title: Estimating pre-symptomatic transmission of COVID-19: a secondary analysis using published data

text: Background: Understanding the extent of virus transmission that can occur before symptom onset is vital for targeting control measures against the global pandemic of COVID-19. Objective: Estimation of (1) the proportion of pre-symptomatic transmission of COVID-19 that can occur and (2) timing of transmission relative to symptom onset. Design: Secondary analysis of published data Data sources: Meta-analysis of COVID-19 incubation period and a rapid systematic review of serial interval and generation time, which are published separately. Methods: Simulations were generated of incubation period and of serial interval or generation time. From these, transmission times relative to symptom onset were calculated and the proportion of pre-symptomatic transmission was estimated. Results: A total of 23 estimates of serial interval and five estimates of generation time from 17 publications were included. These came from nine different data source categories (presented here in descending order of the proportion of pre-symptomatic transmission): Hong Kong, Tianjin, pooled data from Hong Kong and Shenzhen, Singapore, Mainland China excluding Hubei, mixed sources, Shenzhen, northern Italy and Wuhan. Transmission time relative to symptom onset ranged from a mean of 2.05 days before symptom onset for Hong Kong to 1.72 days after symptom onset for Wuhan. Proportion of pre-symptomatic transmission ranged from 33.7% in Wuhan to 72.7% in Hong Kong. Based on individual estimates, transmission time relative to symptom onset ranged from mean of 2.95 days before symptom onset to 1.72 days after symptom onset and proportion of pre-symptomatic transmission ranged from 33.7% to 79.9%. Simple unweighted pooling of estimates based on serial intervals resulted in a mean time of transmission of 0.67 days before symptoms, and an estimated 56.1% of transmission occurring in the pre-symptomatic period. Conclusions: Contact rates between symptomatic infectious and susceptible people are likely to influence the proportion of pre-symptomatic transmission. There is substantial potential for pre-symptomatic transmission of COVID-19 in a range of different contexts. Our work suggests that transmission of SARS-CoV-2 is most likely in the day before symptom onset whereas estimates suggesting most pre-symptomatic transmission highlighted a mean transmission times almost 3 days before symptom onset. These findings highlight the urgent need for extremely rapid and effective case detection, contact tracing and quarantine measures if strict social distancing measures are to be eased.


title: Digesting the crisis: autophagy and coronaviruses

text: Autophagy is a catabolic pathway with multifaceted roles in cellular homeostasis. This process is also involved in the antiviral response at multiple levels, including the direct elimination of intruding viruses (virophagy), the presentation of viral antigens, the fitness of immune cells, and the inhibition of excessive inflammatory reactions. In line with its central role in immunity, viruses have evolved mechanisms to interfere with or to evade the autophagic process, and in some cases, even to harness autophagy or constituents of the autophagic machinery for their replication. Given the devastating consequences of the current COVID-19 pandemic, the question arises whether manipulating autophagy might be an expedient approach to fight the novel coronavirus SARS-CoV-2. In this piece, we provide a short overview of the evidence linking autophagy to coronaviruses and discuss whether such links may provide actionable targets for therapeutic interventions.


title: How does the outbreak of 2019-nCoV spread in mainland China? A retrospective analysis of the dynamic transmission routes

text: The fourth outbreak of the Coronaviruses, known as the 2019-nCoV, has occurred in Wuhan city of Hubei province in China in December 2019. We propose a time-varying sparse vector autoregressive (VAR) model to retrospectively analyze and visualize the dyamic transmission routes of this outbreak in mainland China over January 31 - February 19, 2020. Our results demonstrate that the influential inter-province routes from Hubei have become unidentifiable since February 4, whereas the self-transmission in each province was accelerating over February 4-15. From February 16, all routes became less detectable, and no influential transmissions could be identified on February 18 and 19. Such evidence supports the effectiveness of government interventions, including the travel restrictions in Hubei. Implications of our results suggest that in addition to the origin of the outbreak, virus preventions are of crucial importance in provinces with the largest migrant workers percentages (e.g., Jiangxi, Henan and Anhui) to controlling the spread of 2019-nCoV.


title: Presenting features of COVID-19 in older people: relationships with frailty, inflammation and mortality

text: Purpose To describe the clinical features of COVID-19 in older adults, and relate these to outcomes. Methods Cohort study of 217 individuals ([≥]70 years) hospitalised with COVID-19, followed up for allcause mortality. Secondary outcomes included cognitive and physical function at discharge. C-reactive protein and neutrophil : lymphocyte ratio were used as measures of immune activity. Results Cardinal COVID-19 symptoms (fever, dyspnoea, cough) were common but not universal. Inflammation on hospitalisation was lower in frail older adults. Fever, dyspnoea, delirium and inflammation were associated with mortality. Delirium at presentation was an independent risk factor for cognitive decline at discharge. Conclusions COVID-19 may present without cardinal symptoms as well as implicate a possible role for agerelated changes in immunity in mediating the relationship between frailty and mortality.


title: Identification of a critical horseshoe-shaped region in the nsp5 (Mpro, 3CLpro) protease interdomain loop (IDL) of coronavirus mouse hepatitis virus (MHV)

text: Human coronaviruses are enveloped, positive-strand RNA viruses which cause respiratory diseases ranging in severity from the seasonal common cold to SARS and COVID-19. Of the 7 human coronaviruses discovered to date, 3 emergent and severe human coronavirus strains (SARS-CoV, MERS-CoV, and SARS-CoV-2) have recently jumped to humans in the last 20 years. The COVID-19 pandemic spawned by the emergence of SARS-CoV-2 in late 2019 has highlighted the importance for development of effective therapeutics to target emerging coronaviruses. Upon entry, the replicase genes of coronaviruses are translated and subsequently proteolytically processed by virus-encoded proteases. Of these proteases, nonstructural protein 5 (nsp5, Mpro, or 3CLpro), mediates the majority of these cleavages and remains a key drug target for therapeutic inhibitors. Efforts to develop nsp5 active-site inhibitors for human coronaviruses have thus far been unsuccessful, establishing the need for identification of other critical and conserved non-active-site regions of the protease. In this study, we describe the identification of an essential, conserved horseshoe-shaped region in the nsp5 interdomain loop (IDL) of mouse hepatitis virus (MHV), a common coronavirus replication model. Using site-directed mutagenesis and replication studies, we show that several residues comprising this horseshoe-shaped region either fail to tolerate mutagenesis or were associated with viral temperature-sensitivity. Structural modeling and sequence analysis of these sites in other coronaviruses, including all 7 human coronaviruses, suggests that the identified structure and sequence of this horseshoe regions is highly conserved and may represent a new, non-active-site regulatory region of the nsp5 (3CLpro) protease to target with coronavirus inhibitors. Importance In December 2019, a novel coronavirus (SARS-CoV-2) emerged in humans and triggered a pandemic which has to date resulted in over 8 million confirmed cases of COVID-19 across more than 180 countries and territories (June 2020). SARS-CoV-2 represents the third emergent coronavirus in the past 20 years and the future emergence of new coronaviruses in humans remains certain. Critically, there remains no vaccine nor established therapeutics to treat cases of COVID-19. The coronavirus nsp5 protease is a conserved and indispensable virus-encoded enzyme which remains a key target for therapeutic design. However, past attempts to target the active site of nsp5 with inhibitors have failed stressing the need to identify new conserved non-active-site targets for therapeutic development. This study describes the discovery of a novel conserved structural region of the nsp5 protease of coronavirus mouse hepatitis virus (MHV) which may provide a new target for coronavirus drug development.


title: Red blood cell distribution width (RDW) in Hospitalized COVID-19 Patients

text: Introduction: Coronavirus disease-2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is causing dramatic morbidity and mortality worldwide. The Red Blood Cell Distribution Width (RDW) has been strongly associated with increased morbidity and mortality in multiple diseases. Objective: To assess if elevated RDW is associated with unfavorable outcomes in hospitalized COVID-19. Methods: We retrospectively studied clinical outcomes of hospitalized COVID-19 patients for their RDW values. In-hospital mortality was defined as primary outcome, while septic shock, need for mechanical ventilation, and length of stay (LOS) were secondary outcomes. Results- A total of 294 COVID-19 patients were finally studied. Overall prevalence of increased RDW was 49.7% (146/294). RDW was associated with increased risk of in-hospital mortality (aOR, 4.5; 95%CI, 1.4-14.3) and septic shock (aOR, 4.6; 95%CI, 1.4-15.1) after adjusting for anemia, ferritin, and lactate. The association remained unchanged even after adjusting for other clinical confounders such as age, sex, body mass index, coronary artery disease, hypertension, diabetes mellitus, and chronic obstructive pulmonary disease. No association was found instead with mechanical ventilation and median LOS. Conclusion: Elevated RDW in hospitalized COVID-19 patients is associated with a significantly increased risk of mortality and septic shock.


title: Cross-scale dynamics and the evolutionary emergence of infectious diseases

text: When emerging pathogens encounter new host species for which they are poorly adapted, they must evolve to escape extinction. Pathogens experience selection on traits at multiple scales, including replication rates within host individuals and transmissibility between hosts. We analyze a stochastic model linking pathogen growth and competition within individuals to transmission between individuals. Our analysis reveals a new factor, the cross-scale reproductive number of a mutant virion, that quantifies how quickly mutant strains increase in frequency when they initially appear in the infected host population. This cross-scale reproductive number combines with viral mutation rates, single-strain reproductive numbers, and transmission bottleneck width to determine the likelihood of evolutionary emergence, and whether evolution occurs swiftly or gradually within chains of transmission. We find that wider transmission bottlenecks facilitate emergence of pathogens with short-term infections, but hinder emergence of pathogens exhibiting cross-scale selective conflict and long-term infections. Our results provide a framework to advance the integration of laboratory, clinical and field data in the context of evolutionary theory, laying the foundation for a new generation of evidence-based risk assessment of emergence threats.


