title: SARS-CoV-2 sequence typing, evolution and signatures of selection using CoVa, a Python-based command-line utility

text: The current global pandemic COVID-19, caused by SARS-CoV-2, has resulted in millions of infections worldwide in a few months. Global efforts to tackle this situation have produced a tremendous body of genomic data, which can be used for tracing transmission routes, characterization of isolates, and monitoring variants with potential for unusual virulence. Several groups have analyzed these genomes using different approaches. However, as new data become available, the research community needs a pipeline to perform a set of routine analyses, that can quickly incorporate new genome sequences and update the analysis reports. We developed a programmatic tool, CoVa, with this objective. It is a fast, accurate and user-friendly utility to perform a variety of genome analyses on hundreds of SARS-CoV-2 sequences. Using CoVa, we define a modified sequence typing nomenclature and identify sites under positive selection. Further analysis identified some peptides and sites showing geographical patterns of selection. Specifically, we show differences in sequence type distribution between sequences from India and those from the rest of the world. We also show that several sites show signatures of positive selection uniquely in sequences from India. Preliminary evolutionary analysis, using features that will be incorporated into CoVa in the near future, show a mutation rate of 7.4 × 10−4 substitutions/site/year, confirm a temporal signal with a November 2019 origin of SARS-CoV-2, and a heterogeneity in the geographical distribution of Indian samples.


title: Evaluation of the immunogenicity of prime-boost vaccination with the replication-deficient viral vectored COVID-19 vaccine candidate ChAdOx1 nCoV-19

text: Clinical development of the COVID-19 vaccine candidate ChAdOx1 nCoV-19, a replication-deficient simian adenoviral vector expressing the full-length SARS-CoV-2 spike (S) protein was initiated in April 2020 following non-human primate studies using a single immunisation. Here, we compared the immunogenicity of one or two doses of ChAdOx1 nCoV-19 in both mice and pigs. Whilst a single dose induced antigen-specific antibody and T cells responses, a booster immunisation enhanced antibody responses, particularly in pigs, with a significant increase in SARS-CoV-2 neutralising titres.


title: COVID-19 in England: spatial patterns and regional outbreaks

text: Aims: to investigate the spatiotemporal distribution of COVID-19 cases in England; to provide spatial quantification of risk at a high resolution; to provide information for prospective antigen and serological testing. Approach: We fit a spatiotemporal Negative Binomial generalised linear model to Public Health England SARS-CoV-2 testing data at the Lower Tier Local Authority region level. We assume an order-1 autoregressive model for case progression within regions, coupling discrete spatial units via observed commuting data and time-varying measures of traffic flow. We fit the model via maximum likelihood estimation in order to calculate region-specific risk of ongoing transmission, as well as measuring regional uncertainty in incidence. Results: We detect marked heterogeneity across England in COVID-19 incidence, not only in raw estimated incidence, but in the characteristics of within-region and between-region dynamics of PHE testing data. There is evidence for a spatially diverse set of regions having a higher daily increase of cases than others, having accounted for current case numbers, population size, and human mobility. Uncertainty in model estimates is generally greater in rural regions. Conclusions: A wide range of spatial heterogeneity in COVID-19 epidemic distribution and infection rate exists in England currently. Future work should incorporate fine-scaled demographic and health covariates, with continued improvement in spatially-detailed case reporting data. The method described here may be used to measure heterogeneity in real-time as behavioural and social interventions are relaxed, serving to identify "hotspots" of resurgent cases occurring in diverse areas of the country, and triggering locally-intensive surveillance and interventions as needed. Caveats: There is general concern over the ability of PHE testing data to capture the true prevalence of infection within the population, though this approach is designed to provide measures of spatial prevalence based on testing that can be used to guide further future testing effort. Now-casts of epidemic characteristics are presented based on testing data alone (as opposed to "true" prevalence in any one area). The model used in this analysis is phenomenological for ease and speed of principled parameter inference; we choose the model which best fits the current spatial case timeseries, without attempting to enforce "SIR"-type epidemic dynamics.


title: New S.I.R. model used in the projection of COVID 19 cases in Brazil

text: In this work, we proposed a variant of the SIR model, taking as based on models used to describe the epidemic outbreak in South Korea and Portugal, to study the SARS-CoV-2 epidemic curve in Brazil. The model presented here describes with reasonable agreement the number of COVID-19 cases registered in Brazil between February 26 and April 25, 2020 based on the hypothesis that there a large number no notified cases (11 to 1) and variation in contagion rate according to social isolation measures and greater or lesser exposure to the virus (highest rate in beginning from epidemic). To this end, we introduced an exposure factor, called {beta}1/{beta}2, which allows us to describe the influence of factors such as social isolation on dispersal from disease. The results also corroborate a phenomenon observed in countries that registered a high growth in cases in short period of time, to example of Italy, Spain and USA: if isolation measures are imposed late, the total number of cases explodes when the epidemic is approaching from peak, which implies a higher exposure rate in the first days of case registration. The model also predicts that the peak epidemic outbreak in Brazil, based on the number of cases, will occur around May 20, 2020.


title: What gastroenterologists should know during COVID-19 Pandemic!

text: The WHO has declared a Pandemic due to Novel Corona virus-19 (COVID-19). Patients usually have respiratory symptoms but gastrointestinal and hepatic dysfunction are not uncommon presentations and can lead to a delay in diagnosis and management. Virus shedding can continue even after the nasopharyngeal swab gets negative and could lead to faecal-oral transmission. The effects of COVID-19 on patients with decompensated liver disease is still not clear. Managing immunosuppressive drugs in liver transplant and inflammatory bowel disease is a major challenge without clear guidelines. Only emergency endoscopy is to be done with personal protection equipment. Chloroquine and Hydroxychloroquine has shown some beneficial effects and is being used off-label. Without effective treatment, it is imperative to take precautionary measures.


title: Individualized System for Augmenting Ventilator Efficacy (iSAVE): A Rapidly deployable system to expand ventilator capacity

text: The COVID-19 pandemic is overwhelming healthcare systems worldwide. A significant portion of COVID-19 patients develop pneumonia and acute respiratory distress syndrome (ARDS), necessitating ventilator support. Some health systems do not have the capacity to accommodate this surge in ventilator demand, leading to shortages and inevitable mortality. Some clinicians have, of necessity, jerry-rigged ventilators to support multiple patients, but these devices lack protected air streams or individualized controls for each patient. Moreover, some have not been tested under conditions of ARDS. We have developed the Individualized System for Augmenting Ventilator Efficacy (iSAVE), a rapidly deployable platform to more safely use a single ventilator to simultaneously support multiple critically-ill patients. The iSAVE enables patient-specific volume and pressure control and incorporates safety features to mitigate cross-contamination between patients and flow changes due to patient interdependencies within the respiratory circuit. Here we demonstrate through simulated and in vivo pig evaluation the capacity of the iSAVE to support a range of respiratory clinical states. By leveraging off-the-shelf components that are readily available to intensive care unit (ICU) caregivers, the iSAVE could potentially be translated for human application to expand the ventilation capacity of hospitals using existing ventilators, minimizing the need to procure additional ventilators.


Secondary Traumatic Stress


title: Psoriasis, biologic therapy, and the pandemic of the 21st century

text: The pandemic known as coronavirus disease-19 (COVID-19) has quickly spread worldwide, with a significant impact on lives all over the world. The complexity related to the new coronavirus and the clinical syndrome it causes is not yet fully understood. The impact of COVID-19 on patients with psoriasis under biologic agents is continuously being observed in this rapidly changing pandemic. A case-by-case evaluation must be made by dermatologists, and the final decision should be discussed and decided by both the patient and the specialist. Observations reveal that immunosuppressive therapy may have a role in the treatment of this virus, placing emphasis on the scenario of safety through maintenance of therapy with biologic agents, especially when there are no signs or symptoms related to the infection or contact with an infected patient.


title: COVID-19: Recovering estimates of the infected fatality rate during an ongoing pandemic through partial data

text: In an ongoing epidemic, the case fatality rate is not a reliable estimate of a disease's severity. This is particularly so when a large share of asymptomatic or pauci-symptomatic patients escape testing, or when overwhelmed healthcare systems are forced to limit testing further to severe cases only. By leveraging data on COVID-19, we propose a novel way to estimate a disease's infected fatality rate, the true lethality of the disease, in the presence of sparse and partial information. We show that this is feasible when the disease has turned into a pandemic and data comes from a large number of countries, or regions within countries, as long as testing strategies vary sufficiently. For Italy, our method estimates an IFR of 1.1% (95% CI: 0.2% - 2.1%), which is strongly in line with other methods. At the global level, our method estimates an IFR of 1.6% (95% CI: 1.1% - 2.1%). This method also allows us to show that the IFR varies according to each country's age structure and healthcare capacity.


