title: Commercial stocks of SARS-CoV-2 RNA may report low concentration values, leading to artificially increased apparent sensitivity of diagnostic assays

text: In response to the rapidly evolving COVID-19 pandemic, the U.S. Food and Drug Administration (FDA) has rapidly issued 49 emergency use authorizations (EUAs) for SARS-CoV-2 in vitro diagnostic test-kits. A critical metric in the performance evaluation for a diagnostic test kit is the analytical sensitivity, which is measured by the limit of detection (LOD). Commercial RNA stocks with known titers are used to determine LOD. We identified a problem with the titer reported for the commercial stocks when examining the analytical sensitivity of the reverse transcription quantitative PCR (RT-qPCR) protocol that is recommended by the Centers for Disease Control and Prevention (CDC) using plasmid DNA from Integrated DNA Technologies (IDT), synthetic RNA from BEI Resources (BEI), and extracted genomic RNA from BEI. We detected 3/3 positives for reactions containing synthetic RNA at a concentration of 0.1 copies/reaction (based on the supplier's label concentration). The apparent better-than-single-molecule performance is a statistically highly unlikely event, indicating a potential inaccuracy in the supplier's quantification of the stock material. Using an ultrasensitive and precise assay, reverse transcription digital PCR (RT-dPCR), we independently quantified concentrations of commercial SARS-CoV-2 plasmid DNA and SARS-CoV-2 RNA stocks. For plasmid DNA, the actual concentration measured by RT-dPCR was 11% of the nominal label concentration. For synthetic RNA, the actual concentration measured by RT-dPCR for one lot was 770% of the label concentration and for a different lot was 57% of the label concentration. For genomic RNA, the concentration measured by RT-dPCR for one lot was 240% of the label concentration and for a different lot it was 300% of the label concentration. This SARS-CoV-2 genomic RNA from BEI Resources has been used in at least 11 approved FDA Emergency Use Authorizations as of April 27, 2020. Such deviations of reported RNA or DNA stock concentrations from true concentrations can result in inaccurate quantification and calculation of LOD. Precise and accurate reporting of DNA and RNA stock concentrations by commercial suppliers will enable accurate quantification of assay performance, which is urgently needed to improve evaluation of different assays by diagnostic developers and regulatory bodies.


title: County-level factors influence the trajectory of Covid-19 incidence

text: With new cases of Covid-19 surging in the United States, we need to better understand how the spread of novel coronavirus varies across all segments of the population. We use hierarchical exponential growth curve modeling techniques to examine whether community social and economic characteristics uniquely influence the incidence of Covid-19 cases in the urban built environment. We show that, as of May 3, 2020, confirmed coronavirus infections are concentrated along demographic and socioeconomic lines in New York City and surrounding areas, the epicenter of the Covid-19 pandemic in the United States. Furthermore, we see evidence that, after the onset of the pandemic, timely enactment of physical distancing measures such as school closures is imperative in order to limit the extent of the coronavirus spread in the population. Public health authorities must impose nonpharmaceutical measures early on in the pandemic and consider community-level factors that associate with a greater risk of viral transmission.


title: Bystander CD8 T-Cell-Mediated Demyelination is Interferon-γ-Dependent in a Coronavirus Model of Multiple Sclerosis

text: Mice infected with the coronavirus mouse hepatitis virus, strain JHM (JHM) develop a disease that shares many histological characteristics with multiple sclerosis. We previously demonstrated that JHM-infected mice that only have CD8 T cells specific for an epitope not in the virus develop demyelination on specific activation of these cells. Herein we show that this process of bystander T-cell-mediated demyelination is interferon-γ (IFN-γ)-dependent. The absence of IFN-γ abrogated demyelination but did not change T-cell infiltration or expression levels of inflammatory cytokines or chemokines in the spinal cord. These results are consistent with models in which IFN-γ contributes to CD8 T-cell-mediated demyelination by activation of macrophages/microglia, the final effector cells in the disease process.


title: Incubation period of COVID-19 in the live-house cluster of accurately known infection events and delay time from symptom onset of public reporting observed in cases in Osaka, Japan

text: The incubation period of an infectious disease is very important for control of the disease but estimating the period is not easy because the date of infection is not easy to identify. We report accurate incubation period distributions by examining cases in the cluster generated in live-houses in Osaka, Japan with known infection events. The distribution of the latent period was also estimated. The modes of incubation and latent periods of COVID-19 in Japan were 4.1 days and 3.3 days, respectively. The mode of the delay time from the onset to reporting was estimated to be 4.7 days, telling that the effects of interventions show up in the number of infections two weeks later after the measures.


title: Recent Understandings Toward Coronavirus Disease 2019 (COVID-19): From Bench to Bedside

text: In late December 2019, an unprecedented outbreak of coronavirus disease 2019 (COVID-19) caused by SARS coronavirus 2 (SARS-CoV-2) (previously named 2019-nCoV) in Wuhan became the most challenging health emergency. Since its rapid spread in China and many other countries, the World Health Organization (WHO) declared COVID-19 a public health emergency of international concern (PHEIC) on 30th January 2020 and a pandemic on 11th March 2020. Thousands of people have died, and there are currently no vaccines or specific antiviral drugs for COVID-19. Therefore, it is critical to have a comprehensive understanding of the virus. In this review, we highlight the etiology, epidemiology, pathogenesis and pathology, clinical characteristics, diagnosis, clinical management, prognosis, infection control and prevention of COVID-19 based on recent studies.


title: Comparing library preparation methods for SARS-CoV-2 multiplex amplicon sequencing on the Illumina MiSeq platform

text: Genomic surveillance has a key role in tracking the ongoing COVID-19 pandemic, but information on how different sequencing library preparation approaches affect the data produced are lacking. We compared three library preparation methods using both tagmentation (Nextera XT and Nextera Flex) and ligation-based (KAPA HyperPrep) approaches on both positive and negative samples to provide insights into any methodological differences between the methods, and validate their use in SARS-CoV-2 amplicon sequencing. We show that all three library preparation methods allow us to recover near-complete SARS-CoV-2 genomes with identical SNP calls. The Nextera Flex and KAPA library preparation methods gave better coverage than libraries prepared with Nextera XT, which required more reads to call the same number of genomic positions. The KAPA ligation-based approach shows the lowest levels of human contamination, but contaminating reads had no effect on the downstream analysis. We found some examples of library preparation-specific differences in minority variant calling. Overall our data shows that the choice of Illumina library preparation method has minimal effects on consensus base calling and downstream phylogenetic analysis, and suggests that all methods would be suitable for use if specific reagents are difficult to obtain.


title: Multiple drivers of the COVID-19 spread: role of climate, international mobility, and region-specific conditions

text: The novel Coronavirus Disease 2019 (COVID-19) has spread quickly across the globe. Here, we evaluated the role of climate (temperature and precipitation), region-specific susceptibility (BCG vaccination, malaria infection, and elderly population) and international traveller population (human mobility) in shaping the geographical patterns of COVID-19 cases across 1,055 countries/regions, and examined the sequential shift of multiple drivers of the accumulated cases from December, 2019 to April 12, 2020. The accumulated numbers of COVID-19 cases (per 1 million population) were well explained by a simple regression model. The explanatory power (R2) of the model increased up to > 70% in April 2020 as the COVID-19 spread progressed. Climate, host mobility, and host susceptibility largely explained the variance of the COVID-19 cases (per 1 million population), and their explanatory power improved as the pandemic progressed; the relative importance of host mobility and host susceptibility have been greater than that of climate. The number of days from outbreak onset showed greater explanatory power in the earlier stages of COVID-19 spread but rapidly lost its influence. Our findings demonstrate that the COVID-19 pandemic is deterministically driven by climate suitability, cross-border human mobility, and region-specific susceptibility. The present distribution of COVID-19 cases has not reached an equilibrium and is changing daily, especially in the Southern Hemisphere. Nevertheless, the present results, based on mapping the spread of COVID-19 and identifying multiple drivers of this outbreak trajectory, may contribute to a better understanding of the COVID-19 disease transmission risk and the measures against long-term epidemic.


Takotsubo Cardiomyopathy Caused by Intense Emotional Stress Induced by Voluntary Quarantine During the Coronavirus Disease Crisis


Sentencing Those Who Assault Emergency Workers: A Guideline-influenced Approach: R v Whelan [2020] EWCA Crim 195


title: Doxycycline and Hydroxychloroquine as Treatment for High-Risk COVID-19 Patients: Experience from Case Series of 54 Patients in Long-Term Care Facilities

text: Importance: Patients in long-term care facilities (LTCF) are at a high-risk of contracting COVID-19 due to advanced age and multiple comorbidities. Without effective treatments, outbreaks in such facilities will become commonplace and will result in severe morbidity and mortality. The effectiveness of doxycycline (DOXY) and hydroxychloroquine (HCQ) combination therapy in high risk COVID-19 patients in long-term care facilities is not yet understood. Objective: The goal of this analysis is to describe outcomes after use of DOXY-HCQ combination in high-risk COVID-19 patients in LTCF. Design: Case-series analysis. Setting: Three (3) LTCFs in New York. Participants: From March 19 to March 30, 2020, fifty-four (54) patients, residents of three (3) LTCFs in New York and diagnosed (confirmed or presumed) with COVID-19, were included in this analysis. Exposure: All patients who were diagnosed (confirmed or presumed) with COVID-19 received DOXY-HCQ combination therapy along with standard of care. Main Outcomes and Measures: Patients characteristics, clinical recovery, radiological improvements, medication side-effects, hospital transfer, and death were assessed as outcome measures. Results: A series of fifty-four (54) high-risk patients, who developed a sudden onset of fever, cough, and shortness of breath (SOB) and were diagnosed or presumed to have COVID-19, were started with a combination of DOXY-HCQ and 85% (n=46) patients showed clinical recovery defined as: resolution of fever and SOB, or a return to baseline setting if patients are ventilator-dependent. A total of 11% (n=6) patients were transferred to acute care hospitals due to clinical deterioration and 6% (n=3) patients died in the facilities. Naive Indirect Comparison suggests these data were significantly better outcomes than the data reported in MMWR (reported on March 26, 2020) from a long-term care facility in King County, Washington where 57% patients were hospitalized, and 22% patients died. Conclusion: The clinical experience of this case series indicates DOXY-HCQ treatment in high-risk COVID-19 patients is associated with a reduction in clinical recovery, decreased transfer to hospital and decreased mortality were observed after treatment with DOXY-HCQ.


