title: Increased levels of anxiety among medical and non-medical university students during the COVID-19 pandemic in the United Arab Emirates.

text: Introduction: The COVID-19 pandemic is likely to increase anxiety levels within the community and in particular medical students who are already considered psychologically vulnerable groups. Since the COVID-19 outbreak, no study has yet estimated the effect of this pandemic on university students in the UAE or its impact on the psychological well-being of medical students. Methods: In this study, we surveyed 1485 medical (comprising medical and dental) and non-medical university students across 4 emirates within the UAE. We used an online platform to assess knowledge, sources of information, changes in hygienic behavior, perceptions of fear and worry and anxiety levels using the generalized anxiety disorder 7 (GAD-7) scale. The GAD-7 score was measured at three time points; during hospital visits for medical/dental students, before the introduction of online learning and after online learning for all students. Results: The majority of students demonstrated high levels of knowledge and utilized reliable sources of information. Non-medical students exercised higher compliance with social restrictions, while medical students practiced better hand hygiene. Almost half of students reported anxiety levels ranging from mild to severe with females reporting higher anxiety scores during hospital visits (OR=2.02, 95% CI,1.41 to 2.91) and medical students reporting lower anxiety levels in comparison to dental students (OR=0.61, 95% CI,0.45 to 0.84). Medical students reported higher levels of anxiety during their clinical rotations which decreased with the introduction of online learning, yet, non-medical student's anxiety levels increased with online learning. Conclusions: This is the first study to provide important information on the initial response and anxiety levels in university students across the UAE during the COVID-19 pandemic. The findings from our study can be used to support the development of effective screening strategies and interventions to build psychological resilience among university students during the COVID-19 pandemic or any other public health emergencies in the future.


title: Unit nonresponse biases in estimates of SARS-CoV-2 prevalence

text: Since COVID-19 became a pandemic, many studies are being conducted to get a better un-derstanding of the disease itself and its spread. One crucial indicator is the prevalence of SARS-CoV-2 infections. Since this measure is an important foundation for political decisions, its estimate must be reliable and unbiased. This paper presents reasons for biases in prevalence estimates due to unit nonresponse in typical studies. Since it is difficult to avoid bias in situ-ations with mostly unknown nonresponse mechanisms, we propose the maximum amount of bias as one measure to assess the uncertainty due to nonresponse. An interactive web application is presented that calculates the limits of such a conservative unit nonresponse confidence interval (CUNCI).


title: Modeling COVID 19 in the Basque Country: from introduction to control measure response

text: In March 2020, a multidisciplinary task force (so-called Basque Modelling Task Force, BMTF) was created to assist the Basque Health managers and the Basque Government during the COVID-19 responses. BMTF is a modeling team, working on different approaches, including statistical methods and artificial intelligence. In this paper we describe and present the results obtained by one of the modeling approaches developed within the BMTF, a stochastic SHARUCD-type models able to describe the disease incidence data, provided by the Basque Health Service, with a single parameter set. Data inspection has shown that the partial lockdown measures were effective to slowdown disease transmission in the Basque Country. Short and longer-term predictions are tested with good results adjusted to the current epidemiological data. The growth rate {lambda} is calculated from the model and from the data and the implications for the reproduction ratio r are shown. At the moment, the reproduction ratio r is estimated to be below the threshold behavior of r = 1, but still close to 1, meaning that although the number of new cases are decelerating, a careful monitoring of the development of the outbreak is required. Besides projections on the national health system needs during the increased population demand on hospital admissions, models were able to describe COVID-19 epidemic in the Basque Country, from introduction to control measure response and are now being used to monitor disease transmission when the country lockdown is gradually lifted. These are the first made public available modeling results for the Basque Country and the efforts will be continued taking into consideration the updated data and new information that are generated over time.


title: The confounded crude case-fatality rates for COVID-19 hide more than they reveal - a comparison of age-specific and age-adjusted rates between six countries

text: Background The reported crude case-fatality rates (CFRs) vary widely between countries. The serious limitations of using crude rates for comparisons are sometimes overlooked. In this paper we examined to what extent the age distribution of the cases is responsible for the differences in CFRs between countries. Methods Data on COVID-19 were extracted from the reports of individual countries. Overall and age-specific CFRs were available for six countries. The CFRs by country were adjusted for age using the direct method, using the combined age-specific number of cases of all six countries as the standard population. Findings The age distribution of the cases varied widely between countries. The crude CFRs varied between 1.6% and 11%. The differences in the age-specific CFRs were much smaller and the age-adjusted rates were much closer than the crude rates. The ratio of the crude CFR for the country with the highest to that with the lowest, was reduced substantially from 7.4 to 2.3 for the age-adjusted rates. Conclusions The age structure of the cases dramatically impacts on the differences in the crude CFRs between countries. Adjusting for age substantially reduces this variation. Other factors such as the differences in the definition of the denominators, the definition of a case and the standard of healthcare are likely to account for much of the residual variation. It is misleading to compare the crude COVID-19 CFRs between countries and should be avoided. Comparisons should be based on age-specific and age-adjusted rates. Key words: COVID-19, case-fatality rates, age-specific rates, age-adjusted rates, confounding


title: A one-year hospital-based prospective CVOID-19 open-cohort in the Eastern Mediterranean region: The Khorshid COVID Cohort (KCC) study

text: The COVID-19 is rapidly scattering worldwide, and the number of cases in the Eastern Mediterranean Region is rising, there is a need for immediate targeted actions. We designed a longitudinal study in a hot outbreak zone to analyze the serial findings between infected patients for detecting temporal changes from February 2020. In a hospital-based open-cohort study, patients are followed from admission until one year from their discharge (the 1st, 4th, 12th weeks, and the first year). The measurements included demographic, socio-economics, symptoms, health service diagnosis and treatment, contact history, and psychological variables. The signs improvement, death, length of stay in hospital were considered as primary, and impaired pulmonary function and psychotic disorders were considered as main secondary outcomes. Notably, In the last two follow-ups, each patient attends the hospital to complete the Patient Health Questionnaire-9 (PHQ-9) and the Depression Anxiety Stress Scales (DASS-21). Moreover, clinical symptoms and respiratory functions are being determined in such follow-ups. Among the first 600 COVID-19 cases, a total of 490 patients with complete information (39% female; the average age of 57 {+/-} 15 years) were analyzed. Seven percent of these patients died. The three main leading causes of admission were: fever (77%), dry cough (73%), and fatigue (69%). The most prevalent comorbidities between COVID-19 patients were hypertension (35%), diabetes (28%), and ischemic heart disease (14%). The percentage of primary composite endpoints (PCEP), defined as death, the use of mechanical ventilation, or admission to an intensive care unit was 18%. The following comorbidities were significantly different in the positive and negative PCEP groups: acute kidney disease (p=0.008) and diabetes (p=0.026). For signs and symptoms, fatigue (p=0.020) and sore throat (p=0.001) were significantly different. This long-term prospective Cohort may support healthcare professionals in the management of resources following this pandemic.


title: Longitudinal immunological analyses reveal inflammatory misfiring in severe COVID-19 patients

text: Recent studies have provided insights into the pathogenesis of coronavirus disease 2019 (COVID-19)1-4. Yet, longitudinal immunological correlates of disease outcome remain unclear. Here, we serially analysed immune responses in 113 COVID-19 patients with moderate (non-ICU) and severe (ICU) disease. Immune profiling revealed an overall increase in innate cell lineages with a concomitant reduction in T cell number. We identify an association between early, elevated cytokines and worse disease outcomes. Following an early increase in cytokines, COVID-19 patients with moderate disease displayed a progressive reduction in type-1 (antiviral) and type-3 (antifungal) responses. In contrast, patients with severe disease maintained these elevated responses throughout the course of disease. Moreover, severe disease was accompanied by an increase in multiple type 2 (anti-helminths) effectors including, IL-5, IL-13, IgE and eosinophils. Unsupervised clustering analysis of plasma and peripheral blood leukocyte data identified 4 immune signatures, representing (A) growth factors, (B) type-2/3 cytokines, (C) mixed type-1/2/3 cytokines, and (D) chemokines that correlated with three distinct disease trajectories of patients. The immune profile of patients who recovered with moderate disease was enriched in tissue reparative growth factor signature (A), while the profile for those with worsened disease trajectory had elevated levels of all four signatures. Thus, we identified development of a maladapted immune response profile associated with severe COVID-19 outcome and early immune signatures that correlate with divergent disease trajectories.


title: Rethink management, operation of sports in light of COVID-19 pandemic

text: As the world continues to confront COVID-19, every governing body, conference, and association, and virtually every collegiate institution, continues to carefully monitor, evaluate, and consider both the current situation and their next steps


title: Analysis of the SARS-Cov-2 epidemic in Lombardy (Italy) in its early phase. Are we going in the right direction?

text: BACKGROUND We described the epidemiological features of the codiv-19 outbreak, and evaluated the impact of interventions measures on the epidemic in the Lombardy region, Italy. METHODS Laboratory-confirmed covid-19 cases reported through the beginning of April were extracted from the Italian Civil Protection database. Based on key events and interventions, we divided the epidemic into three periods: before February 21, from February 22 to early March, after early March. We compared epidemiological characteristics across periods and developed a modified susceptible-exposed-infectious-recovered model to study the epidemic and evaluate the impact of interventions. We explicitly took into account for unascertained cases (positive cases with no symptoms or mild symptoms that have not been accounted for in official statistics). RESULTS Currently, the number of positive active cases has increased to around 30,000 in the Lombardy region. Due to restriction measures, the effective reproduction number dropped from 3.33 (95% CI: 2.03-3.69) during the first period, to 2.36 (95% CI: 2.21-2.70) during the second period. In the third period, the effective reproduction number is estimated to have dropped to 1.49 (95% CI: 1.35-1.62). The model estimates a great proportion of unascertained cases, about 90% of infected people has not been accounted for in official statistics. CONCLUSIONS Considerable countermeasures have slowed down the covid-19 outbreak in the Lombardy region. However, notwithstanding the long-lasting lockdown period, the epidemic is still not under control. The effective reproduction number, according to the model used in this work, is still greater than 1.0. Estimation of unascertained cases has important implications on continuing surveillance and interventions.