Recommendations and management in dental practice during corona virus COVID-19


title: Assessment of dispersion of airborne particles of oral/nasal fluid by high flow nasal cannula therapy

text: Background Nasal High Flow (NHF) therapy delivers flows of heated humidified gases up to 60 LPM (litres per minute) via a nasal cannula. Particles of oral/nasal fluid released by patients undergoing NHF therapy may pose a cross-infection risk, which is a potential concern for treating COVID-19 patients. Methods Liquid particles within the exhaled breath of healthy participants were measured with two protocols: (1) high speed camera imaging and counting exhaled particles under high magnification (6 participants) and (2) measuring the deposition of a chemical marker (riboflavin-5-monophosphate) at a distance of 100 and 500 mm on filter papers through which air was drawn (10 participants). The filter papers were assayed with HPLC. Breathing conditions tested included quiet (resting) breathing and vigorous breathing (which here means nasal snorting, voluntary coughing and voluntary sneezing). Unsupported (natural) breathing and NHF at 30 and 60 LPM were compared. Results (1) Imaging: During quiet breathing, no particles were recorded with unsupported breathing or 30 LPM NHF (detection limit for single particles 33 microns). Particles were detected in 2 of 6 participants at 60 LPM quiet breathing at approximately 10% of the rate caused by unsupported vigorous breathing. Unsupported vigorous breathing released the greatest numbers of particles. Vigorous breathing with NHF at 60 LPM, released half the number of particles compared to vigorous breathing without NHF. (2) Chemical marker tests: No oral/nasal fluid was detected in quiet breathing without NHF (detection limit 0.28 microlitres/m3). In quiet breathing with NHF at 60 LPM, small quantities were detected in 4 out of 29 quiet breathing tests, not exceeding 17 microlitres/m3. Vigorous breathing released 200-1000 times more fluid than the quiet breathing with NHF. The quantities detected in vigorous breathing were similar whether using NHF or not. Conclusion During quiet breathing, 60 LPM NHF therapy may cause oral/nasal fluid to be released as particles, at levels of tens of microlitres per cubic metre of air. Vigorous breathing (snort, cough or sneeze) releases 200 to 1000 times more oral/nasal fluid than quiet breathing. During vigorous breathing, 60 LPM NHF therapy caused no statistically significant difference in the quantity of oral/nasal fluid released compares to unsupported breathing. NHF use does not increase the risk of dispersing infectious aerosols above the risk of unsupported vigorous breathing. Standard infection prevention and control measures should apply when dealing with a patient who has an acute respiratory infection, independent of which, if any, respiratory support is being used.


title: Distinct Structural Flexibility within SARS-CoV-2 Spike Protein Reveals Potential Therapeutic Targets

text: The emergence and rapid worldwide spread of the novel coronavirus disease, COVID-19, has prompted concerted efforts to find successful treatments. The causative virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), uses its spike (S) protein to gain entry into host cells. Therefore, the S protein presents a viable target to develop a directed therapy. Here, we deployed an integrated artificial intelligence with molecular dynamics simulation approach to provide new details of the S protein structure. Based on a comprehensive structural analysis of S proteins from SARS-CoV-2 and previous human coronaviruses, we found that the protomer state of S proteins is structurally flexible. Without the presence of a stabilizing beta sheet from another protomer chain, two regions in the S2 domain and the hinge connecting the S1 and S2 subunits lose their secondary structures. Interestingly, the region in the S2 domain was previously identified as an immunodominant site in the SARS-CoV-1 S protein. We anticipate that the molecular details elucidated here will assist in effective therapeutic development for COVID-19.


title: An SEIR Model for Assessment of Current COVID-19 Pandemic Situation in the UK

text: The ongoing COVID-19 pandemic spread to the UK in early 2020 with the first few cases being identified in late January. A rapid increase in confirmed cases started in March, and the number of infected people is however unknown, largely due to the rather limited testing scale. A number of reports published so far reveal that the COVID-19 has long incubation period, high fatality ratio and non-specific symptoms, making this novel coronavirus far different from common seasonal influenza. In this note, we present a modified SEIR model which takes into account the time lag effect and probability distribution of model states. Based on the proposed model, it is estimated that the actual total number of infected people by 1 April in the UK might have already exceeded 610,000. Average fatality rates under different assumptions at the beginning of April 2020 are also estimated. Our model also reveals that the R0 value is between 7.5-9 which is much larger than most of the previously reported values. The proposed model has a potential to be used for assessing future epidemic situations under different intervention strategies.


title: Current tobacco smoking and risk from COVID-19: results from a population symptom app in over 2.4 million people

text: Background: The association between current tobacco smoking, the risk of developing COVID-19 and the severity of illness is an important information gap. Methods: UK users of the COVID Symptom Study app provided baseline data including demographics, anthropometrics, smoking status and medical conditions, were asked to log symptoms daily from 24th March 2020 to 23rd April 2020. Participants reporting that they did not feel physically normal were taken through a series of questions, including 14 potential COVID-19 symptoms and any hospital attendance. The main study outcome was the association between current smoking and the development of classic symptoms of COVID-19 during the pandemic defined as fever, new persistent cough and breathlessness. The number of concurrent COVID-19 symptoms was used as a proxy for severity. In addition, association of subcutaneous adipose tissue expression of ACE2, both the receptor for SARS-CoV-2 and a potential mediator of disease severity, with smoking status was assessed in a subset of 541 twins from the TwinsUK cohort. Results: Data were available on 2,401,982 participants, mean(SD) age 43.6(15.1) years, 63.3% female, overall smoking prevalence 11.0%. 834,437 (35%) participants reported being unwell and entered one or more symptoms. Current smokers were more likely to develop symptoms suggesting a diagnosis of COVID-19; classic symptoms adjusted OR[95%CI] 1.14[1.10 to 1.18]; >5 symptoms 1.29[1.26 to 1.31]; >10 symptoms 1.50[1.42 to 1.58]. Smoking was associated with reduced ACE2 expression in adipose tissue (Beta(SE)= -0.395(0.149); p=7.01x10-3). Interpretation: These data are consistent with smokers having an increased risk from COVID-19.


title: Evaluating COVID-19 screening strategies based on serological tests

text: Background. Facing the SARS-CoV-2 epidemic requires intensive testing on the population to early identify and isolate infected subjects. Although RT-PCR is the most reliable technique to detect ongoing infections, serological tests are frequently proposed as tools in heterogeneous screening strategies. We analyze the performance of a screening strategy proposed in Tuscany (Italy), which first uses qualitative rapid tests for antibody detection, and then RT-PCR tests on the positive subjects. Methods. We simulate the number of RT-PCR tests required by the screening strategy and the undetected ongoing infections in a pseudo-population of 500000 subjects, under different prevalence scenarios and assuming a sensitivity of the serological test ranging from 0.50 to 0.80 (specificity=0.98). A compartmental model is used to predict the number of new infections generated by the false negatives two months after the screening, under different values of the infection reproduction number. Results. Assuming a sensitivity equal to 0.80 and a prevalence of 0.3%, the screening procedure would require on average 11167.6 RT-PCR tests and would produce 300 false negatives, responsible after two months of a number of contagions ranging from 526 to 1132, under the optimistic scenario of a reproduction number between 0.5 to 1. Costs and false negatives increase with the prevalence. Conclusions. The analyzed screening procedure should be avoided unless the prevalence and the rate of contagion are very low. The cost and effectiveness of the screening strategies should be evaluated in the actual context of the epidemic, accounting for the fact that it may change over time.


title: Comprehensive Investigation and Isolation have Effectively Suppressed the Spread of COVID-19

text: The outbreak of COVID-19 since Dec. 2019 has caused severe life and economic damage worldwide, many countries are trapped by medical resource constraints or absence of targeted therapeutics, and therefore the implement of systemic policies to block this pandemic should be prioritized. Based on the transmission mechanisms and physicochemical properties of betacoronaviruses, we construct a fine-grained transmission dynamics model (ICRD) to forecast the crucial information of public concern, therein using dynamical coefficients to quantify the impact of the implement time and intensity of containment policies on the spread of epidemic. We find that the comprehensive investigation policy for susceptible population and the quarantine for suspected cases eminently contribute to reduce casualties during the phase of the dramatic increase of diagnosed cases. Statistic evidences strongly suggest that society should take such forceful public health interventions to cut the infection channels in the initial stage until the pandemic is interrupted.


title: Breath-borne VOC Biomarkers for COVID-19

text: Rapid diagnosis of COVID-19 is key to controlling the pandemic. Here we report the potential breath-borne volatile organic compound (VOC) biomarkers for COVID-19. Higher levels of ethyl butanoate were detected in exhaled breath of COVID-19 patients (N=10) than healthy controls/health care workers (N=21), lung cancer (LC) patients (N=7) and backgrounds. In contrast, breath-borne butyraldehyde and isopropanol (an efficient SARS-CoV-2 inactivation agent) were significantly higher for non-COVID-19 respiratory infections (URTI) (N=22) than COVID-19, HC, LC patients and backgrounds. Breath-borne isopropanol emission from COVID-19 patients varied greatly up to ~100-fold difference. COVID-19 patients had lower acetone levels than other subjects, except LC patients. The monitoring of ethyl butanoate, butyraldehyde and isopropanol could lend considerable support in rapidly screening COVID-19; and alerting the presence of COVID-19 patient in particular environments.


title: A fundamental model and predictions for the spread of the COVID-19 epidemic

text: The spread of the novel coronavirus is characterized by two phases: (I) a natural exponential growth phase that occurs in the absence of intervention and (II) a regulated growth phase that is affected by enforcing social distancing and isolation. We have developed a fundamental spreading model for the COVID-19 epidemic that has two parameters: the community transmission rate and a metric describing the degree of isolation and social distancing in a given community or region (country, state, county, or city). These two parameters are calibrated to data from the community, so the model uncertainty depends on the quality of the data and ability to test for COVID-19. The model shows that social distancing significantly reduces the epidemic spread and flattens the curve. The model predicts well the spreading trajectory and peak time of new infections for a community of any size and provides an upper estimate for the total number of infections and daily new infection rate for weeks into the future, providing the vital information and lead time needed to prepare for and mitigate the epidemic. The theory has immediate and far-reaching applications for ongoing outbreaks or similar future outbreaks of other emergent infectious diseases.


title: Monocyte-derived Prostaglandin E2 inhibits antigen-specific cutaneous immunity during ageing

text: Ageing results in a decline in immune function. We showed previously that healthy older humans (>65 years old) have reduced antigen-specific cutaneous immunity to varicella zoster virus (VZV) antigen challenge. This was associated with p38 MAP kinase driven inflammation that was induced by mild tissue injury caused by the injection of the antigen itself. Here we show that non-specific injury induced by injection of air or saline into the skin of older adults recruits CCR2+CD14+ monocytes by CCL2 produced by senescent fibroblasts. These monocytes reduced TRM proliferation via secretion of prostaglandin E2 (PGE2). Pre-treatment with a p38-MAPK inhibitor (Losmapimod) in older adults in vivo significantly decreased CCL2 expression, recruitment of monocyte into the skin, COX2 expression and PGE2 production. This enhanced the VZV response in the skin. Therefore, local inflammation arising from interaction between senescent cells and monocytes leads to immune decline in the skin during ageing, a process that can be reversed. Summary Inflammation resulting from tissue injury blocks antigen-specific cutaneous immunity during ageing. Monocytes recruited to the skin inhibit TRM function through COX2-derived prostaglandin E2 production. Blocking inflammation and resulting prostaglandin E2 production with a p38-MAP kinase inhibitor significantly enhances cutaneous antigen-specific responses.