Mathematical modelling of COVID-19 in South Africa


title: Accurate Identification of SARS-CoV-2 from Viral Genome Sequences using Deep Learning

text: One of the reasons for the fast spread of SARS-CoV-2 is the lack of accuracy in detection tools in the clinical field. Molecular techniques, such as quantitative real-time RT-PCR and nucleic acid sequencing methods, are widely used to identify pathogens. For this particular virus, however, they have an overall unsatisfying detection rate, due to its relatively recent emergence and still not completely understood features. In addition, SARS-CoV-2 is remarkably similar to other Coronaviruses, and it can present with other respiratory infections, making identification even harder. To tackle this issue, we propose an assisted detection test, combining molecular testing with deep learning. The proposed approach employs a state-of-the-art deep convolutional neural network, able to automatically create features starting from the genome sequence of the virus. Experiments on data from the Novel Coronavirus Resource (2019nCoVR) show that the proposed approach is able to correctly classify SARS-CoV-2, distinguishing it from other coronavirus strains, such as MERS-CoV, HCoV-NL63, HCoV-OC43, HCoV-229E, HCoV-HKU1, and SARS-CoV regardless of missing information and errors in sequencing (noise). From a dataset of 553 complete genome non-repeated sequences that vary from 1,260 to 31,029 bps in length, the proposed approach classifies the different coronaviruses with an average accuracy of 98.75% in a 10-fold cross-validation, identifying SARS-CoV-2 with an AUC of 98%, specificity of 0.9939 and sensitivity of 1.00 in a binary classification. Then, using the same basis, we classify SARS-CoV-2 from 384 complete viral genome sequences with human host, that contain the gene ORF1ab from the NCBI with a 10-fold accuracy of 98.17%, a specificity of 0.9797 and sensitivity of 1.00. Furthermore, an in-depth analysis of the results allow us to identify base pairs sequences that are unique to SARS-CoV-2 and do not appear in other virus strains, that could then be used as a base for designing new primers and examined by experts to extract further insights. These preliminary results seem encouraging enough to identify deep learning as a promising research venue to develop assisted detection tests for SARS-CoV-2. At this end the interaction between viromics and deep learning, will hopefully help to solve global infection problems. In addition, we offer our code and processed data to be used for diagnostic purposes by medical doctors, virologists and scientists involved in solving the SARS-CoV-2 pandemic. As more data become available we will update our system.


title: Anemia and iron metabolism in COVID-19: A systematic review and meta-analysis

text: Iron metabolism and anemia may play an important role in multiple organ dysfunction syndrome in Coronavirus disease 2019 (COVID-19). If confirmed, this has important implications for the more than 1.62 billion people estimated to have anemia globally. We conducted a systematic review and meta-analysis to evaluate biomarkers of anemia and iron metabolism (hemoglobin, ferritin, transferrin, soluble transferrin receptor, hepcidin, haptoglobin, unsaturated iron-binding capacity, erythropoietin, free erythrocyte protoporphyrine, and prevalence of anemia) in patients diagnosed with COVID-19, and explore their prognostic value. Six bibliographic databases were searched up to May 5th 2020. We included 56 unique studies, with data from 14,044 COVID-19 patients (59 years median age). Pooled mean hemoglobin and ferritin levels in COVID-19 patients across all ages were 130.41 g/L (95% Confidence Interval (CI), 128.42; 132.39) and 673.91 ng/mL (95% CI, 420.98; 926.84), respectively. Hemoglobin levels decreased with advancing age and increasing percentage of comorbid and critically ill patients, while levels of ferritin increased with increasing male proportion and mean hemoglobin levels. Compared to moderate cases, severe cases had lower pooled mean hemoglobin [weighted mean difference (WMD), -4.21 (95% CI -6.63; -1.78)] and higher ferritin [WMD, -730.55 ng/mL (95% CI 413.24; 1047.85)]. A significant difference in mean ferritin level of 1027.23 ng/mL (95% CI 819.53; 1234.94) was found between survivors and non-survivors, but not in hemoglobin levels. No studies provided information on anemia or other biomarkers of interest. Future studies should explore the impact of iron metabolism and anemia and in the pathophysiology, prognosis, and treatment of COVID-19.


Sars-CoV-2 (COVID-19) outbreak and breast cancer surgery in Turkey


Basismaßnahmen und erweiterte Maßnahmen zur Wiederbelebung von Kindern: COVID-19-Leitlinien des European Resuscitation Council


title: US chemical output to drop this year

text: The US economy, now under a wide-ranging shutdown due to the novel coronavirus, is likely to shrink 4% this year And US chemical manufacturing will decline by a similar amount, according to a forecast from the American Chemistry Council, the industry’s main trade group In response, the ACC says, chemical firms will cut jobs and hold off on business investment The council estimates that US chemical output will fall by around 3 3% in 2020 if shutdowns are lifted before the end of June, but output could drop by 6 5% if shutdowns last through the fourth quarter The figures do not include pharmaceuticals In December, the association had projected output to rise slightly this year The decline is due not only to public health–motivated shutdowns in the US, but also to unprecedented moves by other governments to restrict the activities of business and consumers “The resulting sudden and severe collapse in


title: COVID-19: Easing the coronavirus lockdowns with caution

text: Background: The spread of the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2) has reached a global level, creating a pandemic. The government of various countries, their citizens, politicians, and business owners are worried about the unavoidable economic impacts of this pandemic. Therefore, there is an eagerness for the pandemic peaking. Objectives: This study uses an objective approach to emphasize the need to be pragmatic with easing of lockdowns measures worldwide through the forecast of the possible trend of COVID-19. This is necessary to ensure that the enthusiasm about SARS-CoV-2 peaking is properly examined, easing of lockdown is done systematically to avoid second-wave of the pandemic. Methods: We used the Facebook prophet on the World Health Organization data for COVID-19 to forecast the spread of SARS-CoV-2 for the 7th April until 3rd May 2020. The forecast model was further used to forecast the trend of the virus for the 8th until 14th May 2020. We presented the forecast of the confirmed and death cases. Results: Our findings from the forecast showed an increase in the number of new cases for this period. Therefore, the need for easing the lockdown with caution becomes imperative. Our model showed good performance when compared to the official report from the World Health Organization. The average forecasting accuracy of our model was 79.6%. Conclusion: Although, the global and economic impact of COVID-19 is daunting. However, excessive optimism about easing the lockdown should be appropriately weighed against the risk of underestimating its spread. As seen globally, the risks appeared far from being symmetric. Therefore, the forecasting provided in this study offers an insight into the spread of the virus for effective planning and decision-making in terms of easing the lockdowns in various countries.


title: ‘These are answers we need.’ WHO plans global study to discover true extent of coronavirus infections

text: In an effort to understand how many people have been infected with the new coronavirus, the World Health Organization (WHO) is planning a coordinated study to test blood samples for the presence of antibodies to the virus Called Solidarity II, the program, which will involve more than half a dozen countries around the globe, will launch in the coming days, says Maria Van Kerkhove, who is helping coordinate WHO’s COVID-19 response Knowing the true number of cases—including mild ones—will help pin down the prevalence and mortality rate of COVID-19 in different age groups It will also help policymakers decide how long shutdowns and quarantines should last “These are answers we need, and we need the right answers to drive policy,” WHO’s executive director for health emergencies, Michael Ryan, told a press briefing on 27 March


title: Change points in the spread of COVID-19 question the effectiveness of nonpharmaceutical interventions in Germany

text: Aims: Nonpharmaceutical interventions against the spread of SARS-CoV-2 in Germany included the cancellation of mass events (from March 8), closures of schools and child day care facilities (from March 16) as well as a "lockdown" (from March 23). This study attempts to assess the effectiveness of these interventions in terms of revealing their impact on infections over time. Methods: Dates of infections were estimated from official German case data by incorporating the incubation period and an empirical reporting delay. Exponential growth models for infections and reproduction numbers were estimated and investigated with respect to change points in the time series. Results: A significant decline of daily and cumulative infections as well as reproduction numbers is found at March 8 (CI [7, 9]), March 10 (CI [9, 11] and March 3 (CI [2, 4]), respectively. Further declines and stabilizations are found in the end of March. There is also a change point in new infections at April 19 (CI [18, 20]), but daily infections still show a negative growth. From March 19 (CI [18, 20]), the reproduction numbers fluctuate on a level below one. Conclusions: The decline of infections in early March 2020 can be attributed to relatively small interventions and voluntary behavioural changes. Additional effects of later interventions cannot be detected clearly. Liberalizations of measures did not induce a re-increase of infections. Thus, the effectiveness of most German interventions remains questionable. Moreover, assessing of interventions is impeded by the estimation of true infection dates and the influence of test volume.


title: Machine learning-based CT radiomics model for predicting hospital stay in patients with pneumonia associated with SARS-CoV-2 infection: A multicenter study

text: Abstract Objectives To develop and test machine learning-based CT radiomics models for predicting hospital stay in patients with pneumonia associated with SARS-CoV-2 infection. Design Cross-sectional Setting Multicenter Participants A total of 52 patients with laboratory-confirmed SARS-CoV-2 infection and their initial CT images were enrolled from 5 designated hospitals in Ankang, Lishui, Zhenjiang, Lanzhou, and Linxia between January 23, 2020 and February 8, 2020. As of February 20, patients remained in hospital or with non-findings in CT were excluded. Therefore, 31 patients with 72 lesion segments were included in the final analysis. Intervention CT radiomics models based on logistic regression (LR) and random forest (RF) were developed on features extracted from pneumonia lesions in training and inter-validation datasets. The predictive performance was further evaluated in test dataset on lung lobe- and patients-level. Main outcomes Short-term hospital stay (≤10 days) and long-term hospital stay (>10 days). Results The CT radiomics models based on 6 second-order features were effective in discriminating short- and long-term hospital stay in patients with pneumonia associated with SARS-CoV-2 infection, with areas under the curves of 0.97 (95%CI 0.83-1.0) and 0.92 (95%CI 0.67-1.0) by LR and RF, respectively, in the test dataset. The LR model showed a sensitivity and specificity of 1.0 and 0.89, and the RF model showed similar performance with sensitivity and specificity of 0.75 and 1.0 in test dataset. Conclusions The machine learning-based CT radiomics models showed feasibility and accuracy for predicting hospital stay in patients with pneumonia associated with SARS-CoV-2 infection.