title: Does BCG protect against SARS-CoV-2 infection ?: elements of proof.

text: Background : There are several factors explaining the difference in the spread of SARS-CoV-2 infection including the BCG vaccination. This fact is supported by the concept of beneficial non specific effect of this live vaccine associated to its interaction with the immune system. Our study aims to identify the correlation between the universal BCG vaccination policy and the mortality attributed to COVID-19. Methods : We conducted an epidemiological study in which we collected COVID-19 pandemic data of April 11th, 2020 from the web site worldometers.info . The exclusion criteria for our study were a number of inhabitants less than one million, low-income countries according to the World Bank classification, a total number of infection cases less than 500 and countries that have performed less than one hundred tests per million inhabitants. Results : Countries that never had universal BCG vaccination policy have a higher mortality (correlated to performed diagnostic tests) attributed to SARS-CoV-2 infection (p<0.001). We found that the year of introduction of vaccination influenced significantly the mortality. Countries that started immunization policy before 1960 had more favorable results (p=0.049). For countries that started the BCG vaccination after 1960, countries with current policies have lower mortality attributed to SARS-CoV-2 infection than countries that have stopped immunization (p=0.047). Conclusions : Countries that have a BCG vaccination policy have a lower mortality attributed to SARS-CoV-2 infection. The populations of countries that applied this immunization before 1960 are more protected even if this universal policy has been interrupted.


title: Is there evidence that BCG vaccination has non-specific protective effects for COVID 19 infections or is it an illusion created by lack of testing?

text: The goal of this paper is to showcase that the COVID-19 disease pattern is evolving and to study the relationship between mandatory BCG policy and caseload/million or death/per million. We analyze seven recent publications on the impact of BCG vaccinations on the development of COVID19 illness and extend presented findings using the latest data from April 10, 2020. We analyze data from 98 countries and we extend existing models by adding the dimension of COVID-19-related testing conducted by the analyzed countries. Similarly to prior studies, we find that COVID-19 attributable case and death incidences across countries share a relationship with the BCG vaccination inclusion in the national immunization program of a country when testing is not taken into consideration. However, this relationship vanishes when we add the dimension of testing. We observe that case and death incidences conditional on testing do not get affected by the BCG vaccination inclusion in the national immunization program of a country. Therefore, we show that there is no statistical evidence to support the assertion that inclusion of BCG vaccination in national immunization program (NIP) has any impact of COVID 19 infections (cases) or mortality.


title: Modeling Return of the Epidemic: Impact of Population Structure, Asymptomatic Infection, Case Importation and Personal Contacts

text: Background: Proactive interventions have halted the pandemic of coronavirus infected disease in some regions. However, without reaching herd immunity, the return of epidemic is possible. We investigate the impact of population structure, case importation, asymptomatic cases, and the number of contacts on a possible second wave of epidemic through mathematical modelling. Methods: we built a modified Susceptible-exposed-Infectious-Removed (SEIR) model with parameters mirroring those of the COVID-19 pandemic and reported simulated characteristics of epidemics for incidence, hospitalizations and deaths under different scenarios. Results: A larger percent of old people leads to higher number of hospitalizations, while a large percent of prior infection will effectively curb the epidemic. The number of imported cases and the speed of importation have small impact on the epidemic progression. However, a higher percent of asymptomatic cases slows the epidemic down and reduces the number of hospitalizations and deaths at the epidemic peak. Finally, reducing the number of contacts among young people alone has moderate effects on themselves, but little effects on the old population. However, reducing the number of contacts among old people alone can mitigate the epidemic significantly in both groups, even though young people remain active within themselves. Conclusion: Reducing the number of contacts among high risk populations alone can mitigate the burden of epidemic in the whole society. Interventions targeting high risk groups may be more effective in containing or mitigating the epidemic.


title: Anaesthetic management of a COVID-19 parturient for caesarean section - Case report and lessons learnt

text: The corona virus disease 2019 (COVID-19) pandemic sweeping across the world has severely strained health care resources (equipment and personnel) forcing us to rethink strategies to provide obstetric care while judiciously using resources. We describe the anaesthetic management of a mildly symptomatic, COVID-19 positive, 28-year-old second gravida with term pregnancy who was taken up for an elective caesarean section under subarachnoid block in a standalone maternity facility. Challenges encountered and modifications of standard procedures so as to optimize patient care and minimize exposure of health care professionals are also discussed.


title: Comparative analysis of non structural protein 1 of SARS-COV2 with SARS-COV1 and MERS-COV: An in silico study

text: The recently emerged SARS-COV2 caused a major pandemic of coronavirus disease (COVID-19). The main goal of this study is to elucidate the structural conformations of non structural protein 1(nsp1), prediction of epitope sites and identification of important residues for targeted therapy against COVID-19. In this study, molecular modelling coupled with molecular dynamics simulations were performed to analyse the conformational change of SARS-COV1, SARS-COV2 and MERS-COV at molecular level. Free energy landscape was constructed by using the first (PC1) and second (PC2) principle components. From the sequence alignment it was observed when compared to SERS-COV1 28 mutations are present in SERS-COV2 nsp1 protein. Several B-cell and T-cell epitopes were identified by immunoinformatics study. The ΔG values for SARS-COV1, SARS-COV2 and MERS-COV nsp1 proteins were 4.44, 5.82 and 6.15 kJ/mol respectively. SARS-COV2 nsp1 protein binds with the interface region of the palm and finger domain of POLA1 by using hydrogen bonds and salt bridges interactions. The present study provided a comprehensive structural model of nsp1 by threading process. The MD simulation parameters indicated that all three nsp1 proteins were stable during the simulation run. These findings can be used to develop therapeutics specific against COVID-19. Highlights Structural elucidation at molecular level of nsp1 of SARS-COV1, SARS-COV2, and MERS-COV Identifications of epitopes by immunoinformatics approach SARS-COV2 nsp1 cover a large conformational space due to greater flexibility Molecular docking between SARS-COV2 nsp1 and POLA1 to identify important residues Structural insights of nsp1 could be used in drug design process against COVID-19 Graphical abstract


title: Clinical Distancing and Mitigation of Coronavirus Disease 2019

text: Social distancing as a technique to limit transmission of infectious disease has come into common parlance following the arrival and rapid spread of a novel coronavirus disease around the world in 2019 and 2020. But in the face of an emerging pandemic threat, it is crucial that we start to apply these principles to the clinic, the emergency department, and the hospital ward. We propose that this dynamic situation calls for a parallel “Clinical Distancing” in which we as a medical culture go against many of our fundamental instincts and, at least in the short term, begin to reduce unnecessary patient-care contacts for the benefit of our patients and our ability to continue to provide care to those who need it most. In this commentary, we provide specific recommendations for the rapid implementation of clinical distancing techniques.


title: No evidence of clinical efficacy of hydroxychloroquine in patients hospitalized for COVID-19 infection with oxygen requirement: results of a study using routinely collected data to emulate a target trial

text: Background Treatments are urgently needed to prevent respiratory failure and deaths from coronavirus disease 2019 (COVID-19). Hydroxychloroquine (HCQ) has received worldwide attention because of positive results from small studies. Methods We used data collected from routine care of all adults in 4 French hospitals with documented SARS-CoV-2 pneumonia and requiring oxygen ≥ 2 L/min to emulate a target trial aimed at assessing the effectiveness of HCQ at 600 mg/day. The composite primary endpoint was transfer to intensive care unit (ICU) within 7 days from inclusion and/or death from any cause. Analyses were adjusted for confounding factors by inverse probability of treatment weighting. Results This study included 181 patients with SARS-CoV-2 pneumonia; 84 received HCQ within 48 hours of admission (HCQ group) and 97 did not (no-HCQ group). Initial severity was well balanced between the groups. In the weighted analysis, 20.2% patients in the HCQ group were transferred to the ICU or died within 7 days vs 22.1% in the no-HCQ group (16 vs 21 events, relative risk [RR] 0.91, 95% CI 0.47-1.80). In the HCQ group, 2.8% of the patients died within 7 days vs 4.6% in the no-HCQ group (3 vs 4 events, RR 0.61, 95% CI 0.13-2.89), and 27.4% and 24.1%, respectively, developed acute respiratory distress syndrome within 7 days (24 vs 23 events, RR 1.14, 95% CI 0.65-2.00). Eight patients receiving HCQ (9.5%) experienced electrocardiogram modifications requiring HCQ discontinuation. Interpretation These results do not support the use of HCQ in patients hospitalised for documented SARS-CoV-2-positive hypoxic pneumonia.


title: Gastrointestinal features of the “new coronavirus” infection/ Manifestaciones gastrointestinales de la infección por el “nuevo coronavirus”

text: The World´s Heath Organization (WHO) declared the new coronavirus infection COVID-19 a pandemic in March 11 2020. The first data about the disease clinical features were reported from Wuhan China the epicenter of the outbreak; aside from the respiratory involvement, gastrointestinal manifestations have been described. Even though the exact mechanism for the new coronavirus tropism for the gastrointestinal tract is not well understood, angiotensin converting enzyme 2 receptor seems to play an important role as the entry site for the virus, since it is widespread located throughout the enteric mucosa. Fecal oral transmission is a possible contagion route, regardless of the presence of gastrointestinal symptoms, the virus has been isolated from feces even 7-12 days after a negative pharyngeal swab. COVID’s-19 gastrointestinal involvement is not an infrequent event, data reports patients who present with these symptoms have worst prognosis. Knowing the possible gastrointestinal manifestations might rise our clinical suspicion in order to establish earlier and timely diagnosis.