title: Proteomics Uncovers Immunosuppression in COVID-19 Patients with Long Disease Course

text: Little is known regarding why a subset of COVID-19 patients exhibited prolonged positivity of SARS-CoV-2 infection. Here, we present a longitudinal sera proteomic resource for 37 COVID-19 patients over nine weeks, in which 2700 proteins were quantified with high quality. Remarkably, we found that during the first three weeks since disease onset, while clinical symptoms and outcome were indistinguishable, patients with prolonged disease course displayed characteristic immunological responses including enhanced Natural Killer (NK) cell-mediated innate immunity and regulatory T cell-mediated immunosuppression. We further showed that it is possible to predict the length of disease course using machine learning based on blood protein levels during the first three weeks. Validation in an independent cohort achieved an accuracy of 82%. In summary, this study presents a rich serum proteomic resource to understand host responses in COVID-19 patients and identifies characteristic Treg-mediated immunosuppression in LC patients, nominating new therapeutic target and diagnosis strategy.


title: The major genetic risk factor for severe COVID-19 is inherited from Neandertals

text: A recent genetic association study (Ellinghaus et al. 2020) identified a gene cluster on chromosome 3 as a risk locus for respiratory failure in SARS-CoV-2. Recent data comprising 3,199 hospitalized COVID-19 patients and controls reproduce this and find that it is the major genetic risk factor for severe SARS-CoV-2 infection and hospitalization (COVID-19 Host Genetics Initiative). Here, we show that the risk is conferred by a genomic segment of ~50 kb that is inherited from Neandertals and occurs at a frequency of ~30% in south Asia and ~8% in Europe.


title: Eddleston M, Davidson R, Wilkinson R, Pierini S, editors. Oxford handbook of tropical medicine, 2nd ed. Oxford: Oxford University Press; 2005, 686pp [with illus, paper, GBP24.95]. ISBN 0-19-852509-5.

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title: Hydrogen Peroxide Vapor sterilization of N95 respirators for reuse

text: Abstract Reprocessing of used N95 respirators may ameliorate supply chain constraints during the COVID-19 pandemic and provide a higher filtration crisis alternative. The FDA Medical Countermeasures Initiative previously funded a study of HP vapor decontamination of respirators using a Clarus C system (Bioquell, Horsham, PA) which normally is used to fumigate hospital rooms. The process preserved respirator function, but it is unknown if HP vapor would be virucidal since respirators have porous fabric that may harbor virus. We evaluated the virucidal activity of HP vapor using a BQ-50 system (Bioquell, Horsham, PA) after inoculating 3M 1870 N95 respirators (3M, St. Paul, MN) with 3 aerosolized bacteriophage that are a reasonable proxy for SARS-CoV-2. Inoculation resulted in contamination of the respirator with 9.87e4 plaque forming units (PFU) of phage phi-6, 4.17e7 PFU of phage T7 and 1.35e7 PFU of phage T1. Respirators were reprocessed with BQ-50 with a long aeration phase to reduce HP vapors. Virucidal activity was measured by a standard plaquing assay prior to and after sterilization. A single HP vapor cycle resulted in complete eradication of phage from masks (limit of detection 10 PFU, lower than the infectious dose of the majority of respiratory viral pathogens). After 5 cycles, the respirators appeared similar to new with no deformity. Use of a Bioquell machine can be scaled to permit simultaneous sterilization of a large number of used but otherwise intact respirators. HP vapor reprocessing may ease shortages and provide a higher filtration crisis alternative to non-NIOSH masks.


title: A Tool to Early Predict Severe 2019-Novel Coronavirus Pneumonia (COVID-19) : A Multicenter Study using the Risk Nomogram in Wuhan and Guangdong, China

text: Background Severe cases of coronavirus disease 2019 (COVID-19) rapidly develop acute respiratory distress leading to respiratory failure, with high short-term mortality rates. At present, there is no reliable risk stratification tool for non-severe COVID-19 patients at admission. We aimed to construct an effective model for early identifying cases at high risk of progression to severe COVID-19. Methods SARS-CoV-2 infected patients from one center in Wuhan city and two centers in Guangzhou city, China were included retrospectively. All patients with non-severe COVID-19 during hospitalization were followed for more than 15 days after admission. Patients who deteriorated to severe or critical COVID-19 and patients who kept non-severe state were assigned to the severe and non-severe group, respectively. We compared the demographic, clinical, and laboratory data between severe and non-severe group. Based on baseline data, least absolute shrinkage and selection operator (LASSO) algorithm and logistic regression model were used to construct a nomogram for risk prediction in the train cohort. The predictive accuracy and discriminative ability of nomogram were evaluated by area under the curve (AUC) and calibration curve. Decision curve analysis (DCA) and clinical impact curve analysis (CICA) were conducted to evaluate the clinical applicability of our nomogram. Findings The train cohort consisted of 189 patients, while the two independent validation cohorts consisted of 165 and 18 patients. Among all cases, 72 (19.35%) patients developed severe COVID-19 and 107 (28.76%) patients had one of the following basic disease, including hypertension, diabetes, coronary heart disease, chronic respiratory disease, tuberculosis disease. We found one demographic and six serological indicators (age, serum lactate dehydrogenase, C-reactive protein, the coefficient of variation of red blood cell distribution width (RDW), blood urea nitrogen, albumin, direct bilirubin) are associated with severe COVID-19. Based on these features, we generated the nomogram, which has remarkably high diagnostic accuracy in distinguishing individuals who exacerbated to severe COVID-19 from non-severe COVID-19 (AUC 0.912 [95% CI 0.846-0.978]) in the train cohort with a sensitivity of 85.71 % and specificity of 87.58% ; 0.853 [0.790-0.916] in validation cohort with a sensitivity of 77.5 % and specificity of 78.4%. The calibration curve for probability of severe COVID-19 showed optimal agreement between prediction by nomogram and actual observation. DCA and CICA further indicated that our nomogram conferred significantly high clinical net benefit. Interpretation Our nomogram could help clinicians to early identify patients who will exacerbate to severe COVID-19. And this risk stratification tool will enable better centralized management and early treatment of severe patients, and optimal use of medical resources via patient prioritization and thus significantly reduce mortality rates. The RDW plays an important role in predicting severe COVID-19, implying that the role of RBC in severe disease is underestimated.


title: A comprehensive germline variant and expression analyses of ACE2, TMPRSS2 and SARS-CoV-2 activator FURIN genes from the Middle East: Combating SARS-CoV-2 with precision medicine

text: The severity of the new COVID-19 pandemic caused by the SARS-CoV-2 virus is strikingly variable in different global populations. SARS-CoV-2 uses ACE2 as a cell receptor, TMPRSS2 protease, and FURIN peptidase to invade human cells. Here, we investigated 1,378 whole-exome sequences of individuals from the Middle Eastern populations (Kuwait, Qatar, and Iran) to explore natural variations in the ACE2, TMPRSS2, and FURIN genes. We identified two activating variants (K26R and N720D) in the ACE2 gene that are more common in Europeans than in the Middle Eastern, East Asian, and African populations. We postulate that K26R can activate ACE2 and facilitate binding to S-protein RBD while N720D enhances TMPRSS2 cutting and, ultimately, viral entry. We also detected deleterious variants in FURIN that are frequent in the Middle Eastern but not in the European populations. This study highlights specific genetic variations in the ACE2 and FURIN genes that may explain SARS-CoV-2 clinical disparity. We showed structural evidence of the functionality of these activating variants that increase the SARS-CoV-2 aggressiveness. Finally, our data illustrate a significant correlation between ACE2 variants identified in people from Middle Eastern origins that can be further explored to explain the variation in COVID-19 infection and mortality rates globally.


title: A Gaussian model for the time development of the Sars-Cov-2 corona pandemic disease. Predictions for Germany made on March 30, 2020

text: For Germany it is predicted that the first wave of the corona pandemic disease reaches its maximum of new infections on April 11th, 2020 +5.4-3.4 days with 90 percent confidence. With a delay of about 7 days the maximum demand on breathing machines in hospitals occurs on April 18th, 2020 +5.4-3.4 days. The first pandemic wave ends in Germany end of May 2020. The predictions are based on the assumption of a Gaussian time evolution well justified by the central limit theorem of statistics. The width and the maximum time and thus the duration of this Gaussian distribution are determined from a statistical Ξ2-fit to the observed doubling times before March 28, 2020.


Considering heparin-related coagulation status when providing motor exercise in patients with COVID-19


Medicare, Telehealth, and DSMT in the Age of COVID-19 and Beyond: An Advocacy Perspective


title: Risk factors associated with mortality in hospitalized patients with SARS-CoV-2 infection. A prospective, longitudinal, unicenter study in Reus, Spain

text: Spain is one of the countries that has suffered the most from the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the strain that causes coronavirus disease 2019 (COVID-19). However, there is a lack of information on the characteristics of this disease in the Spanish population. The objective of this study has been to characterize our patients from an epidemiological point of view and to identify the risk factors associated with mortality in our geographical area. We performed a prospective, longitudinal study on 188 hospitalized cases of SARS-Cov-2 infection in Hospital Universitari de Sant Joan, in Reus, Spain, admitted between 15th March 2020 and 30th April 2020. We recorded demographic data, signs and symptoms and comorbidities. We also calculated the Charlson and McCabe indices. A total of 43 deaths occurred during the study period. Deceased patients were older than the survivors (77.7 ± 13.1 vs. 62.8 ± 18.4 years; p < 0.001). Logistic regression analyses showed that fever, pneumonia, acute respiratory distress syndrome, diabetes mellitus and cancer were the variables that showed independent and statistically significant associations with mortality. The Charlson index was more efficient than the McCabe index in discriminating between deceased and survivors. This is one of the first studies to describe the factors associated with mortality in patients infected with SARS-CoV-2 in Spain, and one of the few in the Mediterranean area. We identified the main factors independently associated with mortality in our population. Further studies in are needed to complete and confirm our findings.


