title: Modelling the COVID-19 epidemics in Brasil: Parametric identification and public health measures influence

text: A SIRU-type epidemic model is proposed for the prediction of COVID-19 spreading within Brasil, and analyse the influence of public health measures on simulating the control of this infectious disease. Since the reported cases are typically only a fraction of the total number of the symptomatic infectious individuals, the model accounts for both reported and unreported cases. Also, the model allows for the time variation of both the transmission rate and the fraction of asymptomatic infectious that become reported symptomatic individuals, so as to reflect public health interventions, towards its control, along the course of the epidemic evolution. An analytical exponential behaviour for the accumulated reported cases evolution is assumed at the onset of the epidemy, for explicitly estimating initial conditions, while a Bayesian inference approach is adopted for parametric estimations employing the present direct problem model with the data from the known portion of the epidemics evolution, represented by the time series for the reported cases of infected individuals. The direct-inverse problem analysis is then employed with the actual data from China, with the first half been employed for the parametric estimation and the second half for validation of the predictive capability of the proposed approach. The full dataset for China is then employed in another parameter identification, including the average times that asymptomatic infectious individuals and that symptomatic individuals are infectious. Following this validation, the available data on reported cases in Brasil from February 15th till March 29th, 2020, is used for estimating parameters and then predict the epidemy evolution under these conditions. Finally, public health interventions are simulated, aimed at diminishing the effects of the disease spreading, by acting on both the transmission rate and the fraction of the total number of the symptomatic infectious individuals, considering time variable exponential behaviours for these two parameters, usually assumed constant in epidemic evolutions without intervention. It is demonstrated that a combination of actions to affect both parameters can have a much faster and effective result in the control of the epidemy dynamics.


title: Monitoring 2011-2020 traffic patterns in Wuhan (China) with COSMO-SkyMed SAR, amidst the 7th CISM military world games and COVID-19 outbreak

text: Vehicle detection from satellite imagery can support different applications, such as security and situational awareness. In the civilian domain, it can provide quantitative evidence to investigate urban mobility and traffic patterns in cities. Satellite synthetic aperture radar (SAR) can help in detecting vehicles in (almost) all weather conditions and during the day and night. In this study, the capability of SAR StripMap imaging mode data to monitor traffic is analyzed using the case study of Wuhan, China. In ordinary times, the bridges crossing the Yangtze river are the key infrastructure allowing for urban mobility inWuhan. More recently, the city has been the first in the world to be put in lockdown due to the outbreak of the Coronavirus Disease of 2019 (COVID-19). Using a very long time series of 294 COSMO-SkyMed StripMap HIMAGE mode scenes collected from 2011 to 2020, we detected vehicles on seven bridges, estimated their speed, and analyzed the traffic pattern over time. Vehicles are detected based on their azimuth shift caused by their across-track motion. Our goal is to monitor the variations in traffic instead of single-car detection. The results from 2011 to 2019 show a general increase in the number of vehicles crossing the bridges, as new infrastructure was built over the years. Variations in detected vehicle numbers were especially found during the two events of the 7th International Military Sports Council (CISM) Military World Games in October 2019, and the COVID-19 lockdown in early 2020. These events were therefore used for internal validation of our assessment of traffic patterns. On the other side, TomTom traffic index data were used for external validation. The results and their comparison with TomTom data prove the effectiveness of our method in detecting traffic patterns, but also demonstrate that mostly large vehicles (e.g., trucks or buses) are detected. Future work should be carried out to improve the detection rate of smaller vehicles.


Grief and new creation: Theopoetics for a pandemic


title: Heparin therapy improving hypoxia in COVID-19 patients - a case series

text: Elevated D-dimer and other markers of coagulation disturbances are predictors of severity and mortality in COVID-19 patients and heparin use during hospital stay has been associated to a decreased mortality. Similar findings have been described in other coronaviruses. COVID-19 patient autopsies have revealed thrombi in the microvasculature, suggesting intravascular coagulation as a prominent feature of organ failure and of the acro-ischaemia increasingly reported in these patients. In COVID-19 pulmonary compliance is preserved despite severe hypoxemia, contrarily to classic ARDS, corroborating the hypothesis that perfusion mismatch may play a significant role in the development of respiratory failure in these patients. Based on this rationale, a series of 27 consecutive COVID-19 patients admitted to our hospital were treated with heparin in doses tailored to clinical severity, ranging from 1 - 2 mg/kg of enoxaparin BD. PaO2/FiO2 ratio increased significantly over the 72 hours following the start of anticoagulation, from 254(SD 90) to 325(SD 80), p=0.013, and over half of the patients were discharged home within an average time of 7.3 (SD 4.0) days. Half of mechanically ventilated patients were extubated within 10.3 (SD 1.5) days. The remaining patients showed progressive, albeit slower improvement, and both the mortality and the bleeding complications rate in these patients were absent. Even though this uncontrolled case series does not offer absolute proof of DIC as the underlying mechanism of respiratory failure in COVID-19, as well as patients positive response to tailored dose heparinization, it contributes to the understanding of the physiopathological mechanism of the disease and provides valuable information for the treatment of these very sick patients while we await the results of further prospective controlled studies.


title: Exploration on mechanism of anti-coronavirus of Sophora flavescens through multi-pathway/ 苦参多路径抗冠状病毒的机制探究

text: The coronavirus disease 2019 (COVID-19), originated in Wuhan city, Hubei Province, China in December 2019, and then quickly spread to most provinces and regions in China and even spread to many countries abroad. COVID-19 is characterized by wide epidemic, strong infectivity, rapid onset and critical condition. In the face of this epidemic, all parts of the country quickly set off a peak in the fight against COVID-19, but no effective drug for COVID-19 has been developed in the short term. Recently, many hospitals have combined traditional Chinese medicine with western medicine in treatment, and the clinical effect is remarkable, which proves the antiviral effect of traditional Chinese medicine. A large number of pharmacological and clinical studies have proved that the Chinese materia medica S. flavescens has significant antiviral effect. In this paper, the mechanism of anti-coronavirus effect of S. flavescens is expounded from multiple pathways, such as type I interferon, NF-κB signal pathway, ERK signal pathway, PI3K/Akt signal pathway and matrine alkaloids, etc. It is intended to provide reference for clinical treatment of coronavirus infection pneumonia and research and development of related drugs of S. flavescens.


title: Breastfeeding of Infants Born to Mothers with COVID-19: A Rapid Review

text: Abstract Background: Existing recommendations on whether mothers with COVID-19 should continue breastfeeding are still conflicting. We aimed to conduct a rapid review of mother-to-child transmission of COVID-19 during breastfeeding. Methods: We systematically searched Medline, Embase, Web of Science, Cochrane library, China Biology Medicine disc, China National Knowledge Infrastructure, Wanfang, and preprint articles up to March 2020. We included studies relevant to transmission through milk and respiratory droplets during breastfeeding of mothers with COVID-19, SARS, MERS and influenza. Two reviewers independently screened studies for eligibility, extracted data, assessed risk of bias and used GRADE to assess certainty of evidence. Results: A total of 4481 records were identified in our literature search. Six studies (five case reports and one case series) involving 58 mothers (16 mothers with COVID-19, 42 mothers with influenza) and their infants proved eligible. Five case reports showed that the viral nucleic acid tests for all thirteen collected samples of breast milk from mothers with COVID-19 were negative. A case series of 42 influenza infected postpartum mothers taking precautions (hand hygiene and wearing masks) before breastfeeding showed that no neonates were infected with influenza during one-month of follow-up. Conclusions: The current evidence indicates that SARS-CoV-2 viral nucleic acid has not been detected in breast milk. The benefits of breastfeeding may outweigh the risk of SARS-CoV-2 infection in infants. Mothers with COVID-19 should take appropriate precautions to reduce the risk of transmission via droplets and close contact during breastfeeding. Keywords: Breastfeeding; COVID-19; infant; mother-to-child transmission; rapid Review.


title: PathoLive – Real-time pathogen identification from metagenomic Illumina datasets

text: Motivation Over the past years, NGS has become a crucial workhorse for open-view pathogen diagnostics. Yet, long turnaround times result from using massively parallel high-throughput technologies as the analysis can only be performed after sequencing has finished. The interpretation of results can further be challenged by contaminations, clinically irrelevant sequences, and the sheer amount and complexity of the data. Results We implemented PathoLive, a real-time diagnostics pipeline for the detection of pathogens from clinical samples hours before sequencing has finished. Based on real-time alignment with HiL-ive2, mappings are scored with respect to common contaminations, low-entropy areas, and sequences of widespread, non-pathogenic organisms. The results are visualized using an interactive taxonomic tree that provides an easily interpretable overview of the relevance of hits. For a human plasma sample that was spiked in vitro with six pathogenic viruses, all agents were clearly detected after only 40 of 200 sequencing cycles. For a real-world sample from Sudan the results correctly indicated the presence of Crimean-Congo hemorrhagic Fever Virus. In a second real-world dataset from the 2019 SARS-CoV-2 outbreak in Wuhan, we found the presence of a SARS Coronavirus as the most relevant hit without the novel virus reference genome being included in the database. For all samples, clinically irrelevant hits were correctly de-emphasized. Our approach is valuable to obtain fast and accurate NGS-based pathogen identifications and correctly prioritize and visualize them based on their clinical significance. Availability PathoLive is open source and available on GitLab (https://gitlab.com/rkibioinformatics/PathoLive) and BioConda (conda install –c bioconda patholive). Contact Bernhard.Renard@hpi.de, NitscheA@rki.de


title: COVID-19 Infection Forecasting based on Deep Learning in Iran

text: Since December 2019 coronavirus disease (COVID-19) is outbreak from China and infected more than 4,666,000 people and caused thousands of deaths. Unfortunately, the infection numbers and deaths are still increasing rapidly which has put the world on the catastrophic abyss edge. Application of artificial intelligence and spatiotemporal distribution techniques can play a key role to infection forecasting in national and province levels in many countries. As methodology, the presented study employs long short-term memory-based deep for time series forecasting, the confirmed cases in both national and province levels, in Iran. The data were collected from February 19, to March 22, 2020 in provincial level and from February 19, to May 13, 2020 in national level by nationally recognised sources. For justification, we use the recurrent neural network, seasonal autoregressive integrated moving average, Holt winter's exponential smoothing, and moving averages approaches. Furthermore, the mean absolute error, mean squared error, and mean absolute percentage error metrics are used as evaluation factors with associate the trend analysis. The results of our experiments show that the LSTM model is performed better than the other methods on the collected COVID-19 dataset in Iran


title: High-resolution influenza mapping of a city reveals socioeconomic determinants of transmission within and between urban quarters

text: With two-thirds of the global population projected to be living in urban areas by 2050, understanding the transmission patterns of viral pathogens within cities is crucial for effective prevention strategies. Here, in unprecedented spatial resolution, we analysed the socioeconomic determinants of influenza transmission in a European city. We combined geographical and epidemiological data with whole genome sequencing of influenza viruses at the scale of urban quarters and statistical blocks, the smallest geographic subdivisions within a city. We observed annually re-occurring geographic clusters of influenza incidences, mainly associated with net income, and independent of population density and living space. Vaccination against influenza was also mainly associated with household income and was linked to the likelihood of influenza-like illness within an urban quarter. Transmissions patterns within and between quarters were complex. High-resolution city-level epidemiological studies combined with social science surveys such as this will be essential for understanding seasonal and pandemic transmission chains and delivering tailored public health information and vaccination programs at the municipal level.