Urology education in the time of COVID-19


title: Distinct patterns of SARS-CoV-2 transmission in two nearby communities in Wisconsin, USA

text: Evidence-based public health approaches that minimize the introduction and spread of new SARS-CoV-2 transmission clusters are urgently needed in the United States and other countries struggling with expanding epidemics. Here we analyze 247 full-genome SARS-CoV-2 sequences from two nearby communities in Wisconsin, USA, and find surprisingly distinct patterns of viral spread. Dane County had the 12th known introduction of SARS-CoV-2 in the United States, but this did not lead to descendant community spread. Instead, the Dane County outbreak was seeded by multiple later introductions, followed by limited community spread. In contrast, relatively few introductions in Milwaukee County led to extensive community spread. We present evidence for reduced viral spread in both counties, and limited viral transmission between counties, following the statewide Safer-at-Home public health order, which went into effect 25 March 2020. Our results suggest that early containment efforts suppressed the spread of SARS-CoV-2 within Wisconsin.


title: Students' Perceptions of the Twists and Turns of E-learning in the Midst of the Covid 19 Outbreak

text: The pandemic corona virus 2019 (COVID-19) has become an international concern and poses challenges to psychological resilience in all fields, one of which is education Therefore an effective learning strategy is needed to deal with this pandemic The purpose of this study was to survey students spread across various universities in Indonesia and Malaysia regarding e-learning systems conducted during the COVID-19 outbreak in Indonesia and Malaysia in 2020, e-learning systems starting from student knowledge about e-learning, planning e-learning, implementing e-learning until evaluating e-learning activities Data will be used for future reference This research is a descriptive study with cross sectional approach The Likert scale survey method is used with a total of 136 student respondents from tertiary institutions in Indonesia and Malaysia The results of the analysis show that students know e-learning as a distance learning system in dealing with the current pandemic corona virus, 51% expressed agreement related to e-learning preparation, 38% stated neutral in e-learning planning and 68% stated neutral in evaluating the implementation of e-learning Student assessment and good perception about e-learning play a big role in the implementation of learning with e-learning E-learning has a positive impact and has become an alternative learning process for lecturers and students Good preparation is needed in implementing e-learning so that e-learning activities can be carried out effectively Interaction can be developed and limited conditions through face-to-face meetings can be answered through e-learning activities


title: Are German endoscopy units prepared for the COVID-19 pandemic? A nationwide survey

text: Objective: The COVID-19 pandemic challenges health care systems worldwide. In this situation, guidelines for health care professionals in endoscopy units with increased risk of infection from inhalation of airborne droplets, conjunctival contact and faeces are urgently needed. Recently, the European Society of Gastrointestinal Endoscopy (ESGE) and the German Society for Pneumology (DGP) issued recommendations. However, real-world data on the conditions and requirements of endoscopy units to adhere to this guidance are missing. Design: We conducted an internet-based survey among German endoscopy units from all levels of care from April 1st to 7th, 2020. The survey comprised 33 questions and was distributed electronically by the German Society of Gastroenterology, Digestive and Metabolic Diseases (DGVS) and the DGP. Results: In total, 656 endoscopy units completed the survey. Overall, 253 units (39%) cancelled fewer than 40% of their procedures. Of note, private practices cancelled less procedures than hospital-based units. Complete separation of high-risk and COVID-19 positive patients was achieved in only 20% of the units. Procedural measures were well adopted, with 91% of the units systematically identifying patients at risk and 85% using risk-adapted personal protective equipment (PPE). For the future, shortages in PPE (81%), staff (69%) and relevant financial losses (77%) were expected. Conclusion: Concise definitions of non-urgent, elective interventions and endoscopic surveillance strategies are needed to better guide endoscopic activity and intervention cancellations. In the short term, a lack of PPE can constitute considerable impairment of endoscopy units' operability and patient outcomes.


title: Build Orientation Effects on Mechanical Properties of 316SS Components Produced by Directed Energy Deposition

text: Abstract Laser Directed Energy Deposition (DED) is an additive manufacturing process whereby a laser fuses metal feed stock to the surface of a part. The process can be complete once to form a cladded layer or can be carried out numerous times to build complex three-dimensional structures. One major obstacle to the widescale acceptance of DED technology is the tightly coupled relationship between mechanical performance and process parameters. This study investigated the effects of layer orientation on the mechanical properties of 316L stainless steel (SS) parts fabricated via DED process. Quasi-static tensile tests were conducted on DED 316L SS specimens fabricated in orientation increments of 15 degrees with respect to the loading direction. Specimens were tested in their as-built condition without post process heat treatments. Yield, ultimate tensile strength (UTS), and maximum elongation measurement were taken, contributing to the ultimate finding that: Young’s Modulus is largely unaffected, yield stress may vary by 73 MPa corresponding to a 30 degree change in layer orientation, ultimate tensile strength does not show a strong statistical outcome based on layer orientation, and ductility shows a strong positive correlation to increases in layer angle with respect to axis of tensile stress.


title: COVID-19 masquerading as Chikungunya fever

text: The COVID-19 outbreak is an unprecedented global public health challenge. It has a myriad of clinical presentations including fever, cough, vomiting, and diarrhea. Here, we present a unique case of COVID-19, with an atypical presentation of arthralgias and false-positive results for the chikungunya virus. By highlighting the importance of this rare association, we want physicians to be vigilant in the time of this pandemic and to have a high suspicion for this novel disease.


title: Time course quantitative detection of SARS-CoV-2 in Parisian wastewaters correlates with COVID-19 confirmed cases

text: Since many SARS-CoV-2 carriers are assumed to exhibit no or few non-specific symptoms, SARS-CoV-2 circulation among human populations may be detected too lately and only when massive human testing is available or when clinal COVID-19 cases are reported. This is obviously a major pitfall for evaluating and possibly controlling the current epidemic. Due to the presence of SARS-CoV-2 in stool samples qualitative detection of SARS-CoV-2 in wastewaters has recently been proposed as a complementary tool to investigate the virus circulation in human populations. If this assumption is correct, SARS-CoV-2 relative amounts in wastewaters should correlate with the number of confirmed COVID-19 cases. To test this hypothesis, we performed a time-course quantitative analysis of SARS-CoV2 by RT-qPCR in 23 raw and 8 treated wastewater samples collected from 3 major wastewater treatment plant (WWTP) of the Parisian area collecting 3 to 4 million inhabitants reject. This study was conducted from 5 March to 7 April 2020. All raw wastewater samples scored positive for SARS-CoV2. Additionally, 6 out of 8 samples from treated wastewater scored positive by RT-qPCR. Treated wastewater effluents showed a 100 times reduction in the viral load compared to the corresponding raw wastewater samples, which agrees with previous work on enteric viruses. We next compared the average level of SARS-CoV2 genomes in wastewater samples over time with the number of confirmed fatal cases of COVID19 in Paris area and in France As expected, we confirmed that the increase of genome units in raw wastewaters accurately followed the increase in the number of fatal cases observed at the regional and national level Therefore, our study demonstrates that the contamination of wastewater and the detection of viral genome occurred before the beginning of the exponential growth of the epidemic. This work demonstrated that a quantitative monitoring of SARS-CoV2 genomes in wastewaters should bring important and additional information for better survey of SARS-CoV2 circulation at the local or regional scale. Additionally, wastewater survey may provide an alternative and possibly early tool to detect pathogens in populations when investigations in humans is difficult for logistic, ethical or economic reasons.


title: Rapid Inactivation of SARS-CoV-2 by Silicon Nitride, Copper, and Aluminum Nitride

text: Introduction Viral disease spread by contaminated commonly touched surfaces is a global concern. Silicon nitride, an industrial ceramic that is also used as an implant in spine surgery, has known antibacterial activity. The mechanism of antibacterial action relates to the hydrolytic release of surface disinfectants. It is hypothesized that silicon nitride can also inactivate the coronavirus SARS-CoV-2. Methods SARS-CoV-2 virions were exposed to 15 wt.% aqueous suspensions of silicon nitride, aluminum nitride, and copper particles. The virus was titrated by the TCD50 method using VeroE6/TMPRSS2 cells, while viral RNA was evaluated by real-time RT-PCR. Immunostaining and Raman spectroscopy were used as additional probes to investigate the cellular responses to virions exposed to the respective materials. Results All three tested materials showed >99% viral inactivation at one and ten minutes of exposure. Degradation of viral RNA was also observed with all materials. Immunofluorescence testing showed that silicon nitride-treated virus failed to infect VeroE6/TMPRSS2 cells without damaging them. In contrast, the copper-treated virus suspension severely damaged the cells due to copper ion toxicity. Raman spectroscopy indicated differential biochemical cellular changes due to infection and metal toxicity for two of the three materials tested. Conclusions Silicon nitride successfully inactivated the SARS-CoV-2 in this study. The mechanism of action was the hydrolysis-mediated surface release of nitrogen-containing disinfectants. Both aluminum nitride and copper were also effective in the inactivation of the virus. However, while the former compound affected the cells, the latter compound had a cytopathic effect. Further studies are needed to validate these findings and investigate whether silicon nitride can be incorporated into personal protective equipment and commonly touched surfaces, as a strategy to discourage viral persistence and disease spread.


title: Multi-epitope Based Peptide Vaccine Design Using Three Structural Proteins (S, E, and M) of SARS-CoV-2: An In Silico Approach

text: Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the novel coronavirus responsible for the ongoing pandemic of coronavirus disease (COVID-19). No sustainable treatment option is available so far to tackle such a public health threat. Therefore, designing a suitable vaccine to overcome this hurdle asks for immediate attention. In this study, we targeted for a design of multi-epitope based vaccine using immunoinformatics tools. We considered the structural proteins S, E and, M of SARS-CoV-2, since they facilitate the infection of the virus into host cell and using different bioinformatics tools and servers, we predicted multiple B-cell and T-cell epitopes having potential for the required vaccine design. Phylogenetic analysis provided insight on ancestral molecular changes and molecular evolutionary relationship of S, E, and M proteins. Based on the antigenicity and surface accessibility of these proteins, eight epitopes were selected by various B cell and T cell epitope prediction tools. Molecular docking was executed to interpret the binding interactions of these epitopes and three potential epitopes WTAGAAAYY, YVYSRVKNL, and GTITVEELK were selected for their noticeable higher binding affinity scores −9.1, −7.4, and −7.0 kcal/mol, respectively. Targeted epitopes had 91.09% population coverage worldwide. In summary, we identified three epitopes having the most significant properties of designing the peptide-based vaccine against SARS-CoV-2.