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title: Differential occupational risks to healthcare workers from SARS-CoV-2: A prospective observational study

text: Background Personal protective equipment (PPE) and social distancing are key measures designed to mitigate the risk of occupational SARS-CoV-2 infection in hospitals. Why healthcare workers nevertheless remain at increased risk is uncertain. Methods We conducted voluntary Covid-19 testing programmes for symptomatic and asymptomatic staff at a large UK teaching hospital using nasopharyngeal PCR testing and immunoassays for IgG antibodies. A positive result by either modality was used as a composite outcome. Risk factors for Covid-19 were investigated using multivariable logistic regression. Results 1083/9809(11.0%) staff had evidence of Covid-19 at some time and provided data on potential risk-factors. Staff with a confirmed household contact were at greatest risk (adjusted odds ratio [aOR] 4.63 [95%CI 3.30-6.50]). Higher rates of Covid-19 were seen in staff working in Covid-19-facing areas (21.2% vs. 8.2% elsewhere) (aOR 2.49 [2.00-3.12]). Controlling for Covid-19-facing status, risks were heterogenous across the hospital, with higher rates in acute medicine (1.50 [1.05-2.15]) and sporadic outbreaks in areas with few or no Covid-19 patients. Covid-19 intensive care unit (ICU) staff were relatively protected (0.46 [0.29-0.72]). Positive results were more likely in Black (1.61 [1.20-2.16]) and Asian (1.58 [1.34-1.86]) staff, independent of role or working location, and in porters and cleaners (1.93 [1.25-2.97]). Contact tracing around asymptomatic staff did not lead to enhanced case identification. 24% of staff/patients remained PCR-positive at [≥]6 weeks post-diagnosis. Conclusions Increased Covid-19 risk was seen in acute medicine, among Black and Asian staff, and porters and cleaners. A bundle of PPE-related interventions protected staff in high-risk ICU areas.


title: Ultra-fast and onsite interrogation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in environmental specimens via surface enhanced Raman scattering (SERS)

text: The outbreak of coronavirus infectious disease-2019 (COVID-19) pneumonia challenges the rapid interrogation of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in human and environmental specimens. In this study, we developed an assay using surface enhanced Raman scattering (SERS) coupled with multivariate analysis to diagnose SARS-CoV-2 in an ultra-fast manner without any pretreatment (e.g., RNA extraction). Using silver-nanorod SERS array functionalized with cellular receptor angiotensin-converting enzyme 2 (ACE2), we obtained strong SERS signals of ACE2 at 1032, 1051, 1089, 1189, 1447 and 1527 cm-1. The recognition and binding of receptor binding domain (RBD) of SARS-CoV-2 spike protein on SERS assay significantly quenched the spectral intensities of most peaks and exhibited a shift from 1189 to 1182 cm-1. On-site tests on 17 water samples with a portable Raman spectrometer proved its accuracy and easy-operation for spot diagnosis of SARS-CoV-2 to evaluate disinfection performance, explore viral survival in environmental media, assess viral decay in wastewater treatment plant and track SARS-CoV-2 in pipe network. Our findings raise a state-of-the-art spectroscopic tool to screen and interrogate viruses with RBD for human cell entry, proving its feasibility and potential as an ultra-fast diagnostic tool for public health.


The Good University: What Universities Actually Do and Why It’s Time for Radical Change


title: Rational Design of the Remdesivir Binding Site in the RNA-dependent RNA Polymerase of SARS-CoV-2: Implications for Potential Resistance

text: SARS-CoV-2 is rapidly evolving with the continuous emergence of new mutations. There is no specific antiviral therapy for COVID-19, and the use of Remdesivir for treating COVID-19 will likely continue before clinical trials are completed. Due to the lengthening pandemic and evolving nature of the virus, predicting potential residues prone to mutations is crucial for the management of Remdesivir resistance. We used a rational ligand-based interface design complemented with mutational mapping to generate a total of 100,000 mutations and provide insight into the functional outcome of mutations in the Remdesivir-binding site in nsp12. After designing 56 residues in the Remdesivir binding site of nsp12, the designs retained 96-98% sequence identity, which suggests that SARS-CoV-2 attains resistance and develops further infectivity with very few mutations in the nsp12. We also identified affinity-attenuating Remdesivir binding designs of nsp12. Several mutants acquired decreased binding affinity with Remdesivir, which suggested drug resistance. These hotspot residues had a higher probability of undergoing selective mutations in the future to develop Remdesivir and related drug-based resistance. A comparison of 21 nsp12 Remdesivir-bound designs to the 13 EIDD-2801-bound nsp12 designs suggested that EIDD-2801 would be more effective in preventing the emergence of resistant mutations and against Remdesivir-resistance strains due to the restricted mutational landscape. Combined with the availability of more genomic data, our information on mutation repertoires is critical to guide scientists to rational structure-based drug discovery. Knowledge of the potential residues prone to mutation improves our understanding and management of drug resistance and disease pathogenesis.


Covid-19: the Sri Lankan response


title: Modeling the situation of COVID-19 and effects of different containment strategies in China with dynamic differential equations and parameters estimation

text: This paper proposed a quarantine-susceptible-exposed-infectious-resistant (QSEIR) model which considers the unprecedented strict quarantine measures in almost the whole of China to resist the epidemic. We estimated model parameters from published information with the statistical method and stochastic simulation, we found the parameters that achieved the best simulation test result. The next stage involved quantitative predictions of future epidemic developments based on different containment strategies with the QSEIR model, focused on the sensitivity of the outcomes to different parameter choices in mainland China. The main results are as follows. If the strict quarantine measures are being retained, the peak value of confirmed cases would be in the range of [52438, 64090] and the peak date would be expected in the range February 7 to February 19, 2020. During March18-30, 2020, the epidemic would be controlled. The end date would be in the period from August 20 to September 1, 2020. With 80% probability, our prediction on the peak date was 4 days ahead of the real date, the prediction error of the peak value is 0.43%, both estimates are much closer to the observed values compared with published studies. The sensitive analysis indicated that the quarantine measures (or with vaccination) are the most effective containment strategy to control the epidemic, followed by measures to increase the cured rate (like finding special medicine). The long-term simulation result and sensitive analysis in mainland China showed that the QSEIR model is stable and can be empirically validated. It is suggested that the QSEIR model can be applied to predict the development trend of the epidemic in other regions or countries in the world. In mainland China, the quarantine measures can't be relaxed before the end of March 2020. China can fully resume production with appropriate anti-epidemic measures beginning in early April 2020. The results of this study also implied that other countries now facing the epidemic outbreaks should act more decisively and take in time quarantine measures though it may have negative short-term public and economic consequences.


title: Three pictures of COVID-19 behavior in Italy: similar growth and different degrowth

text: In this short note, we present an analysis of the data regarding Coronavirus (COVID-19) in Italy. We have used the official database provided by the Italian Civil Protection. Since the total number of people infected by the virus is uncertain, we have considered the trend of ICU patients, ICU patients plus deaths, and finally the sum of hospitalized patients plus the deceased. The growth of the corresponding curves is similar for all the three graphs while the trend after the turning point is completely different. We find that the curve of ICU patients can be a useful tool to monitor the behavior of epidemic and a model to predict the future evolution of COVID-19.


title: Transmission potential of the novel coronavirus (COVID-19) onboard the Diamond Princess Cruises Ship, 2020

text: An outbreak of COVID-19 developed aboard the Princess Cruises Ship during January-February 2020. Using mathematical modeling and time-series incidence data describing the trajectory of the outbreak among passengers and crew members, we characterize how the transmission potential varied over the course of the outbreak. Our estimate of the mean reproduction number in the confined setting reached values as high as ~11, which is higher than mean estimates reported from community-level transmission dynamics in China and Singapore (approximate range: 1.1-7). Our findings suggest that Rt decreased substantially compared to values during the early phase after the Japanese government implemented an enhanced quarantine control. Most recent estimates of Rt reached values largely below the epidemic threshold, indicating that a secondary outbreak of the novel coronavirus was unlikely to occur aboard the Diamond Princess Ship.


title: Dispositivo de bajo costo para disminuir el efecto de aerosol durante la endoscopia de vías digestivas altas en COVID-19/ Low cost devices to reduce aerosol effect during upper gastrointestinal endoscopy in COVID-19

text: Los procedimientos endoscópicos, al estar asociados a la exposición de la vía aérea superior, tienen un mayor riesgo de transmisión del virus SARS-CoV-2; por esta razón, es necesario el planteamiento de in-tervenciones para atenuar o eliminar la exposición a éste. En este artículo nos permitimos presentar una estrategia de mitigación de bajo costo, ya que con el progreso de la pandemia se podría estar en un estado de austeridad de recursos económicos, lo cual haría estos dispositivos totalmente válidos.(AU)


title: An Accurate Free Energy Method for Solvation of Organic Compounds and Binding to Proteins

text: Here, we introduce a new strategy to estimate free energies using single end-state molecular dynamics simulation trajectories. The method is adopted from ANI-1ccx neural network potentials (Machine Learning) for the Atomic Simulation Environment (ASE) and predicts the single point energies at the accuracy of CCSD(T)/CBS level for the entire configurational space that is sampled by Molecular Dynamics (MD) simulations. Our preliminary results show that the method can be as accurate as Bennet-Acceptance-Ration (BAR) with much reduced computational cost. Not only does it enable to calculate solvation free energies of small organic compounds, but it is also possible to predict absolute and relative binding free energies in ligand-protein complex systems. Rapid calculation also enables to screen small organic molecules from databases as potent inhibitors to any drug targets.