title: Inborn errors of immunity and coronovirus pandemic/ İmmün sistemin doğuştan kusurları ve korona virüs pandemisi

text: Inborn errors of immunity (IEI) are a heterogeneous group of diseases, typically characterized by recurrent ve severe infections, autoimmunity, autoinflammatory, allergic diseases and cancer. Since their immune response to pathogens are impaired, they have high risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, which has spread more than 180 countries. It is reported that two groups of people were prone to life-threatening coronavirus disease 2019 (COVID-19): aged (>65 years of age) and people with comorbidities such as hypertension, cardiovascular diseases, chronic lung, renal and liver diseases, diabetes mellitus, obesity, including immunodeficiencies. The aim of this paper is to present information about the new coronavirus, modes of transmission, clinical findings, diagnostic procedures, treatment modalities of COVID-19 to the physicians who is caring patients with primary immunodeficiency. Patients with primary immunodeficiencies, must exclusively rely on hygiene and protective measures to combat SARS-CoV-2, since vaccines or effective antiviral treatments against COVID-19 are still not available.


title: COVID19-Tracker: A shiny app to produce comprehensive data visualization for SARS-CoV-2 epidemic in Spain

text: Data visualization is an essential tool for exploring and communicating findings in medical research, and especially in epidemiological surveillance. The COVID19-Tracker web application systematically produces daily updated data visualization and analysis of the SARS-CoV-2 epidemic in Spain. It collects automatically daily data on COVID-19 diagnosed cases, intensive care unit admissions, and mortality, from February 24th, 2020 onwards. Two applications have already been developed; 1) to analyze data trends and estimating short-term projections; 2) to estimate the case fatality rate, and; 3) To assess the effect of the lockdown measures on the trends of incident data. The application may help for a better understanding of the SARS-CoV-2 epidemic data in Spain.


title: Designing a multi-epitope peptide-based vaccine against SARS-CoV-2

text: COVID-19 pandemic has resulted so far 14,395,16 confirmed cases with 85,711 deaths from the 212 countries, or territories. Due to multifacet issues and challenges in implementation of the safety & preventive measures, inconsistent coordination between societies-governments and most importanly lack of specific vaccine to SARS-CoV-2, the spread of Wuhan originated virus is still uprising after taking a heavy toll on human life. In the present study, we mapped several immunogenic epitopes (B-cell, T-cell, and IFN-gamma) over the entire structural proteins of SARS-CoV-2 and by applying various computational and immunoinformatics approaches, we designed a multi-epitope peptide based vaccine that predicted high immunogenic response in the largest proportion of world’s human population. To ensure high expression of the recombinant vaccine in E. coli, codon optimization and in-silico cloning were also carried out. The designed vaccine with high molecular affinity to TLR3 and TLR4, was found capable to initiate effective innate and adaptive immune response. The immune simulation also suggested uprising high levels of both B-cell and T-cell mediated immunity which on subsequent exposure cleared antigen from the system. The proposed vaccine found promising by yielding desired results and hence, should be tested by practical experimentations for its functioning and efficacy to neutralize SARS-CoV-2.


title: Optimal resource diffusion for suppressing disease spreading in multiplex networks

text: Resource diffusion is an ubiquitous phenomenon, but how it impacts epidemic spreading has received little study. We propose a model that couples epidemic spreading and resource diffusion in multiplex networks. The spread of disease in a physical contact layer and the recovery of the infected nodes are both strongly dependent upon resources supplied by their counterparts in the social layer. The generation and diffusion of resources in the social layer are in turn strongly dependent upon the state of the nodes in the physical contact layer. Resources diffuse preferentially or randomly in this model. To quantify the degree of preferential diffusion, a bias parameter that controls the resource diffusion is proposed. We conduct extensive simulations and find that the preferential resource diffusion can change phase transition type of the fraction of infected nodes. When the degree of interlayer correlation is below a critical value, increasing the bias parameter changes the phase transition from double continuous to single continuous. When the degree of interlayer correlation is above a critical value, the phase transition changes from multiple continuous to first discontinuous and then to hybrid. We find hysteresis loops in the phase transition. We also find that there is an optimal resource strategy at each fixed degree of interlayer correlation where the threshold reaches a maximum and under which the disease can be maximally suppressed. In addition, the optimal controlling parameter increases as the degree of inter-layer correlation increases.


Artificial intelligence plays an important role in containing public health emergencies


title: Estimulación cardiaca tras pandemia de la COVID-19. Propuesta de desescalada de la Sección de Estimulación Cardiaca de la Sociedad Española de Cardiología

text: RESUMEN La pandemia de la enfermedad causada por el coronavirus SARS-CoV-2 (COVID-19) ha afectado seriamente la atención a todas las patologías urgentes, y también el seguimiento de pacientes en tratamiento por enfermedades crónicas. Una vez superado el pico de la pandemia debemos reiniciar la atención a nuestros pacientes, en ocasiones con cambios sustanciales respecto del tipo de asistencia que prestábamos con anterioridad. Desde la Sección de Estimulación Cardiaca de la Sociedad Española de Cardiología proponemos un esquema de trabajo para garantizar una atención eficaz, y también segura para pacientes y profesionales. Las intervenciones quirúrgicas deberán realizarse tras realización de un test o la cumplimentación de un listado de verificación para determinar el riesgo del paciente de estar infectado por SARS-CoV-2. En cuanto al seguimiento posterior apostamos firmemente por una organización centrada en un programa organizado de monitorización remota. ABSTRACT The coronavirus disease 2019 (COVID-19) pandemic has seriously affected care for all urgent diseases, as well as the follow-up of patients with chronic diseases. Once the peak of the pandemic has been overcome, we must restart care for our patients, sometimes with substantial changes in the type of care we previously provided. From the Section on Cardiac Pacing of the Spanish Society of Cardiology we propose a working scheme to ensure effective and also safe care for both patients and professionals. Surgical interventions should be performed, if possible, after a test or the completion of a checklist to determine the patient's risk of being infected with SARS-CoV-2. As for follow-up, we are strongly committed to an organization focused on an organized remote monitoring program.


title: Artificial intelligence applied on chest X-ray can aid in the diagnosis of COVID-19 infection: a first experience from Lombardy, Italy

text: Objectives We tested artificial intelligence (AI) to support the diagnosis of COVID-19 using chest X-ray (CXR). Diagnostic performance was computed for a system trained on CXRs of Italian subjects from two hospitals in Lombardy, Italy. Methods We used for training and internal testing an ensemble of ten convolutional neural networks (CNNs) with mainly bedside CXRs of 250 COVID-19 and 250 non-COVID-19 subjects from two hospitals. We then tested such system on bedside CXRs of an independent group of 110 patients (74 COVID-19, 36 non COVID-19) from one of the two hospitals. A retrospective reading was performed by two radiologists in the absence of any clinical information, with the aim to differentiate COVID-19 from non-COVID-19 patients. Real-time polymerase chain reaction served as reference standard. Results At 10-fold cross-validation, our AI model classified COVID-19 and non COVID-19 patients with 0.78 sensitivity (95% confidence interval [CI] 0.74-0.81), 0.82 specificity (95% CI 0.78-0.85) and 0.89 area under the curve (AUC) (95% CI 0.86-0.91). For the independent dataset, AI showed 0.80 sensitivity (95% CI 0.72-0.86) (59/74), 0.81 specificity (29/36) (95% CI 0.73-0.87), and 0.81 AUC (95% CI 0.73-0.87). Radiologists reading obtained 0.63 sensitivity (95% CI 0.52-0.74) and 0.78 specificity (95% CI 0.61-0.90) in one centre and 0.64 sensitivity (95% CI 0.52-0.74) and 0.86 specificity (95% CI 0.71-0.95) in the other. Conclusions This preliminary experience based on ten CNNs trained on a limited training dataset shows an interesting potential of AI for COVID-19 diagnosis. Such tool is in training with new CXRs to further increase its performance.


title: The Impact of Social Distancing on COVID19 Spread: State of Georgia Case Study

text: As the COVID19 spread in the US continues to grow, local and state officials face difficult decisions about when and how to transition to a new normal. We developed an agent-based simulation model to project the infection spread; outcomes include the number of COVID19 infections and resulting severe outcomes, and the need for hospital capacity under social distancing, particularly, shelter-in-place and voluntary quarantine. We populated the model using COVID19-specific parameters for the natural history of the disease and data from Georgia on the agents interactions and demographics. The simulation study covered a six-month period, testing different social distancing scenarios, including baselines (no-intervention or school closure only) and combinations of shelter-in-place and voluntary quarantine with different timelines and compliance levels. The outcomes are compared at the state and community levels. Main outcomes are the number and percentage of cumulative and daily new and symptomatic and asymptomatic infections, hospitalizations, and deaths; COVID19-related demand for hospital beds, ICU beds, and ventilators. Results: The combined intervention of shelter-in-place followed by voluntary quarantine reduced peak infections from 180,000 under no intervention and 120,000 under school closure, respectively, to below 80,000, and delayed the peak from April to June or later. Increasing shelter-in-place duration from four to five weeks yielded 3-14% and 4-6% decrease in cumulative infection and fatality rates, respectively. Regardless of the shelter-in-place duration, increasing voluntary quarantine compliance decreased daily new infections from almost 80,000 to 50,000, and decreased cumulative infection rate by 50%. The total number of fatalities ranged from 6,150 to 17,900 under different scenarios. Peak infection date varied across scenarios and counties; on average, increasing shelter-in-place duration delayed the peak day by 7 days across counties. The peak percentage is similar across rural and urban counties. Region D is estimated to have the highest COVID19-related healthcare needs with 7,357 hospital beds, 1,141 ICU beds, and 558 ventilators. Conclusions and Relevance Shelter-in-place followed by voluntary quarantine substantially reduce COVID19 infections, healthcare resource needs, and severe outcomes; delay the peak; and enable better preparedness. Time of the peak is projected to vary across locations, enabling reallocation of health system capacity.