title: Characteristics and Mechanism of Liver Injury in 2019 Coronavirus Disease

text: An outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (2019 coronavirus disease, COVID-19) since December 2019, from Wuhan, China, has been posing a significant threat to global human health. The clinical features and outcomes of Chinese patients with COVID-19 have been widely reported. Increasing evidence has witnessed the frequent incident liver injury in COVID-19 patients, and it is often manifested as transient elevation of serum aminotransferases; however, the patients seldom have liver failure and obvious intrahepatic cholestasis, unless pre-existing advanced liver disease was present. The underlying mechanisms of liver injury in cases of COVID-19 might include psychological stress, systemic inflammation response, drug toxicity, and progression of pre-existing liver diseases. However, there is insufficient evidence for SARS-CoV-2 infected hepatocytes or virus-related liver injury in COVID-19 at present. The clinical, pathological and laboratory characteristics as well as underlying pathophysiology and etiology of liver injury in COVID-19 remain largely unclear. In this review, we highlight these important issues based on the recent developments in the field, for optimizing the management and treatment of liver injury in Chinese patients with COVID-19.


title: coronapp: A Web Application to Annotate and Monitor SARS-CoV-2 Mutations

text: The avalanche of genomic data generated from the SARS-CoV-2 virus requires the development of tools to detect and monitor its mutations across the World. Here, we present a webtool, coronapp, dedicated to easily processing user-provided SARS-CoV-2 genomic sequences, in order to detect and annotate protein-changing mutations. This results in an up-to-date status of SARS-CoV-2 mutations, both worldwide and in user-selected countries. The tool allows users to highlight and prioritize the most frequent mutations in specific protein regions, and to monitor their frequency in the population over time. The tool is available at http://giorgilab.dyndns.org/coronapp/ and the full code is freely shared at https://github.com/federicogiorgi/giorgilab/tree/master/coronapp


title: Transient ST Segment Elevation in Two Patients with COVID-19 and a Normal Transthoracic Echocardiogram

text: We continue to learn about cardiac involvement in patients with COVID-19. These patients can develop acute coronary syndrome and severe myocarditis with a reduced ejection fraction. We describe two critically ill COVID-19 patients who developed ST elevation that resolved on repeat ECG without any intervention. LEARNING POINT: ST elevation may occur in critically ill COVID-19 patients.


title: A phenome-wide association study (PheWAS) of COVID-19 outcomes by race using the electronic health records data in Michigan Medicine

text: Blacks/African Americans are overrepresented in the number of hospitalizations and deaths from COVID-19 in the United States, which could be explained through differences in the prevalence of existing comorbidities. We performed a disease-disease phenome-wide association study (PheWAS) using data representing 5,698 COVID-19 patients from a large academic medical center, stratified by race. We explore the association of 1,043 pre-occurring conditions with several COVID-19 outcomes: testing positive, hospitalization, ICU admission, and mortality. Obesity, iron deficiency anemia and type II diabetes were associated with susceptibility in the full cohort, while ill-defined descriptions/complications of heart disease and stage III chronic kidney disease were associated among non-Hispanic White (NHW) and non-Hispanic Black/African American (NHAA) patients, respectively. The top phenotype hits in the full, NHW, and NHAA cohorts for hospitalization were acute renal failure, hypertension, and insufficiency/arrest respiratory failure, respectively. Suggestive relationships between respiratory issues and COVID-19-related ICU admission and mortality were observed, while circulatory system diseases showed stronger association in NHAA patients. We were able to replicate some known comorbidities related to COVID-19 outcomes while discovering potentially unknown associations, such as endocrine/metabolic conditions related to hospitalization and mental disorders related to mortality, for future validation. We provide interactive PheWAS visualization for broader exploration.


title: Patterns of the COVID19 epidemic spread around the world: exponential vs power laws

text: We have analyzed the COVID19 epidemic data of more than 174 countries (excluding China) in the period between January 22 and March 28, 2020. We found that some countries (such as the US, the UK, and Canada) follow an exponential epidemic growth, while others (like Italy and several other European countries) show a power law like growth. At the same time, regardless of the best fitting law, most countries can be shown to follow a trajectory similar to that of Italy, but with varying degrees of delay. We found that countries with ``younger" epidemics tend to exhibit more exponential like behavior, while countries that are closer behind Italy tend to follow a power law growth. We hypothesize that there is a universal growth pattern of this infection that starts off as exponential and subsequently becomes more power law like. Although it cannot be excluded that this growth pattern is a consequence of social distancing measures, an alternative explanation is that it is an intrinsic epidemic growth law, dictated by a spatially distributed community structure, where the growth in individual highly mixed communities is exponential but the longer term, local geographical spread (in the absence of global mixing) results in a power-law. This is supported by computer simulations of a metapopulation model that gives rise to predictions about the growth dynamics that are consistent with correlations found in the epidemiological data. Therefore, seeing a deviation from straight exponential growth may not be a consequence of working non-pharmaceutical interventions (except for, perhaps, restricting the air travel). Instead, this is a normal course of raging infection spread. On the practical side, this cautions us against overly optimistic interpretations of the countries epidemic development and emphasizes the need to continue improving the compliance with social distancing behavior recommendations.


title: Ethnic and socioeconomic differences in SARS-CoV2 infection in the UK Biobank cohort study

text: Background Understanding of the role of ethnicity and socioeconomic position in the risk of developing SARS-CoV-2 infection is limited. We investigated this in the UK Biobank study. Methods The UK Biobank study recruited 40-70 year olds in 2006-2010 from the general population, collecting information about self-defined ethnicity and socioeconomic variables (including Townsend deprivation index and educational attainment). SARS-CoV-2 test results from Public Health England were linked to baseline UK Biobank data. Poisson regression with robust standard errors was used to assess risk ratios (RRs) between the exposures and dichotomous variables for: being tested, having a positive test and testing positive in hospital. We also investigated whether ethnicity and socioeconomic position were associated with having a positive test amongst those tested. We adjusted for covariates including age, sex, social variables (including healthcare work and household size), behavioural risk factors and baseline health. Findings Among 428,225 participants, 1,474 had been tested and 669 had tested positive between 16 March and 13 April 2020. Black, south Asian and white Irish people were more likely to have confirmed infection (RR 4.01 (95%CI 2.92-5.12); RR 2.11 (95%CI 1.43-3.10); and RR 1.60 (95% CI 1.08-2.38) respectively) and were more likely to be hospitalised compared to White British. While they were more likely to be tested, they were also more likely to test positive. Adjustment for baseline health and behavioural risk factors led to little change, with only modest attenuation when accounting for socioeconomic variables. Area socioeconomic deprivation and having no qualifications were consistently associated with a higher risk of confirmed infection (RR 1.91 (95%CI 1.53-2.38); and RR 2.26 (95%CI 1.76-2.90) respectively). Interpretation Some minority ethnic groups have a higher risk of confirmed SARS-CoV-2 infection in the UK Biobank study which was not accounted for by differences in socioeconomic conditions, measured baseline health or behavioural risk factors. An urgent response to addressing these elevated risks is required. Funding Medical Research Council, Chief Scientist Office.


title: ACE2 and TMPRSS2 expression by clinical, HLA, immune, and microbial correlates across 34 human cancers and matched normal tissues: implications for SARS-COV-2 COVID-19

text: Background: Pandemic COVID-19 by SARS-COV-2 infection is facilitated by the ACE2 receptor and protease TMPRSS2. Modestly sized case series have described clinical factors associated with COVID-19, while ACE2 and TMPRSS2 expression analyses have been described in some cell types. Cancer patients may have worse outcomes to COVID-19. Methods: We performed an integrated study of ACE2 and TMPRSS2 gene expression across and within organ systems, by normal versus tumor, across several existing databases (The Cancer Genome Atlas, Census of Immune Single Cell Expression Atlas, The Human Cell Landscape, and more). We correlated gene expression with clinical factors (including but not limited to age, gender, race, BMI and smoking history), HLA genotype, immune gene expression patterns, cell subsets, and single-cell sequencing as well as commensal microbiome. Results: Matched normal tissues generally display higher ACE2 and TMPRSS2 expression compared with cancer, with normal and tumor from digestive organs expressing the highest levels. No clinical factors were consistently identified to be significantly associated with gene expression levels though outlier organ systems were observed for some factors. Similarly, no HLA genotypes were consistently associated with gene expression levels. Strong correlations were observed between ACE2 expression levels and multiple immune gene signatures including interferon-stimulated genes and the T cell-inflamed phenotype as well as inverse associations with angiogenesis and transforming growth factor-{beta} signatures. ACE2 positively correlated with macrophage subsets across tumor types. TMPRSS2 was less associated with immune gene expression but was strongly associated with epithelial cell abundance. Single-cell sequencing analysis across nine independent studies demonstrated little to no ACE2 or TMPRSS2 expression in lymphocytes or macrophages. ACE2 and TMPRSS2 gene expression associated with commensal microbiota in matched normal tissues particularly from colorectal cancers, with distinct bacterial populations showing strong associations. Conclusions: We performed a large-scale integration of ACE2 and TMPRSS2 gene expression across clinical, genetic, and microbiome domains. We identify novel associations with the microbiota and confirm host immunity associations with gene expression. We suggest caution in interpretation regarding genetic associations with ACE2 expression suggested from smaller case series.