title: Secondary pneumonia in critically ill ventilated patients with COVID-19

text: Background Pandemic COVID-19 caused by the coronavirus SARS-CoV-2 has a high incidence of patients with severe acute respiratory syndrome (SARS). Many of these patients require admission to an intensive care unit (ICU) for invasive artificial ventilation and are at significant risk of developing a secondary, ventilator-associated pneumonia (VAP). Objectives To study the incidence of VAP, as well as differences in secondary infections, and bacterial lung microbiome composition of ventilated COVID-19 and non-COVID-19 patients. Methods In this prospective observational study, we compared the incidence of VAP and secondary infections using a combination of a TaqMan multi-pathogen array and microbial culture. In addition, we determined the lung microbime composition using 16S RNA analyisis. The study involved eighteen COVID-19 and seven non-COVID-19 patients receiving invasive ventilation in three ICUs located in a single University teaching hospital between April 13th 2020 and May 7th 2020. Results We observed a higher percentage of confirmed VAP in COVID-19 patients. However, there was no statistical difference in the detected organisms or pulmonary microbiome when compared to non-COVID-19 patients. Conclusion COVID-19 makes people more susceptible to developing VAP, partly but not entirely due to the increased duration of ventilation. The pulmonary dysbiosis caused by COVID-19, and the array of secondary infections observed are similar to that seen in critically ill patients ventilated for other reasons.


title: Noninvasive respiratory support in acute hypoxemicrespiratory failure associated with COVID-19 and other viralinfections

text: Introduction: Noninvasive respiratory support (NRS) such as noninvasive ventilation (NIV) and high flow nasal therapy (HFNT) have been used in the treatment of acute hypoxemic respiratory failure (AHRF) related to the coronavirus disease (COVID-19) and other viral infections. However, there is a lack of consensus in favor of or against NRS use due to the risks of worsening hypoxemia, intubation delay, and aerosols environmental contamination associated with the use of these tools. We aimed to summarize the evidence on the use of NRS in adult patients with COVID-19 and other viral pneumonia (i.e. H1N1, SARS, MERS) and AHRF. We also searched for studies evaluating the risk of aerosolization/contamination with these tools. Evidence Acquisition: We searched MEDLINE, PubMed EMBASE and two major preprint servers (biorXiv and medRxiv) from inception to April 14, 2020, for studies on the use of respiratory support in AHRF and viral pneumonia. Evidence Synthesis: The search identified 4086 records and we found only one randomized controlled trial out of 58 studies included, with great variabilities in support utilization and failure rates. Fifteen studies explored the issue of aerosolization/contamination showing a high risk of airborne transmission via droplets generation during the use of these modalities Conclusions: Use of NRS and treatment failure in the context of COVID-19 and viral infection associated-AHRF, varied widely. Dispersion of exhaled air is different depending on the type of respiratory therapies and interfaces. Data from randomized controlled trials are lacking.


title: Planning by Scale: The Role of Perceived Scale in Determining Residential Satisfaction

text: This article suggests that the domination of the scale of the neighborhood in planning distorts our understanding of urban phenomena and that a multiscalar approach is required. It examines the association of perceived scales with residential satisfaction. The findings suggest that the neighborhood is not the dominant scale with which people perceive and define their residential area, rather they consider smaller than the neighborhood scales. Moreover, we found that the perceived scale is a significant predictor of residential satisfaction. We conclude that scale matters for understanding urban issues, and become even more significant in a time of crisis such as the coronavirus epidemic, and that urban planning should consider and be informed by smaller than the neighborhood scales.


title: COVID-19 associate neurological complications

text: 2019-novel Coronavirus disease (COVID-19) is a global health problem that affected >2.000.000 people in the world. Although the main component of the disease is pulmonary disturbances, recent reports suggested neurological manifestations. Neurological complications have been rarely reported with other Coronavirus associated diseases. In this short review, we would like to draw attention to COVID-19-related neurological symptoms. Heath-care providers should be aware that COVID-19 can associate neurological manifestations.


title: Vulnerabilities of the SARS-CoV-2 virus to proteotoxicity – opportunity for repurposed chemotherapy of COVID-19 infection

text: There is an urgent requirement for improved treatments of COVID-19 disease. A strategy for chemotherapy is to increase levels of endogenous reactive metabolites - such as reactive oxygen species and arginine-directed glycating agent, methylglyoxal - for selective toxicity to SARS-CoV-2. Sequence analysis of functional domains in the SARS-CoV-2 proteome showed 0.8-fold depletion of cysteine residues and 4.9-fold enrichment of arginine residues, suggesting methylglyoxal modification may inactivate the virus. We discovered the peptide motif for MG modification: 3 – 5-fold enrichment of cationic residues preceding the target arginine. There was 5-fold enrichment of methylglyoxal modification sites in the SARS-CoV-2 proteome, compared to the human host - indicating selective toxicity of methylglyoxal to the virus. We found antitumor drugs, doxorubicin and paclitaxel, increase cellular methylglyoxal to virucidal levels. Taken together, these findings reveal a proteomic vulnerability of SARS-CoV-2 to methylglyoxal modification and provide a rationale for repurposing doxorubicin and paclitaxel for COVID-19 treatment.


title: Estimation of COVID-19 spread curves integrating global data and borrowing information

text: Currently, novel coronavirus disease 2019 (COVID-19) is a big threat to global health. Rapid spread of the virus has created pandemic, and countries all over the world are struggling with a surge in COVID-19 infected cases. Scientists are working on estimating or predicting infection trajectory for the COVID-19 confirmed cases, which will be useful for future planning and policymaking to effectively cope with the disease. There are no drugs or other therapeutics approved by the US Food and Drug Administration to prevent or treat COVID-19 (on April 13, 2020): information on the disease is very limited and scattered even if it exists. This motivates the use of data integration, combining data from diverse sources and eliciting useful information with a unified view of them. In this paper, we propose a Bayesian hierarchical model that integrates global data to estimate COVID-19 infection trajectories. Due to information borrowing across multiple countries, the proposed growth curve models provide a powerful predictive tool endowed with uncertainty quantification. They outperform the existing individual country-based models. Additionally, we use countrywide covariates to adjust infection trajectories. A joint variable selection technique has been integrated into the proposed modeling scheme, which aimed to identify the possible country-level risk factors for severe disease due to COVID-19.


title: Effects of fear factors in disease propagation

text: Upon an outbreak of a dangerous infectious disease, people generally tend to reduce their contacts with others in fear of getting infected. Such typical actions apparently help slow down the spreading of infection. Thanks to today's broad public media coverage, the fear factor may even contribute to prevent an outbreak from happening. We are motivated to study such effects by adopting a complex network approach. Firstly we evaluate the simple case where connections between individuals are randomly removed due to fear factor. Then we consider a different case where each individual keeps at least a few connections after contact reduction. Such a case is arguably more realistic since people may choose to keep a few social contacts, e.g., with their family members and closest friends, at any cost. Finally a study is conducted on the case where connection removals are carried out dynamically while the infection is spreading out. Analytical and simulation results show that the fear factor may not easily prevent an epidemic outbreak from happening in scale-free networks. However, it significantly reduces the fraction of the nodes ever getting infected during the outbreak.


title: Dynamics of COVID‐19 epidemics: SEIR models underestimate peak infection rates and overestimate epidemic duration

text: Compartment models of infectious diseases, such as SEIR, are being used extensively to model the COVID-19 epidemic. Transitions between compartments are modelled either as instantaneous rates in differential equations, or as transition probabilities in discrete time difference or matrix equations. These models give accurate estimates of the position of equilibrium points, when the rate at which individuals enter each stage is equal to the rate at which they exit from it. However, they do not accurately capture the distribution of times that an individual spends in each compartment, so do not accurately capture the transient dynamics of epidemics. Here we show how matrix models can provide a straightforward route to accurately model stage durations, and thus correctly reproduce epidemic dynamics. We apply this approach to modelling the dynamics of a COVID-19 epidemic. We show that a SEIR model underestimates peak infection rates (by a factor of three using published parameter estimates based on the progress of the epidemic in Wuhan) and substantially overestimates epidemic persistence after the peak has passed.


title: High-Throughput Human Primary Cell-Based Airway Model for Evaluating Influenza, Coronavirus, or other Respiratory Viruses in vitro

text: Influenza and other respiratory viruses represent a significant threat to public health, national security, and the world economy, and can lead to the emergence of global pandemics such as the current COVID-19 crisis. One of the greatest barriers to the development of effective therapeutic agents to treat influenza, coronaviruses, and many other infections of the respiratory tract is the absence of a robust preclinical model. Preclinical studies currently rely on high-throughput, low-fidelity in vitro screening with cell lines and/or low-throughput animal models that often provide a poor correlation to human clinical responses. Here, we introduce a human primary airway epithelial cell-based model integrated into a high-throughput platform where tissues are cultured at an air-liquid interface (PREDICT96-ALI). We present results on the application of this platform to influenza and coronavirus infections, providing multiple readouts capable of evaluating viral infection kinetics and potentially the efficacy of therapeutic agents in an in vitro system. Several strains of influenza A virus are shown to successfully infect the human primary cell-based airway tissue cultured at an air-liquid interface (ALI), and as a proof-of-concept, the effect of the antiviral oseltamivir on one strain of Influenza A is evaluated. Human coronaviruses NL63 (HCoV-NL63) and SARS-CoV-2 enter host cells via ACE2 and utilize the protease TMPRSS2 for protein priming, and we confirm expression of both in our ALI model. We also demonstrate coronavirus infection in this system with HCoV-NL63, observing sufficient viral propagation over 96 hours post-infection to indicate successful infection of the primary cell-based model. This new capability has the potential to address a gap in the rapid assessment of therapeutic efficacy of various small molecules and antiviral agents against influenza and other respiratory viruses including coronaviruses.