title: Predicting the epidemic curve of the coronavirus (SARS-CoV-2) disease (COVID-19) using artificial intelligence

text: Objectives: The current form of severe acute respiratory syndrome called coronavirus disease 2019 (COVID19) caused by a coronavirus (SARSCoV2) is a major global health problem. The aim of our study was to use the official data and predict the possible outcomes of the COVID 19 pandemic using artificial intelligence (AI) based RNNs (Recurrent Neural Networks), then compare and validate the predicted and observed data. Materials and Methods: We used the publicly available datasets of World Health Organization and Johns Hopkins University to create the training dataset, then have used recurrent neural networks (RNNs) with gated recurring units (Long Short Term Memory: LSTM units) to create 2 Prediction Models. Information collected in the first t time steps were aggregated with a fully connected (dense) neural network layer and a consequent regression output layer to determine the next predicted value. We used root mean squared logarithmic errors (RMSLE) to compare the predicted and observed data, then recalculated the predictions again. Results: The result of our study underscores that the COVID19 pandemic is probably a propagated source epidemic, therefore repeated peaks on the epidemic curve (rise of the daily number of the newly diagnosed infections) are to be anticipated. The errors between the predicted and validated data and trends seems to be low. Conclusions: The influence of this pandemic is great worldwide, impact our everyday lifes. Especially decision makers must be aware, that even if strict public health measures are executed and sustained, future peaks of infections are possible. The AI based predictions might be useful tools for predictions and the models can be recalculated according to the new observed data, to get more precise forecast of the pandemic.


title: Changes in RT-PCR-positive SARS-CoV-2 rates in adults and children according to the epidemic stages

text: Aim To describe the trends of RT-PCR positive SARS-CoV-2 rates in children and adults according to the time of COVID-19 epidemic. Methods In this prospective multicenter study involving 45 pediatric units, we collected the results of nasopharyngeal swabs in France from March 2, 2020 to April 26, 2020. Results During the study period, 52,588 RT-PCR tests for SARS-CoV-2 were performed, 6,490 in children and 46,098 in adults. The rate of positive tests for children was 2- to 7-fold less than that for adults. These rates varied according to the time of the epidemic and were higher at the peak. The lower rates of positive test in children persisted during the surveillance period but varied according to the time in the epidemic. Conclusion The rate of positive RT-PCR positive SARS-CoV-2 tests for children was always less than that for adults but vary according to the epidemic stage.


title: Distribution and clinical significance of ACE2, a key receptor of 2019-nCoV, in ocular tissues/ 新型冠状病毒关键受体ACE2在眼部的分布及其临床意义

text: Coronavirus disease-19 (COVID-19) has reached pandemic status, and its pathogeny is the 2019 novel coronavirus (2019-nCoV). 2019-nCoV mainly causes human respiratory infection and pulmonary inflammation; however, some COVID-19 patients are found to present viral conjunctivitis. Bilateral viral conjunctivitis is an initial symptom in some other cases. It is therefore, vital to understand whether the eye can be directly infected by the virus, as well as the consequences of the viral infection in the ocular tissue. 2019-nCoV invades human cells primarily by binding to the angiotensin-converting enzyme 2 (ACE2) receptors. ACE2 expresses, not only in the lungs, kidneys, and cardiovascular system, but also in human conjunctiva, cornea, aqueous humor, and retina. Therefore, it is crucial to comprehensively expand the present understanding of the COVID-19 infection mechanism and pathogenesis by clarifying the distribution of ACE2 in the eye. ACE2 is not only the receptor of 2019-nCoV, but also a key enzyme in the renin-angiotensin system (RAS). RAS, which appears relatively independent in the eye, plays a modulating role and is associated with many common eye diseases. This article reviews the distribution and clinical significance of ACE2 in ocular tissues.


Reply To The Article “Bariatric Surgical Practice During the Initial Phase of COVID-19 Outbreak.” by Aminian, A., Kermansaravi, M., Azizi, S. et al. Published in Obesity Surgery


title: How many COVID-19 cases could have been prevented in the US if its interventions were as effective as those in China and South Korea?

text: The COVID-19 pandemic has forced governments to take measures to contain the spread of the disease; however, the effects have varied significantly from one country to another contingent on governments' responses. Countries that have flattened their coronavirus curves prove that interventions can bring COVID-19 under control. These achievements hold lessons, such as the strict social distancing and coordinated efforts of all government levels in China and massive testing in South Korea, for other countries battling the coronavirus around the world. In this work, we attempt to estimate how many COVID-19 cases could have been prevented in the United States (US) when compared with the US's actual number of cases assuming that on a certain date, the US took China-like or South Korea-like interventions and that these interventions would have been as effective in the US as in China and South Korea. We found that if that date was at the early stage of the outbreak (March 10), more than 99% (1.15 million) fewer infected cases could be expected by the end of the epidemic. This number decreases to 66.03% and 73.06% fewer infected cases with the China-like scenario and the South Korea-like scenario, respectively, if actions were taken on April 1, highlighting the need to respond quickly and effectively to fight the virus. Furthermore, we found that although interventions in both China and South Korea allowed the COVID-19 outbreak to be managed, the epidemic could still oscillate without strict large-scale lockdown measures, as shown in South Korea. Our results demonstrate that early effective interventions can save considerably more people from infection and provide a worldwide alert regard the need for swift response.


title: Modeling and Experimental Analysis of Energy Attenuation and Partitioning during Laser Based Direct Energy Deposition

text: Abstract Energy attenuation and partitioning are important phenomena during laser-material interaction in laser based direct energy deposition (DED). They have immediate impact on molten pool thermal history and thus affecting the quality of the fabricated part. In this paper, a lumped capacity model was developed to analyze the energy attenuation and partitioning in DED for Inconel (IN) 718 fabrication. Energy absorption and reflection by powders and substrate, energy loss due to radiation and convection as well as latent heat of fusion were quantified based on experimental analysis. High-resolution infrared camera was used to measure the temperature of the molten pool. The energy attenuation by the powders was measured by a power meter. The results suggest that the energy attenuation coefficient of IN 718 in DED is 6.13 % when laser power is 250 W. Also, it is concluded that about 36.3 % of the laser energy is absorbed by the substrate, only a small amount of energy (less than 1 %) is lost due to radiation and convection.


title: Radiological Findings in Patients with COVID-19

text: After its origin in Wuhan, China, coronavirus related respiratory illness spread across the globe, being declared as a pandemic by WHO on March 13, 2020. Because it is acquired via respiratory droplets, community spread is responsible for the recent global crisis. The current diagnostic options include real-time polymerase chain reaction (RT-PCR) and a few serology tests, including but not limited to the recently approved five minutes serology tests. The disease presents as a lower respiratory tract illness. Anecdotal experiences have shown that imaging characteristics are crucial to diagnosis as radiological evidence of disease appears prior to clinical manifestations and tends to evolve over time, which can be useful in predicting the stage of the disease. CT scan is more sensitive than a chest X-ray in highlighting these changes.


title: Anxiety and Depression in Health Workers and General Population During COVID-19 Epidemic in IRAN: A Web-Based Cross-Sectional Study

text: The COVID-19 outbreak has exerted a great deal of psychological pressure on Iranian health workers and the general population. In the present study, the prevalence of anxiety and depression symptoms along with the related variables in this epidemic were investigated.An online cross-sectional study was conducted for the general public and healthcare workers in IRAN using a questionnaire comprised of demographic questions and Hospital Anxiety and Depression Scale. Chi square test was used to compare categorical variables, and univariate and multivariate logistic regression models were conducted.Of the 2045 participants,1136 (65.6%) were considered to have moderate and severe anxiety symptoms, and 865(42.3%) had moderate and severe depression symptoms. Based on the logistic regression models, the prevalence of anxiety was higher in the females than in the males (OR=1.4, 95% CI: 1.123-1.643, P=.002); the prevalence of anxiety was significantly higher in those aged 30-39 years than in other age groups (OR=1.6, 95% CI: 1.123-2.320, P=0.001); furthermore, the prevalence of anxiety and depression was significantly higher in doctors and nurses compared with other occupations (OR=1.9, 95% CI: 1.367-2.491, P< 0.001) and(OR=1.5, 95% CI: 1.154-2.021, P=0.003). In addition, the prevalence of anxiety symptoms in the likely-infected COVID-19 group was higher than in the noninfected COVID-19 group (OR=1.35, 95% CI: 1.093-1.654, P=0.005).A majority of health workers and general population have anxiety and depression symptoms. These symptoms are more widespread in doctors and nurses in comparison to other occupations, and psychological interventions might be conducive to reducing the negative symptoms.


title: Comparison of Flow Stress of Aluminum Alloy 6061-T6 Obtained From Chip Pulling Orthogonal Cutting and Kolsky Bar Testing

text: Abstract Machining can be used as a test for the flow stress of materials under conditions of high strain (ε > 1) and strain rate (102/s to 106/s). Constitutive models of metallic materials are conventionally obtained by dynamic compression tests such as the Split-Hopkinson (Kolsky) bar test at lower strain (ε < 0.3) and strain rate (103/s to 104/s). To compare the flow stress obtained from both tests under identical conditions, the strain in the primary shear zone (PSZ) in orthogonal cutting tests has been lowered using high rake angle (α = 45°) cutting tools to ε ≈ 0.8, and by adding chip pulling to ε ≈ 0.5. To our knowledge this is the first time that flow stress estimates are obtained from machining at such low strain values. With some modifications, the strain in Kolsky bar testing has been increased up to ε = 0.8, and the stress-strain curve obtained is compared to flow stress estimates from orthogonal cutting tests under the same strain and similar strain rates. The results work, show for the first time, that the flow stress measured from cutting tests agree closely with those obtained from Kolsky bar testing.