title: Pharmacological inhibition of lysine-specific demethylase 1 (LSD1) induces global transcriptional deregulation and ultrastructural alterations that impair viability in Schistosoma mansoni

text: Treatment and control of schistosomiasis still rely on only one effective drug, praziquantel (PZQ), and due to mass treatment, the increasing risk of selecting for schistosome strains that are resistant to PZQ has alerted investigators to the urgent need to develop novel therapeutic strategies. The histone-modifying enzymes (HMEs) represent promising targets for the development of epigenetic drugs against Schistosoma mansoni. In the present study, we targeted the S. mansoni lysine-specific demethylase 1 (SmLSD1), a transcriptional corepressor, using a novel and selective synthetic inhibitor, MC3935. We synthesized a novel and potent LSD1 inhibitor, MC3935, which was used to treat schistosomula or adult worms in vitro. By using cell viability assays and optical and electron microscopy, we showed that treatment with MC3935 affected parasite motility, egg-laying, tegument, and cellular organelle structures, culminating in the death of schistosomula and adult worms. In silico molecular modeling and docking analysis suggested that MC3935 binds to the catalytic pocket of SmLSD1. Western blot analysis revealed that MC3935 inhibited SmLSD1 demethylation activity of H3K4me1/2. Knockdown of SmLSD1 by RNAi recapitulated MC3935 phenotypes in adult worms. RNA-seq analysis of MC3935-treated parasites revealed significant differences in gene expression related to critical biological processes. Collectively, our findings show that SmLSD1 is a promising drug target for the treatment of schistosomiasis and strongly support the further development and in vivo testing of selective schistosome LSD1 inhibitors. Author Summary Schistosomiasis mansoni is a chronic and debilitating tropical disease caused by the helminth Schistosoma mansoni. The control and treatment of the disease rely almost exclusively on praziquantel (PZQ). Thus, there is an urgent need to search for promising protein targets to develop new drugs. Drugs that inhibit enzymes that modify the chromatin structure have been developed for a number of diseases. We and others have shown that S. mansoni epigenetic enzymes are also potential therapeutic targets. Here we evaluated the potential of the S. mansoni histone demethylase LSD1 (SmLSD1) as a drug target. We reported the synthesis of a novel and potent LSD1 inhibitor, MC3935, and show that it selectively inhibited the enzymatic activity of SmLSD1. Treatment of juvenile or adult worms with MC3935 caused severe damage to the tegument of the parasites and compromised egg production. Importantly, MC3935 proved to be highly toxic to S. mansoni, culminating in the death of juvenile or adult worms within 96 h. Transcriptomic analysis of MC3935-treated parasites revealed changes in the gene expression of hundreds of genes involved in key biological processes. Importantly, SmLSD1 contains unique sequences within its polypeptide chain that could be explored to develop a S. mansoni selective drug.


title: Higher clinical acuity and 7-day hospital mortality in non-COVID-19 acute medical admissions: prospective observational study.

text: Abstract Objectives: To understand the effect of COVID-19 lockdown measures on severity of illness and mortality in non-COVID-19 acute medical admissions. Design: A prospective observational study Setting: 3 large acute medical receiving units in NHS Lothian, Scotland. Participants: Non-covid-19 acute admissions (n = 1756) were examined over the first 31 days after the implementation of the COVID-19 lockdown policy in the United Kingdom on 23rd March 2019. Patients admitted over a matched interval in the previous 5 years were used as a comparator cohort (n = 14961). Main outcome measures: Patient demography, biochemical markers of clinical acuity and 7-day hospital inpatient mortality. Results: Non-covid-19 acute medical admissions reduced by a mean 43.8% (95% CI 27.3, 59.4) across all 3 sites in comparison to the mean of the preceding 5 years P < 0.001. The reduction in admissions predominated in the over 75 age category and a greater proportion arrived by emergency ambulance transport. Non-covid-19 admissions during lockdown had a greater incidence of severe renal injury, hyperlactataemia and over twice the risk of hospital death within 7 days 5.01% vs 2.49% which persisted after adjustment for confounders (OR 2.17, 95% CI 1.70,2.73, P < 0.0001) Conclusions: These data support current fears that patients are delaying seeking medical attention for acute illness which is associated with worsening clinical parameters and a higher risk of death following admission.


title: Forecasting Novel Corona Positive Cases in Indiausing Truncated Information: A Mathematical Approach

text: Novel corona virus is declared as pandemic and India is struggling to control this from a massive attack of death and destruction, similar to the other countries like China, Europe, and the United States of America. India reported 2545 cases novel corona confirmed cases as of April 2, 2020 and out of which 191 cases were reported recovered and 72 deaths occurred. The first case of novel corona is reported in India on January 30, 2020. The growth in the initial phase is following exponential. In this study an attempt has been made to model the spread of novel corona infection. For this purpose logistic growth model with minor modification is used and the model is applied on truncated information on novel corona confirmed cases in India. The result is very exiting that till date predicted number of confirmed corona positive cases is very close to observed on. The time of point of inflexion is found in the end of the April, 2020 means after that the increasing growth will start decline and there will be no new case in India by the end of July, 2020.


title: The nexus of travel restriction, air pollution and COVID-19 infection: Investigation from a megacity of the southern China

text: To control and prevent the spread of COVID-19, generalized social distancing measures, such as traffic control and travel restriction acted in China. Previous studies indicated that the traffic conditions had significant influence on the air quality, and which was related to the respiratory diseases. This study aimed to reveal the nexus of travel restriction, air pollution and COVID-19. Shenzhen, one of the top 4 megacities in China was considered as the study area, statistical analysis methods, including linear/nonlinear regression and bivariate correlation was conducted to evaluate the relationship of the traffic and passenger population, travel intensity, NO2, PM10, PM2.5 and the number of COVID-19 confirmed cases. The results suggested that traffic control and travel restriction had a significant correlation with the number of COVID-19 confirmed cases, which shown negative correlation with the traffic intensity of the city, NO2, PM10 and PM2.5 show significant positive correlation with the traffic intensity, traffic control and travel restriction would slow down and prevent the spread of the viruses at the outbreak period. Different study scale might results in different results, thus the research focused on the nexus of traffic control and travel restriction, air pollution and COVID-19 should been enhanced in future, and differentiated epidemic control and prevention measures should be considered according to the different situation of cities as well as countries.


title: Atlas of ACE2 gene expression in mammals reveals novel insights in transmisson of SARS-Cov-2

text: Background COVID-19 has become a worldwide pandemic. It is caused by a novel coronavirus named SARS-CoV-2 with elusive origin. SARS-CoV-2 infects mammalian cells by binding to ACE2, a transmembrane protein. Therefore, the conservation of ACE2 and its expression pattern across mammalian species, which are yet to be comprehensively investigated, may provide valuable insights into tracing potential hosts of SARS-CoV-2. Methods We analyzed gene conservation of ACE2 across mammals and collected more than 140 transcriptome datasets from human and common mammalian species, including presumed hosts of SARS-CoV-2 and other animals in close contact with humans. In order to enable comparisons across species and tissues, we used a unified pipeline to quantify and normalize ACE2 expression levels. Results We first found high conservation of ACE2 genes among common mammals at both DNA and peptide levels, suggesting that a broad range of mammalian species can potentially be the hosts of SARS-CoV-2. Next, we showed that high level of ACE2 expression in certain human tissues is consistent with clinical symptoms of COVID-19 patients. Furthermore, we observed that ACE2 expressed in a species-specific manner in the mammals examined. Notably, high expression in skin and eyes in cat and dog suggested that these animals may play roles in transmitting SARS-CoV-2 to humans. Conclusions Through building the first atlas of ACE2 expression in pets and livestock, we identified species and tissues susceptible to SARS-CoV-2 infection, yielding novel insights into the viral transmission.


title: Identification of Drugs Blocking SARS-CoV-2 Infection using Human Pluripotent Stem Cell-derived Colonic Organoids

text: The current COVID-19 pandemic is caused by SARS-coronavirus 2 (SARS-CoV-2). There are currently no therapeutic options for mitigating this disease due to lack of a vaccine and limited knowledge of SARS-CoV-2 biology. As a result, there is an urgent need to create new disease models to study SARS-CoV-2 biology and to screen for therapeutics using human disease-relevant tissues. COVID-19 patients typically present with respiratory symptoms including cough, dyspnea, and respiratory distress, but nearly 25% of patients have gastrointestinal indications including anorexia, diarrhea, vomiting, and abdominal pain. Moreover, these symptoms are associated with worse COVID-19 outcomes1. Here, we report using human pluripotent stem cell-derived colonic organoids (hPSC-COs) to explore the permissiveness of colonic cell types to SARS-CoV-2 infection. Single cell RNA-seq and immunostaining showed that the putative viral entry receptor ACE2 is expressed in multiple hESC-derived colonic cell types, but highly enriched in enterocytes. Multiple cell types in the COs can be infected by a SARS-CoV-2 pseudo-entry virus, which was further validated in vivo using a humanized mouse model. We used hPSC-derived COs in a high throughput platform to screen 1280 FDA-approved drugs against viral infection. Mycophenolic acid and quinacrine dihydrochloride were found to block the infection of SARS-CoV-2 pseudo-entry virus in COs both in vitro and in vivo, and confirmed to block infection of SARS-CoV-2 virus. This study established both in vitro and in vivo organoid models to investigate infection of SARS-CoV-2 disease-relevant human colonic cell types and identified drugs that blocks SARS-CoV-2 infection, suitable for rapid clinical testing.


title: Prediction of specific cutting forces and maximum tool temperatures in orthogonal machining by Support Vector and Gaussian Process Regression Methods

text: Abstract In this paper, machine learning (ML) models, namely Support Vector Regression (SVR) and Gaussian Process Regression (GPR), are presented for the prediction of specific cutting forces and maximum tool temperatures during orthogonal machining processes. The training/test data for building the ML models is generated from finite element (FE) simulations. The simulations are performed using the commercial FE package Abaqus/Explicit and validated using experimental results. The FE generated data consists of cutting speed, uncut chip thickness, and rake angle as the input parameters. The response variables are the cutting force and maximum tool temperature. The data is split into training and test sets using 80-20 split. The optimal SVR and GPR models are selected using grid search on the training data. The predictions on the test data sets show that both the models perform well with high accuracy in predicting cutting force and maximum tool temperature. Between the two models, the mean square errors (MSE) for SVR are less than those for GPR.