Energy access is needed to maintain health during pandemics


title: The impact of Covid-19 Movement Control Order on SMEs' businesses and survival strategies

text: Coronavirus outbreak is the latest world tragedy that have affected all sectors in economy The lockdown, confinement, limited movement order and social distancing are amongst the preemptive governments' effort to safeguard the public health While recognizing the importance of the national order in preventing the immense spread of the virus, the authors contend that there are certain undiscovered impacts of the control order policy on SMEs in Malaysia The objectives of this article are to scrutinize the implications of the Covid-19 Movement Control Order (MCO) on SMEs businesses and to identify survival strategies based on the owners' perspectives The study applies qualitative approach conducted through phone-based interviews with six selected SMEs' owners during the first phase of control order from March 18, 2020 to March 31, 2020 In summary, the impacts of MCO on SMEs are classified into the operational problems (i e operation distruption;supply chain distruption;foresighting the future business direction) and the financial problems (i e cash flow imbalance;access to stimulus packages;risk of bankcruptcy) Meanwhile, the major themes of current survival strategies fall under the financial and marketing strategies The paper recommends few suggestions for future research work, business development agencies and entrepreneurs


title: Social Distancing Causally Impacts the Spread of SARS-CoV-2: A U.S. Nationwide Event Study

text: Background: To date, no study has examined the effectiveness of social distancing, while controlling for social mobility and social distancing restrictions in the United States. We utilize the quasi-experimental setting created by the nationwide protests precipitated by George Floyd's tragic death on May 25, 2020, to assess the causal impact of social distancing on the spread of SARS-CoV-2. Methods: Our sample period spans from January 22, 2020, to June 20, 2020, and consists of 474,422 county-days representing 3,142 counties from all 50 states and the District of Columbia. To assess the change in COVID-19 case counts following the protests, we employ a differences in differences estimation strategy in a multivariate setting, in which we control for social distancing restrictions and social mobility across counties. We also control for covariates that may influence COVID-19 transmission, and implement placebo tests using a Monte Carlo simulation. Findings: We document a country wide increase of over 3.06 cases per day, per 100,000 population, following the onset of the protests (95%CI: 2.47-3.65), and a further increase of 1.73 cases per day, per 100,000 population, in the counties in which the protests took place (95%CI: 0.59- 2.87). Relative to the week preceding the onset of the protests, this represents a 61.2% country wide increase in COVID-19 cases, and a further 34.6% increase in the protest counties. Interpretation: Our study documents a significant increase in COVID-19 case counts in counties that experienced a protest, and we conclude that social distancing practices causally impact the spread of SARS-CoV-2. The observed effect cannot be explained by changes in social distancing restrictions and social mobility, and placebo tests rule out the possibility that this finding is attributable to chance.


title: Population anxiety and positive behaviour change during the COVID-19 epidemic: Cross-sectional surveys in Singapore, China and Italy

text: Background On 31 December 2019, an epidemic of pneumonia of unknown aetiology was first reported in the city of Wuhan, Hubei Province, People's Republic of China. A rapidly progressing epidemic of COVID-19 ensued within China, with multiple exportations to other countries. We aimed to measure perceptions and responses towards COVID-19 in three countries to understand how population-level anxiety can be mitigated in the early phases of a pandemic. Methods Between February and March 2020, we conducted online surveys in Singapore, China and Italy with a total of 4,505 respondents to measure knowledge, perceptions, anxiety and behaviours towards the COVID-19 epidemic, and identified factors associated with lower anxiety and more positive behavioural responses. Findings Respondents reported high awareness of COVID-19 and its accompanying symptoms, comparable information seeking habits and similarly high levels of information sufficiency, adherence to and acceptance of public health control measures. Higher self-efficacy was associated with lower anxiety levels in all three countries, while willingness to comply with restrictive measures and greater information sufficiency were associated with more positive behavioural changes to reduce spread of infection. Interpretation Population-level anxiety and behavioural responses to an outbreak can be influenced by information provided. This should be used to inform future outbreak preparedness plans, taking into account the importance of increasing population-level self-efficacy and information sufficiency to reduce anxiety and promote positive behavioural changes. Funding This was supported by the Saw Swee Hock School of Public Health, the Department of Communications and New Media, National University of Singapore, and the National Medical Research Council, Singapore


title: Manufacturing of Bulk Al-12Zn-3.7Mg-1Cu Alloy with TiC Nanoparticles

text: Abstract Aluminum alloys are significant in various applications, and the desire is strong to develop higher strength with balanced other properties out of high Zn and Mg contents in aluminum. However, high contents of Zn and Mg will make the matrix brittle and incompatible for mass manufacturing. As nanoparticles could effectively and dynamically control the brittle secondary phases, it opens a new route to design and manufacture high-Zn and high-Mg aluminum alloys. Here, we demonstrate the feasibility of nanomanufacturing of Al-12Zn-3.7Mg-1Cu alloy system with the help from TiC nanoparticles for potential ultrahigh-strength light-weight alloys. By applying the “hot rolling-natural aging” and “solution treatment-natural aging” processing routes, Al-12Zn-3.7Mg-1Cu alloy with TiC nanoparticles can achieve higher microhardness via natural aging and better machinability when compared with the pure Al-12Zn-3.7Mg-1Cu alloy. Microstructure and thermodynamic studies reveal that the reasons for the peak hardness difference of Al-12Zn-3.7Mg-1Cu alloy and Al-12Zn-3.7Mg-1Cu/1.5 vol.% TiC nanocomposites are due to the free energy difference by solution treatment temperature and the strain energy sustained by the residual secondary phases. The enhanced mechanical properties in Al-12Zn-3.7Mg-1Cu alloy with TiC nanoparticles at the peak-microhardness state after “solution treatment-natural aging” processing route prove the feasibility of the abovementioned nano-treating manufacturing method.


title: Hospital reconversion in response to the COVID-19 pandemic/ Reconversión hospitalaria ante la pandemia de COVID-19

text: The hospital transformation is well recognized as one of the paramount strategic points through history in order to prepare for the pandemic appearance. In 2020, the WHO declared COVID-19 a pandemic on March 11. As a result in the world and in our country, measures were taken in accordance to the individual capacity of each region. The speed of reaction for the completion of the transformation adds an extra element that burdens even more, this huge task. This process starts with the conjointly work of the hospital authorities and involves as well all the medical staff and health personnel trained in the diagnostic and treatment of the infected patients, which can reach a critical point in the developing of the disease. The launching of this process begins with the recount of the available resources, continuing with de transformation of hospital beds that were intended for other purposes to function as Intensive Therapy beds along with ventilatory support, besides making sure the participation of prepared health staff and enough medical supplies. In the pandemic development nowadays in our country the detection of the issues and the decision making should be made accordingly to the constant changes of this huge threat.


title: The role of comorbidities and clinical predictors of severe disease in COVID-19: a systematic review and meta-analysis

text: Background COVID_19 is unpredictable due to non-specific symptoms and clinical course diversity in different individuals. We analyzed studies regarding the factors associated with severe status of the disease to identify unique findings in severely affected patients. Methods We systematically searched the electronic databases, including PubMed, Scopus, EMBASE, Web of Science, and Google Scholar from inception to 12th of March 2020. Cochranes Q and I-square statistics were used to assess the existence of heterogeneity between the included studies. We used the random-effects model to pool the odds ratios (ORs) at 95% confidence intervals (CIs). Results Seventeen articles out of 3009 citations were included. These contained 3189 patients, of whom 732 were severely affected (severe group) and 3189 were in non-severe group. Using the random-effects model, our meta-analyses showed that the odds of comorbidities, including COPD, DM, HTN, CVD, CKD, and symptoms, including dyspnea, dizziness, anorexia, and cough, were significantly higher among the severe group compared with the non-severe group. There were no significant changes in odds of CVA, liver disease, immunodeficiency/immunosuppression, fever, fatigue, myalgia, headache, diarrhea, sore throat, nasal congestion, sputum, nausea, vomiting, chest pain between the two groups. Conclusions Early recognition and intervention can be critical in management, and might stop progression to severe disease. Predictive symptoms and comorbidities can be used as a predictor in patients who are at risk of severe disease.


title: Within the lack of chest COVID-19 X-ray dataset: A novel detection model based on GAN and deep transfer learning

text: The coronavirus (COVID-19) pandemic is putting healthcare systems across the world under unprecedented and increasing pressure according to theWorld Health Organization (WHO). With the advances in computer algorithms and especially Artificial Intelligence, the detection of this type of virus in the early stages will help in fast recovery and help in releasing the pressure off healthcare systems. In this paper, a GAN with deep transfer learning for coronavirus detection in chest X-ray images is presented. The lack of datasets for COVID-19 especially in chest X-rays images is the main motivation of this scientific study. The main idea is to collect all the possible images for COVID-19 that exists until the writing of this research and use the GAN network to generate more images to help in the detection of this virus from the available X-rays images with the highest accuracy possible. The dataset used in this research was collected from different sources and it is available for researchers to download and use it. The number of images in the collected dataset is 307 images for four different types of classes. The classes are the COVID-19, normal, pneumonia bacterial, and pneumonia virus. Three deep transfer models are selected in this research for investigation. The models are the Alexnet, Googlenet, and Restnet18. Those models are selected for investigation through this research as it contains a small number of layers on their architectures, this will result in reducing the complexity, the consumed memory and the execution time for the proposed model. Three case scenarios are tested through the paper, the first scenario includes four classes from the dataset, while the second scenario includes 3 classes and the third scenario includes two classes. All the scenarios include the COVID-19 class as it is the main target of this research to be detected. In the first scenario, the Googlenet is selected to be the main deep transfer model as it achieves 80.6% in testing accuracy. In the second scenario, the Alexnet is selected to be the main deep transfer model as it achieves 85.2% in testing accuracy, while in the third scenario which includes two classes (COVID-19, and normal), Googlenet is selected to be the main deep transfer model as it achieves 100% in testing accuracy and 99.9% in the validation accuracy. All the performance measurement strengthens the obtained results through the research.