title: The role of alexithymia in the mental health problems of home-quarantined university students during the COVID-19 pandemic in China

text: OBJECTIVE: While it is well known that mental health problems are common consequences of deadly pandemics, the association with alexithymia is less clear. This study examined this association in an evaluation of home-quarantined university students during the 2019/2020 COVID-19 pandemic in China. METHODS: In total, 2501 home-quarantined students from six southwest Chinese universities completed the following questionnaires: the 20-item Toronto Alexithymia Scale (TAS-20), the Posttraumatic Stress Disorder Checklist-Civilian Version (PCL—C), and the Patients Health Questionnaire-9 (PHQ-9), after which structural equation modeling (SEM) and mediation analyses were employed to extract and evaluate the possible associations. RESULTS: It was found that participants with probable depression or PTSD also reported more severe alexithymia features, such as difficulties in identifying feelings (DIF) or describing feelings (DDF). Alexithymia was also found to partially mediate the effect of number of exposures on mental health problems. CONCLUSION: These results suggested that implementing strategies to assist young people identify and deal with their own emotions and those of others could prevent or mitigate the mental health problems associated with deadly pandemic events. However, future longitudinal studies are needed to examine the specific involvement of DIF or DDF in people with mental health problems.


title: The protein expression profile of ACE2 in human tissues

text: The novel SARS-coronavirus 2 (SARS-CoV-2) poses a global challenge on healthcare and society. For understanding the susceptibility for SARS-CoV-2 infection, the cell type-specific expression of the host cell surface receptor is necessary. The key protein suggested to be involved in host cell entry is Angiotensin I converting enzyme 2 (ACE2). Here, we report the expression pattern of ACE2 across >150 different cell types corresponding to all major human tissues and organs based on stringent immunohistochemical analysis. The results were compared with several datasets both on the mRNA and protein level. ACE2 expression was mainly observed in enterocytes, renal tubules, gallbladder, cardiomyocytes, male reproductive cells, placental trophoblasts, ductal cells, eye and vasculature. In the respiratory system, the expression was limited, with no or only low expression in a subset of cells in a few individuals, observed by one antibody only. Our data constitutes an important resource for further studies on SARS-CoV-2 host cell entry, in order to understand the biology of the disease and to aid in the development of effective treatments to the viral infection.


title: Flattening the curve before it flattens us: hospital critical care capacity limits and mortality from novel coronavirus (SARS-CoV2) cases in US counties

text: ABSTRACT Background As of March 26, 2020, the United States had the highest number of confirmed cases of Novel Coronavirus (COVID-19) of any country in the world. Hospital critical care is perhaps the most important medical system choke point in terms of preventing deaths in a disaster scenario such as the current COVID-19 pandemic. We therefore brought together previously established disease modeling estimates of the growth of the COVID-19 epidemic in the US under various social distancing contact reduction assumptions, with local estimates of the potential critical care surge response across all US counties. Methods Estimates of spatio-temporal COVID-19 demand and medical system critical care supply were calculated for all continental US counties. These estimates were statistically summarized and mapped for US counties, regions and urban versus non-urban areas. Estimates of COVID-19 infections and patients needing critical care were calculated from March 24, 2020 to April 24, 2020 for three different estimated population levels - 0%, 25%, and 50% - of contact reduction (through actions such as social distancing). Multiple national public and private datasets were linked and harmonized in order to calculate county-level critical care bed counts that included currently available beds and those that could be made available under four surge response scenarios - very low, low, medium, and high - as well as excess deaths stemming from inaccessible critical care. Results Surge response scenarios ranged from a very low total supply 77,588 critical care beds to a high total of 278,850 critical care beds. Over the four week study period, excess deaths from inaccessible critical care ranged from 24,688 in the very low response scenario to 13,268 in the high response scenario. Northeastern and urban counties were projected to be most affected by excess deaths due to critical care shortages, and counties in New York, Colorado, and Virginia were projected to exceed their critical care bed limits despite high levels of COVID-19 contact reduction. Over the four week study period, an estimated 12,203-19,594 excess deaths stemming from inaccessible critical care could be averted through greater preventive actions such as travel restrictions, publicly imposed contact precautions, greater availability of rapid testing for COVID-19, social distancing, self-isolation when sick, and similar interventions. An estimated 4,029-11,420 excess deaths stemming from inaccessible critical care could be averted through aggressive critical care surge response and preparations, including high clearance of ICU and non-ICU critical care beds and extraordinary measures like using a single ventilator for multiple patients. Conclusions Unless the epidemic curve of COVID-19 cases is flattened over an extended period of time, the US COVID-19 epidemic will cause a shortage of critical care beds and drive up otherwise preventable deaths. The findings here support value of preventive actions to flatten the epidemic curve, as well as the value of exercising extraordinary surge capacity measures to increase access to hospital critical care for severely ill COVID-19 patients.


title: Multi-Omics integration analysis of respiratory specimen characterizes baseline molecular determinants associated with COVID-19 diagnosis.

text: Abstract: Rapid diagnosis and precise prognostication of SARS-CoV-2 infection remains a major challenge. A multi-omic approach was adopted, and in the discovery phase, global proteome/metaproteome/metabolome were analysed in the respiratory specimens of SARS-CoV-2 positive [n=20], negative [n=20], and H1N1 positive [n=5] cases. We identified MX1 (MX Dynamin Like GTPase 1) and WARS (Tryptophan--tRNA ligase) as clues to viral diagnosis and validated in 200 SARS-CoV-2 suspects. MX1 >30pg/ml and WARS >25ng/ml segregated virus positives patients [(AUC=94%CI(0.91-0.97)]. Distinct increase in SARS-CoV-2 induced immune activation, metabolic reprograming and a decrease in oxygen transport, wound healing, fluid regulation, vitamin and steroid metabolism was seen (p<0.05). Multi-omics profiling correlated with viraemia and segregated asymptomatic COVID-19 patients. Additionally, the multiomics approach identified increased respiratory pathogens [Burkholderiales, Klebsiella pneumonia] and decreased lactobacillus salivarius (FDR<0.05, p<0.05) in COVID-19 specimens. Conclusion: Novel proteins [MX1 and WARS] can rapidly and reliably diagnose SARS-CoV-2 infection and identify asymptomatic and mild disease.


title: INTRODUCTION

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title: Risk assessment and prediction of severe or critical illness of COVID-19 in the elderly

text: Background: This study aims to investigate the clinical characteristics and risk prediction of severe or critical events of COVID-19 in the elderly patients in China. Methods: The clinical data of COVID-19 in the elderly patients admitted to the Shanghai Public Health Clinical Center during the period of January 20, 2020 to March 16, 2020 were collected. A retrospective cohort study design was conducted to screen out independent factors through Cox univariable regression analysis and multivariable regression analysis, and the efficacy of risk prediction of severe or critical illness was examined through the receiver operating characteristic (ROC) curve. Results: A total of 110 elderly patients with COVID-19 were enrolled. 52 (47.3%) were males and 21 (19.1%) had severe or critical illness. Multivariable regression analysis showed that CD4 cells and D-dimer were independent risk factors. D-dimer, CD4 cells, and D-dimer/CD cells ratios with cut off values of 0.65 (mg/L), 268 (cell/ul) and 431 were in the prediction of severe or critical illness of the elderly COVID-19. The AUC value of D-dimer, CD4 cells, CD4 cells/D-dimer ratio, the tandem group and the parallel group were 0.703, 0.804, 0.794, 0.812 and 0.694, respectively. Conclusions: D-dimer, CD4 cells and their combination have risk assessment value in predicting severe or critical illness of COVID-19 in the elderly.


title: A general model of population dynamics accounting for multiple kinds of interaction

text: Population dynamics has been modelled using differential equations almost since Malthus times, more than two centuries ago. Basic ingredients of population dynamics models are typically a growth rate, a saturation term in the form of Verhulst’s logistic brake, and a functional response accounting for interspecific interactions. However intraspecific interactions are not usually included in the equations. The simplest models use linear terms to represent a simple picture of the nature, meanwhile to represent more complex landscapes, it is necessary to include more terms with higher order or analytically more complex. The problem to use a simpler or more complex model depends on many factors: mathematical, ecological, or computational. To address it, here we discuss a new model based on a previous logistic-mutualistic model. We have generalised the interspecific terms (for antagonistic and competitive relationships) and we have also included new polynomial terms to explain any intraspecific interaction. We show that by adding simple intraspecific terms, new free-equilibrium solutions appear driving a much richer dynamics. These new solutions could represent more realistic ecological landscapes by including a new high order term.


title: Companies are racing to develop COVID-19 tests for the US. Will the tests help?

text: These speed bumps are some of the reasons why many industry watchers and public health officials are praising the development of a 5 min bedside, or point-of-care, test produced by Abbott Laboratories Approved in late March, the test relies on PCR but uses a different method of copying genetic material, allowing it to be done at a constant temperature and quickly Other companies that use this method, called isothermal amplification, for infectious disease diagnostics have developed specialized enzymes that can copy viral RNA without the temperature cycling used in more traditional PCR It’s not clear exactly how Abbott is employing isothermal amplification, but the company says the test can be done in a small, portable machine that many hospitals already use to diagnose other infectious diseases Abbott says this test and another, more traditional PCR diagnostic it developed can perform up to 5 million COVID-19 tests per month total


Coronavirus pandemic (COVID-19): what speech therapists should know/ Pandemia de coronavirus (COVID-19): o que os fonoaudiologos devem saber


title: Potential magnitude of COVID-19-induced healthcare resource depletion in Ontario, Canada

text: Background: The global spread of coronavirus disease 2019 (COVID-19) continues in several jurisdictions, causing significant strain to healthcare systems. The purpose of our study is to predict the impact of the COVID-19 pandemic on patient outcomes and the healthcare system in Ontario, Canada. Methods: We developed an individual-level simulation to model the flow of COVID-19 patients through the Ontario healthcare system. We simulated different combined scenarios of epidemic trajectory and healthcare capacity. Outcomes include numbers of patients needing admission to the ward, Intensive Care Unit (ICU), and requiring ventilation; days to resource depletion; and numbers of patients awaiting resources and deaths associated with limited access to resources. Findings: We demonstrate that with effective early public health measures system resources need not be depleted. For scenarios considering late or ineffective implementation of physical distancing, health system resources would be depleted within 14-26 days. Resource depletion was also avoided or delayed with aggressive measures to rapidly increase ICU, ventilator, and acute care hospital capacity. Interpretation: We found that without aggressive physical distancing measures the Ontario healthcare system would have been inadequately equipped to manage the expected number of patients with COVID-19, despite the rapid capacity increase. This overall lack of resources would have led to an increase in mortality. By slowing the spread of the disease via ongoing public health measures and having increased healthcare capacity, Ontario may have avoided catastrophic stresses to its health care system.