title: D-dimer and C-reactive Protein Blood Levels Over Time Used to Predict Pulmonary Embolism in Two COVID-19 Patients

text: The diagnosis of pulmonary embolism is challenging in symptomatic COVID-19 patients since shortness of breath, chest pain, tachycardia, tachypnoea, fever, oxygen desaturation and high D-dimer blood levels might be features of both diseases. We present two COVID-19 patients in whom pulmonary embolism was suspected (and diagnosed) due to a discrepancy between an increase in D-dimer blood levels and a decrease in C-reactive protein blood levels over time. We believe that an opposite change in the blood levels of both biomarkers over time may be used as a novel method to predict pulmonary embolism in COVID-19 patients. LEARNING POINTS: The diagnosis of pulmonary embolism is challenging in COVID-19 patients since symptoms, signs and high D-dimer blood levels might be similar in both diseases. An increase in D-dimer blood levels and a decrease in C-reactive protein blood levels over time may be used as a novel method to predict pulmonary embolism in COVID-19 patients.


title: Blank geometry design for carbon fiber reinforced plastic (CFRP) preforming using finite element analysis (FEA)

text: Abstract Carbon fiber reinforced plastics (CFRPs) have attracted growing attention from transportation industry because of their superior performance over metal counterparts. The thermoforming process has been invented for mass-production of CFRP parts. This thermoforming process involves multiple steps and numerous parameters, and one of the most important process parameters is the initial blank geometry. To optimize blank geometry in thermoforming and minimize trimming work for the final part, an innovative approach integrating automatic mesh adjustment and FEA modeling method for preforming is developed as foundation of design and reported in this paper. Preliminary trial-and-error optimization algorithm demonstrates that this newly-developed approach can accurately design blank geometry under various typical process conditions.


title: Association of Renin Angiotensin System Blockers with Outcomes in Patients with Covid-19: A Systematic Review and Meta-analysis

text: Background: Patients with cardiovascular disease are at increased risk of critical illness and mortality from Covid-19 disease. Conflicting findings have raised concerns regarding the association of angiotensin converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARBs) use with likelihood or severity of infection during this pandemic. Objective: To study the cumulative evidence for association of ACEI/ARB use with outcomes among patients with confirmed Covid-19. Methods: The MEDLINE and EMBASE databases were thoroughly searched from November 01, 2019 to May 15, 2020 for studies reporting on outcomes based on ACEI/ARB use in patients with confirmed Covid-19. Preferred reporting items for systematic review and meta-analysis guidelines were used for the present study. Relevant data was collected and pooled odds ratios (OR) with 95% confidence intervals (CI) were calculated using random-effects model. Main Outcome measures: In-hospital mortality was the primary end of interest. Second end-point was severe or critical illness defined as either need for intensive care unit, invasive mechanical ventilation, or mortality. Results: Fifteen studies with total of 23,822 patients (N ACEI/ARB=6,650) were included in the present analysis. Overall, prevalence of ACEI/ARB use ranged from 7.7% to 46.2% across studies. Among 10 studies, patients using ACEI/ARB had similar odds of mortality [OR 1.03 (0.69-1.55)] and severe or critical illness [1.18 (0.91-1.54)] compared to those not on ACEI/ARB. In an analysis restricted to patients with hypertension, ACEI/ARB use was associated with significantly lower mortality [0.64 (0.45-0.89)], while the odds of severe/critical illness [0.76(0.52-1.12); p=0.16] remained non-significant compared with non-ACEI/ARB users. Conclusion: There is no evidence for increased risk of severe illness or mortality in patients using ACEI/ARB compared with non-users. In patients with hypertension, ACE/ARB use might be associated with reduced mortality, however these findings need to be confirmed in prospective randomized controlled trials.


Anxiety and depression among general population in China at the peak of the COVID‐19 epidemic


title: Frequency of Coronavirus NL63 Infection in Children with Upper Respiratory Infection by Real-Time PCR

text: Background: Human coronavirus NL63 (HCoV-NL63) is a new respiratory virus associated with acute respiratory infection in children Infection with this virus is usually accompanied by upper and lower infections of the respiratory tract in adults Objectives: In a retrospective study, we investigated the incidence of coronavirus infection in children under the age of five years Methods: We collected 138 specimens (nasal and throat swabs) from children less than five-years-old with acute respiratory infection from October 2018 to December 2019 Then, HCoV-NL63 was investigated using real-time PCR Results: Out of 138 samples, 33 (23 9%) were positive for coronavirus NL63, including 21 (63 6%) male samples and 12 (36 4%) female samples There was no significant correlation between gender and positivity for coronavirus infection (P > 0 05) However, the association of clinical symptoms with the virus was statistically significant (P < 0 05) Conclusions: This study was conducted for the first time in Kerman Province In this study, the frequency of coronavirus NL63 was evaluated among children with acute respiratory infection with a highly sensitive method, real-time PCR The prevalence of this virus was 33%, which was more frequent than in similar studies


title: A comparative analysis of statistical methods to estimate the reproduction number in emerging epidemics with implications for the current COVID-19 pandemic

text: As the SARS-CoV-2 pandemic continues its rapid global spread, quantification of local transmission patterns has been, and will continue to be, critical for guiding pandemic response. Understanding the accuracy and limitations of statistical methods to estimate the reproduction number, R0, in the context of emerging epidemics is therefore vital to ensure appropriate interpretation of results and the subsequent implications for control efforts. Using simulated epidemic data we assess the performance of 6 commonly-used statistical methods to estimate R0 as they would be applied in a real-time outbreak analysis scenario - fitting to an increasing number of data points over time and with varying levels of random noise in the data. Method comparison was also conducted on empirical outbreak data, using Zika surveillance data from the 2015-2016 epidemic in Latin America and the Caribbean. We find that all methods considered here frequently over-estimate R0 in the early stages of epidemic growth on simulated data, the magnitude of which decreases when fitted to an increasing number of time points. This trend of decreasing bias over time can easily lead to incorrect conclusions about the course of the epidemic or the need for control efforts. We show that true changes in pathogen transmissibility can be difficult to disentangle from changes in methodological accuracy and precision, particularly for data with significant over-dispersion. As localised epidemics of SARS-CoV-2 take hold around the globe, awareness of this trend will be important for appropriately cautious interpretation of results and subsequent guidance for control efforts.


title: Estimate of Covid-19 prevalence using imperfect data

text: The real number of people who were truly infected with SARS-CoV-2, is certainly significantly larger than the official record. Few countries have tracking and testing procedures that are sufficiently robust to discover nearly all infections. In most countries they are inadequate, hence the true extent of the pandemic is unknown. The current study proposes the estimate of the COVID-19 extent for countries with sufficiently high number of deaths and cases. The estimate is based on a simple model of mortality. This model was developed for a reference country with a large number of cases and high intensity of COVID-19 testing. The model is then applied to compute apparent mortality in the target and reference countries. The number of cases in the target country is then estimated assuming constant underlying true mortality. The estimate of cases in most countries is significantly higher than the official record. As of April 12, 2020, the global estimate is 5.2 million compared to 1.8 million in the official record. The models developed in this study are available at covid-model.net. The model ignores several factors that are known to influence mortality, such as the demographics and health condition of population, state of epidemic and sociological differences between countries. While the model is rough, it nevertheless provides a unified approach to producing a systematic global estimate of the extent of the COVID-19 epidemic and can be useful for its monitoring.


title: Smoking Cessation as a Public Health Measure to Limit the Coronavirus Disease 2019 Pandemic

text: The novel coronavirus disease 2019 (COVID-19) has already evolved into a rapidly expanding pandemic. Risk factors for COVID-19, such as cardiovascular disease, chronic obstructive pulmonary disease and diabetes, are all strongly associated with smoking habits. The effects of cigarette smoking on the transmission of the virus and worsening of COVID-19 have been less addressed. Emerging data indicate that smoking history is the major determinant of worsening COVID-19 outcomes. Smoking cessation recovers airway ciliary clearance and immune function. Thus, smoking cessation awareness is strongly encouraged as a public health measure to limit the global impact of COVID-19.


title: Screening of active components from Chinese materia medica against SARS-CoV-2 based on literature mining and molecular docking/ 基于文献挖掘与分子对接技术的抗新型冠状病毒中药活性成分筛选

text: Objective: To screen the active components from Chinese materia medica (CMM) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) based on literature mining and molecular docking. Methods: Candidate CMMs were collected from recently published prescriptions against COVID-19. The active components and protein targets of candidate CMMs were collected from TCMSP, CNKI and PubMed. SARS-CoV-2 3CL hydrolase (Mpro) has been determined by academician Zihe Rao’s team at Shanghai Technical University. The molecular docking was performed by AutoDock vina software. Results: A total of 11 high-frequency used candidate CMMs were obtained by literature mining, and 469 candidate components were found from TCMSP and literatures. The binding energy of all the components were calculated by molecular docking and 41 components of them were less than -33.44 kJ/mol. Among them, saikosaponin (E, B1, D, F, B2, C2, A) and glycyrrhizin had the lower binding energies. The results showed that Bupleuri Radix, Glycyrrhizae Radix et Rhizoma and Lonicerae Japonicae Flos contained more active components against SARS-CoV-2. Conclusion: The active components of CMMs against SARS-CoV-2 were screened based on literature mining and molecular docking, which provides a reference for exploration and discovery of new anti-SARS-CoV-2 drugs.