Breaking News: There Won't Be Enough COVID-19 Tests, So Use Clinical Symptoms as a Guide


title: Using Supervised Machine Learning and Empirical Bayesian Kriging to reveal Correlates and Patterns of COVID-19 Disease outbreak in sub-Saharan Africa: Exploratory Data Analysis

text: Introduction: Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that was first reported in Wuhan, China, and has subsequently spread worldwide. Knowledge of coronavirus-related risk factors can help countries build more systematic and successful responses to COVID-19 disease outbreak. Here we used Supervised Machine Learning and Empirical Bayesian Kriging (EBK) techniques to reveal correlates and patterns of COVID-19 Disease outbreak in sub-Saharan Africa (SSA). Methods: We analyzed time series aggregate data compiled by Johns Hopkins University on the outbreak of COVID-19 disease across SSA. COVID-19 data was merged with additional data on socio-demographic and health indicator survey data for 39 of SSA 48 countries that reported confirmed cases and deaths from coronavirus between February 28, 2020 through March 26, 2020. We used supervised machine learning algorithm, Lasso for variable selection and statistical inference. EBK was used to also create a raster estimating the spatial distribution of COVID-19 disease outbreak. Results: The lasso Cross-fit partialing out predictive model ascertained seven variables significantly associated with the risk of coronavirus infection (i.e. new HIV infections among pediatric, adolescent, and middle-aged adult PLHIV, time (days), pneumococcal conjugate-based vaccine, incidence of malaria and diarrhea treatment). Our study indicates, the doubling time in new coronavirus cases was 3 days. The steady three-day decrease in coronavirus outbreak rate of change (ROC) from 37% on March 23, 2020 to 23% on March 26, 2020 indicates the positive impact of countries' steps to stymie the outbreak. The interpolated maps show that coronavirus is rising every day and appears to be severely confined in South Africa. In the West African region (i.e. Burkina Faso, Ghana, Senegal, CotedIviore, Cameroon, and Nigeria), we predict that new cases and deaths from the virus are most likely to increase. Interpretation: Integrated and efficiently delivered interventions to reduce HIV, pneumonia, malaria and diarrhea, are essential to accelerating global health efforts. Scaling up screening and increasing COVID-19 testing capacity across SSA countries can help provide better understanding on how the pandemic is progressing and possibly ensure a sustained decline in the ROC of coronavirus outbreak. Funding: Authors were wholly responsible for the costs of data collation and analysis.


title: Two patients with acute meningo-encephalitis concomitant to SARS-CoV-2 infection

text: Human coronaviruses are known for their tropism for central nervous system and to be associated with neurological complications. SARS-CoV-2 pandemy represent a major health issue and if respiratory symptoms are at the forefront, neurological symptoms should be expected. Here we report the case of two patient that developed encephalitic symptoms with neuropsychological impairment and pathologic cerebrospinal fluid features concomitantly to SARS-CoV-2 documented infection. Both patient recovered promptly without treatment. This report raises the question of central nervous system involvement in SARS-CoV-2 infection and the need for investigation of neuropsychological complications in infected patient.


title: Estimation of fatality rate in Africa through the behavior of COVID-19 in Italy relevance to age profiles

text: The emergence and pandemic of COVID-19 has rapidly become a global concern. In Italy, on 27 March 2020, there were 8165 deaths and 80539 confirmed cases of COVID-19. Demographic situations, like age profiles is reported to be the cause of high case fatality rate (CFR) in Italy. In Africa, the COVID-19 pandemic has not yet grasped epic proportion, but the estimation of CFR is still needed. We compared the CFR observed in Italy with the age profiles in 46 Africa countries and 2 territories which are already confirmed COVID-19 case. The estimation of the CFR in Africa ranges between (1.0%-5.4%) while in Italy is 10.1%. The five highest CFR countries and territories in Africa are Reunion (5.4%), Mauritius (5.1 %), Tunisia (3.9%), Seychelles (3.8%) and Morocco (3.3%). The last three countries with low CFR are Uganda (1.0%), Zambia (1.1%) and Angola (1.1%). The observed difference is related to the age profiles.


title: A Bayesian Logistic Growth Model for the Spread of COVID-19 in New York

text: We use Bayesian Estimation for the logistic growth model in order to estimate the spread of the coronavirus epidemic in the state of New York. Models weighting all data points equally as well as models with normal error structure prove inadequate to model the process accurately. On the other hand, a model with larger weights for more recent data points and with t-distributed errors seems reasonably capable of making at least short term predictions.


COVID-19: Wirksamkeit integrativer Medizin?


title: Experimental investigation of porosity distribution in selective laser melted Inconel 718

text: Abstract This paper reviews the mechanisms of pore forming in additively manufactured metals and presents the statistical analysis of porosity and its distribution in selective laser melted Inconel 718. Samples were printed at different combinations of laser powers and scanning speeds. Printed samples were sectioned, ground, and polished for porosity study. Imaging techniques captured the pore profile and distribution at different region for comparison: from inside to outside and from bottom to top of a sample. Although a linear energy density of 350 J/m significantly reduced porosity in a sample, choosing different combinations of power and scanning speed for the same energy density produced different results in porosity. Pore density at the periphery of a sample was about 3-20 times denser than that in the interior. Finish machining with at least 200 µm depth of cut was recommended to enhance surface finish, control dimension and tolerance while removing the high density porosity layer.


title: The Effects of Stringent Interventions for Coronavirus Pandemic

text: The pandemic of COVID-19 has caused severe public health consequences around the world. Many interventions of COVID-19 have been implemented. It is of great public health and societal importance to evaluate the effects of interventions in the pandemic of COVID-19. In this paper, with help of synthetic control method, regression discontinuity and a Susceptible-Infected and infectious without isolation-Hospitalized in isolation-Removed (SIHR) model, we evaluate the horizontal and longitudinal effects of stringent interventions implemented in Wenzhou, a representative urban city of China, where stringent interventions were enforced to curb its own epidemic situation with rapidly increasing newly confirmed cases. We found that there were statistically significant treatment effects of those stringent interventions which reduced the cumulative confirmed cases of COVID-19. Those reduction effects would increase over time. Also, if the stringent interventions were delayed by 2 days or mild interventions were implemented instead, the expected number of cumulative confirmed cases would have been nearly 2 times or 5 times of the actual number. The effects of stringent interventions are significant in mitigating the epidemic situation of COVID-19. The slower the interventions were implemented, the more severe the epidemic would have been, and the stronger the interventions would have been required.


title: A drug repurposing screen identifies hepatitis C antivirals as inhibitors of the SARS-CoV-2 main protease

text: The SARS coronavirus type 2 (SARS-CoV-2) emerged in late 2019 as a zoonotic virus highly transmissible between humans that has caused the COVID-19 pandemic 1,2. This pandemic has the potential to disrupt healthcare globally and has already caused high levels of mortality, especially amongst the elderly. The overall case fatality rate for COVID-19 is estimated to be ∼2.3% overall 3 and 32.3% in hospitalized patients age 70-79 years 4. Therapeutic options for treating the underlying viremia in COVID-19 are presently limited by a lack of effective SARS-CoV-2 antiviral drugs, although steroidal anti-inflammatory treatment can be helpful. A variety of potential antiviral targets for SARS-CoV-2 have been considered including the spike protein and replicase. Based upon previous successful antiviral drug development for HIV-1 and hepatitis C, the SARS-CoV-2 main protease (Mpro) appears an attractive target for drug development. Here we show the existing pharmacopeia contains many drugs with potential for therapeutic repurposing as selective and potent inhibitors of SARS-CoV-2 Mpro. We screened a collection of ∼6,070 drugs with a previous history of use in humans for compounds that inhibit the activity of Mpro in vitro. In our primary screen we found ∼50 compounds with activity against Mpro (overall hit rate <0.75%). Subsequent dose validation studies demonstrated 8 dose responsive hits with an IC50 ≤ 50 μM. Hits from our screen are enriched with hepatitis C NS3/4A protease targeting drugs including Boceprevir (IC50=0.95 μM), Ciluprevir (20.77μM). Narlaprevir (IC50=1.10μM), and Telaprevir (15.25μM). These results demonstrate that some existing approved drugs can inhibit SARS-CoV-2 Mpro and that screen saturation of all approved drugs is both feasible and warranted. Taken together this work suggests previous large-scale commercial drug development initiatives targeting hepatitis C NS3/4A viral protease should be revisited because some previous lead compounds may be more potent against SARS-CoV-2 Mpro than Boceprevir and suitable for rapid repurposing.


title: Covid19 infection spread in Greece: Ensemble forecasting models with statistically calibrated parameters and stochastic noise

text: Following the outbreak of the novel coronavirus SARS-Cov2 in Europe and the subsequent failure of national healthcare systems to sufficiently respond to the fast spread of the pandemic , extensive statistical analysis and accurate forecasting of the epidemic in local communities is of primary importance in order to better organize the social and healthcare interventions and determine the epidemiological characteristics of the disease. For this purpose, a novel combination of Monte Carlo simulations, wavelet analysis and least squares optimization is applied to a known basis of SEIR compartmental models , resulting in the development of a novel class of stochastic epidemiological models with promising short and medium-range forecasting performance. The models are calibrated with the epidemiological data of Greece, while data from Switzerland and Germany are used as a supplementary background. The developed models are capable of estimating parameters of primary importance such as the reproduction number and the real magnitude of the infection in Greece. A clear demonstration of how the social distancing interventions managed to promptly restrict the epidemic growth in the country is included. The stochastic models are also able to generate robust 30-day and 60-day forecast scenarios in terms of new cases, deaths, active cases and recoveries.


title: Rapid, field-deployable nucleobase detection and identification using FnCas9

text: Detection of pathogenic sequences or variants in DNA and RNA through a point-of-care diagnostic approach is valuable for rapid clinical prognosis. In recent times, CRISPR based detection of nucleic acids has provided an economical and quicker alternative to sequencing-based platforms which are often difficult to implement in the field. Here, we present FnCas9 Editor Linked Uniform Detection Assay (FELUDA) that employs a highly accurate enzymatic readout for detecting nucleotide sequences, identifying nucleobase identity and inferring zygosity with precision. We demonstrate that FELUDA output can be adapted to multiple signal detection platforms and can be quickly designed and deployed for versatile applications including rapid diagnosis during infectious disease outbreaks like COVID-19.