title: ProtTrans: Towards Cracking the Language of Life’s Code Through Self-Supervised Deep Learning and High Performance Computing

text: Motivation Natural Language Processing (NLP) continues improving substantially through auto-regressive (AR) and auto-encoding (AE) Language Models (LMs). These LMs require expensive computing resources for self-supervised or un-supervised learning from huge unlabelled text corpora. The information learned is transferred through so-called embeddings to downstream prediction tasks. Computational biology and bioinformatics provide vast gold-mines of structured and sequentially ordered text data leading to extraordinarily successful protein sequence LMs that promise new frontiers for generative and predictive tasks at low inference cost. As recent NLP advances link corpus size to model size and accuracy, we addressed two questions: (1) To which extent can High-Performance Computing (HPC) up-scale protein LMs to larger databases and larger models? (2) To which extent can LMs extract features from single proteins to get closer to the performance of methods using evolutionary information? Methodology Here, we trained two auto-regressive language models (Transformer-XL and XLNet) and two auto-encoder models (BERT and Albert) on 80 billion amino acids from 200 million protein sequences (UniRef100) and one language model (Transformer-XL) on 393 billion amino acids from 2.1 billion protein sequences taken from the Big Fat Database (BFD), today’s largest set of protein sequences (corresponding to 22- and 112-times, respectively of the entire English Wikipedia). The LMs were trained on the Summit supercomputer, using 936 nodes with 6 GPUs each (in total 5616 GPUs) and one TPU Pod, using V3-512 cores. Results We validated the feasibility of training big LMs on proteins and the advantage of up-scaling LMs to larger models supported by more data. The latter was assessed by predicting secondary structure in three- and eight-states (Q3=75- 83, Q8=63-72), localization for 10 cellular compartments (Q10=74) and whether a Preprint. Under review. protein is membrane-bound or water-soluble (Q2=89). Dimensionality reduction revealed that the LM-embeddings from unlabelled data (only protein sequences) captured important biophysical properties of the protein alphabet, namely the amino acids, and their well orchestrated interplay in governing the shape of proteins. In the analogy of NLP, this implied having learned some of the grammar of the language of life realized in protein sequences. The successful up-scaling of protein LMs through HPC slightly reduced the gap between models trained on evolutionary information and LMs. Additionally, our results highlighted the importance of bi-directionality when processing proteins as the uni-directional TransformerXL was outperformed by its bi-directional counterparts.


title: The Coronavirus Pandemic and Europe's Undeclared Economy: Impacts and a Policy Proposal

text: The coronavirus pandemic has led to a loss of revenues for enterprises and workers due to workplace closures and restrictions on movement to 'flatten the curve' In response, governments have made available temporary financial support to enterprises and workers affected This paper evaluates a group currently excluded from this support, namely enterprises and workers in the undeclared economy, and a possible government policy response To identify those involved, a 2019 Eurobarometer survey of undeclared work in Europe is reported This reveals that one in every 132 European citizens relies wholly on undeclared earnings and the sectors and population groups involved Given their reduced revenues and inability to access the temporary financial support, a voluntary disclosure initiative is recommended which brings undeclared enterprises and workers into the declared economy and onto the radar of state authorities by offering access to this temporary financial support if they disclose their previous undeclared work


title: The need of health policy perspective to protect Healthcare Workers during COVID-19 pandemic. A GRADE rapid review on the N95 respirators effectiveness.

text: Background Protecting Health Care Workers (HCWs) during routine care of suspected or confirmed COVID-19 patients is of paramount importance to halt the SARS-CoV-2 (Severe Acute Respiratory Syndrome-Coronavirus-2) pandemic. The WHO, ECDC and CDC have issued conflicting guidelines on the use of respiratory filters (N95) by HCWs. Methods We searched PubMed, Embase and The Cochrane Library from the inception to March 21, 2020 to identify randomized controlled trials (RCTs) comparing N95 respirators versus surgical masks for prevention of COVID-19 or any other respiratory infection among HCWs. The grading of recommendations, assessment, development, and evaluation (GRADE) was used to evaluate the quality of evidence. Findings Four RCTs involving 8736 HCWs were included. We did not find any trial specifically on prevention of COVID-19. However, wearing N95 respirators can prevent 73 more (95% CI 46-91) clinical respiratory infections per 1000 HCWs compared to surgical masks (2 RCTs; 2594 patients; low quality of evidence). A protective effect of N95 respirators in laboratory-confirmed bacterial colonization (RR= 0.41; 95%CI 0.28-0.61) was also found. A trend in favour of N95 respirators was observed in preventing laboratory-confirmed respiratory viral infections, laboratory-confirmed respiratory infection, and influenza like illness. Interpretation We found no direct high quality evidence on whether N95 respirators are better than surgical masks for HCWs protection from SARS-CoV-2. However, low quality evidence suggests that N95 respirators protect HCWs from clinical respiratory infections. This finding should be contemplated to decide the best strategy to support the resilience of healthcare systems facing the potentially catastrophic SARS-CoV-2 pandemic.


Does COVID-19 Spread Through Droplets Alone?


title: An early assessment of the efficacy of medicines in the treatment of patients with COVID-19/ РАННЯЯ ОЦЕНКА ЭФФЕКТИВНОСТИ ЛЕКАРСТВЕННЫХ СРЕДСТВ ПРИ ЛЕЧЕНИИ БОЛЬНЫХ С COVID-19

text: Coronavirus infection 2019 is considered a modern challenge to the world community. In the absence of vaccines and antivirals, effective and safe medicines are an urgent request from the healthcare system. We have evaluated the medical technologies for COVID-19 which are being examined. The search was conducted on the СlinicalTrials.gov at the beginning of April 2020. As a result it was shown that the growth of new clinical trials in the world devoted to COVID-19 is growing by 65% per week. More often, interventional clinical trials of the II and III phases are carried out. Most studies are planned or conducted in Western Europe (n = 92), China (n = 79), and the United States (n = 51). Surrogate points are usually evaluated, such as: clinical recovery, symptom-based disease relief (fever, cough, diarrhea, myalgia, shortness of breath), lack of progression of shortness of breath, rate of artificial ventilation, rate of admission to the intensive care unit, etc. It is antimalarial drugs that are mainly studied. Currently, it is not possible to discuss the efficacy and safety of a drug in the treatment of COVID-19, as most studies have just begun. The therapeutic regimens proposed now in clinical recommendations have no evidence base, and the studies indicated in them are at best considered hypothesizing.


title: Alpha 1 Antitrypsin is an Inhibitor of the SARS-CoV2–Priming Protease TMPRSS2

text: The transmembrane serine protease TMPRSS2 is indispensable for S protein priming of the MERS, SARS-CoV, and SARS-CoV2 coronaviruses, a process that is necessary for entry of the virus into host cells. Therefore, inhibiting TMPRSS2 holds promise as an approach toward preventing transmission of coronaviruses. Herein, we developed an in vitro system to measure TMPRSS2 activity and tested the inhibition of TMPRSS2 by several synthetic and natural protease inhibitors. Camostat mesylate and bromhexine hydrochloride (BHH) inhibited TMPRSS2 proteolytic function. In addition, we identified the small molecule 4-(2-aminomethyl)benzenesulfonyl fluoride (AEBSF) and the human, anti-inflammatory protein alpha 1 antitrypsin (A1AT) as inhibitors of TMPRSS2. AEBSF and A1AT inhibited TMPRSS2 activity in a dose-dependent manner. AEBSF and A1AT inhibited TMPRSS2 in the same range of concentrations (100-0.1 μM). We suggest that treatment with these inhibitors, particularly A1AT, which is an FDA-approved drug, might be effective in limiting SARS-CoV and SARS-CoV2 transmissibility and as a COVID-19 treatment.


title: Potential Barriers amongst Health Care Professionals of Pakistan in managing COVID-19 patients

text: OBJECTIVES: To evaluate basic knowledge of Health Care Professionals (HCPs) of Pakistan in managing COVID 19 patients. It includes information regarding infection control measures, administrative and professional support. This was followed by evaluation of psychological factor that can act as a barrier in effective management of these patients. METHODS: The survey was conducted on line using Google Form. After approval from hospital ethical committee survey link was disseminated to HCPs using social media. RESULTS: Four hundred fifteen HCPs were participated. Most of them were younger than 30 years and majority of them were postgraduate trainees. Results showed gaps in the knowledge about basic infection control measure like donning/doffing and understanding about high-risk procedures. On job training, professional and administrative support is compromising. Many of HCPs are anxious nowadays, having symptoms related to burn out with logical reasons behind. Even with all those hurdles they are committed and ready to volunteer themselves. CONCLUSION: The HCPs of Pakistan needs urgent attention for providing them Formal training regarding infection control measure. Administrative and professional support is required from institutions and scientific societies. Online teaching modules and webinar is a suitable option. The symptoms of burn out are significant and would increase with passage of time. This needs to be supported by occupational health committees.