Will the COVID-19 pandemic make us reconsider the relevance of short food supply chains and local productions?


title: Nosocomial Infections Among Patients with COVID-19, SARS and MERS: A Rapid Review and Meta-Analysis

text: Background: COVID-19, a disease caused by SARS-CoV-2 coronavirus, has now spread to most countries and regions of the world. As patients potentially infected by SARS-CoV-2 need to visit hospitals, the incidence of nosocomial infection can be expected to be high. Therefore, a comprehensive and objective understanding of nosocomial infection is needed to guide the prevention and control of the epidemic. Methods: We searched major international and Chinese databases Medicine, Web of science, Embase, Cochrane, CBM(China Biology Medicine disc), CNKI (China National Knowledge Infrastructure) and Wanfang database)) for case series or case reports on nosocomial infections of COVID-19, SARS(Severe Acute Respiratory Syndromes) and MERS(Middle East Respiratory Syndrome) from their inception to March 31st, 2020. We conducted a meta-analysis of the proportion of nosocomial infection patients in the diagnosed patients, occupational distribution of nosocomial infection medical staff and other indicators. Results: We included 40 studies. Among the confirmed patients, the proportions of nosocomial infections were 44.0%, 36.0% and 56.0% for COVID-19, SARS and MERS, respectively. Of the confirmed patients, the medical staff and other hospital-acquired infections accounted for 33.0% and 2.0% of COVID-19 cases, 37.0% and 24.0% of SARS cases, and 19.0% and 36.0% of MERS cases, respectively. Nurses and doctors were the most affected among the infected medical staff. The mean numbers of secondary cases caused by one index patient were 29.3 and 6.3 for SARS and MERS, respectively. Conclusions: The proportion of nosocomial infection in patients with COVID-19 was 44%. Patients attending hospitals should take personal protection. Medical staff should be awareness of the disease to protect themselves and the patients. Keywords: COVID-19; meta-analysis; nosocomial infection; rapid review.


title: Benchmarking Methodology for Selection of Optimal COVID-19 Diagnostic Model Based on Entropy and TOPSIS Methods

text: Nowadays, coronavirus (COVID-19) is getting international attention due it considered as a life-threatened epidemic disease that hard to control the spread of infection around the world Machine learning (ML) is one of intelligent technique that able to automatically predict the event with reasonable accuracy based on the experience and learning process In the meantime, a rapid number of ML models have been proposed for predicate the cases of COVID-19 Thus, there is need for an evaluation and benchmarking of COVID-19 ML models which considered the main challenge of this study Furthermore, there is no single study have addressed the problem of evaluation and benchmarking of COVID diagnosis models However, this study proposed an intelligent methodology is to help the health organisations in the selection COVID-19 diagnosis system The benchmarking and evaluation of diagnostic models for COVID-19 is not a trivial process There are multiple criteria requires to evaluate and some of the criteria are conflicting with each other Our study is formulated as a decision matrix (DM) that embedded mix of ten evaluation criteria and twelve diagnostic models for COVID-19 The multi-criteria decision-making (MCDM) method is employed to evaluate and benchmarking the different diagnostic models for COVID19 with respect to the evaluation criteria An integrated MCDM method are proposed where TOPSIS applied for the benchmarking and ranking purpose while Entropy used to calculate the weights of criteria The study results revealed that the benchmarking and selection problems associated with COVID19 diagnosis models can be effectively solved using the integration of Entropy and TOPSIS The SVM (linear) classifier is selected as the best diagnosis model for COVID19 with the closeness coefficient value of 0 9899 for our case study data Furthermore, the proposed methodology has solved the significant variance for each criterion in terms of ideal best and worst best value, beside issue when specific diagnosis models have same ideal best value


title: Dreaming during the Covid-19 pandemic: Computational assessment of dream reports reveals mental suffering associated with negative feelings and contagion fear

text: Neuroscience and psychology agree that dreaming helps to cope with negative emotions and learn from experience. The current global threat related to the COVID-19 pandemic led to widespread social isolation. How does this situation affect dreams? Is dreaming during the pandemic related to mental suffering? Does the act of observing dreams help to mitigate mental suffering? To address these questions, we applied natural language processing tools to study 210 dream reports (n=67, Pandemic group n=42, plus control group balanced for age, sex and education) either before the Covid-19 outbreak or during March-April, 2020, following the pandemic announcement by the WHO and quarantine was imposed in Brazil. Post-announcement dreams showed a higher proportion of words related to anger and sadness, and higher average semantic similarities to the terms contamination and cleanness, which tended to increase over time. These features were associated with mental suffering related to social isolation, as they explained 39% of the variance in PANSS negative subscale (p=0.0092). Besides, dream observation was positively self-evaluated and dream similarities to contamination and cleanness revealed different impacts of the dream observation effect. These results corroborate the hypothesis that pandemic dreams reflect mental suffering, fear of contagion, and important changes in daily habits.


title: More than just a ticket canceller: The mitochondrial processing peptidase matures complex precursor proteins at internal cleavage sites

text: Most mitochondrial proteins are synthesized in the cytosol as precursors that carry N-terminal presequences. After import into mitochondria, these targeting signals are cleaved off by the mitochondrial processing peptidase MPP, giving rise to shorter mature proteins. Using the mitochondrial tandem protein Arg5,6 as a model substrate, we demonstrate that MPP has an additional role in preprotein maturation, beyond the removal of presequences. Arg5,6 is synthesized as a polyprotein precursor that is imported into the mitochondrial matrix and subsequently separated into two distinct enzymes that function in arginine biogenesis. This internal processing is performed by MPP, which cleaves the Arg5,6 precursor both at its N-terminus and at an internal site between the Arg5 and Arg6 parts. The peculiar organization and biogenesis of Arg5,6 is conserved across fungi and might preserve the mode of co-translational subunit association of the arginine biosynthesis complex of the polycistronic arginine operon in prokaryotic mitochondrial ancestors. Putative MPP cleavage sites are also present at the junctions in other mitochondrial fusion proteins from fungi, plants and animals. Our data suggest that, in addition to its role as “ticket canceller” for the removal of presequences, MPP exhibits a second, widely conserved activity as internal processing peptidase for complex mitochondrial precursor proteins.


docid: myaiilra

title: Spatiotemporal Analysis of Medical Resource Deficiencies in the U.S. under COVID-19 Pandemic

text: A data-driven approach is developed to estimate medical resource deficiencies or medical burden at county level during the COVID-19 pandemic from February 15, 2020 to May 1, 2020 in the U.S. Multiple data sources were used to extract local population, hospital beds, critical care staff, COVID-19 confirmed case numbers, and hospitalization data at county level. We estimate the average length of stay from hospitalization data at state level, and calculate the hospitalized rate at both state and county level. Then we develop two medical resource deficiency indices that measure the local medical burden based on the number of accumulated active confirmed cases normalized by local maximum potential medical resources, and the number of hospitalized patients that can be supported per ICU beds per critical care staff, respectively. The medical resources data, and the two medical resource deficiency indices are illustrated in a dynamic spatiotemporal visualization platform based on ArcGIS Pro Dashboards. Our results provide new insights into the U.S. pandemic preparedness and local dynamics relating to medical burdens in response to the COVID-19 pandemic.


title: Identification of Tumor-Reactive B Cells and Systemic IgG in Breast Cancer Based on Clonal Frequency in the Sentinel Lymph Node

text: A better understanding of antitumor immune responses is key to advancing the field of cancer immunotherapy. Endogenous immunity in cancer patients, such as circulating anticancer antibodies or tumor-reactive B cells, has been historically yet incompletely described. Here, we demonstrate that tumor-draining (sentinel) lymph node (SN) is a rich source for tumor-reactive B cells that give rise to systemic IgG anticancer antibodies circulating in the bloodstream of breast cancer patients. Using a synergistic combination of high-throughput B-cell sequencing and quantitative immunoproteomics, we describe the prospective identification of tumor-reactive SN B cells (based on clonal frequency) and also demonstrate an unequivocal link between affinity-matured expanded B-cell clones in the SN and antitumor IgG in the blood. This technology could facilitate the discovery of antitumor antibody therapeutics and conceivably identify novel tumor antigens. Lastly, these findings highlight the unique and specialized niche the SN can fill in the advancement of cancer immunotherapy. SIGNIFICANCE Using high-throughput molecular cloning and antibody proteomics to study coordinated antitumor immunity in breast cancer patients, we simultaneously demonstrate that the sentinel lymph node is a localized source of expanded antitumor B cells undergoing affinity maturation and that their secreted antibodies are abundant as systemic IgG circulating in blood.


docid: ozxpwrzy

title: Transcranial Focused Ultrasound Neuromodulation of Voluntary Movement-related Cortical Activity in Humans

text: Transcranial focused ultrasound (tFUS) is an emerging non-invasive brain stimulation tool for safely and reversibly modulating brain circuits. The effectiveness of tFUS on human brain has been demonstrated, but how tFUS influences the human voluntary motor processing in the brain remains unclear. We apply low-intensity tFUS to modulate the movement-related cortical potential (MRCP) originating from human subjects practicing a voluntary foot tapping task. 64-channel electroencephalograph (EEG) is recorded concurrently and further used to reconstruct the brain source activity specifically at the primary leg motor cortical area using the electrophysiological source imaging (ESI). The ESI illustrates the ultrasound modulated MRCP source dynamics with high spatiotemporal resolutions. The MRCP source is imaged and its source profile is further evaluated for assessing the tFUS neuromodulatory effects on the voluntary MRCP. Moreover, the effect of ultrasound pulse repetition frequency (UPRF) is further assessed in modulating the MRCP. ESI results show that tFUS significantly increases the MRCP source profile amplitude (MSPA) comparing to a sham ultrasound condition, and further, a high UPRF enhances the MSPA more than a low UPRF. This work provides the first evidence of tFUS enhancing the human voluntary movement-related cortical activity through excitatory modulation.