title: In-depth phenotyping of human peripheral blood mononuclear cells in convalescent COVID-19 patients following a mild versus severe disease course

text: Background: Covid-19, the disease caused by infection with SARS-CoV-2, has developed to a pandemic causing more than 239, 000 deaths worldwide as of 6th May according to the World Health Organization (WHO). It presents with a highly variable disease course ranging from a large proportion of asymptomatic cases to severe respiratory failure in 17-29% of cases even in the absence of apparent comorbidities 1, 2. This implies a diverse host immune response to SARS-CoV-2. The immunological characteristics underlying these divergent disease courses, however, still remain elusive. While insights into abrogations of innate immunity begin to emerge, adaptive immune responses towards SARS-CoV-2 are poorly investigated, although they serve as immune signatures of protection and vaccine responses. We therefore set out to characterize immune signatures of convalescent COVID-19 patients stratified according to their disease severity. Methods: We performed high-dimensional flow cytometric profiling of peripheral blood mononuclear cells of convalescent COVID-19 patients who we stratified according to their disease severity by a physician-assisted questionnaire based assessment of COVID-19 symptoms. Results: Surprisingly, we did not observe any difference in the relative proportions of any major immune cell type in convalescent patients presenting with different severity of COVID-19 disease except for a reduction in monocytes. The frequency of Tnaive T cells was significantly reduced in CD4+ and CD8+ T cells, whereas other T cell differentiations states (TCM, TEM, TEMRA) remained relatively unaffected by COVID-19 severity as assessed approximately two weeks after infection. Conclusions In our COVID-19 patient cohort, which is characterized by absence of comorbidities and therapeutic interventions other than symptomatic antipyretics, the immunophenotype is similar irrespective of a highly variable disease severity. Convalescence is therefore associated with a rather uniform immune signature. Abrogations, which were previously identified in the innate and adaptive immune compartment of COVID-19 patients should be scrutinized for direct associations with a preconditioned immune system shaped and made vulnerable for SARS-CoV-2 by preexisting comorbidities.


title: Can you put a price on COVID-19 options? Experts weigh lives versus economics

text: Economist Sergio Rebelo has spent the past 2 weeks holed up in his Chicago home, working feverishly to crack the economics of the coronavirus Armed with a hybrid model that combines how viruses spread with how people work and consume, the Northwestern University researcher is one of a number of macroeconomists now trying to shed light on the balance between the economic impact of locking down major parts of the economy and the economic damage wrought by the disease itself “When you think about the optimal policy, you really want to see the effect between the economy and epidemiology,” Rebelo says


title: ACE2 and TMPRSS2 variants and expression as candidates to sex and country differences in COVID-19 severity in Italy

text: Background: As the outbreak of coronavirus disease 2019 (COVID-19) progresses, prognostic markers for early identification of high-risk individuals are an urgent medical need. Italy has the highest rate of SARS-CoV-2 infection, the highest number of deaths, and the highest mortality rate among large countries. Worldwide, a more severe course of COVID-19 is associated with older age, comorbidities, and male sex. Hence, we searched for possible genetic components of the peculiar severity of COVID-19 among Italians, by looking at expression levels and variants in ACE2 and TMPRSS2 genes, which are crucial for viral infection. Methods: Exome and SNP array data from a large Italian cohort representative of the country's population were used to compare the burden of rare variants and the frequency of polymorphisms with European and East Asian populations. Moreover, we looked into gene expression databases to check for sex-unbalanced expression. Results: While we found no significant evidence that ACE2 is associated with disease severity/sex bias in the Italian population, TMPRSS2 levels and genetic variants proved to be possible candidate disease modulators, contributing to the observed epidemiological data among Italian patients. Conclusions: Our analysis suggests a role for TMPRSS2 variants and expression levels in modulating COVID-19 severity, a hypothesis that fosters a rapid experimental validation on large cohorts of patients with different clinical manifestations.


title: Production the industrial levels of bioethanol from glycerol by engineered yeast “Bioethanol-4th generation”

text: Besides the pledges for expanding uses of biofuels to sustain the humanosphere, abruptly massive needs emerged for sanitizers with turns COVID-19 to a pandemic. Therefore, ethanol is topping the social-demanding, although the three generations of production, from molasses/starch, lignocelluloses, and algae. Owing to the limited-availability of fermentable sugars from these resources, we addressed glycerol as a fourth bio-based carbon resource from biodiesel, soap, and fatty acid industries, which considers as a non-applicable source for bioethanol production. Here, we show the full strategy to generate efficient glycerol fermenting yeast by innovative rewriting the oxidation of cytosolic nicotinamide-adenine-dinucleotide (NADH) by O2-dependent dynamic shuttle while abolishing glycerol biosynthesis route. Besides, imposing a vigorous glycerol-oxidative pathway, the engineered strain demonstrated a breakthrough in conversion efficiency (up to 98%). Its capacity extending to produce up to 90g /l ethanol and > 2 g 1-1 h-1, which promoting the industrial view. Visionary metabolic engineering here provides horizons for further tremendous economic and health benefits with assuring for its enhancing for the other scenarios of biorefineries. Summary Efficiently fermenting glycerol in yeast was developed by comprehensive engineering the glycerol pathways and rewriting NADH pathways.


title: Fast and easy conversion oforthoamidoaryldiselenides into the corresponding ebselen-like derivatives driven by theoretical investigations

text: DFT calculations performed on amidoaryldiselenides as electrophilic derivatives evidenced the presence of a prevalent Se⋯O weak interaction when selenium is bonded to a Se atom (diselenides), a Br atom (selenenyl bromide) and an O atom (selenenic acid), while for selenenyl iodide derivatives, a prevalent contribution of the Se⋯N interaction was predicted. Thisin silicoobservation has been experimentally exploited for the efficient synthesis of a small library ofN-substituted benzoisoselenazol-3(2H)-ones and benzoisothiazol-3(2H)-ones considering the pharmacological relevance of ebselen recently reported also as an antiviral agent against Sars-Cov2.


title: Corona virus: A novel outbreak

text: In December 2019, a new pneumonia case emerged in the Wuhan, Hubei province of China which had an association with the novel Corona Virus (2019-nCoV). Most of the diagnosed cases had exposure to the Huanan seafood market. The present case is the successor of three earlier similar cases of Coronavirus known as SARS-Corona (Severe Acute Respiratory Syndrome) Virus and MERS-Corona Virus (Middle Eastern Respiratory Syndrome). The origin of the epidemic is still unknown and a lot of other uncertainties hinders the development of vaccines for the virus. As studies suggest that this virus is an evolution of SARS virus concerns are growing around the world as death toll has already surpassed that of SARS virus. This paper explores about the coronavirus, its relation to the similar SARS and MERS virus, its outreach and global impact according to the current scenario.


title: Correlation of coagulation parameters with clinical outcomes in Coronavirus-19 affected minorities in United States: Observational cohort

text: Importance: COVID-19 has caused a worldwide illness and New York has become the epicenter of COVID-19 in the United States. Currently Bronx has the highest prevalence per capita in New York. Objective: To investigate the coagulopathic presentation of COVID and its natural course and to investigate whether hematologic and coagulation parameters can be used to assess illness severity and death. Design: Retrospective case study of positive COVID inpatients between 3/20/2020-3/31/2020. Setting: Montefiore Health System main hospital, Moses, a large tertiary care center in the Bronx. Participants: Adult inpatients with positive COVID tests hospitalized at MHS. Exposure (for observational studies): Datasets of participants were queried for physiological, demographic (age, sex, socioeconomic status and self-reported race and/or ethnicity) and laboratory data. Main Outcome and Measures: Relationship and predictive value of measured parameters to mortality and illness severity. Results: Of the 217 in this case review, 70 died during hospitalization while 147 were discharged home. Only the admission PT and first D-Dimer could very significantly differentiate those who were discharged alive and those who died. Logistic regression analysis shows increased odds ratio for mortality by first D-Dimer within 48 hrs. of admission. The optimal cut-point for the initial D-Dimer to predict mortality was found to be 1.65 mcg/mL. Conclusions: We describe here a comprehensive assessment of hematologic and coagulation parameters in COVID and examine the relationship of these to mortality. We demonstrate that both initial and maximum D-Dimer values are biomarkers that can be used for survival assessments.


title: Lymphocytopaenia is associated with severe SARS-CoV-2 disease: A Systematic Review and Meta-Analysis of Clinical Data

text: Background: Most patients infected by SARS-CoV-2 have favourable outcomes, however some develop severe disease which may progress to acute respiratory distress syndrome, multi-organ failure, and death. Markers that could predict patients at risk of poor outcomes would be extremely useful clinically. Evidence has emerged that low lymphocyte count is associated with increased disease severity. Methods: We performed a systematic review and meta-analysis to assess the association between lymphocyte count and severity of SARS-CoV-2 associated clinical disease. Results: Seven papers were included in the meta-analysis. These papers included data from 2083 patients, 25% (n=521) with severe SAR-CoV-2 disease and 75% (n=1562) with non-severe SAR-CoV-2 disease. Heterogenicity was seen in the definition of severe disease. Metanalysis produced metamedians of 1x109/L (95% CI 1-1.1) and 0.7x109/L (95% CI 0.63-0.8) lymphocytes for patients with non-severe and severe disease respectively (p-value of p=0.006 Wilcoxon test). Calculation of metamedians from the two papers classifying severe disease according to death alone gave 1.1 1x109/L lymphocytes (95% CI 1.0-1.1) for “survivors” (n=163) and 0.63 1x109/L lymphocytes (95% CI 0.60-0.63) for “non-survivors” (n=253) of SAR-CoV-2 disease. Conclusions: Lower lymphocyte counts are significantly associated with more severe disease in patients with SARS-CoV-2 infection. Lymphocytopenia may therefore be useful laboratory measure to allow prognostication of patients presenting with SARS-CoV-2 infection.