The implications of COVID-19 for the children of Africa


title: Les représentations de la pandémie SARS-CoV-2 et du confinement dans une patientèle de psychiatrie libérale à Paris

text: Abstract A brief description of attitudes and représentations of SARS-Cov-2 pandemic among patients in a psychiatric parisian office. Collected Data suggest that the confinement’s measure has been accepted. However the end of confinement has been a time of increased anxiety for many. The representations of Covid-19 and the one of the other’s body tended to be assimilated. Some perplexity over preventive measures has been observed.


title: The spatio-temporal epidemic dynamics of COVID-19 outbreak in Africa

text: The novel coronavirus (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in the city of Wuhan, China in December 2019. Although, the disease appears on the African continent late, it has spread to virtually all the countries. We provide early spatio-temporal dynamics of COVID-19 within the first 62 days of the disease's appearance on the African continent. We used a two-parameter hurdle Poisson model to simultaneously analyze the zero counts and the frequency of occurrence. We investigate the effects of important healthcare capacities including hospital beds and number of medical doctors in the different countries. The results show that cases of the pandemic vary geographically across Africa with notable high incidence in neighboring countries particularly in West and North Africa. The burden of the disease (per 100,000) was most felt in Djibouti Tunisia, Morocco and Algeria. Temporally, during the first 4 weeks, the burden was highest in Senegal, Egypt and Mauritania, but by mid-April it shifted to Somalia, Chad, Guinea, Tanzania, Gabon, Sudan, and Zimbabwe. Currently, Namibia, Angola, South Sudan, Burundi and Uganda have the least burden. The findings could be useful in implementing epidemiological intervention and allocation of scarce resources based on heterogeneity of the disease patterns.


title: Deep Vein Thrombosis and Pulmonary Embolism: Two Complications of COVID-19 Pneumonia?

text: Coronavirus disease 19 (COVID-19) is a worldwide infection which was recently declared a global health emergency by the WHO Emergency Committee. The most common symptoms are fever and cough, which can progress to pneumonia, acute respiratory distress syndrome (ARDS) and/or end-organ failure. Risk factors associated with ARDS and death are older age, comorbidities (e.g., hypertension, diabetes, hyperlipidaemia), neutrophilia, and organ and coagulation dysfunction. Disseminated intravascular coagulation and coagulopathy can contribute to death. Anticoagulant treatment is associated with decreased mortality in severe COVID-19 pneumonia. In this report we describe two patients with COVID-19 pneumonia who developed venous thromboembolism. LEARNING POINTS: Deep vein thrombosis and pulmonary embolism can occur in patients with COVID-19 pneumonia. Low-molecular-weight heparin prophylaxis does not decrease the risk of venous thromboembolism (VTE) in COVID-19 pneumonia. In the presence of clinical signs and/or suspicion of VTE, compression ultrasound and echocardiography should be always performed, irrespective of disease stage.


title: Seroprevalence of SARS-CoV-2 in Hong Kong and in residents evacuated from Hubei province, China: a multicohort study

text: Summary Background The role of subclinical severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in perpetuating the COVID-19 pandemic is unknown because population seroprevalence data are absent We aimed to establish the sensitivity and specificity of our enzyme immunoassay and microneutralisation assay, and the seroprevalence of SARS-CoV-2 in Hong Kong before and after the pandemic, as well as in Hong Kong residents evacuated from Hubei province, China Methods We did a multicohort study in a hospital and university in Hong Kong We evaluated the sensitivity of our enzyme immunoassay and microneutralisation assay with RT-PCR data from patients positive for SARS-CoV-2 and the specificity of our enzyme immunoassay and microneutralisation assay with archived serum samples collected before 2019 We compared the seropositivity of the general population of Hong Kong before and after the pandemic had begun, and determined the seropositivity of Hong Kong residents evacuated from Hubei province, China, in March, 2020 Findings Between Feb 26 and March 18, 2020, we assessed RT-PCR samples from 45 patients who had recovered from COVID-19 to establish the sensitivity of our enzyme immunoassay and microneutralisation assay To establish the specificity of these assays, we retrieved archived serum The sensitivity was 91·1% (41 of 45 [95% CI 78·8–97·5]) for the microneutralisation assay, 57·8% (26 of 45 [42·2–72·3]) for anti-nucleoprotein IgG, 66·7% (30 of 45 [51·1–80·0]) for anti-spike protein receptor binding domain (RBD) IgG, and 73·3% (33 of 45 [58·1–85·4]) for enzyme immunoassay (either positive for anti-nucleoprotein or anti-RBD IgG) The specificity was 100% (152 of 152 [95% CI 97·6–100·0]) for both the enzyme immunoassay and microneutralisation assay Among the Hong Kong general population, 53 (2·7%) of 1938 were enzyme immunoassay positive, but of those who were positive, all 53 were microneutralisation negative, and no significant increase was seen in the seroprevalence between April 12, 2018, and Feb 13, 2020 Among asymptomatic Hubei returnees, 17 (4%) of 452 were seropositive with the enzyme immunoassay or the microneutralisation assay, with 15 (88%) of 17 seropositive with the microneutralisation assay, and two familial clusters were identified Interpretation Our serological data suggest that SARS-CoV-2 is a new emerging virus The seropositivity rate in Hubei returnees indicates that RT-PCR-confirmed patients only represent a small proportion of the total number of cases The low seroprevalence suggests that most of the Hong Kong and Hubei population remain susceptible to COVID-19 Future waves of the outbreak are inevitable without a vaccine or antiviral prophylaxis The role of age-related cross reactive non-neutralising antibodies in the pathogenesis of COVID-19 warrants further investigation Funding Richard and Carol Yu, May Tam Mak Mei Yin, Shaw Foundation (Hong Kong), Michael Tong, Marina Lee, and the Government Consultancy Service (see acknowledgments for full list)


title: Synergistic effects of anionic surfactants on coronavirus (SARS-CoV-2) virucidal efficiency of sanitizing fluids to fight COVID-19

text: Our surrounding environment, especially often-touched contaminated surfaces, plays an important role in the transmission of pathogens in society. The shortage of effective sanitizing fluids, however, became a global challenge quickly after the coronavirus disease-19 (COVID-19) outbreak in December 2019. In this study, we present the effect of surfactants on coronavirus (SARS-CoV-2) virucidal efficiency in sanitizing fluids. Sodium dodecylbenzenesulfonate (SDBS), sodium laureth sulfate (SLS), and two commercial dish soap and liquid hand soap were studied with the goal of evaporation rate reduction in sanitizing liquids to maximize surface contact time. Twelve fluids with different recipes composed of ethanol, isopropanol, SDBS, SLS, glycerin, and water of standardized hardness (WSH) were tested for their evaporation time and virucidal efficiency. Evaporation time increased by 17-63% when surfactant agents were added to the liquid. In addition, surfactant incorporation enhanced the virucidal efficiency between 15-27% according to the 4-field test in the EN 16615:2015 European Standard method. Most importantly, however, we found that surfactant addition provides a synergistic effect with alcohols to inactivate the SARS-CoV-2 virus. This study provides a simple, yet effective solution to improve the virucidal efficiency of commonly used sanitizers.


title: Energetics based epitope screening in SARS CoV-2 (COVID 19) spike glycoprotein by Immuno-informatic analysis aiming to a suitable vaccine development

text: The recent outbreak by SARS-CoV-2 has generated a chaos in global health and economy and claimed/infected a large number of lives. Closely resembling with SARS CoV, the present strain has manifested exceptionally higher degree of spreadability, virulence and stability possibly due to some unidentified mutations. The viral spike glycoprotein is very likely to interact with host Angiotensin-Converting Enzyme 2 (ACE2) and transmits its genetic materials and hijacks host machinery with extreme fidelity for self propagation. Few attempts have been made to develop a suitable vaccine or ACE2 blocker or virus-receptor inhibitor within this short period of time. Here, attempt was taken to develop some therapeutic and vaccination strategies with a comparison of spike glycoproteins among SARS-CoV, MERS-CoV and the SARS-CoV-2. We verified their structure quality (SWISS-MODEL, Phyre2, Pymol) topology (ProFunc), motifs (MEME Suite, GLAM2Scan), gene ontology based conserved domain (InterPro database) and screened several epitopes (SVMTrip) of SARS CoV-2 based on their energetics, IC50 and antigenicity with regard to their possible glycosylation and MHC/paratopic binding (Vaxigen v2.0, HawkDock, ZDOCK Server) effects. We screened here few pairs of spike protein epitopic regions and selected their energetic, IC50, MHC II reactivity and found some of those to be very good target for vaccination. A possible role of glycosylation on epitopic region showed profound effects on epitopic recognition. The present work might be helpful for the urgent development of a suitable vaccination regimen against SARS CoV-2.


title: Forecasting the dynamics of COVID-19 Pandemic in Top 15 countries in April 2020: ARIMA Model with Machine Learning Approach

text: We here predicted some trajectories of COVID-19 in the coming days (until April 30, 2020) using the most advanced Auto-Regressive Integrated Moving Average Model (ARIMA). Our analysis predicted very frightening outcomes, which defines to worsen the conditions in Iran, entire Europe, especially Italy, Spain, and France. While South Korea, after the initial blast, has come to stability, the same goes for the COVID-19 origin country China with more positive recovery cases and confirm to remain stable. The United States of America (USA) will come as a surprise and going to become the epicenter for new cases during the mid-April 2020. Based on our predictions, public health officials should tailor aggressive interventions to grasp the power exponential growth, and rapid infection control measures at hospital levels are urgently needed to curtail the COVID-19 pandemic.


title: Energy dynamics for systemic configurations of virus-host co-evolution

text: Virus cause multiple outbreaks, for which comprehensive tailored therapeutic strategies are still missing. Virus and host cell dynamics are strictly connected, and convey in virion assembly to ensure virus spread in the body. Study of the systemic behavior of virus-host interaction at the single-cell level is a scientific challenge, considering the difficulties of using experimental approaches and the limited knowledge of the behavior of emerging novel virus as a collectivity. This work focuses on positive-sense, single-stranded RNA viruses, like human coronaviruses, in their virus-individual host interaction, studying the changes induced in the host cell bioenergetics. A systems-thinking representation, based on stock-flow diagramming of virus-host interaction at the cellular level, is used here for the first time to simulate the system energy dynamics. We found that reducing the energy flow which fuels virion assembly is the most affordable strategy to limit the virus spread, but its efficacy is mitigated by the contemporary inhibition of other flows relevant for the system. Summary Positive-single-strand ribonucleic acid ((+)ssRNA) viruses can cause multiple outbreaks, for which comprehensive tailored therapeutic strategies are still missing. Virus and host cell dynamics are strictly connected, generating a complex dynamics that conveys in virion assembly to ensure virus spread in the body. This work focuses on (+)ssRNA viruses in their virus-individual host interaction, studying the changes induced in the host cell bioenergetics. A systems-thinking representation, based on stock-flow diagramming of virus-host interaction at the cellular level, is used here for the first time to simulate the energy dynamics of the system. By means of a computational simulator based on the systemic diagramming, we identifid host protein recycling and folded-protein synthesis as possible new leverage points. These also address different strategies depending on time setting of the therapeutic procedures. Reducing the energy flow which fuels virion assembly is addressed as the most affordable strategy to limit the virus spread, but its efficacy is mitigated by the contemporary inhibition of other flows relevant for the system. Counterintuitively, targeting RNA replication or virion budding does not give rise to relevant systemic effects, and can possibly contribute to further virus spread. The tested combinations of multiple systemic targets are less efficient in minimizing the stock of virions than targeting only the virion assembly process, due to the systemic configuration and its evolution overtime. Viral load and early addressing (in the first two days from infection) of leverage points are the most effective strategies on stock dynamics to minimize virion assembly and preserve host-cell bioenergetics. As a whole, our work points out the need for a systemic approach to design effective therapeutic strategies that should take in account the dynamic evolution of the system.


