two different methods were selected to estimate the excess mortality due to COVID19: (DEV) deviation from the expected value from homologue periods, and (RSTS) remainder after seasonal time series decomposition. We estimate total, age- and gender-specific excess mortality. Furthermore, we compare different policy responses to COVID-19. RESULTS Excess mortality was found in all 5 countries, ranging from 10.6% in Portugal (DEV) to 98.5% in Italy (DEV). Furthermore, excess mortality is higher than COVID-attributed deaths in all 5 countries. DISCUSSION The impact of COVID-19 on mortality appears to be larger than officially attributed deaths, in varying degrees in different countries. Comparisons between countries would be useful, but large disparities in mortality surveillance data could not be overcome. Unreliable data, and even a lack of cause-specific mortality data undermine the understanding of the impact of policy choices on both direct and indirect deaths during COVID-19. European countries should invest more on mortality surveillance systems to improve the publicly available data.


title: Can herd immunity be achieved without breaking ICUs?

text: The current COVID-19 pandemic led to the rapid overload of Intensive Care Units (ICUs) in countries where the outbreaks was not quickly controlled. The containment measures put in place to control the outbreaks had a huge social and economic impacts, and countries are looking for strategies to relax these measures while maintaining the R_0 close or below 1, in an attempt to safely reach herd immunity. In this paper we analyse the feasibility of reaching herd immunity without saturating ICUs across countries. We provide an online tool, available at www.about-the-curve.net that simulates the time required for such a scenario with a SIR model. For United States, we find that a minimum of 5 months would be required, 22 months for UK, 1 year for Italy and 9 months for Belgium.


title: Proteome Organization of COVID-19: Illustrating Targets for Vaccine Development

text: 'COVID-19' the recent virulent viral infection had influenced the lives of millions globally leading to both loss of life, economic and financial crisis Coronavirus belongs to family coronaviridae with four genus viz alpha/beta and gamma-coronavirus, infecting both aves and mammals The SARS-Cov-2 emerged in Wuhan, China in Dec, 2019 and since then had spread to 213 countries Its origin is debatable with both natural origin and conspiracy theory providing no conclusive evidences Coronavirus have '+'ive RNA and encodes for 29 proteins, which carries out its life cycle including infection and disease progression The study of its proteome organization could illustrate the proteins which act as the key molecular players in the infection cycle of the virus These proteins can also act as important drug targets in combating COVID-19 infection Majority of the drugs have been formulated in order to act as agonist to spike proteins inhibiting infection by binding to ACE2 receptors Proteome analysis has also revealed the critical mutated proteins that are responsible for COVID-19 pathogenesis and virulence mRNA based vaccines (mRNA-1273, BNT162) also targets these spike proteins Although DNA vaccine has also been attempted using RDT, but the high rate of mutation associated with COVID-19 have made such vaccines ineffective even before use Thus evolutionarily conserved proteins have been the best candidature for vaccine development Similarly phylogenetic analysis of its proteins could help us to understand the evolutionary pattern of COVID-19 It could be used to develop a predictable model for such pathogenic infections, preparing ourselves to take preventive action against its reoccurrence


Call for international cooperation and collaboration to effectively tackle the COVID-19 pandemic


title: Empowering Virus Sequences Research through Conceptual Modeling

text: The pandemic outbreak of the coronavirus disease has attracted attention towards the genetic mechanisms of viruses. We hereby present the Viral Conceptual Model (VCM), centered on the virus sequence and described from four perspectives: biological (virus type and hosts/sample), analytical (annotations and variants), organizational (sequencing project) and technical (experimental technology). VCM is inspired by GCM, our previously developed Genomic Conceptual Model, but it introduces many novel concepts, as viral sequences significantly differ from human genomes. When applied to SARS-CoV2 virus, complex conceptual queries upon VCM are able to replicate the search results of recent articles, hence demonstrating huge potential in supporting virology research. In addition to VCM, we also illustrate the data dictionary for patient’s phenotype used by the COVID-19 Host Genetic Initiative. Our effort is part of a broad vision: availability of conceptual models for both human genomics and viruses will provide important opportunities for research, especially if interconnected by the same human being, playing the role of virus host as well as provider of genomic and phenotype information.