Tracing infection from mobility data


title: Intestinal inflammation modulates the expression of ACE2 and TMPRSS2 and potentially overlaps with the pathogenesis of SARS-CoV-2 related disease

text: Immune dysregulation and cytokine release syndrome have emerged as pathological hallmarks of severe Coronavirus Disease 2019 (COVID-19), leading to the evaluation of cytokine antagonists as therapeutic agents. A number of immune-directed therapies being considered for COVID-19 patients are already in clinical use in chronic inflammatory conditions like inflammatory bowel disease (IBD). These considerations led us to systematically examine the intersections between COVID-19 and the GI tract during health and intestinal inflammation. We have observed that IBD medications, both biologic and non-biologic, do not significantly impact ACE2 and TMPRSS2 expression in the uninflamed intestines. Additionally, by comparing SARS CoV2-induced epithelial gene signatures with IBD-associated genes, we have identified a shared molecular subnetwork between COVID-19 and IBD. These data generate a novel appreciation of the confluence of COVID-19- and IBD-associated inflammation and provide mechanistic insights supporting further investigation of specific IBD drugs in the treatment of COVID-19.


What aerosol physics tells us about airborne pathogen transmission


title: Decentralized governance may lead to higher infection levels and sub-optimal releases of quarantines amid the COVID-19 pandemic

text: The outbreak of the novel Coronavirus (COVID-19) has lead countries worldwide to administer quarantine policies. However, each country or state decides independently what mobility restrictions to administer within its borders, while aiming to maximize its own citizens' welfare. In turn, since individuals travel between countries and states, at least during periods when quarantines are less restrictive, the policy in one country may ultimately affect the infection level in other countries. Therefore, major questions are whether the policy dictated by a decentralized government is efficient, and if not, how the governments can coordinate a better policy. Here, we focus on the decision regarding the timing of releasing the quarantines. We consider a game theory model in which each of two governments decides when to switch from a restrictive to a non-restrictive quarantine and vice versa. We used parameter values driven by the literature and publically available data. We show that, if travel is sufficiently frequent during the non-restrictive quarantine periods, then the strategies are sub-optimal: Each governor tends to release the quarantine sooner, which ultimately leads to longer periods of restrictive quarantines and a higher prevalence of the disease. In turn, if the governments restrict international and interstate travel to a low level even when the quarantines are non-restrictive, the policy dictated by the decentralized governance may become optimal.


title: Age-Dependent Risks of Incidence and Mortality of COVID-19 in Hubei Province and Other Parts of China

text: The new coronavirus SARS-CoV-2 pandemic of early 2020 poses an enormous challenge to global public health. Coronavirus Disease 2019 (COVID-19) caused by the virus has spread rapidly throughout the world, taking thousands of lives in just over 2 months. It is critical to refine the incidence and mortality risks of COVID-19 for the effective management of the general public and patients during the outbreak. In this report, we investigate the incidence and mortality risks of the infection by analyzing the age composition of 5,319 infected patients, 76 fatal cases, and 1,144,648 individuals of the general public in China. Our results show a relatively low incidence risk for young people but a very high mortality risk for seniors. Notably, mortality risk could be as high as 0.48 for people older than 80 years. Furthermore, our study suggests that a good medical service can effectively reduce the mortality rate of the viral infection to 1% or less.


title: Tuberculosis and COVID-19 in 2020: lessons from the past viral outbreaks and possible future outcomes

text: Background. The threat of contagious infectious diseases is constantly evolving, as demographic explosion, travel globalization and changes in human lifestyle increase the risk of spreading pathogens, leading to accelerated changes in disease landscape. Of particular interest is the aftermath of superimposing viral epidemics (especially SARS-CoV-2) over long-standing diseases, such as tuberculosis (TB), which remains a significant disease for public health worldwide and especially in emerging economies. Methods and Results. PubMed electronic database was requested for relevant articles linking TB, influenza and SARS-CoV viruses and subsequently assessed eligibility according to inclusion criteria. Using a data mining approach, we also queried the COVID-19 Open Research Dataset (CORD-19). We aimed to answer the following questions: What can be learned from other coronavirus outbreaks (with a focus on TB patients)? Is coinfection (TB and SARS-CoV-2) more severe? Is there a vaccine for SARS-CoV-2? How does the TB vaccine affect COVID-19? How does one diagnosis affect the other? Discussions. Few essential elements about TB and SARS-CoV coinfections were discussed. First, lessons from the past outbreaks (other coronaviruses), as well as influenza pandemic / seasonal outbreaks have taught the importance of infection control to avoid the severe impact on TB patients. Second, although challenging due to data scarcity, investigating the pathological pathways linking TB and SARS-CoV-2 leads to the idea that their coexistence might yield a more severe clinical evolution. Finally, we addressed the issues of vaccination and diagnostic reliability in the context of coinfection. Conclusions. Because viral respiratory infections and TB impede the host's immune responses, it can be assumed that their harmful synergism may contribute to more severe clinical evolution. Despite the rapidly growing number of cases, the data needed to predict the impact of the COVID-19 pandemic on patients with latent TB and TB sequelae still lies ahead.


title: Machine Learning to Predict Mortality and Critical Events in COVID-19 Positive New York City Patients

text: Coronavirus 2019 (COVID-19), caused by the SARS-CoV-2 virus, has become the deadliest pandemic in modern history, reaching nearly every country worldwide and overwhelming healthcare institutions. As of April 20, there have been more than 2.4 million confirmed cases with over 160,000 deaths. Extreme case surges coupled with challenges in forecasting the clinical course of affected patients have necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods for achieving this are lacking. In this paper, we present a decision tree-based machine learning model trained on electronic health records from patients with confirmed COVID-19 at a single center within the Mount Sinai Health System in New York City. We then externally validate our model by predicting the likelihood of critical event or death within various time intervals for patients after hospitalization at four other hospitals and achieve strong performance, notably predicting mortality at 1 week with an AUC-ROC of 0.84. Finally, we establish model interpretability by calculating SHAP scores to identify decisive features, including age, inflammatory markers (procalcitonin and LDH), and coagulation parameters (PT, PTT, D-Dimer). To our knowledge, this is one of the first models with external validation to both predict outcomes in COVID-19 patients with strong validation performance and identification of key contributors in outcome prediction that may assist clinicians in making effective patient management decisions.


title: Python nidoviruses, more than respiratory pathogens

text: In recent years nidoviruses have emerged as an important respiratory pathogen of reptiles, affecting especially captive python populations. In pythons, nidovirus infection induces an inflammation of the upper respiratory and alimentary tract which can develop into a severe and often fatal proliferative pneumonia. We observed pyogranulomatous and fibrinonecrotic lesions in organ systems other than the respiratory tract during full post mortem examinations on 30 nidovirus RT-PCR positive pythons of varying species originating from Switzerland and Spain. The observations prompted us to study whether the atypical tissue tropism associates with previously unknown nidoviruses or changes in the nidovirus genome. RT-PCR and inoculation of Morelia viridis cell cultures served to recruit the cases and to obtain virus isolates. Immunohistochemistry and immunofluorescence staining against nidovirus nucleoprotein demonstrated that the virus not only infects a broad spectrum of epithelial (respiratory and alimentary epithelium, hepatocytes, renal tubules, pancreatic ducts etc.), but also intravascular monocytes, intralesional macrophages and endothelial cells. By next-generation sequencing we obtained full length genome for a novel nidovirus species circulating in Switzerland. Analysis of viral genomes recovered from pythons showing nidovirus infection-associated respiratory or systemic disease did not explain the observed phenotypes. The results indicate that python nidoviruses have a broad cell and tissue tropism, further suggesting that the course of infection could vary and involve lesions in a broad spectrum of tissues and organ systems as a consequence of monocyte-mediated systemic spread of the virus. IMPORTANCE During the last years, python nidoviruses have become a primary cause of fatal disease in pythons. Nidoviruses represent a threat to captive snake collections, as they spread rapidly and can be associated with high morbidity and mortality. Our study indicates that, different from previously evidence, the viruses do not only affect the respiratory tract, but can spread in the entire body with blood monocytes, have a broad spectrum of target cells, and can induce a variety of lesions. Nidovirales is an order of animal and human viruses that compromise important zoonotic pathogens such as MERS-CoV and SARS-CoV, as well as the recently emerged SARS-CoV-2. Python nidoviruses belong to the same subfamily as the mentioned human viruses and show similar characteristics (rapid spread, respiratory and gastrointestinal tropism, etc.). The present study confirms the relevance of natural animal diseases to better understand the complexity of viruses of the order nidovirales.


Helping Canadian health care providers to optimize Sleep Disordered Breathing management for their patients during the COVID-19 pandemic


title: Are we #stayinghome to Flatten the Curve?

text: The recent spread of COVID-19 across the U.S. led to concerted efforts by states to ``flatten the curve" through the adoption of stay-at-home mandates that encourage individuals to reduce travel and maintain social distance and indeed using data on travel activity we find that residents start reducing mobility early in most states. Combining data on changes in travel activity with COVID-19 health outcomes and variation in state policy adoption, we characterize the direct impact of stay-at-home mandates on mobility and social distancing and link these behavioral changes to health benefits. We find evidence of dramatic declines in mobility nationwide prior to the adoption of statewide mandates. Despite these early reductions, we find that statewide stay-at-home policies induced "mandate effects" of between 4.1 and 5.9 percentage point declines relative to pre-COVID-19 levels for the first four states to introduce such policies. These effects persist when considering all states' mandates and alternate estimation strategies that account for states' differences in travel behavior prior to policy adoption. Using previous changes in mobility, we find significant effects on current mortality, with 1% reductions in visits to non-essential businesses weeks prior being associated with 9.2 fewer deaths per 100 million per day, corresponding with over 74,000 lives saved nationwide and resulting economic benefits between $249-$745 billion for observed behavioral changes in March and April. Observed reductions in mobility indeed contribute to flattening the curve and reduce the strain on the medical system during those two months. Our findings provide evidence that statewide stay-at-home ordinances induce additional social distancing, and ultimately attenuate the negative health consequences of COVID-19, revealing themselves as important policy tools in the fight against pandemic. Further, substantial reductions in mobility prior to state-level policies convey important policy implications.