title: Analysis of medication characteristics of 66 preventive formulae for COVID-19 in China/ 新型冠状病毒肺炎（COVID-19）全国66个预防方的用药特点分析

text: Coronavirus disease 2019 (COVID-19) is a serious threat to the lives and health of our people, but there is currently no clear target for therapeutic drugs. Therefore, prevention is of great significance for the prevention and control of COVID-19. The Health Management Administration of the different provinces and cities have successively released the “Traditional Chinese Medicine Diagnosis and Treatment Programs for New Coronavirus Pneumonia” in response to the epidemic situation, among them including preventive prescriptions, which showed the theoretical characteristics of “treating disease before its onset” of traditional Chinese medicine (TCM), and also showed the characteristics of medication in different provinces. Therefore, we collected 66 formulas for treating COVID-19 in China and studied the rules of TCM prevention in various provinces and autonomous regions, and unified the thinking of medication, which could provide a reference for the prevention of COVID-19a.


title: Pns121 Does the Choice of Independent Expert Committee Affect Icer Outcomes?

text: Objectives: The Institute for Clinical and Economic Review (ICER) publishes reports on the clinical and economic value of drugs for US payers. Each report is subject to a public meeting by one of three independent expert committees (the California Technology Assessment Forum [CTAF], Midwest Comparative Effectiveness Public Advisory Council [CEPAC], and New England CEPAC) discusses the report and votes on the evidence presented. This research compares and contrasts outcomes by committee. Methods: All publicly available final ICER reports of pharmaceuticals (01/01/2014-12/31/2019) were screened and key data extracted. Results: 38 ICER reports of pharmaceuticals were identified (CTAF: 11; Midwest CEPAC: 12; New England CEPAC: 15), encompassing 110 drugs in 78 conditions/subgroups. Clinical ratings were provided for 277 drug comparisons (CTAF: 41; Midwest CEPAC: 46; New England CEPAC: 190). For the CTAF, Midwest CEPAC, New England CEPAC, respectively, 19 (46%), 23 (50%), and 33 (17%) drug comparisons achieved a rating of A, B, or B+; 3 (7%), 9 (20%), and 80 (42%) achieved a rating of C, C+, C-, or D; 19 (46%), 14 (30%), and 77 (41%) achieved a rating of P/I or I. Cost-utility assessments were undertaken for 117 treatment settings (CTAF: 35; Midwest CEPAC: 32; New England CEPAC: 50). At a willingness-to-pay threshold of $150,000/QALY, 11 therapies (31%) were deemed cost-effective/cost-saving by the CTAF, 9 (28%) by the Midwest CEPAC, and 21 (42%) by the New England CEPAC. Of the 51 votes for healthcare value, most drugs had a majority vote of low or intermediate value: CTAF: 9 (90%); Midwest CEPAC: 12 (86%); New England CEPAC: 22 (81%). Conclusions: There are generally few differences between ICER committee outcomes, although there are some variances, which are likely due to therapy area focus. Considering healthcare value, ICER committees are generally consistent in reporting that most drugs provide low to intermediate value.


The patient-urologist relationship in the COVID-19 era and beyond


title: A Simulated Single Ventilator / Dual Patient Ventilation Strategy for Acute Respiratory Distress Syndrome During the COVID-19 Pandemic

text: The potential for acute shortages of ventilators at the peak of Covid-19 pandemic has raised the possibility of needing to support two patients from a single ventilator. To provide a system for understanding and prototyping designs we have developed a mathematical model of two patients supported by a mechanical ventilator. We propose a standard setup where we simulate the introduction of T-splitters to supply air to two patients and a modified setup where we introduce a variable resistance in each inhalation pathway and one-way valves in each exhalation pathway. Using the standard setup, we demonstrate that ventilating two patients with mismatched lung compliances from a single ventilator will lead to clinically-significant reductions in tidal volume in the patient with the lowest respiratory compliance. Using the modified setup, we demonstrate that it is possible to achieve the same tidal volumes in two patients with mismatched lung compliances, and we show that the tidal volume of one patient can be manipulated independently of the other. The results indicate that, with appropriate modifications, two patients could be supported from a single ventilator with independent control of tidal volumes.


title: COVID-19 outbreak in Greece has passed its rising inflection point and stepping into its peak

text: Since the beginning of 2020, COVID-19 is the most urgent and challenging task for the international scientific community, in order to identify its behaviour, track its progress and plan effective mitigation policies. In this study, Greece is the main focus for assessing the national outbreak and estimating the general trends and outlook of it. Multiple data analytics procedures, spectral decomposition and curve-fitting formulations are developed based on the data available at hand. Standard SIEQRDP epidemic modelling is applied for Greece and for the general region around it, providing hints for the outbreak progression in the mid- and long-term, for various infections under-reporting rates. The overall short-term outlook for Greece seems to be towards positive, with a downward trend in infections rate daily increase (i.e., now beyond the exponential growth rate), a possible peak within a few days beyond April 14th, as well as the high availability level of ICU w.r.t. expected demand at peak. On the negative side, the fade-out period seems to be in the order of several months, with high probability of recurrent surges of the outbreak. The mitigation policies for the `next day' should be focused on close tracking of the epidemic via large-scale tests, strict border checking in international travelling and an adaptive plan for selective activation of mitigation measures when deemed necessary.


Chest CT as a screening tool for COVID-19 in unrelated patients and asymptomatic subjects without contact history is unjustified


title: Lopinavir-Ritonavir in treatment of COVID-19: A dynamic systematic benefit-risk assessment

text: Background: COVID-19 is an ongoing, global public health crisis for which safe and effective treatments need to be identified. The benefit-risk balance for use of lopinavir-ritonavir in COVID-19 needs to be monitored on an ongoing basis, therefore a systematic benefit-risk assessment was designed and conducted. A key objective of this study was to provide a platform for a dynamic systematic benefit-risk evaluation; although initially this evaluation is likely to contain limited information, it is required due to the urgent unmet public need. Importantly it allows additional data to be incorporated as it becomes available, and re-evaluation of the benefit-risk profile. Methods: A systematic benefit-risk assessment was conducted using the Benefit-Risk Action team (BRAT) framework. The exposure of interest was lopinavir-ritonavir treatment in COVID-19 compared to standard of care, placebo or other treatments. A literature search was conducted in PubMed and EmBase to identify peer-reviewed papers reporting clinical outcomes. Two clinicians constructed a value tree and ranked key benefits and risks in order of considered clinical importance. Results: In comparison to standard of care, data for several key benefits and risks were identified for lopinavir-ritonavir. Time to clinical improvement was not significantly different for lopinavir-ritonavir in comparison to standard of care (HR=1.31, 95% CI:0.95, 1.80). There appeared to be fewer serious adverse events with lopinavir-ritonavir (20%) vs standard of care (32%). In particular, there were fewer cases of acute respiratory distress syndrome with lopinavir-ritonavir compared to standard of care (13% vs 27%). Limited data were available for comparison of lopinavir-ritonavir to other treatments. Conclusions: Based on currently available data, there was no clear benefit for use of lopinavir-ritonavir compared to standard of care in severe COVID-19. Risk data suggested a possible decrease in serious adverse events, including acute respiratory distress syndrome. Overall, the benefit-risk profile for lopinavir-ritonavir in severe COVID-19 cannot be considered positive until further efficacy and effectiveness data become available.


Uso de máscara facial para limitar a transmissão da COVID-19/ Uso de mascarillas para limitar la transmisión de COVID-19/ Use of facemasks to limit COVID-19 transmission


title: Benchmarking Deep Learning Models and Automated Model Design for COVID-19 Detection with Chest CT Scans

text: COVID-19 pandemic has spread all over the world for months. As its transmissibility and high pathogenicity seriously threaten people's lives, the accurate and fast detection of the COVID-19 infection is crucial. Although many recent studies have shown that deep learning based solutions can help detect COVID-19 based on chest CT scans, there lacks a consistent and systematic comparison and evaluation on these techniques. In this paper, we first build a clean and segmented CT dataset called Clean-CC-CCII by fixing the errors and removing some noises in a large CT scan dataset CC-CCII with three classes: novel coronavirus pneumonia (NCP), common pneumonia (CP), and normal controls (Normal). After cleaning, our dataset consists of a total of 340,190 slices of 3,993 scans from 2,698 patients. Then we benchmark and compare the performance of a series of state-of-the-art (SOTA) 3D and 2D convolutional neural networks (CNNs). The results show that 3D CNNs outperform 2D CNNs in general. With extensive effort of hyperparameter tuning, we find that the 3D CNN model DenseNet3D121 achieves the highest accuracy of 88.63% (F1-score is 88.14% and AUC is 0.940), and another 3D CNN model ResNet3D34 achieves the best AUC of 0.959 (accuracy is 87.83% and F1-score is 86.04%). We further demonstrate that the mixup data augmentation technique can largely improve the model performance. At last, we design an automated deep learning methodology to generate a lightweight deep learning model MNas3DNet41 that achieves an accuracy of 87.14%, F1-score of 87.25%, and AUC of 0.957, which are on par with the best models made by AI experts. The automated deep learning design is a promising methodology that can help health-care professionals develop effective deep learning models using their private data sets. Our Clean-CC-CCII dataset and source code are available at: https://github.com/arthursdays/HKBU_HPML_COVID-19.