title: Role of ACE2/TMPRSS2 genes regulation by intestinal microRNA isoforms in the covid-19 pathogenesis/ РОЛЬ РЕГУЛЯЦИИ ГЕНОВ AПФ2/TMPRSS2 ИЗОФОРМАМИ микроРНК КИШЕЧНИКА В ПАТОГЕНЕЗЕ COVID-19

text: Coronavirus SARS-CoV-2, the cause of the COVID-19 pandemic, enters the cell by binding the cell surface proteins: angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). The expression of these proteins varies significantly in individual organs and tissues of the human body. One of the proteins' expression regulation mechanisms is based on the activity of the microRNA (miRNA) molecules, small non-coding RNAs, the most important function of which is the post-transcriptional negative regulation of gene expression. The study was aimed to investigate the mechanisms of the interactions between miRNA isoforms and ACE2/TMPRSS2 genes in the colon tissues known for the high level of expression of the described enzymes. The search for interactions was performed using the correlation analysis applied to the publicly available paired mRNA/miRNA sequencing data of colon tissues. Among the others, such miRNAs as miR-30c and miR-200c were identified known for their involvement in the coronavirus infection and acute respiratory distress syndrome pathogenesis. Thus, new potential mechanisms for the ACE2 and TMPRSS2 enzymes regulation were ascertained, as well as their possible functional activity in a cell infected with coronavirus.


title: Two mutations P/L and Y/C in SARS-CoV-2 helicase domain exist together and influence helicase RNA binding

text: RNA helicases play pivotal role in RNA replication by catalysing the unwinding of complex RNA duplex structures into single strands in ATP/NTP dependent manner. SARS coronavirus 2 (SARS-CoV-2) is a single stranded positive sense RNA virus belonging to the family Coronaviridae. The viral RNA encodes non structural protein Nsp13 or the viral helicase protein that helps the viral RNA dependent RNA polymerase (RdRp) to execute RNA replication by unwinding the RNA duplexes. In this study we identified a novel mutation at position 541of the helicase where the tyrosine (Y) got substituted with cytosine (C). We found that Y541C is a destabilizing mutation increasing the molecular flexibility and leading to decreased affinity of helicase binding with RNA. Earlier we had reported a mutation P504L in the helicase protein for which had not performed RNA binding study. Here we report that P504L mutation leads to increased affinity of helicase RNA interaction. So, both these mutations have opposite effects on RNA binding. Moreover, we found a significant fraction of isolate population where both P504L and Y541C mutations were co-existing.


title: Real-time detection of COVID-19 epicenters within the United States using a network of smart thermometers

text: Containing outbreaks of infectious disease requires rapid identification of transmission hotspots, as the COVID-19 pandemic demonstrates. Focusing limited public health resources on transmission hotspots can contain spread, thus reducing morbidity and mortality, but rapid data on community-level disease dynamics is often unavailable. Here, we demonstrate an approach to identify anomalously elevated levels of influenza-like illness (ILI) in real-time, at the scale of US counties. Leveraging data from a geospatial network of thermometers encompassing more than one million users across the US, we identify anomalies by generating accurate, county-specific forecasts of seasonal ILI from a point prior to a potential outbreak and comparing real-time data to these expectations. Anomalies are strongly correlated with COVID-19 case counts and may provide an early-warning system to locate outbreak epicenters.


title: Favipiravir versus Arbidol for COVID-19: A Randomized Clinical Trial

text: Background No clinically proven effective antiviral strategy exists for the epidemic Coronavirus Disease 2019 (COVID-19). Methods We conducted a prospective, randomized, controlled, open-label multicenter trial involving adult patients with COVID-19. Patients were randomly assigned in a 1:1 ratio to receive conventional therapy plus Umifenovir (Arbidol) (200mg*3/day) or Favipiravir (1600mg*2/first day followed by 600mg*2/day) for 10 days. The primary outcome was clinical recovery rate of Day 7. Latency to relief for pyrexia and cough, the rate of auxiliary oxygen therapy (AOT) or noninvasive mechanical ventilation (NMV) were the secondary outcomes. Safety data were collected for 17 days. Results 240 enrolled COVID-19 patients underwent randomization; 120 patients were assigned to receive Favipiravir (116 assessed), and 120 to receive Arbidol (120 assessed). Clinical recovery rate of Day 7 does not significantly differ between Favipiravir group (71/116) and Arbidol group (62/120) (P=0.1396, difference of recovery rate: 0.0954; 95% CI: -0.0305 to 0.2213). Favipiravir led to shorter latencies to relief for both pyrexia (difference: 1.70 days, P<0.0001) and cough (difference: 1.75 days, P<0.0001). No difference was observed of AOT or NMV rate (both P>0.05). The most frequently observed Favipiravir-associated adverse event was raised serum uric acid (16/116, OR: 5.52, P=0.0014). Conclusions Among patients with COVID-19, Favipiravir, compared to Arbidol, did not significantly improve the clinically recovery rate at Day 7. Favipiravir significantly improved the latency to relief for pyrexia and cough. Adverse effects caused Favipiravir are mild and manageable. This trial is registered with Chictr.org.cn (ChiCTR2000030254).


title: Spatial Distribution Characteristics of PM(2.5) and PM(10) in Xi’an City Predicted by Land Use Regression Models

text: PM(2.5) and PM(10) could increase the risk for cardiovascular and respiratory diseases in the general public and severely limit the sustainable development in urban areas. Land use regression models are effective in predicting the spatial distribution of atmospheric pollutants, and have been widely used in many cities in Europe, North America and China. To reveal the spatial distribution characteristics of PM(2.5) and PM(10) in Xi'an during the heating seasons, the authors established two regression prediction models using PM(2.5) and PM(10) concentrations from 181 monitoring stations and 87 independent variables. The model results are as follows: for PM(2.5), R(2) = 0.713 and RMSE =8.355 μg/m(3); for PM(10), R(2) = 0.681 and RMSE = 14.842 μg/m(3). In addition to the traditional independent variables such as area of green space and road length, the models also include the numbers of pollutant discharging enterprises, restaurants, and bus stations. The prediction results reveal the spatial distribution characteristics of PM(2.5) and PM(10) in the heating seasons of Xi'an. These results also indicate that the spatial distribution of pollutants is closely related to the layout of industrial land and the location of enterprises that generate air pollution emissions. Green space can mitigate pollution, and the contribution of traffic emission is less than that of industrial emission. To our knowledge, this study is the first to apply land use regression models to the Fenwei Plain, a heavily polluted area in China. It provides a scientific foundation for urban planning, land use regulation, air pollution control, and public health policy making. It also establishes a basic model for population exposure assessment, and promotes the sustainability of urban environments.


title: Efficient inactivation of SARS-CoV-2 by WHO-recommended hand rub formulations and alcohols

text: The recent emergence of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing COVID-19 is a major burden for health care systems worldwide. It is important to address if the current infection control instructions based on active ingredients are sufficient. We therefore determined the virucidal activity of two alcohol-based hand rub solutions for hand disinfection recommended by the World Health Organization (WHO), as well as commercially available alcohols. Efficient SARS-CoV-2 inactivation was demonstrated for all tested alcohol-based disinfectants. These findings show the successful inactivation of SARS-CoV-2 for the first time and provide confidence in its use for the control of COVID-19. Importance The current COVID-19 outbreak puts a huge burden on the world’s health care systems. Without effective therapeutics or vaccines being available, effective hygiene measure are of utmost importance to prevent viral spreading. It is therefore crucial to evaluate current infection control strategies against SARS-CoV-2. We show the inactivation of the novel coronavirus for the first time and endorse the importance of disinfectant-based hand hygiene to reduce SARS-CoV-2 transmission.


title: Immediate and Near Future Prediction of COVID-19 Patients in the U.S. Population Aged 65+ With the Prior Medical Conditions of Hypertension, Cardiovascular and Lung Diseases: Methods, Models and Acute Care Estimates

text: Our aim is to provide model-based estimates of the number of individuals aged 65 and greater who will become infected with COVID-19 during the period April 7 to June 30, 2020, 2020 who also have one or more combinations of three prior medical conditions: hypertension, cardiovascular disease, and lung diseases. We provide a breakdown of cases by each possible combination of a medical condition. We estimate that there are 13 million individuals aged 65+ who have one or a combination of three major prior medical conditions or a combination of these medical conditions aged 65+ in the U.S. who have one or at risk of acquiring COVID-19 during April and June, 2020 if proper precautions are not implemented and adhered. The model-based estimate of COVID-19 numbers for those aged 65+ is predicted to be between 34,000 to 104,000; a higher estimate attributable to inadequate precautions is predicted at 477,000 during April and June, 2020. Hospitalizations of patients both with and without ICU-admissions with more prevalent underlying conditions could range between 37,000 to 94,000 cases during the same period. These estimates may aid us in better understanding the potential volumes of patients requiring inpatient care.


title: Even more to handle: Additional sources of stress and trauma for clients from marginalized racial and ethnic groups in the United States during the COVID-19 pandemic

text: In addition the general stressors occurring as a result of the COVID-19 pandemic, individuals who are members of marginalized racial or ethnic minority groups in the United States may face additional stressors, such as pandemic-related, racially-based prejudice and discrimination and the magnification of pre-existing health disparities and their effects. Such stressors may increase pandemic-related and general health risks both directly and indirectly and increase the risk for both general and traumatic stress. These stressors and their historical and social contexts are discussed, and implications for clinicians are provided.