title: A molecular pore spans the double membrane of the coronavirus replication organelle

text: Coronavirus genome replication is associated with virus-induced cytosolic double-membrane vesicles, which may provide a tailored micro-environment for viral RNA synthesis in the infected cell. However, it is unclear how newly synthesized genomes and mRNAs can travel from these sealed replication compartments to the cytosol to ensure their translation and the assembly of progeny virions. Here, using cellular electron cryo-microscopy, we unveiled a molecular pore complex that spans both membranes of the double-membrane vesicle and would allow export of RNA to the cytosol. A hexameric assembly of a large viral transmembrane protein was found to form the core of the crown-shaped complex. This coronavirus-specific structure likely plays a critical role in coronavirus replication and thus constitutes a novel drug target


title: What influences COVID-19 infection rates: A statistical approach to identify promising factors applied to infection data from Germany

text: The recent COVID-19 pandemic is of big and world-wide concern. There is an intense discussion and uncertainty which factors and sanctions can reduce infection rates. The overall aim is to prevent an overload of the medical system. Even within one country, there is frequently a strong local variability in both -- political sanctions as well as other local factors -- which may influence infection rates. The main focus of study is analysis and interpretation of recent temporal developments (infection rates). We present a statistical framework designed to identify local factors which reduce infection rates. The approach is robust with respect to the number of undetected infection cases. We apply the framework to spatio-temporal infection data from Germany. In particular, we demonstrate that (1) infection rates are in average significantly decreasing in Germany; (2) there is a high spatial variability of these rates, and (3) both, early emergence of first infections and high local infection densities has led to strong recent decays in infection rates, suggesting that psychological effects (such as awareness of danger) lead to behaviour changes that reduce infection rates. However, the full potential of the presented method cannot yet be exploited, since more precise spatio-temporal data, such as local cell phone-based mobility data, are not yet available. In the nearest future, the presented framework could be applied to data from other countries at any state of infection, even during the exponential phase of the growth of infection rates.


title: Concerns on the Emerging Research of SARS-CoV-2 on Felines: Could They be Significant Hosts/Reservoirs?

text: With the growing evidence of cases and studies showing natural and experimental infection due to SARS-CoV-2 in felines, including cats, lion, and tigers, there is also an increasing concern about its susceptibility and their role in urban cycles of SARS-CoV-2 transmission, initially from humans-to-animals, but with uncertainty about reverse transmission In this review, we addressed the evidence around this situation


title: Impact of ethnicity on outcome of severe COVID-19 infection. Data from an ethnically diverse UK tertiary centre

text: During the current COVID-19 pandemic, anecdotal reports suggest that BAME background patients may be disproportionately affected compared to White but few objective data are available. We took advantage of near real-time hospital data access and analysis pipelines to look at the impact of ethnicity in 437 consecutive patients admitted during March to Kings College Hospital NHS Trust in London. Our key findings are firstly that BAME patients are significantly younger and have different co-morbidity profiles than White individuals. Secondly, there is no significant effect of ethnicity itself on severe outcomes (death or ITU admission) within 14-days of symptom onset, with adjustment for age, sex, comorbidities.


title: Evaluating new evidence in the early dynamics of the novel coronavirus COVID-19 outbreak in Wuhan, China with real time domestic traffic and potential asymptomatic transmissions

text: The novel coronavirus (COVID-19), first detected in Wuhan, China in December 2019, has spread to 28 countries/regions with over 43,000 confirmed cases. Much about this outbreak is still unknown. At this early stage of the epidemic, it is important to investigate alternative sources of information to understand its dynamics and spread. With updated real time domestic traffic, this study aims to integrate recent evidence of international evacuees extracted from Wuhan between Jan. 29 and Feb. 2, 2020 to infer the dynamics of the COVD-19 outbreak in Wuhan. In addition, a modified SEIR model was used to evaluate the empirical support for the presence of asymptomatic transmissions. Based on the data examined, this study found little evidence for the presence of asymptomatic transmissions. However, it is still too early to rule out its presence conclusively due to sample size and other limitations. The updated basic reproductive number was found to be 2.12 on average with a 95% credible interval of [2.04, 2.18]. It is smaller than previous estimates probably because the new estimate factors in the social and non-pharmaceutical mitigation implemented in Wuhan through the evacuee dataset. Detailed predictions of infected individuals exported both domestically and internationally were produced. The estimated case confirmation rate has been low but has increased steadily to 23.37% on average. The findings of this study depend on the validity of the underlying assumptions, and continuing work is needed, especially in monitoring the current infection status of Wuhan residents.


title: The influence of comorbidity on the severity of COVID-19 disease: systematic review and analysis

text: A novel form of coronavirus disease (SARS-CoV-2) has spread rapidly across the world. This disease, originating in Wuhan, China, has become a global pandemic. What risk factors influence the severity of the disease is of considerable importance. This research is intended to offer a systematic review/meta-analysis for assessing how common clinical conditions and comorbidities correlate with COVID-19. The meta-analysis incorporated seven studies covering 4101 COVID-19 patients from Chinese hospitals who had their diagnosis confirmed through laboratory testing. The findings demonstrate that the most common comorbidities with the disease were COPD (2.53%, OR 3.24 [95% CI: 1.99-4.45], p< 0.0006), cardiovascular disease (10.76%, OR 2.89 [95% CI: 1.90-4.40], p <0.0001), coronary heart disease (5.52%, OR 2.97 [95% CI: 1.99-4.45], p <0.0001), diabetes (11.34%, OR 2.27, [95% CI: 1.46-3.53], p = 0.0003), and hypertension (22.07%, OR 2.43 [95% CI: 1.71-3.45], p <0.0001). No significant associations were found for disease severity with the comorbidities of kidney disease, liver disease, or cancer. The most frequently exhibited clinical symptoms were fever (74.52%, OR 1.37, 95% CI: 1.01-1.86, p = 0.04), cough (62.15%, OR 1.25, 95% CI: 0.97-1.60, p = 0.0823), myalgia/fatigue (38.77%, OR 1.31, 95% CI: 1.11-1.55, p = 0.0018), dyspnea (33.9%, OR 3.61, 95% CI: 2.57-5.06, p = <0.0001), respiratory failure/ARDS (20.6%, OR 11.46, 95% CI: 3.24-40.56, p = 0.0002), diarrhea (11.21%) and chest tightness/pain (16.82%, OR 2.17, 95% CI: 1.40-3.36, p = 0.0006). Meta-analysis also revealed that neither the duration of the incubation period nor current smoking status associated with disease severity.


title: A Simulation Algorithm of a Digital Twin for Manual Assembly Process

text: Abstract Digital twin (DT) is one of the key concepts for Industry 4.0 as it is a critical component in driving real-time simulation and decision making in complex systems. The existing scientific literature on Digital twin primarily refers to a product entity or a physical machine but the core concept can be applied to the entire product lifecycle, particularly the assembly process of a complex product system. In addition, majority of existing work focus on the Digital Twins of individual machines on a shop-floor. This paper focuses on aspects the process to build DTs of a production schedule for a complex defence weapon system. The process is inherently high variety and low quantity in a very manual assembly process. This paper consists of three elements. (1) It reviews the current state of art along with the research gap and discusses how DT can become a tool to the manual assembly process. (2) A data-driven simulation algorithm is proposed to model the complex and manual manufacturing process in a generic-reusable way. (3) Finally, an appropriate complex industrial case study is studied to exemplify the proposed framework. Results demonstrate that the production managers can make more informed early decisions that can help bring assembly schedules in check and limit wasteful efforts when disruptions in the supply chain of parts sourced for the assembly occur.


title: Post-lockdown detection of SARS-CoV-2 RNA in the wastewater of Montpellier, France

text: The evolution of the COVID-19 pandemic can be monitored through the detection of SARS-CoV-2 RNA in sewage. Here, we measured the amount of SARS-CoV-2 RNA at the inflow point of the main waste water treatment plant (WWTP) of Montpellier, France. We collected samples 4 days before the end of lockdown and up to 45 days post-lockdown. We detected increased amounts of SARS-CoV-2 RNA at the WWTP, which was not correlated with the number of newly diagnosed patients. Future epidemiologic investigations may explain such asynchronous finding.


title: Moving-average based index to timely evaluate the current epidemic situation after COVID-19 outbreak

text: A pneumonia outbreak caused by a novel coronavirus (COVID-19) occurred in Wuhan, China at the end of 2019 and then spread rapidly to the whole country. A total of 81,021 laboratory-confirmed cases, including 3,194 deaths (3.9%) had been reported in China by March 14, 2020, meanwhile, 61,518 laboratory-confirmed cases and 2,199 deaths were reported outside China. Common symptoms of COVID-19 pneumonia included fever, fatigue and dry cough. Faced with such a sudden outbreak of new infectious diseases, we have no history to learn from and no evidence to count on. Traditional models often predict inconsistent results. Aiming at estimate the epidemic trend timely after the outbreak, we mainly used 7-day moving average of log-transformed daily new cases (LMA) to establish a new index named "epidemic trend index", which will be used to predict the evolutionary trend of the epidemic situation and support epidemic control decision making processes. We used SARS epidemic data from Hong Kong in 2003 to verify the practicability of the new index, which shows that the index is acceptable. The epidemic trend index was then applied to the COVID-19 epidemic analysis in China. The results show that during the epidemic, the trend direction of different districts of China changed on different date. In the whole country and in Hubei Province alone, the epidemic reached the peak on February 9. While the peak appeared earlier, i.e. on February 5 in other provinces. It indicated that decisive outbreak control measures of the Chinese government are effective. While local governments should adjust management measures based on local risk level of epidemic. Although the epidemic has eased since late February, continued efforts in epidemic control are still needed to accelerate the end of the epidemic in China. However, the global COVID-19 epidemic outside China continues to expand as indicated by the epidemic trend index we proposed. In order to cope with the novel coronavirus pandemic, people all over the world should work together and governments of all countries should take efficient measures in the light of China's experience and according to national circumstances and local conditions.