title: A short therapeutic regimen based on hydroxychloroquine plus azithromycin for the treatment of COVID-19 in patients with non-severe disease. A strategy associated with a reduction in hospital admissions and complications.

text: The new SARS-CoV-2 infection named COVID-19 has severely hit our Health System. At the time of writing this paper no medical therapy is officially recommended or has shown results in improving the outcomes in COVID-19 patients. With the aim of diminishing the impact in Hospital admissions and reducing the number of medical complications, we implemented a strategy based on a Hospital Home-Care Unit (HHCU) using an easy-to-use treatment based on an oral administration regimen outside the hospital with hydroxychloroquine (HCQ) plus azithromycin (AZM) for a short period of 5 days. Patients and methods: Patients [≥] 18 years old visiting the emergency room at the Hospital Universitario San Pedro de Logrono (La Rioja) between March, 31st and April, 12th diagnosed with COVID-19 with confirmed SARS-CoV-2 infection by a specific PCR, as follows: Patients with pneumonia (CURB [≤] 1) who did not present severe comorbidities and had no processes that contraindicated this therapeutic regime. Olygosimptomatic patients without pneumonia aged [≥] 55 years. Patients [≥] 18 years old without pneumonia with significant comorbidities. We excluded patients with known allergies to some of the antimicrobials used and patients treated with other drugs that increase the QTc or with QTc >450msc. The therapeutic regime was: HCQ 400 mg every twice in a loading dose followed by 200 mg twice for 5 days, plus AZM 500 mg on the first day followed by 250 mg daily for 5 days. A daily telephone follow-up was carried out from the hospital by the same physician. The end-points of our study were: 1.- To measure the need for hospital admission within 15 days after the start of treatment. 2.- To measure the need to be admitted to the intensive care unit (ICU) within 15 days after the start of the treatment. 3.- To describe the severity of the clinical complications developed. 4.- To measure the mortality within 30 days after starting treatment (differentiating if the cause is COVID-19 or something else). 5.-To describe the safety and adverse effects of the therapeutic regime. Results: During the 13 days studied a total of 502 patients were attended in the emergency room due to COVID-19. Forty-two were sent at home; 80 were attended by the HHCU (patients on this study) and 380 were admitted to the Hospital. In our series there were a group of 69 (85.18%) patients diagnosed with pneumonia (37 males and 32 females). Most of them, 57 (82.60%) had a CURB65 score of <1 (average age 49) and 12 (17.40%) a CURB score of 1 (average age 63). Eighteen (22.50%) of the pneumonia patients also had some morbidity as a risk factor. 11 patients (13.75%) without pneumonia were admitted to the HHCU because comorbidities or age [≥] 55 years. Six patients with pneumonia had to be hospitalized during the observation period, 3 of them because side effects and 3 because of worsening. One of these patients, with morbid obesity and asthma, had clinical worsening needing mechanical ventilation at ICU and developed acute distress respiratory syndrome. With the exception of the patient admitted to the ICU, the rest of the patients were discharged at home in the following 8 days (3 to 8 days). Twelve patients (15%), 11 of whom had pneumonia, experienced side effects affecting mainly the digestive. In another patient a QTc interval prolongation (452 msc) was observed. In total 3 of these patients had to be admitted in the Hospital, 2 because of vomiting and 1 because a QTc interval lengthening. None of the patients needed to stop the HCQ or AZM and all the 80 patients finished the therapeutic strategy. From the group without pneumonia only a patient developed diarrhea that did not require hospitalization or stop the medication. Conclusions: Our strategy has been associated with a reduction in the burden of hospital pressure, and it seems to be successful in terms of the number of patients who have developed serious complications and / or death. None of the patients died in the studied period and only 6 have to be admitted in conventional hospitalization area.


title: Heart Disease Deaths during the Covid-19 Pandemic

text: The SARS-CoV-2 pandemic is associated with a reduction in hospitalization for an acute cardiovascular conditions. In a major health system in Massachusetts, there was a 43% reduction in these types of hospitalizations in March 2020 compared with March 2019.4 Whether mortality rates from heart disease have changed over this period is unknown. We assembled information from the National Center for Health Statistics (Centers for Disease Control and Prevention) for 118,356,533 person-weeks from Week 1 (ending January 4) through Week 17 (ending April 25) of 2020 for the state of Massachusetts. We found that heart disease deaths are unchanged during the Covid-19 pandemic period as compared to the corresponding period of 2019. This is despite reports that admissions for acute myocardial infarction have fallen during this time.


title: EXCESS MORTALITY FROM COVID-19. WEEKLY EXCESS DEATH RATES BY AGE AND SEX FOR SWEDEN.

text: Objectives: Mortality from Covid-19 is monitored in detail both within as well as between countries with different strategies against the virus. However, death counts and relative risks based on crude numbers can be misleading. Instead, age specific death rates should be used for comparability. Given the difficulty of ascertainment of Covid-19 specific deaths, excess all-cause mortality is currently more appropriate for comparisons. By estimating age- and sex-specific death rates we aim to get more accurate estimates of the excess mortality attributed to Covid-19, as well as the difference between men and women in Sweden. Design: We make use of Swedish register data about total weekly deaths, total population at risk, and estimate age- and sex-specific weekly death rates for 2020 and the 5 previous years. The data is provided by Statistics Sweden. Results: From the first week of April and onwards, the death rates at all ages above 60 are higher than those in previous years in Sweden. Persons above age 80 are dis-proportionally more affected, and men suffer higher levels of excess mortality than women at all ages with 75% higher death rates for males and 50% higher for females. Current excess mortality corresponds to a decline in remaining life expectancy of 3 years for men and 2 years for women. Conclusion: The Covid-19 pandemic has so far had a clear and consistent effect on total mortality in Sweden, with male death rates being comparably more affected. What consequences the pandemic will eventually have on mortality and life expectancy will depend on the progression of the pandemic, the extent that some of the deaths would have occurred in the absence of the pandemic, only somewhat later, the consequences for other health conditions, as well as the health care sector at large.


title: COVID-19 outbreak and surgeons’ response at a Cancer Center in the United States

text: In the pandemic of severe acute respiratory syndrome due to coronavirus-2 (SARS-CoV-2), United States (U S ) also experienced the spread of coronavirus disease 2019 (COVID-19) Here, we report the current status of Houston, Texas and the response to COVID-19 at MD Anderson Cancer Center (MDACC) and in the Department of Surgical Oncology MDACC has taken the institutional measures in order to prevent its employees and patients from COVID-19 Furthermore, surgeons have also responded aggressively in the outpatient setting, operating room and inpatient care The predicted peak in Texas is on April 29 and our mitigation measures appear to be effective at the time of writing, however there still remain a lot of unknowns about SARS-CoV-2 and the performance of cancer operations remains an ongoing and delicate issue In order to minimize the risks to patients, our healthcare system, and our community, MDACC has navigated the countering pressures through honest and open communication with patients, judicious use of alternative treatment strategies, and thoughtful selection of surgical cases


Cancer Trials, Treatment Harmed by COVID-19 Pandemic


title: Clinical trials press on for conditions other than COVID-19. Will the pandemic’s effects sneak into their data?

text: Myron Cohen has run clinical trials through hurricanes and civil unrest Now, the infectious disease researcher at the University of North Carolina, Chapel Hill, says he and his colleagues are in a new situation: trying to carry out large, international trials in the midst of coronavirus lockdowns Cohen co-leads a network of HIV prevention trials, some of which have paused during the pandemic But for other studies, he says, “stopping would be of grave consequence” to participants So study teams have bought and shipped protective equipment to personnel at clinical trial sites, secured special permits where necessary for trial participants to leave their homes for medical visits, and arranged their private transportation to avoid public buses Not all clinical trials have had to go through such logistical gymnastics But across diverse fields, investigators have managed to keep treating patients who might benefit from experimental therapies Slowdowns and pauses in recruiting new participants will delay results—but for many studies, data are still flowing in


title: Fuzzy Autocatalytic analysis of Covid-19 outbreak in Malaysia

text: The objective of this research is to demonstrate a mathematical technique to analyze the Covid-19 outbreak, particularly with respect to Malaysia. The technique is able to accommodate scarcity, quantity, and availability of the data set. The obtained results can offer descriptive insight for reflecting and strategizing actions in combating the pandemic.


New threat: 2019 novel Coronavirus infection and infection control perspective in Turkey


COVID-19 Causing Financial Problems for HospitalsSimple, Low-Cost Ventilator Builds on Available Resuscitation Bags


title: Forecast and interpretation of daily affected people during 21 days lockdown due to COVID 19 pandemic in India

text: The problem of facing difficulty to control the spreading of newly detected novel corona virus 2019 is a matter of attention throughout the whole world. The total numbers of infected individuals have already crossed 2 million throughout the world. The government of all the affected countries have already taken many measures like lockdown to stop the spread. Therefore, it is important to study the nature of growth and interpretations are necessary for taking needful by the government. In this paper, we have tried to interpret the spreading capability of novel corona virus in India taking into consideration of 21 days lockdown data. The prediction is based on the present number of available cases and number of new cases reporting daily. We have explained the number of infected people in India comparing with Italy, China, Spain, and USA data of 21 days individually after announcing lockdown. The plot of daily new cases with the number of days spent after lockdown is fitted by linear and polynomial function. The best fitted graph is chosen for interpretation and that is based on the parameters obtained from fitting. The forecast of maximum spreading possibility is discussed with linear and 4-degree polynomial fitting parameters. Finally, some further preventive measurements are also discussed.


title: Social heterogeneity and the COVID-19 lockdown in a multi-group SEIR model

text: The goal of the lockdown is to mitigate and if possible prevent the spread of an epidemic. It consists in reducing social interactions. This is taken into account by the introduction of a factor of reduction of social interactions q, and by decreasing the transmission coefficient of the disease accordingly. Evaluating q is a difficult question and one can ask if it makes sense to compute an average coefficient q for a given population, in order to make predictions on the basic reproduction rate R0, the dynamics of the epidemic or the fraction of the population that will have been infected by the end of the epidemic. On a very simple example, we show that the computation of R0 in a heterogeneous population is not reduced to the computation of an average q but rather to the direct computation of an average coefficient R0. Even more interesting is the fact that, in a range of data compatible with the Covid-19 outbreak, the size of the epidemic is deeply modified by social heterogeneity, as is the height of the epidemic peak, while the date at which it is reached mainly depends on the average R0 coefficient.


title: Air and surface measurements of SARS-CoV-2 inside a bus during normal operation

text: Transmission pathways of SARS-CoV-2 are through aerosol, droplet and touching infected material. Indoor locations are more likely environments for the diffusion of the virus contagion among people, but direct detection of SARS-CoV-2 in air or on surfaces is quite sparse, especially regarding public transport. In fact, an important demand is to know how and if it is safe to use them. To understand the possible spreading of COVID-19 inside a city bus during normal operation and the effectiveness of the protective measures adopted for transportation, we analysed the air and the surfaces most usually touched by passengers. The measurements were carried out across the last week of the lockdown and the first week when gradually all the travel restrictions were removed.


title: A Systems Framework for Vaccine Design

text: Numerous challenges have been identified in vaccine development, including variable efficacy as a function of population demographics and a lack of characterization and mechanistic understanding of immune correlates of protection able to guide delivery and dosing. There is tremendous opportunity in recent technological and computational advances to elucidate systems level understanding of pathogen-host interactions and correlates of immunity. A systems biology approach to vaccinology provides a new paradigm for rational vaccine design in a “precision medicine” context.