title: A deep learning algorithm using CT images to screen for Corona Virus Disease (COVID-19)

text: Background: The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) has caused more than 2.5 million cases of Corona Virus Disease (COVID-19) in the world so far, with that number continuing to grow. To control the spread of the disease, screening large numbers of suspected cases for appropriate quarantine and treatment is a priority. Pathogenic laboratory testing is the gold standard but is time-consuming with significant false negative results. Therefore, alternative diagnostic methods are urgently needed to combat the disease. Based on COVID-19 radiographical changes in CT images, we hypothesized that Artificial Intelligence's deep learning methods might be able to extract COVID-19's specific graphical features and provide a clinical diagnosis ahead of the pathogenic test, thus saving critical time for disease control. Methods and Findings: We collected 1,065 CT images of pathogen-confirmed COVID-19 cases (325 images) along with those previously diagnosed with typical viral pneumonia (740 images). We modified the Inception transfer-learning model to establish the algorithm, followed by internal and external validation. The internal validation achieved a total accuracy of 89.5% with specificity of 0.88 and sensitivity of 0.87. The external testing dataset showed a total accuracy of 79.3% with specificity of 0.83 and sensitivity of 0.67. In addition, in 54 COVID-19 images that first two nucleic acid test results were negative, 46 were predicted as COVID-19 positive by the algorithm, with the accuracy of 85.2%. Conclusion: These results demonstrate the proof-of-principle for using artificial intelligence to extract radiological features for timely and accurate COVID-19 diagnosis.


title: Family Life Education for Families Facing Acute Stress: Best Practices and Recommendations

text: Acute family stress in this article is defined as the sudden or unexpected onset of moderate to severe discomfort or disequilibrium and feeling of inadequacy among family members in light of perceived insufficient available resources. Historically, there has been some ambivalence about stress—especially acute stress—and family life education. More recently, authors have suggested that the important issue determining appropriateness is not the topic but the approach used by the professionals. Several approaches are presented here that have been used by professionals to help children and families dealing with acute stress. They include care for self, identify acute stress, support caregivers and central figures in social networks, help families understand stress and coping, help adults talk with children, connect families with the familiar, collaborate with other professionals, and advocate for families.


title: Molecular Architecture of Early Dissemination and Evolution of the SARS-CoV-2 Virus in Metropolitan Houston, Texas

text: We sequenced the genomes of 320 SARS-CoV-2 strains from COVID-19 patients in metropolitan Houston, Texas, an ethnically diverse region with seven million residents. These genomes were from the viruses causing infections in the earliest recognized phase of the pandemic affecting Houston. Substantial viral genomic diversity was identified, which we interpret to mean that the virus was introduced into Houston many times independently by individuals who had traveled from different parts of the country and the world. The majority of viruses are apparent progeny of strains derived from Europe and Asia. We found no significant evidence of more virulent viral types, stressing the linkage between severe disease, underlying medical conditions, and perhaps host genetics. We discovered a signal of selection acting on the spike protein, the primary target of massive vaccine efforts worldwide. The data provide a critical resource for assessing virus evolution, the origin of new outbreaks, and the effect of host immune response. Significance COVID-19, the disease caused by the SARS-CoV-2 virus, is a global pandemic. To better understand the first phase of virus spread in metropolitan Houston, Texas, we sequenced the genomes of 320 SARS-CoV-2 strains recovered from COVID-19 patients early in the Houston viral arc. We identified no evidence that a particular strain or its progeny causes more severe disease, underscoring the connection between severe disease, underlying health conditions, and host genetics. Some amino acid replacements in the spike protein suggest positive immune selection is at work in shaping variation in this protein. Our analysis traces the early molecular architecture of SARS-CoV-2 in Houston, and will help us to understand the origin and trajectory of future infection spikes.


title: Knowledge, attitude, and perceptions towards the 2019 Coronavirus Pandemic: A bi-national survey in Africa

text: The current Coronavirus (COVID-19) pandemic has changed and impacted lives on a global scale since its emergence and spread from China in late 2019. It has caused millions of infections, and thousands of deaths worldwide. However, the control of this pandemic still remains unachievable in many African countries including Egypt and Nigeria, despite the application of some strict preventive and control measures. Therefore, this study assessed the knowledge, attitude and perceptions of Egyptians and Nigerians towards COVID-19 pandemic. A total of 1437 respondents were included in this preliminary cross-sectional survey. The mean knowledge score was 14.7 plusmn 2.3. The majority of the respondents (61.6%) had a satisfactory knowledge of the disease. Age (18-39 years), education (College/bachelors) and background of respondents were factors influencing knowledge levels. The attitude of most respondents (68.9%) towards the preventive measures was satisfactory with an average attitude score of 6.9 plusmn 1.2. The majority of the respondents (96%) practiced self-isolation and social-distancing but only 36% follow all health recommendations. The perception of most respondents (62.1%) on the global efforts at controlling the virus and preventing further spread was satisfactory with an average score of 10.9 plusmn 2.7. A satisfactory knowledge of COVID-19 was significantly associated with good attitude and perceptions (p < 0.001) of respondents. Only 22% of the respondents were satisfied with their country prime s handling of the pandemic. It is imperative that to avoid Africa being the next epicenter of the pandemic. Governments need to strengthen health systems, improve their surveillance activities in detecting cases, and effectively apply standard infection prevention and control measures.


title: Domestic violence and abuse, coronavirus, and the media narrative

text: Following lockdowns in countries around the world, reports emerged of a 'surge' or 'spikes' in the number of domestic violence and abuse cases It is critical to contextualise this: more men are not starting to be abusive or violent;rather, the patterns of abuse are becoming more frequent Spiking and surging make us think in terms of more one-off incidents but it is more likely that the pattern of abuse that is already there is increasing in terms of frequency and type because both parties remain together at all times Amid such a crisis, it is imperative that we continue to see the dynamics of domestic violence and abuse as both a pattern of abusive behaviours and a product of gendered social and cultural norms, rather than a reaction to a specific factor or event, such as COVID-19


title: Nuevo coronavirus 2019-ncov: impacto en salud global

text:
Se trata de una revisión sistemática de una selección de artículos publicados en diferentes fuentes de información, post aparición del primer caso de 2019-nCoV en China, que incluye la infor-mación disponible a febrero 2 del año 2020 sobre diferentes aspectos clínico-epidemiológicos de la epidemia
Se incluye también un análisis comparativo de la forma de transmisión, origen, mortalidad, período de incubación y el número reproductivo básico (R0) o la velocidad con que una enfermedad puede propagarse en una población, de este nuevo coronavirus (2019-nCoV), con la evidencia disponible de estos parámetros para el SARS-CoV y el MERS-CoV, al 2 de febrero del año 2020
Se concluye recomendando la creación de unidades de salud global, lo cual podría favorecer que el sistema de salud perpetúe su impacto en los indicadores de salud de entidades de mayor prevalencia y de comportamiento endémico, mientras que, dichas unidades, orienten los esfuerzos a la implementación efectiva de las medidas de contención y prevención de brotes epidémicos en puertos de entrada y puntos estratégicos de una nación en particular, así como también mejorar la interconexión con otras unidades de similar envergadura y objetivos, en un principio, a nivel regional, pero, como fin último, a nivel global


title: Predicting the second wave of COVID-19 in Washtenaw County, MI

text: Marissa Renardy and Denise Kirschner University of Michigan Medical School The COVID-19 pandemic has highlighted the patchwork nature of disease epidemics, with infection spread dynamics varying wildly across countries and across states within the US. These heteroge- neous patterns are also observed within individual states, with patches of concentrated outbreaks. Data is being generated daily at all of these spatial scales, and answers to questions regarded re- opening strategies are desperately needed. Mathematical modeling is useful in exactly these cases, and using modeling at a county scale may be valuable to further predict disease dynamics for the purposes of public health interventions. To explore this issue, we study and predict the spread of COVID-19 in Washtenaw County, MI, the home to University of Michigan, Eastern Michigan University, and Google, as well as serving as a sister city to Detroit, MI where there has been a serious outbreak. Here, we apply a discrete and stochastic network-based modeling framework allowing us to track every individual in the county. In this framework, we construct contact net- works based on synthetic population datasets specific for Washtenaw County that are derived from US Census datasets. We assign individuals to households, workplaces, schools, and group quarters (such as prisons). In addition, we assign casual contacts to each individual at random. Using this framework, we explicitly simulate Michigan-specific government-mandated workplace and school closures as well as social distancing measures. We also perform sensitivity analyses to identify key model parameters and mechanisms contributing to the observed disease burden in the three months following the first observed cases on COVID-19 in Michigan. We then consider several scenarios for relaxing restrictions and reopening workplaces to predict what actions would be most prudent. In particular, we consider the effects of 1) different timings for reopening, and 2) different levels of workplace vs. casual contact re-engagement. Through simulations and sensitivity analyses, we explore mechanisms driving magnitude and timing of a second wave of infections upon re-opening. This model can be adapted to other US counties using synthetic population databases and data specific to those regions.


title: The current state of COVID-19 in Australia: importation and spread

text: Background: The rapid global spread of coronavirus disease (COVID-19) is unprecedented. The outbreak has quickly spread to more than 100 countries reporting over 100,000 confirmed cases. Australia reported its first case of COVID-19 on 25th January 2020 and has since implemented travel restrictions to stop further introduction of the virus. Methods: We analysed daily global COVID-19 data published by the World Health Organisation to investigate the spread of the virus thus far. To assess the current risk of COVID-19 importation and local spread in Australia we predict international passenger flows into Australia during 2020. Findings: Our analysis of global data shows that Australia can expect a similar growth rate of reported cases as observed in France and the United States. We identify travel patterns of Australian citizens/residents and foreign travellers that can inform the implementation of new and the alteration of existing travel restrictions related to COVID-19. Interpretation: Our findings identify the risk reduction potential of current travel bans, based on the proportion of returning travellers to Australia that are residents or visitors. The similarity of the exponential growth in the epidemic curve in Australia to other countries guides forecasts of COVID-19 growth in Australia, and opportunities for drawing lessons from other countries with more advanced outbreaks.