title: The association of cardiovascular disease and other pre-existing comorbidities with COVID-19 mortality: A systematic review and meta-analysis

text: Importance. Exploring the association of coronavirus-2019 disease (COVID-19) mortality with chronic pre-existing conditions may promote the importance of targeting these populations during this pandemic in order to optimize survival. Objective. To explore the association of pre-existing conditions with COVID-19 mortality. Data Sources. MEDLINE, the OVID databases, SCOPUS, and Cochrane Register of Controlled Trials were searched for the period October 1, 2019 to May 1, 2020. Snowballing was used to identify additional studies. Study Selection. Observational studies (n=19) reporting on 61,455 patients with relative risks (RR) or hazard ratios or odds ratios that reported the risk of mortality in patients with COVID-19 and comorbid conditions were included for the current study. Data Extraction and Synthesis. Two independent reviewers extracted data and assessed the risk of bias. All analyses were performed using random-effects models and heterogeneity was quantified. Main Outcomes and Measures The outcome of interest was the risk of COVID-19 mortality in patients with and without pre-existing conditions, reported as RR. Comorbidities explored were cardiovascular diseases (coronary artery disease, hypertension, cardiac arrhythmias, and congestive heart failure), chronic obstructive pulmonary disease, type 2 diabetes, cancer, chronic kidney disease, chronic liver disease, and stroke. Results. Ten chronic conditions from 19 studies were included in the meta-analysis (n=61,455 patients with COVID-19; mean age, 61 years; 57% male). Any cardiovascular disease, coronary heart disease, hypertension, congestive heart failure, and cancer significantly increased the risk of mortality from COVID-19. Cardiovascular disease was associated with a 135% higher risk of COVID-19 mortality (RR=2.35, 95%CI 1.44-3.84 n=9). The risk of mortality from COVID-19 in patients with coronary heart disease was 2.4 times as high as those without coronary heart disease (RR= 2.40, 95%CI=1.71-3.37, n=5) and twice as high in patients with hypertension as high as that compared to those without hypertension (RR=1.89, 95%CI= 1.58-2.27, n=9). Patients with cancer also were at twice the risk of mortality from COVID-19 compared to those without cancer (RR=1.93 95%CI 1.15-3.24, n=4), and those with congestive heart failure were at 2.5 times the risk of mortality compared to those without congestive heart failure (RR=2.66, 95%CI 1.58-4.48, n=3). Conclusions and Relevance COVID-19 patients with all any cardiovascular disease, coronary heart disease, hypertension, congestive heart failure, and cancer have an increased risk of mortality. Tailored infection prevention and treatment strategies targeting this high-risk population are warranted to optimize survival.


title: An experimental trial of recombinant human interferon alpha nasal drops to prevent coronavirus disease 2019 in medical staff in an epidemic area

text: Objective To investigate the efficacy and safety of recombinant human interferon alpha1b (rhIFN-α) nasal drops in healthy medical staff to prevent 2019 novel coronavirus disease (COVID-19). Methods A prospective, open-label study was conducted. Starting January 21, 2020, at Taihe Hospital in Shiyan City, Hubei Province, 2944 medical staff members were recruited and allocated into a low-risk group or a high-risk group according to whether they were directly exposed to the coronavirus. Participants in the low-risk group received rhIFN-α nasal drops (2-3 drops/nostril/time, 4 times/day) for 28 days; those in the high-risk group received rhIFN-α nasal drops combined with thymosin-α1 (1.6 mg, hypodermic injection, once a week). The primary outcome was new-onset COVID-19 over 28 days. The secondary outcome was new-onset fever or respiratory symptoms but with negative pulmonary images. The results were compared with the number of new cases in medical staff in the same areas of Hubei Province (including Wuhan) during the same period. Adverse reactions to interferon nasal drops were also observed. Results Among the 2944 subjects in our study, 2415 were included in the low-risk group, including 997 doctors and 1418 nurses with average ages of 37.38 and 33.56 years, respectively; 529 were included in the high-risk group, including 122 doctors and 407 nurses with average ages of 35.24 and 32.16 years, respectively. The 28-day incidence of COVID-19 was zero in both the high- and low-risk groups. The 28-day incidence of new-onset clinical symptoms with negative images for pneumonia was also zero in both the high- and low-risk groups. As controls, a total of 2035 medical personnel with confirmed COVID-19 pneumonia from the same area (Hubei Province) was observed between January 21 to February 23, 2020. There were no serious adverse effects in the 2944 subjects treated during the intervention period. Conclusion In this investigator-initiated open-label study, we observed that rhIFN-α nasal drops can effectively prevent COVID-19 in treated medical personnel. Our results also indicate that rhIFN-α nasal drops have potential promise for protecting susceptible healthy people during the coronavirus pandemic.


title: Immunochromatographic assays for COVID-19 epidemiological screening: our experience

text: In March 2020, the World Health Organization (WHO) declared a pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Due to the absence of effective treatment or biomedical prevention, understanding potential post infection immunity has important implications for epidemiologic assessments. For this reason, increasing number of in vitro diagnostic companies are developing serological assays to detect antibodies against SARS-CoV-2, but most of them lack the validation by third parties in relation to their quality, limiting their usefulness. We submitted to serological screening by two different immunochromatographic (IC) rapid testing for detection of IgG and IgM against SARS-CoV-2, 151 asymptomatic or minimally symptomatic healthcare workers previously tested positive for SARS-CoV-2 RT-PCR in order to evaluate the performance of rapid assays. Results showed discrepancies between molecular and IC results, and an inconsistency of immunoglobulins positivity patterns when compared to ELISA/CLIA results, highlighting the absolute necessity of assays performance validation before their marketing and use, in order to avoid errors in the results evaluation at both clinical and epidemiological level.


title: Two mechanisms for accelerated diffusion of COVID-19 outbreaks in regions with high intensity of population and polluting industrialization: the air pollution-to-human and human-to-human transmission dynamics

text: What is COVID-19? Coronavirus disease 2019 (COVID-19) is viral infection that generates a severe acute respiratory syndrome with serious pneumonia that may result in progressive respiratory failure and death. What are the goals of this investigation? This study explains the geo-environmental determinants of the accelerated diffusion of COVID-19 in Italy that is generating a high level of deaths and suggests general lessons learned for a strategy to cope with future epidemics similar to COVID-19 to reduce viral infectivity and negative impacts in economic systems and society. What are the results of this study? The main results are: o The accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution. o Hinterland cities have average days of exceeding the limits set for PM10 (particulate matter 10 micrometers or less in diameter) equal to 80 days, and an average number of infected more than 2,000 individuals as of April 1st, 2020, coastal cities have days of exceeding the limits set for PM10 equal to 60 days and have about 700 infected in average. o Cities that average number of 125 days exceeding the limits set for PM10, last year, they have an average number of infected individual higher than 3,200 units, whereas cities having less than 100 days (average number of 48 days) exceeding the limits set for PM10, they have an average number of about 900 infected individuals. o The results reveal that accelerated transmission dynamics of COVID-19 in specific environments is due to two mechanisms given by: air pollution-to-human transmission and human-to-human transmission; in particular, the mechanisms of air pollution-to-human transmission play a critical role rather than human-to-human transmission. o The finding here suggests that to minimize future epidemic similar to COVID-19, the max number of days per year in which cities can exceed the limits set for PM10 or for ozone, considering their meteorological condition, is less than 50 days. After this critical threshold, the analytical output here suggests that environmental inconsistencies because of the combination between air pollution and meteorological conditions (with high moisture%, low wind speed and fog) trigger a take-off of viral infectivity (accelerated epidemic diffusion) with damages for health of population, economy and society. What is a socioeconomic strategy to prevent future epidemics similar to COVID-19? Considering the complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity, lessons learned for COVID-19 have to be applied for a proactive socioeconomic strategy to cope with future epidemics, especially an environmental policy based on reduction of air pollution mainly in hinterland zones of countries, having low wind speed, high percentage of moisture and fog that create an environment that can damage immune system of people and foster a fast transmission of viral infectivity similar to the COVID-19. This study must conclude that a strategy to prevent future epidemics similar to COVID 19 has also to be designed in environmental and sustainability science and not only in terms of biology.


title: A preliminary study on analytical performance of serological assay for SARS-CoV-2 IgM/IgG and application in clinical practice

text: Objective: To investigate the performance of serological test and dynamics of serum antibody with the progress of SARS-CoV-2 infections. Methods: A total of 419 patients were enrolled including 19 confirmed cases and 400 patients from fever clinics. Their serial serum samples collected during the hospitalization were menstruated for IgM and IgG against SARS-CoV-2 using gold immunochromatographic assay and chemiluminescence immunoassay. We investigated whether thermal inactivation could affect the results of antibody detection. The dynamics of antibodies with the disease progress and false positive factors for antibody testing were also analyzed. Results: The positive rate of IgG detection was 91.67% and 83.33% using two CLIA, respectively. However, the IgM positive rate was dramatically declined might due to the lack of blood samples at early stages of the disease. The chemiluminescence immunoassay had a favorable but narrow linear range. Our work showed increased IgG values in serums from virus-negative patients and four negative samples were IgG weak-positive after thermal incubation. Our data showed the specificity of viral N+S proteins was higher than single antigen. Unlike generally thought that IgM appeared earlier than IgG, there is no certain chronological order of IgM and IgG seroconversion in COVID-19 patients. It was difficult to detect antibodies in asymptomatic patients suggesting that their low viral loads were not enough to cause immune response. Analysis of common interferent in three IgG false-positive patients, such as rheumatoid factor, proved that false positives were not caused by these interfering substances and antigenic cross-reaction. Conclusions: Viral serological test is an effective means for SARS-CoV-2 infect detection using both chemiluminescence immunoassay and gold immunochromatographic assay. Chemiluminescence immunoassay against multi-antigens has obvious advantages but still need improve in reducing false positives.


title: Race to get ready

text: As the coronavirus spreads in countries other than China, no nation is fully prepared for a pandemic, reports Michael Le Page


title: Modeling the Effective Control Strategy for Transmission Dynamics of Global Pandemic COVID-19

text: The novel coronavirus disease (namely COVID-19) has taken attention because of its deadliness across the globe, causing a massive death as well as critical situation around the world. It is an infectious disease which is caused by newly discovered coronavirus. Our study demonstrates with a nonlinear model of this devastating COVID-19 which narrates transmission from human-to-human in the society. Pontryagin Maximum principle has also been applied in order to obtain optimal control strategies where the maintenance of social distancing is the major control. The target of this study is to find out the most fruitful control measures of averting coronavirus infection and eventually, curtailed of the COVID-19 transmission among people. The model is investigated analytically by using most familiar necessary conditions of Pontryagin maximum principle. Furthermore, numerical simulations have been performed to illustrate the analytical results. The analysis reveals that implementation of educational campaign, social distancing and developing human immune system are the major factors which can be able to plunge the scenario of becoming infected.