Wild West Politics in Trump’s America


Neurologists in Italy to Colleagues in US: Look for Poorly-Defined Neurologic Conditions in Patients with COVID-19


title: The basic reproduction number and prediction of the epidemic size of the novel coronavirus (COVID-19) in Shahroud, Iran

text: Objectives: To estimate the basic reproduction number (R0) of COVID-19 in the early stage of the epidemic and predict the expected number of new cases in Shahroud, Northeast of Iran. Methods: The R0 of COVID-19 was estimated using the serial interval distribution and the number of incidence cases. The serial interval was fit with a gamma distribution. The probable incidence and cumulative incidence in the next 30 days were predicted using the assumption that daily incidence follows a Poisson distribution determined by daily infectiousness. Data analysis was done using earlyR and projections packages in R software. Results: The maximum-likelihood value of R0 was 2.7 (95% confidence interval (CI): 2.1 to 3.4) for the COVID-19 epidemic in the early 14 days and decreased to 1.13 (95% CI: 1.03 to 1.25) by the end of the day 41. The expected average number of new cases in Shahroud is 9.0 case/day with a standard deviation of 3.8, which means an estimated total of 271 (95% CI: 178-383) new cases in the next 30 days. Conclusions: It is essential to reduce the R0 to values below one. Therefore, we strongly recommend enforcing and continuing the current preventive measures, restricting travel, and providing screening tests for a larger proportion of the population.


title: COVID-19 Disease Dynamics in Germany: First Models and Parameter Identification

text: Since the end of 2019 an outbreak of a new strain of coronavirus, called SARS-CoV-2, is reported from China and later other parts of the world. Since January 21, WHO reports daily data on confirmed cases and deaths from both China and other countries. The Johns Hopkins University collects those data from various sources worldwide on a daily basis. For Germany, the Robert-Koch-Institute (RKI) also issues daily reports on the current number of infections and infection related fatal cases. However, due to delays in the data collection, the data from RKI always lags behind those reported by Johns Hopkins. In this work we present an extended SEIR-model to describe the disease dynamics in Germany. The parameter values are identified by matching the model output to the officially reported cases. An additional parameter to capture the influence of unidentified cases is also included in the model.


title: Manufacturing for Design: A sustaining approach to drive manufacturing process evolution, then innovation

text: Abstract Often today’s designers are relegated to degrade their own output to realize mass production on existing manufacturing capital equipment. These considerations are typically encoded in the design process through “Design for Manufacturing” where constraints on the production processes available and limits to each manufacturing approach are ideally considered early in design. This Design for Manufacturing guise inhibits true designer creativity and the possibility to realize truly revolutionary products. In this paper, the authors formalize their previous introduction of the concept of Manufacturing for Design (MFD), a framework whereby product design creativity is used instead as a motive force of innovation to rethink manufacturing process approaches and assist in facilitating real innovation in manufacturing. This is not proposed as a replacement for DFM, but an extension that can help “question” the manufacturing-based requirements during the development process. It is clear that existing machines cannot be abandoned, but one can instead consider an intermediate augmentation step to feasibly enhance existing capital, to realize new designs in new materials, or to achieve new functional requirements and desires. The blending of MFD and DFM strategies (a proposed MFD|DFM approach) can lead to feasible evolution of manufacturing, and ultimately disruptive process innovation, defined as a rethinking of manufacturing rather than just improvement on existing solutions. Herein is reported the integration of the MFD|DFM concept to two separate education programs, one undergraduate and one graduate. These programs are independent but share resources together with those of an Advanced Manufacturing technical college program to educate students across disciplines and curricula in the dichotomy of Design and Manufacturing, and how the concepts can be properly considered together.


title: Meso-scale modeling of COVID-19 spatio-temporal outbreak dynamics in Germany

text: The COVID-19 pandemic has kept the world in suspense for the past months. In most federal countries such as Germany, locally varying conditions demand for state- or county-level decisions. However, this requires a deep understanding of the meso-scale outbreak dynamics between micro-scale agent models and macro-scale global models. Here, we introduce a reparameterized SIQRD network model that accounts for local political decisions to predict the spatio-temporal evolution of the pandemic in Germany at county and city resolution. Our optimized model reproduces state-wise cumulative infections and deaths as reported by the Robert-Koch Institute, and predicts development for individual counties at convincing accuracy. We demonstrate the dominating effect of local infection seeds, and identify effective measures to attenuate the rapid spread. Our model has great potential to support decision makers on a state and community politics level to individually strategize their best way forward.


title: Spreading Analysis of COVID-19 Epidemic in Bangladesh by Dynamical Mathematical Modelling

text: The coronavirus disease 2019 (COVID-19), which emerged from Wuhan, China, is now a pandemic, affecting across the globe. Bangladesh also is experiencing the rapid growth of COVID-19 infection and death cases started from 8th March 2020. The purpose of providing a simple yet effective explanatory model for prediction of the future evolution of the contagion and verification of the effectiveness of the containment and lockdown measures in Bangladesh. In this study, using a modified SIR (Susceptible-Infected-Recovered) model a forecast is generated to predict the trends of COVID-19 cases in Bangladesh. The epidemic model was proposed to accommodate the effects of lockdown and individual based precautionary measures. Data has been taken and analyzed for before and after the movement control order (MCO) and during the MCO period. Modified SIR model in this work offers us an idea how the outbreak would progress based on the current data. It also has estimated that, the peak in terms of the number of infected cases will start from last of June 2020. For the total population (100%) the model gets the peaks at 214875 (infected cases) and 7743 (death cases). For the 90% population, the model shows the peaks at 244356 (infected cases) and 9100 (death cases). Analysis revealed that the lockdown and recommended individual hygiene can slow down the outbreak but unable to eradicate the disease from the society. With the current infection and death rate and existing level of personal precautionary the number of infected individuals will be increasing.


title: How diseases rise and fall with the seasons—and what it could mean for coronavirus

text: Scientists and doctors have observed for thousands of years that some diseases, such as polio and influenza, rise and fall with the seasons But why? Ongoing research in animals and humans suggests a variety of causes, including changes in the environment (like pH, temperature, and humidity) and even seasonal and daily changes to our own immune systems Figuring out those answers could one day make all the difference in minimizing the impact of infectious disease outbreaks—such as coronavirus disease 2019


docid: ojfrvtuy

title: Coincidence of COVID-19 epidemic and olfactory dysfunction outbreak

text: Background Recent surge of olfactory dysfunction in patients who were referred to ENT clinics and concurrent COVID-19epidemic in Iran motivated us to evaluate anosmic/hyposmic patients to find any relation between these two events. Methods This is a cross-sectional study with an online checklist on voluntary cases in all provinces of Iran between the 12th and 17th March, 2020. Cases was defined as self-reported anosmia/hyposmia in responders fewer than 4 weeks later (from start the of COVID-19 epidemic in Iran). Variables consist of clinical presentations, related past medical history, family history of recent respiratory tract infection and hospitalization. Results In this study 10069 participants aged 32.5 +/- 8.6 (7-78) years, 71.13% female and 81.68% non-smoker completed online checklist. They reported 10.55% a history of a trip out of home town and 1.1% hospitalization due to respiratory problems recently. From family members 12.17% had a history of severe respiratory disease in recent days and 48.23% had anosmia/hyposmia. Correlation between the number of olfactory disorder and reported COVID-19 patients in all 31 provinces till 16th March 2020 was highly significant (Spearman correlation coefficient=0.87, p-Value<0.001). The onset of anosmia was sudden in 76.24% and till the time of filling the questionnaire in 60.90% of patients decreased sense of smell was constant. Also 83.38 of this patients had decreased taste sensation in association with anosmia. Conclusions It seems that we have a surge in outbreak of olfactory dysfunction happened in Iran during the COVID-19 epidemic. The exact mechanism of anosmia/hyposmia in COVID-19 patients needs further investigations.


title: Bulk and single-cell gene expression profiling of SARS-CoV-2 infected human cell lines identifies molecular targets for therapeutic intervention

text: The coronavirus disease 2019 (COVID-19) pandemic, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an ongoing global health threat with more than two million infected people since its emergence in late 2019. Detailed knowledge of the molecular biology of the infection is indispensable for understanding of the viral replication, host responses, and disease progression. We provide gene expression profiles of SARS-CoV and SARS-CoV-2 infections in three human cell lines (H1299, Caco-2 and Calu-3 cells), using bulk and single-cell transcriptomics. Small RNA profiling showed strong expression of the immunity and inflammation-associated microRNA miRNA-155 upon infection with both viruses. SARS-CoV-2 elicited approximately two-fold higher stimulation of the interferon response compared to SARS-CoV in the permissive human epithelial cell line Calu-3, and induction of cytokines such as CXCL10 or IL6. Single cell RNA sequencing data showed that canonical interferon stimulated genes such as IFIT2 or OAS2 were broadly induced, whereas interferon beta (IFNB1) and lambda (IFNL1-4) were expressed only in a subset of infected cells. In addition, temporal resolution of transcriptional responses suggested interferon regulatory factors (IRFs) activities precede that of nuclear factor-κB (NF-κB). Lastly, we identified heat shock protein 90 (HSP90) as a protein relevant for the infection. Inhibition of the HSP90 charperone activity by Tanespimycin/17-N-allylamino-17-demethoxygeldanamycin (17-AAG) resulted in a reduction of viral replication, and of TNF and IL1B mRNA levels. In summary, our study established in vitro cell culture models to study SARS-CoV-2 infection and identified HSP90 protein as potential drug target for therapeutic intervention of SARS-CoV-2 infection.