title: Register

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title: Using early data to estimate the actual infection fatality ratio from COVID-19 in France

text: Background. The number of screening tests carried out in France and the methodology used to target the patients tested do not allow for a direct computation of the actual number of cases and the infection fatality ratio (IFR). The main objective was to estimate the actual number of people infected with COVID-19 during the observation window in France and to deduce the IFR. Methods. We develop a 'mechanistic-statistical' approach coupling a SIR epidemiological model describing the unobserved epidemiological dynamics, a probabilistic model describing the data acquisition process and a statistical inference method. Results. The actual number of infected cases in France is probably higher than the observations: we find here a factor x 8 (95%-CI: 5-12) which leads to an IFR in France of 0.5% (95%-CI: 0.3-0.8) based on hospital death counting data. Adjusting for the number of deaths in nursing homes, we obtain an IFR of 0.8% (95%-CI: 0.45-1.25). Conclusions. This IFR is consistent with previous findings in China (0.66%) and in the UK (0.9%) and lower than the value previously computed on the Diamond Princess cruse ship data (1.3%).


title: Rural public health systems and accountability politics: insights from grassroots health rights defenders in Guatemala

text: As the pandemic reveals how multiple intersecting inequalities affect public health, the work of rural activists defending their communities' rights to health, land, and gender, ethnic and environmental justice demonstrate how intersectional analysis can be put into practice In the interviews that follow, Guatemalan Maya Tz'utujil activists Paulina Culum and Benilda Batzin describe how 'health rights defenders' seek justice for rural indigenous communities - work that the pandemic makes more critical than ever Their strategies and insights have implications for addressing rural health rights around the world


title: Multiplex Isothermal Amplification Coupled with Nanopore Sequencing for Rapid Detection and Mutation Surveillance of SARS-CoV-2

text: Molecular testing and surveillance of the spread and mutation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are critical public health measures to combat the pandemic. There is an urgent need for methods that can rapidly detect and sequence SARS-CoV-2 simultaneously. Here we describe a method for multiplex isothermal amplification of the SARS-CoV-2 genome in 20 minutes. Based on this, we developed NIRVANA (Nanopore sequencing of Isothermal Rapid Viral Amplification for Near real-time Analysis) to detect viral sequences and monitor mutations in multiple regions of SARS-CoV-2 genome for up to 96 patients at a time. NIRVANA uses a newly developed algorithm for on-the-fly data analysis during Nanopore sequencing. The whole workflow can be completed in as short as 3.5 hours, and all reactions can be done in a simple heating block. NIRVANA provides a rapid field-deployable solution of SARS-CoV-2 detection and surveillance of pandemic strains.


title: De novo 3D models of SARS-CoV-2 RNA elements and small-molecule-binding RNAs to guide drug discovery

text: The rapid spread of COVID-19 motivates development of antivirals targeting conserved molecular machinery of the SARS-CoV-2 virus. The SARS-CoV-2 genome includes conserved RNA elements that offer potential targets for RNA-targeting small-molecule drugs, but 3D structures of most of these elements have not been experimentally characterized. Here, we provide a dataset called ‘FARFAR2-SARS-CoV-2’, a collection of 3D coordinates modeled using Rosetta’s FARFAR2 algorithm, including de novo models for thirteen RNA elements in SARS-CoV-2 and homology models for a fourteenth. These elements comprise SL1, SL2, SL3, SL4, SL5, putative SL6 and SL7 in the extended 5′ UTR, as well as the entire extended 5′ UTR; the frameshifting element (FSE) from the SARS-CoV-2 ORF1a/b gene and a putative dimer of FSE; and the extended pseudoknot, hypervariable region, and the s2m of the 3′ UTR, as well as the entire 3′ UTR. For five of these elements (SL1, SL2, SL3, FSE, s2m), convergence of lowest predicted energy structures supports their accuracy in capturing low energy states that might be targeted for small molecule binding. To aid efforts to discover small molecule RNA binders guided by computational models, we provide a second benchmarking dataset called ‘FARFAR2-Apo-Riboswitch’, which consists of similarly prepared Rosetta-FARFAR2 models for RNA riboswitch aptamer regions that bind small molecules. Both datasets include up to 400 3D models for each RNA element, which may facilitate drug discovery approaches targeting dynamic ensembles of low-energy excited states of RNA molecules.


title: A Critical Appraisal of COVID-19 in Malaysia and Beyond

text: When the first report of COVID-19 appeared in December 2019 from Wuhan, China, the world unknowingly perceived this as another flu-like illness. Many were surprised at the extreme steps that China had subsequently taken to seal Wuhan from the rest of the world. However, by February 2020, the SARS-CoV-2 virus, which causes COVID-19, had spread so quickly across the globe that the World Health Organization officially declared COVID-19 a pandemic. COVID-19 is not the first pandemic the world has seen, so what makes it so unique in Malaysia, is discussed to avoid a future coronacoma.


title: APPENDIX References Used for Figures and Tables

text: Unknown


title: Dynamics of the COVID-19 Contagion and Mortality: Country Factors, Social Media, and Market Response Evidence From a Global Panel Analysis

text: This research asks how an epidemic affects human behaviour Probably the COVID-19 contagion is the most adverse global public health, economic, social, and technological stress since the Second World War It affects almost all countries and challenges the globalisation particularly the global supply chain The research community struggles with the multidimensional consequences of the SARS-CoV-2 virus infections The critical goal is to quickly implement an efficient vaccine, as the society faces a tradeoff between death exposure and the size of the economic downturn With this paper, we search for factors affecting contagion, mortality, and the time span between the country virus inception and first death Additionally, we analyse the development of social media and financial markets We applied a panel data set on all of the countries across the globe from 31 December 2019 until 31 March 2020 to investigate the patterns of epidemic development We examined 7,642 country-daily data We constructed classification tree regression, panel, and cross-sectional regression models Our results support the conclusion that: 1) the speed of severity and contagion is different between themselves and across continents, 2) financial markets and social media respond differently to factors affecting contagion and severity, and 3) the time span between the first contagion in the economy and first death case cannot be plausibly explained with time-invariant variables This research supports the policymakers with robust data for the informative allocation of scarce resources


title: Major ongoing clinical trials for COVID-19 treatment and studies currently being conducted or scheduled in Japan

text: The outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a serious threat to global public health and economies Currently, hundreds of clinical trials on a wide variety of treatments against COVID-19 are being conducted around the world Here, we conducted a search for ongoing clinical trials for the treatment of COVID-19 at the clinicaltrials gov database on April 2, 2020 In total, 48 clinical trials were identified, and of these, 41 trials adopted drug intervention and the other 7 trials utilized biological intervention The number of trials stratified by a chief country conducting the investigation were 18 in China, 5 in the United States, 4 in Canada, 3 in Italy, 2 in France and Brazil, and 4 trials are being performed multinationally The drugs utilized in more than one trials were remdesivir (6 trials), lopinavir/ritonavir (6 trials), hydroxychloroquine (6 trials), interferon (5 trials), methylprednisolone (3 trials), nitric oxide gas (3 trials), oseltamivir (2 trials), arbidol (2 trials), and vitamin C (2 trials) We also described the Japanese trials which are now being conducted or scheduled, utilizing lopinavir/ritonavir, remdesivir, favipiravir, ciclesonide and nafamostat


title: The accelerated infectious disease risk in the Anthropocene: more outbreaks and wider global spread

text: The greatly accelerated economic growth during the Anthropocene has resulted in astonishing improvements in many aspects of human well-being, but has also caused the acceleration of risks, such as the interlinked biodiversity and climate crisis. Here, we report on another risk: the accelerated infectious disease risk associated with the number and geographic spread of human infectious disease outbreaks. Using the most complete, reliable, and up-to-date database on human infectious disease outbreaks (GIDEON), we show that the number of disease outbreaks, the number of diseases involved in these outbreaks, and the number of countries affected have increased during the entire Anthropocene. Furthermore, the spatial distribution of these outbreaks is becoming more globalized in the sense that the overall modularity of the disease networks across the globe has decreased, meaning disease outbreaks have become increasingly pandemic in their nature. This decrease in modularity is correlated with the increase in air traffic. We finally show that those countries and regions which are most central within these disease networks tend to be countries with higher GDPs. Therefore, one cost of increased global mobility and greater economic growth is the increased risk of disease outbreaks and their faster and wider spread. We briefly discuss three different scenarios which decision-makers might follow in light of our results.