title: Estimating critical care capacity needs and gaps in Africa during the COVID-19 pandemic

text: Objective The purpose of this analysis was to describe national critical care capacity shortages for 52 African countries and to outline needs for each country to adequately respond to the COVID-19 pandemic. Methods A modified SECIR compartment model was used to estimate the number of severe COVID-19 cases at the peak of the outbreak. Projections of the number of hospital beds, ICU beds, and ventilators needed at outbreak peak were generated for four scenarios (if 30, 50, 70, or 100% of patients with severe COVID-19 symptoms seek health services) assuming that all people with severe infections would require hospitalization, that 4.72% would require ICU admission, and that 2.3% would require mechanical ventilation. Findings Across the 52 countries included in this analysis, the average number of severe COVID-19 cases projected at outbreak peak was 138 per 100,000 (SD: 9.6). Comparing current national capacities to estimated needs at outbreak peak, we found that 31of 50 countries (62%) do not have a sufficient number of hospital beds per 100,000 people if 100% of patients with severe infections seek out health services and assuming that all hospital beds are empty and available for use by patients with COVID-19. If only 30% of patients seek out health services then 10 of 50 countries (20%) do not have sufficient hospital bed capacity. The average number of ICU beds needed at outbreak peak across the 52 included countries ranged from 2 per 100,000 people (SD: 0.1) when 30% of people with severe COVID-19 infections access health services to 6.5 per 100,000 (SD: 0.5) assuming 100% of people seek out health services. Even if only 30% of severely infected patients seek health services at outbreak peak, then 34 of 48 countries (71%) do not have a sufficient number of ICU beds per 100,000 people to handle projected need. Only four countries (Cabo Verde, Egypt, Gabon, and South Africa) have a sufficient number of ventilators to meet projected national needs if 100% of severely infected individuals seek health services assuming all ventilators are functioning and available for COVID-19 patients, while 35 other countries require two or more additional ventilators per 100,000 people.


title: Research strategy of drugs against 2019-novel coronavirus based on supramolecular “qi chromatography” theory of TCM/ 基于中医药超分子“气析”理论探讨抗新型冠状病毒药物的研究策略

text: At present, the 2019-novel coronavirus (2019-nCoV) is rampant all over the country, and controlling the spread of its epidemic has become a top priority. It is very difficult to control the epidemic spreading because there is no specific drug to fight against it. Therefore, it is urgent task for us to develop a specific drug as soon as possible, and attracting worldwide attention. The studies on anti-2019-nCoV drugs were generally carried out in three modes, as vaccine, chemical drugs and traditional Chinese medicine (TCM). Because the developing on vaccines and chemicals takes too long, it is hard to solve the urgent problem. Moreover, the RNA of coronavirus has been recombined so quickly that the vaccines and drugs studied with great efforts not only may miss the epidemic time, but also cannot be used in the next generation of new coronavirus treatment, as a result that the work of epidemic prevention is formidable. However, the prescriptions from traditional Chinese medicine theory can cure the epidemic disease, but how to develop it into a specific drug with clear chemical composition and clear pharmacologic mechanism, is also an urgent problem to be solved. In this paper, the new coronavirus and its drug development are reviewed, while the advantages and disadvantages are analyzed, and the drug dilemma research phenomenon is clarified by using the supramolecular “qi chromatography” theory. It is suggested that the strategy of anti-coronavirus drug developing should be put forward based on the impact of “qi chromatography” of biological supramolecular “imprinting template”, in order to develop new drugs against 2019-nCoV to control the spread of the epidemic as quick as we can, and establish a new research and development model of anti-coronavirus drug on integration of traditional Chinese and Western medicine, turning passive into active.


title: Fundamental principles of epidemic spread highlight the immediate need for large-scale serological surveys to assess the stage of the SARS-CoV-2 epidemic

text: The spread of a novel pathogenic infectious agent eliciting protective immunity is typically characterised by three distinct phases: (I) an initial phase of slow accumulation of new infections (often undetectable), (II) a second phase of rapid growth in cases of infection, disease and death, and (III) an eventual slow down of transmission due to the depletion of susceptible individuals, typically leading to the termination of the (first) epidemic wave. Before the implementation of control measures (e.g. social distancing, travel bans, etc) and under the assumption that infection elicits protective immunity, epidemiological theory indicates that the ongoing epidemic of SARS-CoV-2 will conform to this pattern. Here, we calibrate a susceptible-infected-recovered (SIR) model to data on cumulative reported SARS-CoV-2 associated deaths from the United Kingdom (UK) and Italy under the assumption that such deaths are well reported events that occur only in a vulnerable fraction of the population. We focus on model solutions which take into consideration previous estimates of critical epidemiological parameters such as the basic reproduction number (R0), probability of death in the vulnerable fraction of the population, infectious period and time from infection to death, with the intention of exploring the sensitivity of the system to the actual fraction of the population vulnerable to severe disease and death. Our simulations are in agreement with other studies that the current epidemic wave in the UK and Italy in the absence of interventions should have an approximate duration of 2-3 months, with numbers of deaths lagging behind in time relative to overall infections. Importantly, the results we present here suggest the ongoing epidemics in the UK and Italy started at least a month before the first reported death and have already led to the accumulation of significant levels of herd immunity in both countries. There is an inverse relationship between the proportion currently immune and the fraction of the population vulnerable to severe disease. This relationship can be used to determine how many people will require hospitalisation (and possibly die) in the coming weeks if we are able to accurately determine current levels of herd immunity. There is thus an urgent need for investment in technologies such as virus (or viral pseudotype) neutralization assays and other robust assays which provide reliable read-outs of protective immunity, and for the provision of open access to valuable data sources such as blood banks and paired samples of acute and convalescent sera from confirmed cases of SARS-CoV-2 to validate these. Urgent development and assessment of such tests should be followed by rapid implementation at scale to provide real-time data. These data will be critical to the proper assessment of the effects of social distancing and other measures currently being adopted to slow down the case incidence and for informing future policy direction.


title: COVID-19 Control Strategies and Intervention Effects in Resource Limited Settings: A Modeling Study

text: Background Many countries with weaker health systems are struggling to put together a coherent strategy against the COVID-19 epidemic. We explored COVID-19 control strategies that could offer the greatest benefit in resource limited settings. Methods Using an age-structured SEIR model, we explored the effects of COVID-19 control interventions--a lockdown, physical distancing measures, and active case finding (testing and isolation, contact tracing and quarantine)-- implemented individually and in combination to control a hypothetical COVID-19 epidemic in Kathmandu (population 2.6 million), Nepal. Results A month-long lockdown that is currently in place in Nepal will delay peak demand for hospital beds by 36 days, as compared to a base scenario of no interventions (peak demand at 108 days (IQR 97-119); a 2 month long lockdown will delay it by 74 days, without any difference in annual mortality, or healthcare demand volume. Year-long physical distancing measures will reduce peak demand to 36% (IQR 23%-46%) and annual morality to 67% (IQR 48%-77%) of base scenario. Following a month long lockdown with ongoing physical distancing measures and an active case finding intervention that detects 5% of the daily infection burden could reduce projected morality and peak demand by more than 99%. Interpretation Limited resources settings are best served by a combination of early and aggressive case finding with ongoing physical distancing measures to control the COVID-19 epidemic. A lockdown may be helpful until combination interventions can be put in place but is unlikely to reduce annual mortality or healthcare demand.


Tragic Intersection: Where the Back Pain Crisis and the COVID-19 Pandemic Meet


Plastic Surgery in Coronavirus Disease 2019 Emergencies: Report from Northern Italy


title: Sacrifice and risk in the time of COVID-19

text: The COVID-19 pandemic has changed the face of healthcare delivery This article discusses the concept of medical sacrifice and personal risk, and how healthcare workers can apply these concepts when working outside their comfort zones, while remaining within the limits of their clinical competence Guidance from the General Medical Council and the medical defence organisations is reviewed and considered in its practical application We explore how a medical student, now a 'fast tracked' junior doctor, and a senior consultant, with pre-existing health issues, can feel confident working as part of the NHS response to COVID-19


title: One-step RNA extraction for RT-qPCR detection of 2019-nCoV

text: The global outbreak of coronavirus disease 2019 (COVID-19) has placed an unprecedented burden on healthcare systems as the virus spread from the initial 27 reported cases in the city of Wuhan, China to a global pandemic in under three months1. Resources essential to monitoring virus transmission have been challenged with a demand for expanded surveillance. The CDC 2019-nCoV Real-Time Diagnostic Panel uses a real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) consisting of two TaqMan probe and primer sets specific for the 2019-nCoV N gene, which codes for the nucleocapsid structural protein that encapsulates viral RNA, for the qualitative detection of 2019-nCoV viral RNA in respiratory samples. To isolate RNA from respiratory samples, the CDC lists RNA extraction kits from three manufacturers. In anticipation of a limited supply chain of RNA extraction kits and the need for test scalability, we sought to identify alternative RNA extraction methods. Here we show that direct lysis of respiratory samples can be used in place of RNA extraction kits to run the CDC 2019-nCoV Real-Time Diagnostic assay with the additional benefits of higher throughput, lower cost, faster turnaround and possibly higher senitivity and improved saftey.


title: How sick will the coronavirus make you? The answer may be in your genes

text: COVID-19, caused by the new pandemic coronavirus, is strangely—and tragically—selective Only some infected people get sick, and although most of the critically ill are elderly or have complicating problems such as heart disease, some killed by the disease are previously healthy and even relatively young Researchers are now gearing up to scour the patients’ genomes for DNA variations that explain this mystery The findings could be used to identify those most at risk of serious illness and those who might be protected, and they might also guide the search for new treatments


title: Comparative genomics suggests limited variability and similar evolutionary patterns between major clades of SARS-CoV-2

text: Phylogenomic analysis of SARS-CoV-2 as available from publicly available repositories suggests the presence of 3 prevalent groups of viral episomes (super-clades), which are mostly associated with outbreaks in distinct geographic locations (China, USA and Europe). While levels of genomic variability between SARS-CoV-2 isolates are limited, to our knowledge, it is not clear whether the observed patterns of variability in viral super-clades reflect ongoing adaptation of SARS-CoV-2, or merely genetic drift and founder effects. Here, we analyze more than 1100 complete, high quality SARS-CoV-2 genome sequences, and provide evidence for the absence of distinct evolutionary patterns/signatures in the genomes of the currently known major clades of SARS-CoV-2. Our analyses suggest that the presence of distinct viral episomes at different geographic locations are consistent with founder effects, coupled with the rapid spread of this novel virus. We observe that while cross species adaptation of the virus is associated with hypervariability of specific protein coding regions (including the RDB domain of the spike protein), the more variable genomic regions between extant SARS-CoV-2 episomes correspond with the 3’ and 5’ UTRs, suggesting that at present viral protein coding genes should not be subjected to different adaptive evolutionary pressures in different viral strains. Although this study can not be conclusive, we believe that the evidence presented here is strongly consistent with the notion that the biased geographic distribution of SARS-CoV-2 isolates should not be associated with adaptive evolution of this novel pathogen.