title: The IGNITE Trial: Participant Recruitment Lessons Prior to SARS-CoV-2

text: Full and diverse participant enrollment is critical to the success and generalizability of all large-scale Phase III trials. Recruitment of sufficient participants is among the most significant challenges for many studies. The novel SARS-CoV-2 coronavirus pandemic has further changed and challenged the landscape for clinical trial execution, including screening and randomization. The Investigating Gains in Neurocognition in an Intervention Trial of Exercise (IGNITE) study has been designed as the most comprehensive test of aerobic exercise effects on cognition and brain health. Here we assess recruitment into IGNITE prior to the increased infection rates in the United States, and examine new challenges and opportunities for recruitment with a goal of informing the remaining required recruitment as infection containment procedures are lifted. The results may assist the design and implementation of recruitment for future exercise studies, and outline opportunities for study design that are flexible in the face of emerging threats.


title: Orthogonal Functions for Evaluating Social Distancing Impact on CoVID-19 Spread

text: Early CoVID-19 growth often obeys: N{t}=N/Iexp[+K/ot], with K/o=[(ln2)/(t/dbl)], where t/dbl is the pandemic doubling time, prior to society-wide Social Distancing. Previously, we modeled Social Distancing with t/dbl as a linear function of time, where N[t]=1exp[+K/A t/(1+ gamma/o t)] is used here. Additional parameters besides {K/o,gamma/o} are needed to better model different rho[t]=dN[t]/dt shapes. Thus, a new Orthogonal Function Model [OFM] is developed here using these orthogonal function series: N(Z) = sum[m=0,M/F] g/m L/m(Z) exp[-Z] , R(Z) = sum[m=0,M/F] c/m L/m(Z) exp[-Z] , where N(Z) and Z[t] form an implicit N[t]=N(Z[t]) function, giving: G/o = [K/A / gamma/o ] , Z[t] = +[ G/o / (1+ gamma/ot) ] , rho[t] = [ gamma/o / G/o ] (Z^2) R(Z) , with L/m(Z) being the Laguerre Polynomials. At large M/F values, nearly arbitrary functions for N[t] and rho[t]=dN[t]/dt can be accommodated. How to determine {K/A, gamma/o} and the {g/m; m=(0,+M/F)} constants from any given N(Z) dataset is derived, with rho[t] set by: c/(M/F - k) = sum[m=0,k] g/m . The bing.com USA CoVID-19 data was analyzed using M/F=(0,1,2) in the OFM. All results agreed to within about 10 percent, showing model robustness. Averaging over all these predictions gives the following overall estimates for the number of USA CoVID-19 cases at the pandemic end: = 5,009,677 (+/-) 269,450 (data to 5/3/20), and = 4,422,803 (+/-) 162,580 (data to 6/7/20), which compares the pre- and post-early May bing.com revisions. The CoVID-19 pandemic in Italy was examined next. The M/F=2 limit was inadequate to model the Italy rho[t] pandemic tail. Thus, regions with a quick CoVID-19 pandemic shutoff may have additional Social Distancing factors operating, beyond what can be easily modeled by just progressively lengthening pandemic doubling times (with 13 Figures).


title: An epidemic CC1-MRSA-IV clone yields false negative test results in molecular MRSA identification assays: a note of caution

text: Background: A variety of rapid molecular PCR tests has been developed and commercialised that interrogate the junction site between the staphylococcal core genome, and the mobile genetic element (SCCmec) which harbours the gene responsible for methicillin-/beta-lactam-resistance. Aim: The purpose of the present study was to investigate why a clinical MRSA isolate yielded false negative test results with widely used, commercial orfX/SCCmec junction site PCR tests. Methods: A collection of isolates that belonged to the same epidemic strain as the index isolate were investigated with commercial MRSA assays and all isolates were sequenced in order to explain this observation. Results: It was found that isolates of the epidemic European CC1-MRSA-IV clone, which likely originated in South-Eastern Europe and subsequently spread to Western Europe, generally exhibit this behaviour. The failure of the assays was attributable to a characteristic large insertion in the orfX/SCCmec integration site presumably targeted by such tests. In contrast to MW2 (GenBank BA000033.2, a CC1 USA400 strain which also harbours SCCmec IVa), the European CC1 clone harbours an insertion of ca. 5,350 nucleotides adjacent to orfX. This sequence starts with a novel SCC terminal sequence alternate to dcs and encodes six different hypothetical proteins (E7MHX1, ydiL2, C5QAP8, A8YYX4, npd-SCC, H4AYD7; nucleotide positions 280,690-286,024 of GenBank RBVO000005.1). An SCCmec element with the same insertion was previously found in a Staphylococcus epidermidis isolate (GenBank MH188467.1) suggesting transfer between staphylococcal species. Conclusion: In order to ensure the reliability of molecular MRSA tests, it is vital to monitor the emergence of new SCCmec junction sites, not only in Staphylococcus aureus but also in coagulase-negative staphylococci.


title: Fault Diagnosis of Ball Screw in Industrial Robots Using Non-Stationary Motor Current Signals

text: Abstract With the advancement of intelligent manufacturing, different kinds of industrial robots have been applied in modern factories. The liquid crystal display transfer robot (LCDTR) has been widely used in LCD production lines to transport panels. Effective fault diagnosis and prognosis of the industrial robots are of great importance, since unplanned downtime caused by faulty robots significantly reduces the production capacity. Specifically, the ball screw is the critical component in the LCDTR. The failure of the ball screw can cause long downtime. Conventionally, the fault diagnosis of the ball screw is usually based on the vibration signals. However, it is extremely difficult to install the vibration sensors in the industrial robots. Therefore, in order to address this issue in condition monitoring, this paper proposes a data-driven fault diagnosis methodology using the motor current signals of the ball screw. Two time-frequency domain analysis methods are investigated, including short-time Fourier transform (STFT) and wavelet packet decomposition (WPD). The statistical features are extracted, and Fisher score is used to select features. Furthermore, the logistic regression and k-nearest neighbors are applied for the final fault diagnosis. Experiments on a real-world industrial robot dataset are carried out for validation. 100% diagnosis accuracy can be basically achieved by the proposed method, which indicates the non-stationary current signal can be effectively used to identify the health states of the ball screw in the LCDTR.


title: Liver Chemistries in Patients with Severe or Non-Severe COVID-19: a Meta-Analysis

text: Background & Aims: Cumulating observations have indicated that COVID-19 patients undergo different patterns of abnormal liver chemistries. We performed a meta-analysis of published liver manifestations and tried to describe the liver damage. Methods: We searched PubMed, google scholar, Embase, Cochrane Library, medRxiv, bioRxiv, and three Chinese electronic databases through April 18, 2020 according to the Preferred Reporting Items for Meta-Analyses. We analyzed pooled data on liver chemistries stratified by the severity of COVID-19 using a fixed or random effects model. Results: In a meta-analysis of 37 studies, comprising 6,235 patients, the pooled mean of ALT was 36.4 IU/L in the severe cases of COVID-19 while 27.8 IU/L in the non-severe cases (95% CI: -9.4- -5.1, p<0.0001). Pooled average of AST was 46.8 IU/L in the severe cases while 30.4 IU/L in the non-severe cases (95% CI: -15.1- -10.4, p<0.0001). Compared with the non-severe cases, the severe cases tended to have higher γ-Glutamyltransferase while lower albumin. Conclusions: In this meta-analysis, we comprehensively described three patterns of liver impairment related to COVID-19, including hepatocellular injury, cholestasis, and synthetic disfunction, according to the severity of the COVID-19. Patients with abnormal liver tests are at higher risks of progressing to severe disease. Close monitoring on liver chemistries helps to early warn against disease progression.


title: Multiscale 3-dimensional pathology findings of COVID-19 diseased lung using high-resolution cleared tissue microscopy

text: The study of pulmonary samples from individuals who have died as a direct result of COVID-19 infection is vital to our understanding of the pathogenesis of this disease. Histopathologic studies of lung tissue from autopsy of patients with COVID-19 specific mortality are only just emerging. All existing reports have relied on traditional 2-dimensional slide-based histological methods for specimen preparation. However, emerging methods for high-resolution, massively multiscale imaging of tissue microstructure using fluorescence labeling and tissue clearing methods enable the acquisition of tissue histology in 3-dimensions, that could open new insights into the nature of SARS-Cov-2 infection and COVID-19 disease processes. In this article, we present the first 3-dimensional images of lung autopsy tissues taken from a COVID-19 patient, including 3D “virtual histology” of cubic-millimeter volumes of the diseased lung, providing unique insights into disease processes contributing to mortality that could inform frontline treatment decisions.


title: Reducing SARS-CoV-2 infectious spreading patterns by removing S and R compartments from SIR model equation

text: This research points to the asymptotic instability of SIR model and its variants to predict the behavior of SARS-CoV-2 infection spreading patterns over the population and time aspects. Mainly for the S and R terms of the equation, the predictive results fail due to confounding environment of variables that sustain the virus contagion within population complex network basis of analysis. While S and R are not homologous data of analysis, thus with improper topological metrics used in many researches, these terms leads to the asymptotic feature of I term as the most stable point of analysis to achieve proper predictive methods. Having in its basis of formulation the policies adopted by countries, I therefore presents a stable fixed point orientation in order to be used as a predictive analysis of nearby future patterns of SARS-CoV-2 infection. New metrics using a Weinbull approach for I are presented and fixed point orientation (sensitivity of the method) are demonstrated empirically by worldwide statistical data.


title: Overview on COVID-19 outbreak indicators across Brazilian federative units

text: Background: The 2019 coronavirus disease pandemic (COVID 19) spread rapidly across Brazil. The country has 27 federative units, with wide regional differences related to climate, lifestyle habits, socioeconomic characteristics and population density. Therefore, we aimed to document and monitor the increase in COVID 19 cases across each federative unit in Brazil, by tracking its progression from inception to 15 May 2020. Methods: Observational study. Results: The first confirmed COVID 19 case in the country was notified in Sao Paulo on 26 February, while the first death occurred on 17 March, in Rio de Janeiro. Since then, there has been a dramatic increase in both confirmed cases and deaths from the disease. Sao Paulo, in the Southeast region, was initially considered the COVID 19 epidemic epicentre in Brazil. However, 10 states in the North and Northeast regions were ranked among the 14 highest incidences (over 100 cases per 100,000 people) observed on 15 May. Higher incidence rates (>100 cases per 100,000) were associated to higher rates of inadequate water supply and sewerage (OR, 5.83 (95% CI, 1.08 to 29.37, P=0.041)). North and Northeast states with the highest social vulnerability index scores had higher increases in the incidence rate between 14 April and 15 May. States with medium human development index (HDI) showed higher incidence increases from 14 April to 15 May, being seven of them with ratios in the range from 27.49 to 63.73 times. Conclusion: Spreading of COVID 19 in Brazil differs across both regions and federative units, being influenced by different socioeconomic contexts.