title: A Review of Potential Antiviral Drugs and Vaccines to Treat COVID-19

text: Coronavirus disease 19 (COVID-19) is a challenge to the whole humanity COVID-19 was first reported in China and rigorous researches are going on for developing vaccine for the pandemic This review was prepared by following PRISMA guidelines and used the resources from the Web of Science and PubMed This research focuses on the niches of symptoms and vaccines for COVID-19 The research for vaccine involves research for new vaccine and drug repurposing Out of various drug repurposing options, Remdesivir, and Favipiravir, Chloroquine and Lopinavir/Ritonavir were found to be the popular ones for treating COVID-19 patients across the world Even though there are concerns regarding asymptotic patients, the most dominant symptoms of COVID-19 are fever and cough, followed by Dyspnoea and muscle ache This review concludes that the COVID-19 related research should focus on developing immunity vaccines, and repurposing of drugs Research on the problems of quarantine life, patient monitoring, and usage of information technology in facing COVID-19 will improve the quality of patient handling during the pandemic The research on the effectiveness of various models of lockdown and regulation of social life during lockdown periods, improving the safety of health care workers in the workplace will definitely help the governments in their fight against COVID-19


title: eClinic: increasing use of telehealth as a risk reduction strategy during the covid-19 pandemic

text: Prior to the covid-19 pandemic, telehealth was already being rapidly adopted nationally by healthcare systems. During the covid-19 pandemic, increased use of telehealth may be considered as a risk reduction strategy. Benefits of this strategy may be conferred to both patients and health providers.


title: A flexible COVID-19 model to assess mitigation, reopening, virus mutation and other changes

text: The COVID-19 epidemic which began in China last year has expanded worldwide. A flexible SEIRD epidemiological model with time-dependent parameters is applied to modeling the pandemic. The value of the effective reproduction ratio is varied to quantify the impact of quarantines and social distancing on the number of infections and deaths, on their daily changes. and on the maxima in these daily rates expected during the epidemic. The effect of changing Reff is substantial. It ought to inform policy decisions around resource allocation, mitigation strategies and their duration, and economic tradeoffs. The model can also calculate the impact of changes in infectiousness or morbidity as the virus mutates, or the expected effects of a new therapy or vaccine assumed to arrive at a future date. The paper concludes with a discussion of a potential endemic end of COVID-19, which might involve times of about 100 years.


docid: konqndla

title: Does the COVID-19 pandemic refute probability neglect?

text: Cass Sunstein coined the term 'probability neglect' to characterize the cognitive bias of disregarding probability when assessing low-probability but high-impact threats He also related this cognitive bias to terrorism risk, andapplied the concept to the COVID-19 pandemic In this article, I show that such claims are not justified I argue that an alternative hypothesis could be that people who downplay the epidemiological threat and do not take precautionary measures suffer from exponential-growth bias I also show that probability theory, and thus the concept of probability neglect, cannot be easily applied to real-world problems, such as terrorist attacks or pandemics, occurring in a non-ergodic, uncertain environment


title: Social Distancing is Effective at Mitigating COVID-19 Transmission in the United States

text: COVID-19 is present in every state and over 90 percent of all counties in the United States. Decentralized government efforts to reduce spread, combined with the complex dynamics of human mobility and the variable intensity of local outbreaks makes assessing the effect of large-scale social distancing on COVID-19 transmission in the U.S. is a challenge. We generate a novel metric to represent social distancing behavior derived from mobile phone data, and examine its relationship with COVID-19 case reports at the county level. Our analysis reveals that social distancing is strongly correlated with decreased COVID-19 case growth rates for the 25 most affected counties in the United States, with a lag period consistent with the incubation time of SARS-CoV-2. We also demonstrate evidence that social distancing was already under way in many U.S. counties before county and state-level policies were implemented. This study strongly supports social distancing as an effective way to mitigate COVID-19 transmission in the United States.


title: Electric-field-driven microfluidics for rapid CRISPR-based diagnostics and its application to detection of SARS-CoV-2

text: The rapid spread of COVID-19 across the world has revealed major gaps in our ability to respond to new virulent pathogens. Rapid, accurate, and easily configurable molecular diagnostic tests are imperative to prevent global spread of new diseases. CRISPR-based diagnostic approaches are proving to be useful as field-deployable solutions. In a basic form of this assay, the CRISPR-Cas12 enzyme complexes with a synthetic guide RNA (gRNA). This complex is activated when it highly specifically binds to target DNA, and the activated complex non-specifically cleaves single-stranded DNA reporter probes labeled with a fluorophore-quencher pair. We recently discovered that electric field gradients can be used to control and accelerate this CRISPR assay by co-focusing Cas12-gRNA, reporters, and target. We achieve an appropriate electric field gradient using a selective ionic focusing technique known as isotachophoresis (ITP) implemented on a microfluidic chip. Unlike previous CRISPR diagnostic assays, we also use ITP for automated purification of target RNA from raw nasopharyngeal swab sample. We here combine this ITP purification with loop-mediated isothermal amplification, and the ITP-enhanced CRISPR assay to achieve detection of SARS-CoV-2 RNA (from raw sample to result) in 30 min for both contrived and clinical nasopharyngeal swab samples. This electric field control enables a new modality for a suite of microfluidic CRISPR-based diagnostic assays. Significance statement Rapid, early-stage screening is especially crucial during pandemics for early identification of infected patients and control of disease spread. CRISPR biology offers new methods for rapid and accurate pathogen detection. Despite their versatility and specificity, existing CRISPR-diagnostic methods suffer from the requirements of up-front nucleic acid extraction, large reagent volumes, and several manual steps—factors which prolong the process and impede use in low resource settings. We here combine on-chip electric-field control in combination with CRIPSR biology to directly address these limitations of current CRISPR-diagnostic methods. We apply our method to the rapid detection of SARS-CoV-2 RNA in clinical samples. Our method takes 30 min from raw sample to result, a significant improvement over existing diagnostic methods for COVID-19.


title: Basal Ganglia Involvement and Altered Mental Status: A Unique Neurological Manifestation of Coronavirus Disease 2019

text: Like other respiratory viruses, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may enter the central nervous system (CNS) via the hematogenous or neuronal path. However, neurological complications of coronavirus disease 2019 (COVID-19) have not been reported frequently. Encephalopathy has been described as a presenting symptom or complication of COVID-19 in some reports. We report a case of a 54-year-old patient who presented with unique clinical characteristics and imaging with brain basal ganglia involvement likely due to SARS-CoV-2 infection. In our experience, the incidence of spontaneous bilateral basal ganglia hemorrhage is rare. Further study will be needed to investigate this finding of the CNS and altered mental status in patients with this new type of coronavirus infection. Based on the case presented and other cases, understanding the pathways of virus neuroinvasion is necessary to help recognize possible pathologically related consequences of infection and to evaluate new diagnostic and management approaches that will help improve SARS-CoV-2 infection treatment and control.


title: Epidemiological identification of a novel infectious disease in real time: Analysis of the atypical pneumonia outbreak in Wuhan, China, 2019-20

text: Objective: Virological tests indicate that a novel coronavirus is the most likely explanation for the 2019-20 pneumonia outbreak in Wuhan, China. We demonstrate that non-virological descriptive characteristics could have determined that the outbreak is caused by a novel pathogen in advance of virological testing. Methods: Characteristics of the ongoing outbreak were collected in real time from two medical social media sites. These were compared against characteristics of ten existing pathogens that can induce atypical pneumonia. The probability that the current outbreak is due to "Disease X" (i.e., previously unknown etiology) as opposed to one of the known pathogens was inferred, and this estimate was updated as the outbreak continued. Results: The probability that Disease X is driving the outbreak was assessed as over 32% on 31 December 2019, one week before virus identification. After some specific pathogens were ruled out by laboratory tests on 5 Jan 2020, the inferred probability of Disease X was over 59%. Conclusions: We showed quantitatively that the emerging outbreak of atypical pneumonia cases is consistent with causation by a novel pathogen. The proposed approach, that uses only routinely-observed non-virological data, can aid ongoing risk assessments even before virological test results become available. Keywords: Epidemic; Causation; Bayes' theorem; Diagnosis; Prediction; Statistical model


title: Face Masks Considerably Reduce Covid-19 Cases in Germany

text: We use the synthetic control method to analyze the effect of face masks on the spread of Covid-19 in Germany. Our identification approach exploits regional variation in the point in time when face masks became compulsory. Depending on the region we analyse, we find that face masks reduced the cumulative number of registered Covid-19 cases between 2.3% and 13% over a period of 10 days after they became compulsory. Assessing the credibility of the various estimates, we conclude that face masks reduce the daily growth rate of reported infections by around 40%.


title: How and When to End the COVID-19 Lockdown: An Optimization Approach

text: Countries around the world are in a state of lockdown to help limit the spread of SARS-CoV-2. However, as the number of new daily confirmed cases begins to decrease, governments must decide how to release their populations from quarantine as efficiently as possible without overwhelming their health services. We applied an optimal control framework to an adapted Susceptible-Exposure-Infection-Recovery (SEIR) model framework to investigate the efficacy of two potential lockdown release strategies, focusing on the UK population as a test case. To limit recurrent spread, we find that ending quarantine for the entire population simultaneously is a high-risk strategy, and that a gradual re-integration approach would be more reliable. Furthermore, to increase the number of people that can be first released, lockdown should not be ended until the number of new daily confirmed cases reaches a sufficiently low threshold. We model a gradual release strategy by allowing different fractions of those in lockdown to re-enter the working non-quarantined population. Mathematical optimization methods, combined with our adapted SEIR model, determine how to maximize those working while preventing the health service from being overwhelmed. The optimal strategy is broadly found to be to release approximately half the population 2–4 weeks from the end of an initial infection peak, then wait another 3–4 months to allow for a second peak before releasing everyone else. We also modeled an “on-off” strategy, of releasing everyone, but re-establishing lockdown if infections become too high. We conclude that the worst-case scenario of a gradual release is more manageable than the worst-case scenario of an on-off strategy, and caution against lockdown-release strategies based on a threshold-dependent on-off mechanism. The two quantities most critical in determining the optimal solution are transmission rate and the recovery rate, where the latter is defined as the fraction of infected people in any given day that then become classed as recovered. We suggest that the accurate identification of these values is of particular importance to the ongoing monitoring of the pandemic.


title: The real time effective reproductive number for COVID-19 in the United States

text: none.