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title: Prefacio

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title: Clinical features of imported cases of coronavirus disease 2019 in Tibetan patients in the Plateau area

text: Abstract Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has rapidly spread throughout China, but the clinical characteristics of Tibetan patients living in the Qinghai-Tibetan plateau are unknown. We aimed to investigate the epidemiological, clinical, laboratory and radiological characteristics of these patients. We included 67 Tibetan patients with confirmed SARS-CoV-2 infection. The patients were divided into two groups based on the presence of clinical symptoms at admission, with 31 and 36 patients in the symptomatic and asymptomatic groups, respectively. The epidemiological, clinical, laboratory and radiological characteristics were extracted and analysed. No patient had a history of exposure to COVID-19 patients from Wuhan or had travelled to Wuhan. The mean age of Tibetan patients was 39.3 years and 59% of the patients were male. Seven patients presented with fever on admission and lymphocytopenia was present in 20 patients. 47 patients had abnormal chest CTs at admission instead of stating that 20 were unchanged. Lactate dehydrogenase levels were increased in 31 patients. Seven patients progressed to severe COVID-19; however, after treatment, their condition was stable. No patients died. Of the 36 asymptomatic patients, the mean age was younger than the symptomatic group (34.4vs 44.9 years, P=0.02). Lymphocyte count and prealbumin levels were higher in the asymptomatic group than the group with clinical symptoms (1.6 vs 1.3 and 241.8 vs 191.9, respectively; P<0.05). Imported cases of COVID-19 in Tibetan patients were generally mild in this high-altitude area. Absence of fever or radiologic abnormalities on initial presentation were common


Testosterone and longevity in men and women: A Mendelian randomization study in the UK Biobank


title: Early estimation of the risk factors for hospitalisation and mortality by COVID-19 in Mexico

text: Background. With its high prevalence of chronic non-degenerative diseases, it is suspected that in Mexico there is a high risk of fatal complications from COVID-19. The present study aims to estimate the risk factors for hospitalisation and death in the Mexican population infected by SARS-CoV-2. Methods and Findings. We used the publicly available data released by the Epidemiological Surveillance System for Viral Respiratory Diseases of the Mexican Ministry of Health (Secretaria de Salud, SS). All records of positive SARS-CoV-2 cases were included. Two multiple logistic regression models were fitted to estimate the association between the hospitalisation and mortality, with other covariables. Data on 10,544 individuals (57.68% men), with mean age 46.47 SD 15.62, were analysed. Men were about 1.54 times as likely to be hospitalized than women (p<0.001, 95% C.I. 1.37-1.74); individuals aged 50-74 and >=74 years were more likely to be hospitalized than people from 25-49 years (OR 2.05, p<0.001, 95% C.I. 1.81-2.32, and OR 23.84, p<0.001, 95% C.I. 2.90-5.15, respectively). People with hypertension, obesity, and diabetes were more likely to be hospitalised than people without these morbidities (p<0.01). Men had more risk of death in comparison to women (OR=1.53, p<0.001, 95% C.I. 1.30-1.81) and individuals aged 50-74 and [≥]75 years were more likely to die than people from 25-49 years (OR 1.96, p<0.001, 95% C.I. 1.63-2.34, and OR 3.74, p<0.001, 95% C.I. 2.80-4.98, respectively). Hypertension, obesity, and diabetes presented in combination, provided a higher risk of dying in comparison to not having these diseases (OR=2.10; p<0.001, 95% C.I. 1.50-2.93). Hospitalisation, intubation and pneumonia conferred a higher risk of dying (OR 5.02, p<0.001, 95% C.I. 3.88-6.50; OR 4.27, p<0.001, 95% C.I. 3.26-5.59, and OR=2.57; p<0.001, 95% C.I. 2.11-3.13, respectively). The main limitation of our study is the lack of information on mild (asymptomatic) or moderate cases of COVID-19. Conclusions. The present study points out that in Mexico, where an important proportion of the population develops two or more chronic conditions simultaneously, high mortality is a sever outcome for those infected by SARS-CoV-2.


title: COVID-19 Epidemic Dynamics and Population Projections from Early Days of Case Reporting in a 40 million population from Southern India

text: India reported its first COVID19 case on 30 January 2020. Since then the epidemic has taken different trajectories across different geographical locations in the country. This study explores the population aggregated trajectories of COVID19 susceptible, infected and recovered or dead cases in the south Indian state of Telangana with a population of approximately 40 million. Information on cases reported from March 2 to April 4 was collated from government records. The susceptible-infected-removed (SIR) model for the spread of an infectious disease was used. Transmission parameters were extracted from existing literature that has emerged over past weeks from other regions with similar population densities as Telangana. Optimisation algorithms were used to get basic reproduction rate for different phases of nonpharmaceutical interventions rolled by the government. Peak accumulation is projected towards end of July with 36% of the population being infected by August 2020 if the population lockdown or social distancing mechanism is not continued. The number of deaths assuming no intervention is projected to be 488000 (95% CI: (329400, 646600)). A draconian enforcement of population lockdown combined with hand and face hygiene adherence would reduce the transmission by at least 99.7% whereas partial social distancing and hygiene would reduce it by 51.2%. Transmission parameters reported should be interpreted with caution as they are population aggregated and do not consider unique characteristics of susceptibility among micro-clusters and vulnerable individuals. More data will need to be collected to optimize transmission parameters and evaluate the full complexity, to simulate real world scenarios in the models.


title: Voices from the frontline: findings from a thematic analysis of a rapid online global survey of maternal and newborn health professionals facing the COVID-19 pandemic

text: Objective To prospectively document experiences of frontline maternal and newborn healthcare providers during the COVID-19 pandemic. Design Cross-sectional study via an online survey disseminated through professional networks and social media in 12 languages. We analysed responses using descriptive statistics and qualitative thematic analysis disaggregating by low- and middle-income countries (LMICs) and high-income countries (HICs). Setting 81 countries, between March 24 and April 10, 2020. Participants 714 maternal and newborn healthcare providers. Main outcome measures Preparedness for and response to COVID-19, experiences of health workers providing care to women and newborns, and adaptations to 17 outpatient and inpatient care processes during the pandemic. Results Only one third of respondents received training on COVID-19 from their health facility and nearly all searched for information themselves. Half of respondents in LMICs received updated guidelines for care provision compared with 82% in HICs. Overall, only 47% of participants in LMICs, and 69% in HICs felt mostly or completely knowledgeable in how to care for COVID-19 maternity patients. Facility-level responses to COVID-19 (signage, screening, testing, and isolation rooms) were more common in HICs than LMICs. Globally, 90% of respondents reported somewhat or substantially higher levels of stress. There was a widespread perception of reduced use of routine maternity care services, and of modification in care processes, some of which were not evidence-based. Conclusions Substantial knowledge gaps exist in guidance on management of maternity cases with or without COVID-19. Formal information sharing channels for providers must be established and mental health support provided. Surveys of maternity care providers can help track the situation, capture innovations, and support rapid development of effective responses.


title: Management of cervical cancer patients during the COVID-19 pandemic: a challenge for developing countries

text: During the COVID-19 pandemic, health services worldwide are going through important adaptations to assist patients infected with COVID-19, at the same time as continuing to provide assistance to other potentially life-threatening diseases. Although patients with cancer may be at increased risk for severe events related to COVID-19 infection, their oncologic treatments frequently cannot be delayed for long periods without jeopardising oncologic outcomes. Considering this, a careful consideration for treatment management of different malignancies is required. Cervical cancer is concentrated mainly in low-middle income countries (LMICs), which face particular challenges during the COVID-19 pandemic due to the scarcity of health resources in many places. Although cervical cancer is the fourth cause of cancer death among women, it receives little attention from international Oncology societies and scientific research studies. In this review paper, we discuss the cervical cancer landscape and provide specialists recommendations for its management during the COVID-19 pandemic, particularly focused on LMICs’ reality.


title: Buying time: an ecological survival analysis of COVID-19 spread based on the gravity model

text: COVID-19 has spread in a matter of months to most countries in the world. Various social and economic factors determine the time in which a pandemic reaches a country. This time is essential, because it allows countries to prepare their response. This study considered a gravity model that expressed time to first case as a function of multiple socio-economic factors. First, Kaplan-Meier analysis was performed for each variable in the model by dividing countries into two groups according to the median of the respective variable. In order to measure the effect of these variables, parameters of the gravity model were estimated using accelerated failure time (AFT) survival analysis. In the Kaplan-Meier analysis the differences between high and low value groups were significant for every variable except population. The AFT analysis determined that increased personal freedom had the largest effect on lowering the survival time, controlling for detection capacity. Higher GDP per capita and a larger population also reduced survival time, while a greater distance from the outbreak source increased it. Understanding the influence of factors affecting time to index case can help us understand disease spread in the early stages of a pandemic.


title: Analyses and Forecast for COVID-19 epidemic in India

text: COVID-19 is a highly infectious disease that is causing havoc to the entire world due to the newly discovered coronavirus SARS-CoV-2. In this study, the dynamics of COVID-19 for India and a few selected states with different demographic structures have been analyzed using a SEIRD epidemiological model. A systematic estimation of the basic reproductive ratio R0 is made for India and for each of the selected states. The study has analysed and predicted the dynamics of the temporal progression of the disease in Indian and the selected eight states: Andhra Pradesh, Chhattisgarh, Delhi, Gujarat, Madhya Pradesh, Maharashtra, Tamil Nadu, and Uttar Pradesh. For India, the most optimistic scenario with respect to duration of the epidemic shows, the peak of infection will appear before mid September with the estimated R0=1.917, from the SEIRD model. Further, we show, a Gaussian fit of the daily incidences also indicates the peak will appear around middle of August this year. Our analyses suggest, the earliest dates when the epidemic will start to decline in most states are between Jun-August. For India, the number of infected people at the time of peak will be around 1.6 million including asymptomatic people. If the community transmission is prohibited, then the epidemic will infect not more than 3.1 million people in India. We also compared India's position in containing the disease with two countries with higher and lower number of infections than India and show the early imposition of lockdown has reduced the number of infected cases significantly.


title: Coronavirus outbreak in Italy: Physiological benefits of home-based exercise during pandemic

text: The Coronavirus Disease 2019 (COVID-19) pandemic has forced the hardest-hit populations, like Italians, to radically change their daily habits, starting with social distancing, strict preventive measures, and self-isolation. These precautions also apply to sport-related facilities and activities. The difficulty to practice physical activity during this dramatic moment in time adds to the risks associated with sedentary habits, due to staying all the time at home. Here, the importance and the benefits of maintaining exercise routine, even at home, are emphasized in order to avoid the consequences of inactivity.