title: Epidemiological, Clinical Characteristics and Outcome of Medical Staff Infected with COVID-19 in Wuhan, China: A Retrospective Case Series Analysis

text: Backgrounds Since December 2019, a novel coronavirus epidemic has emerged in Wuhan city, China and then rapidly spread to other areas. As of 20 Feb 2020, a total of 2,055 medical staff confirmed with coronavirus disease 2019 (COVID-19) caused by SARS-Cov-2 in China had been reported. We sought to explore the epidemiological, clinical characteristics and prognosis of novel coronavirus-infected medical staff. Methods In this retrospective study, 64 confirmed cases of novel coronavirus-infected medical staff admitted to Union Hospital, Wuhan between 16 Jan, 2020 to 15 Feb, 2020 were included. Two groups concerned were extracted from the subjects based on duration of symptoms: group 1 (<= 10 days) and group 2 (>10 days). Epidemiological and clinical data were analyzed and compared across groups. The Kaplan-Meier plot was used to inspect the change in hospital discharge rate. The Cox regression model was utilized to identify factors associated with hospital discharge. Findings The median age of medical staff included was 35 years old. 64% were female and 67% were nurses. None had an exposure to Huanan seafood wholesale market or wildlife. A small proportion of the cohort had contact with specimens (5%) as well as patients in fever clinics (8%) and isolation wards (5%). Fever (67%) was the most common symptom, followed by cough (47%) and fatigue (34%). The median time interval between symptoms onset and admission was 8.5 days. On admission, 80% of medical staff showed abnormal IL-6 levels and 34% had lymphocytopenia. Chest CT mainly manifested as bilateral (61%), subpleural (80%) and ground-glass (52%) opacities. During the study period, no patients was transferred to intensive care unit or died, and 34 (53%) had been discharged. Higher body mass index (BMI) (HR 0.14; 95% CI 0.03-0.73), fever (HR 0.24; 95% CI 0.09-0.60) and higher levels of IL-6 on admission (HR 0.31; 95% CI 0.11-0.87) were unfavorable factors for discharge. Interpretation In this study, medical staff infected with COVID-19 have relatively milder symptoms and favorable clinical course, which may be partly due to their medical expertise, younger age and less underlying diseases. Smaller BMI, absence of fever symptoms and normal IL-6 levels on admission are favorable for discharge for medical staff. Further studies should be devoted to identifying the exact patterns of SARS-CoV-2 infection among medical staff.


title: VirusDIP: Virus Data Integration Platform

text: Motivation The Coronavirus Disease 2019 (COVID-19) pandemic poses a huge threat to human public health. Viral sequence data plays an important role in the scientific prevention and control of epidemics. A comprehensive virus database will be vital useful for virus data retrieval and deep analysis. To promote sharing of virus data, several virus databases and related analyzing tools have been created. Results To facilitate virus research and promote the global sharing of virus data, we present here VirusDIP, a one-stop service platform for archive, integration, access, analysis of virus data. It accepts the submission of viral sequence data from all over the world and currently integrates data resources from the National GeneBank Database (CNGBdb), Global initiative on sharing all influenza data (GISAID), and National Center for Biotechnology Information (NCBI). Moreover, based on the comprehensive data resources, BLAST sequence alignment tool and multi-party security computing tools are deployed for multi-sequence alignment, phylogenetic tree building and global trusted sharing. VirusDIP is gradually establishing cooperation with more databases, and paving the way for the analysis of virus origin and evolution. All public data in VirusDIP are freely available for all researchers worldwide. Availability https://db.cngb.org/virus/ Contact weixiaofeng@cngb.org


title: SARS-CoV-2 genome evolution exposes early human adaptations

text: The set of mutations observed at the outset of the SARS-CoV-2 pandemic may illuminate how the virus will adapt to humans as it continues to spread. Viruses are expected to quickly acquire beneficial mutations upon jumping to a new host species. Advantageous nucleotide substitutions can be identified by their parallel occurrence in multiple independent lineages and are likely to result in changes to protein sequences. Here we show that SARS-CoV-2 is acquiring mutations more slowly than expected for neutral evolution, suggesting purifying selection is the dominant mode of evolution during the initial phase of the pandemic. However, several parallel mutations arose in multiple independent lineages and may provide a fitness advantage over the ancestral genome. We propose plausible reasons for several of the most frequent mutations. The absence of mutations in other genome regions suggests essential components of SARS-CoV-2 that could be the target of drug development. Overall this study provides genomic insights into how SARS-CoV-2 has adapted and will continue to adapt to humans. SUMMARY In this study we sought signals of evolution to identify how the SARS-CoV-2 genome has adapted at the outset of the COVID-19 pandemic. We find that the genome is largely undergoing purifying selection that maintains its ancestral sequence. However, we identified multiple positions on the genome that appear to confer an adaptive advantage based on their repeated evolution in independent lineages. This information indicates how SARS-CoV-2 will evolve as it diversifies in an increasing number of hosts.


title: 2019 novel coronavirus disease in hemodialysis (HD) patients: Report from one HD center in Wuhan, China

text: The outbreak of COVID-19 originated in Wuhan has become a global epidemic of contagious diseases, which poses a serious threat to human life and health, especially for those with underlined diseases. However, Impacts of COVID-19 epidemic on HD center and HD patients are still unknown. In this report, we reviewed the whole course of the epidemic emerged in the HD center of Renmin Hospital, Wuhan University from January 14, 2020, the day the first case was confirmed, to February 17, 2020, the day the epidemic extinction. There are totally 37 cases among 230 HD patients and 4 cases among 33 staff being diagnosed with COVID-19. The epidemiology, clinical presentation and immune profile of dialysis patients contracted COVID-19 were further studied. We found that the two key measures we took in response to the epidemic, one was upgrading level of prevention and protection on January 21 and the other one starting universal screening, isolating, and distributing the infected cases on February 4, were effective in the epidemic control. No new COVID-19 case had been diagnosed since February 13. During the epidemic, 7 HD patients died, including 6 with COVID-19 and 1 without COVID-19. The presumed causes of death were not directly related to pneumonia, but due to cardiovascular and cerebrovascular diseases, hyperkalemia, etc. Most of the leukocytes in the peripheral blood of the HD patients infected with COVID-19 decreased, and the CT images of the chest mostly showed the ground glass like changes on the right side. The symptoms of most of the patients were mild, and there were no cases admitted to ICU. The frequency of lymphocytes in PBMCs and the serum level of inflammatory cytokines were assessed in HD patients contracted COVID-19 or not, non-HD COVID-19 patients, as well as healthy volunteers. The results showed that lymphocytes of T cell, Th cells, killer T cells, as well as NK cells in PBMCs of HD patients decreased significantly than other groups. HD patients with COVID-19 also displayed remarkable lower serum level of inflammatory cytokines than other COVID-19 patients. Our study indicates that HD patients are the highly susceptible population and HD centers are high risk area in the outbreak of COVID-19 epidemic. Measures of prevention, protection, screening, isolation, and distribution are essential in the epidemic management and should be taken in the early stage. HD Patients with COVID-19 are mostly clinical mild and unlikely progress to severe pneumonia due to the impaired cellular immune function and incapability of mounting cytokines storm. More attention should be paid to prevent cardiovascular events, which may be the collateral impacts of COVID-19 epidemic on HD patients.


title: Cutting force and stability prediction for inserted cutters

text: Abstract This paper presents an approach for inserted end/face mill force and stability predictions using a reverse engineering approach. Structured light scanning is implemented to identify the spatial coordinates of the points that define the multiple insert cutting edges. These points are analyzed to extract the cutting edge radius and angle values, which are then incorporated in a time domain simulation that predicts cutting force and tool/workpiece deflection for user-selected operating parameters. Good agreement between predicted and measured cutting forces is first demonstrated. The process stability is then predicted using the validated force model and measured structural dynamics. Observations about the stability dependence on insert geometry are finally presented for a selected end mill.


title: Clinical and historical features associated with severe COVID-19 infection: a systematic review

text: Background: There is an urgent need for rapid assessment methods to guide pathways of care for COVID-19 patients, as frontline providers need to make challenging decisions surrounding rationing of resources. This study aimed to evaluate existing literature for factors associated with COVID-19 illness severity. Methods: A systematic review identified all studies published between 1/12/19 and 19/4/20 that used primary data and inferential statistics to assess associations between the outcome of interest - disease severity - and historical or clinical variables. PubMed, Scopus, Web of Science, and the WHO Database of Publications on Coronavirus Disease were searched. Data were independently extracted and cross-checked independently by two reviewers using PRISMA guidelines, after which they were descriptively analysed. Quality and risk of bias in available evidence were assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) framework. This review was registered with PROSPERO, registration number CRD42020178098. Results: Of the 6202 relevant articles found, 63 were eligible for inclusion; these studies analysed data from 17648 COVID-19 patients. The majority (n=57, 90.5%) were from China and nearly all (n=51, 90.5%) focussed on admitted adult patients. Patients had a median age of 52.5 years and 52.8% were male. The predictors most frequently associated with COVID-19 disease severity were age, absolute lymphocyte count, hypertension, lactate dehydrogenase (LDH), C-reactive protein (CRP), and history of any pre-existing medical condition. Conclusion: This study identified multiple variables likely to be predictive of severe COVID-19 illness. Due to the novelty of SARS-CoV-2 infection, there is currently no severity prediction tool designed to, or validated for, COVID-19 illness severity. Findings may inform such a tool that can offer guidance on clinical treatment and disposition, and ultimately reduce morbidity and mortality due to the pandemic.


Resorting to mathematical modelling approach to contain the coronavirus disease 2019 (COVID-19) outbreak


Crise du COVID – 19: l’économiste et l’infectiologue - Le regard de Jean Tirole