title: Empirical evidence for safety of mechanical ventilation during simulated cardiopulmonary resuscitation on a physical model

text: Background: Cardiac arrest is a critical event requiring adequate and timely response in order to increase patient chances of survival. In patients mechanically ventilated with advance airways cardiopulmonary resuscitation (CPR) maneuver may be simplified by keeping the ventilator on. This work assessed the response of a intensive care mechanical ventilator to CPR using a patient manikin ventilated in three conventional modes. Methods: Volume controlled (VCV), pressure controlled (PCV) and pressure regulated volume controlled (PRVC) ventilation were applied in a thorax physical model with or without chest compressions. The mechanical ventilator was set with inspiratory time of 1.0 s, ventilation rate of 10 breaths/minute, positive end-expiratory pressure of 0 cmH2O, FiO2 of 1.0, target tidal volume of 600 ml and trigger level of -20 cmH2O. Airway opening pressure and ventilatory flow signals were continuously recorded. . Results: Chest compression resulted in increased airway peak pressure in all ventilation modes (p<0.001), specially with VCV (137% in VCV, 83% in PCV, 80% in PRVC). However, these pressures were limited to levels similar to release valves in manual resuscitators (~60 cmH2O). In pressure controlled modes tidal/minute volumes decreased (PRVC=11%, p=0.027 and PCV=12%, p<0.001), while still within the variability observed during bag-valve-mask ventilation. During VCV, variation in tidal/minute volumes were not significant (p=0.140). Respiratory rates were constant with and without chest compression. Conclusions: A intensive care mechanical ventilator could provide adequate ventilation during compressions in a manikin model while using conventional ventilation modes.


title: Impact of asymptomatic infection on coupled disease-behavior dynamics in complex networks

text: Studies on how to model the interplay between diseases and behavioral responses (so-called coupled disease-behavior interaction) have attracted increasing attention. Owing to the lack of obvious clinical evidence of diseases, or the incomplete information related to the disease, the risks of infection cannot be perceived and may lead to inappropriate behavioral responses. Therefore, how to quantitatively analyze the impacts of asymptomatic infection on the interplay between diseases and behavioral responses is of particular importance. In this Letter, under the complex network framework, we study the coupled disease-behavior interaction model by dividing infectious individuals into two states: U-state (without evident clinical symptoms, labelled as U) and I-state (with evident clinical symptoms, labelled as I). A susceptible individual can be infected by U- or I-nodes, however, since the U-nodes cannot be easily observed, susceptible individuals take behavioral responses \emph{only} when they contact I-nodes. The mechanism is considered in the improved Susceptible-Infected-Susceptible (SIS) model and the improved Susceptible-Infected-Recovered (SIR) model, respectively. Then, one of the most concerned problems in spreading dynamics: the epidemic thresholds for the two models are given by two methods. The analytic results \emph{quantitatively} describe the influence of different factors, such as asymptomatic infection, the awareness rate, the network structure, and so forth, on the epidemic thresholds. Moreover, because of the irreversible process of the SIR model, the suppression effect of the improved SIR model is weaker than the improved SIS model.


title: Rapid development of COVID-19 rapid diagnostics for low resource settings: accelerating delivery through transparency, responsiveness, and open collaboration

text: In January, Mologic, embarked on a product development pathway for COVID-19 diagnostics focusing on ELISA and rapid diagnostic tests (RDTs), with anticipated funding from Wellcome Trust and DFID. 755 clinical samples from known COVID-19 patients and hospital negative controls were tested on Mologics IgG ELISA. The reported sensitivity on 191 SGUL prospectively enrolled patients was 95% on day 7 or more post diagnosis, and 97% 10 days or more post-diagnosis. A specificity panel comprising 564 samples pre-December 2019 were tested to include most common respiratory pathogens, other types of coronavirus, and flaviviruses. Specificity in this panel was 97%. This is the first in a series of Mologic products for COVID-19, which will be deployed for COVID-19 diagnosis, contact tracing and sero-epidemiological studies to estimate disease burden and transmission with a focus on ensuring access, affordability, and availability to lowest resource settings.


title: Negligible Risk of the COVID-19 Resurgence Caused by Work Resuming in China (outside Hubei): a Statistical Probability Study

text: The COVID-19 outbreak in China appears to reach the late stage since late February 2020, and a stepwise restoration of economic operations is implemented. Risk assessment for such economic restoration is of significance. Here we estimated the probability of COVID-19 resurgence caused by work resuming in typical provinces/cities, and found that such probability is very limited (<5% for all the regions except Beijing). Our work may inform provincial governments to make risk level-based, differentiated control measures.


title: Studying COVID-19 in light of critical approaches to risk and uncertainty: research pathways, conceptual tools, and some magic from Mary Douglas

text: This editorial is a response to the recent COVID-19 pandemic and underlines the valuable role that critical social science approaches to risk and uncertainty can play in helping us understand how risk is being understood and mitigated. Drawing on Heyman’s approach to understanding risk as a configuration of probabilistic knowledge, time-framing, categories and values, I explore COVID-19 risk in relation to each of these features while also emphasising how different features stabilise one another. I suggest lines of inquiry into each of these features and their interrelatedness. I then move to present some important insights from the work of Mary Douglas which are especially germane to studying the risk of COVID-19 and, again, I raise possibilities for future research. Emphasising the centrality of ritual to Douglas’s theory, I develop these considerations to encourage an exploration of magic and magical thinking, alongside rational approaches to COVID-19 risk.


title: Computed Tomography Findings and Short-term follow-up with Novel Coronavirus Pneumonia

text: Objective: To assess the characteristics of computed tomography (CT) features and changes in CT monitoring in patients with novel coronavirus pneumonia (NCP) . Methods: In this retrospective, two-center study, we reviewed the medical records of 57 patients with NCP in CT from January 21 to February 12, 2020. Cases were confirmed by the results of nucleic acid test positive, and were analyzed for demographic, clinical, and CT features. Results: Of the 57 patients, 31cases were male, and 45.6% were female. The average age was 46.5 years. Patients had fever (84.2%), cough (49.1%), weak (31.6%), muscle ache (17.5%), shortness of breath (12.3%). The distribution of abnormality was a subpleural lesions in 51 cases, with 96.5% ground-glass opacity (GGO) and 68.4% consolidation. Another observation reveals 45.6% fibrosis, 33.3% lymph node enlargement, 21.1% pleural thickening, 17.5% small nodule, 7.0% white lung, 5.3% emphysema, and 3.5% bronchiectasis. Importantly, the group of men had more septal thickening and air trapping than the female group (p < 0.05); Compared with the younger, the elderly had higher of subpleural lesion, interlobular septal thickening and pleural thickening (p < 0.05). In the first monitoring, there were 37.3% improvement, 60.8% progress. In the second monitoring, there were 55% improvement, 35% progress. The improvement rate during the third follow-up visit was 100%. Conclusions: CT features and CT dynamic observation play a vital role in the diagnosis and treatment with NCP. It is conducive to early diagnosis, deepen the knowledge of NCP and accumulate experience.


title: Attach importance to research and development of Chinese materia medica based on prevention and control needs of SARS-CoV-2 infection/ 基于新型冠状病毒感染防控需求，重视中药科学研发与应用

text: In the first 20 years of the new century, two times of coronavirus “visiting” China has become a public health emergency, which has attracted great attention at home and abroad. At the critical time of epidemic prevention and control in SARS-CoV-2 infection, the excellent achievements of traditional Chinese medicine (TCM) show the advantages and contributions of TCM. In view of the complexity of the symptoms of patients with coronavirus infection, the diversity of organ and tissue damage and functional damage or failure, how to adapt to the needs of clinical prevention and treatment is not only a problem of modern medicine, but also a problem of TCM. In this review article, the authors combed the research of TCM prescription and single medicine after understanding the cause of coronavirus infection and pathogenicity and multiple organ dysfunction and failure caused by coronavirus. Based on the emphasis on the TCM scientific research and application, the TCM therapeutic effect on SARS-CoV-2 infection is discussed. The framework of new drug research and development based on possible “target” is proposed, and we put forward the ideas for researching new TCM products through the expanding molecular mechanism of infection.


title: The architecture of SARS-CoV-2 transcriptome

text: SARS-CoV-2 is a betacoronavirus that is responsible for the COVID-19 pandemic. The genome of SARS-CoV-2 was reported recently, but its transcriptomic architecture is unknown. Utilizing two complementary sequencing techniques, we here present a high-resolution map of the SARS-CoV-2 transcriptome and epitranscriptome. DNA nanoball sequencing shows that the transcriptome is highly complex owing to numerous recombination events, both canonical and noncanonical. In addition to the genomic RNA and subgenomic RNAs common in all coronaviruses, SARS-CoV-2 produces a large number of transcripts encoding unknown ORFs with fusion, deletion, and/or frameshift. Using nanopore direct RNA sequencing, we further find at least 41 RNA modification sites on viral transcripts, with the most frequent motif being AAGAA. Modified RNAs have shorter poly(A) tails than unmodified RNAs, suggesting a link between the internal modification and the 3′ tail. Functional investigation of the unknown ORFs and RNA modifications discovered in this study will open new directions to our understanding of the life cycle and pathogenicity of SARS-CoV-2. Highlights We provide a high-resolution map of SARS-CoV-2 transcriptome and epitranscriptome using nanopore direct RNA sequencing and DNA nanoball sequencing. The transcriptome is highly complex owing to numerous recombination events, both canonical and noncanonical. In addition to the genomic and subgenomic RNAs common in all coronaviruses, SARS-CoV-2 produces transcripts encoding unknown ORFs. We discover at least 41 potential RNA modification sites with an AAGAA motif.


Acute Stroke Management During the Coronavirus Disease 2019 (COVID-19) Pandemic: From Trough of Disillusionment to Slope of Enlightenment