title: The Seasonal End of Human Coronavirus Hospital Admissions with Implications for SARS-CoV-2

text: The seasonality of influenza viruses and endemic human coronaviruses was tracked over an 8-year period to assess key epidemiologic reduction points in disease incidence for an urban area in the northeast United States. Patients admitted to a pediatric hospital with worsening respiratory symptoms were tested using a multiplex PCR assay from nasopharyngeal swabs. The additive seasonal effects of outdoor temperatures and indoor relative humidity (RH) were evaluated. The 8-year average peak activity of human coronaviruses occurred in the first week of January, when droplet and contact transmission was enabled by the low indoor RH of 20-30%. Previous studies have shown that an increase in RH to 50% has been associated with markedly reduced viability and transmission of influenza virus and animal coronaviruses. As disease incidence was reduced by 50% in early March, to 75% in early April, to greater than 99% at the end of April, a relationship was observed from colder temperatures in January with a low indoor RH to a gradual increase in outdoor temperatures in April with an indoor RH of 45-50%. As a lipid-bound, enveloped virus with similar size characteristics to endemic human coronaviruses, SARS-CoV-2 should be subject to the same dynamics of reduced viability and transmission with increased humidity. In addition to the major role of social distancing, the transition from lower to higher indoor RH with increasing outdoor temperatures could have an additive effect on the decrease in SARS-CoV-2 cases in May. Over the 8-year period of this study, human coronavirus activity was either zero or >99% reduction in the months of June through September, and the implication would be that SARS-Cov-2 may follow a similar pattern.


title: The role of absolute humidity on transmission rates of the COVID-19 outbreak

text: A novel coronavirus (COVID-19) was identified in Wuhan, Hubei Province, China, in December 2019 and has caused over 40,000 cases worldwide to date. Previous studies have supported an epidemiological hypothesis that cold and dry (low absolute humidity) environments facilitate the survival and spread of droplet-mediated viral diseases, and warm and humid (high absolute humidity) environments see attenuated viral transmission (i.e., influenza). However, the role of absolute humidity in transmission of COVID-19 has not yet been established. Here, we examine province-level variability of the basic reproductive numbers of COVID-19 across China and find that changes in weather alone (i.e., increase of temperature and humidity as spring and summer months arrive in the North Hemisphere) will not necessarily lead to declines in COVID-19 case counts without the implementation of extensive public health interventions.


title: Predictions, role of interventions and effects of a historic national lockdown in India's response to the COVID-19 pandemic: data science call to arms

text: Importance: India has taken strong and early public health measures for arresting the spread of the COVID-19 epidemic. With only 536 COVID-19 cases and 11 fatalities, India - a democracy of 1.34 billion people - took the historic decision of a 21-day national lockdown on March 25. The lockdown was further extended to May 3, soon after the analysis of this paper was completed. Objective: To study the short- and long-term impact of an initial 21-day lockdown on the total number of COVID-19 cases in India compared to other less severe non-pharmaceutical interventions using epidemiological forecasting models and Bayesian estimation algorithms; to compare effects of hypothetical durations of lockdown from an epidemiological perspective; to study alternative explanations for slower growth rate of the virus outbreak in India, including exploring the association of the number of cases and average monthly temperature; and finally, to outline the pivotal role of reliable and transparent data, reproducible data science methods, tools and products as we reopen the country and prepare for a post lock-down phase of the pandemic. Design, Setting, and Participants: We use the daily data on the number of COVID-19 cases, of recovered and of deaths from March 1 until April 7, 2020 from the 2019 Novel Coronavirus Visual Dashboard operated by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE). Additionally, we use COVID-19 incidence counts data from Kaggle and the monthly average temperature of major cities across the world from Wikipedia. Main Outcome and Measures: The current time-series data on daily proportions of cases and removed (recovered and death combined) from India are analyzed using an extended version of the standard SIR (susceptible, infected, and removed) model. The eSIR model incorporates time-varying transmission rates that help us predict the effect of lockdown compared to other hypothetical interventions on the number of cases at future time points. A Markov Chain Monte Carlo implementation of this model provided predicted proportions of the cases at future time points along with credible intervals (CI). Results: Our predicted cumulative number of COVID-19 cases in India on April 30 assuming a 1-week delay in people's adherence to a 21-day lockdown (March 25 - April 14) and a gradual, moderate resumption of daily activities after April 14 is 9,181 with upper 95% CI of 72,245. In comparison, the predicted cumulative number of cases under "no intervention" and "social distancing and travel bans without lockdown" are 358 thousand and 46 thousand (upper 95% CI of nearly 2.3 million and 0.3 million) respectively. An effective lockdown can prevent roughly 343 thousand (upper 95% CI 1.8 million) and 2.4 million (upper 95% CI 38.4 million) COVID-19 cases nationwide compared to social distancing alone by May 15 and June 15, respectively. When comparing a 21-day lockdown with a hypothetical lockdown of longer duration, we find that 28-, 42-, and 56-day lockdowns can approximately prevent 238 thousand (upper 95% CI 2.3 million), 622 thousand (upper 95% CI 4.3 million), 781 thousand (upper 95% CI 4.6 million) cases by June 15, respectively. We find some suggestive evidence that the COVID-19 incidence rates worldwide are negatively associated with temperature in a crude unadjusted analysis with Pearson correlation estimates [95% confidence interval] between average monthly temperature and total monthly incidence around the world being -0.185 [-0.548, 0.236] for January, -0.110 [-0.362, 0.157] for February, and -0.173 [-0.314, -0.026] for March. Conclusions and Relevance: The lockdown, if implemented correctly in the end, has a high chance of reducing the total number of COVID-19 cases in the short term, and buy India invaluable time to prepare its healthcare and disease monitoring system. Our analysis shows we need to have some measures of suppression in place after the lockdown for the best outcome. We cannot heavily rely on the hypothetical prevention governed by meteorological factors such as temperature based on current evidence. From an epidemiological perspective, a longer lockdown between 42-56 days is preferable. However, the lockdown comes at a tremendous price to social and economic health through a contagion process not dissimilar to that of the coronavirus itself. Data can play a defining role as we design post-lockdown testing, reopening and resource allocation strategies. Software: Our contribution to data science includes an interactive and dynamic app (covind19.org) with short- and long-term projections updated daily that can help inform policy and practice related to COVID-19 in India. Anyone can visualize the observed data for India and create predictions under hypothetical scenarios with quantification of uncertainties. We make our prediction codes freely available (https://github.com/umich-cphds/cov-ind-19) for reproducible science and for other COVID-19 affected countries to use them for their prediction and data visualization work.


title: Differences in power-law growth over time and indicators of COVID-19 pandemic progression worldwide

text: An automated statistical and error analysis of 45 countries or regions with more than 1000 cases of COVID-19 as of March 28, 2020, has been performed. This study reveals differences in the rate of disease spreading rate over time in different countries. This survey observes that most countries undergo a beginning exponential growth phase, which transitions into a power-law phase, as recently suggested by Ziff and Ziff. Tracking indicators of growth, such as the power-law exponent, are a good indication of the relative danger different countries are in and show when social measures are effective towards slowing the spread. The data compiled here are usefully synthesizing a global picture, identifying country to country variation in spreading, and identifying countries most at risk. This analysis may factor into how best to track the effectiveness of social distancing policies and quarantines in real-time as data is updated each day.


title: Correlation of population mortality of COVID-19 and testing coverage: a comparison among 36 OECD countries and Taiwan

text: Although testing is widely regarded as critical to fighting the Covid-19 pandemic, what measure and level of testing best reflects successful infection control remains unresolved. Our aim was to compare the sensitivity of two testing metrics--population testing number and testing coverage--to population mortality outcomes and identify a benchmark for testing adequacy with respect to population mortality and capture of potential disease burden. This ecological study aggregated publicly available data through April 12 on testing and outcomes related to COVID-19 across 36 OECD (Organization for Economic Development) countries and Taiwan. All OECD countries and Taiwan were included in this population-based study as a proxy for countries with highly developed economic and healthcare infrastructure. Spearman correlation coefficients were calculated between the aforementioned metrics and following outcome measures: deaths per 1 million people, case fatality rate, and case proportion of critical illness. Fractional polynomials were used to generate scatter plots to model the relationship between the testing metrics and outcomes. Testing coverage, but not population testing number, was highly correlated with population mortality (rs= -0.79, P=5.975e-09 vs rs =- 0.3, P=0.05) and case fatality rate (rs= -0.67, P=9.067e-06 vs rs = -0.21, P=0.20). A testing coverage threshold of 15-45 signified adequate testing: below 15, testing coverage was associated with exponentially increasing population mortality, whereas above 45, increased testing did not yield significant incremental mortality benefit. Testing coverage was better than population testing number in explaining country performance and can be used as an early and sensitive indicator of testing adequacy and disease burden. This may be particularly useful as countries consider re-opening their economies.


title: Crisis-Critical Intellectual Property: Findings from the COVID-19 Pandemic

text: Within national and international innovation systems a pandemic calls for large-scale action by many actors across sectors, to mobilise resources, developing and manufacturing Crisis-Critical Products (CC-Products) efficiently and in the huge quantities needed. Nowadays, this also includes digital innovations from complex epidemiological models, AI, to open data platforms for prevention, diagnostic and treatment. Amongst the many challenges during a pandemic, innovation and manufacturing stakeholders find themselves engaged in new relationships, and are likely to face intellectual property (IP) related challenges. This paper adopts an IP perspective on the COVID-19 pandemic to identify pandemic related IP considerations and IP challenges. The focus is on challenges related to research, development and urgent upscaling of capacity to manufacture CC-Products in the huge volumes suddenly in demand. Its purpose is to provide a structure for steering clear of IP challenges to avoid delays in fighting a pandemic. We identify 4 stakeholder groups concerned with IP challenges: (i) governments, (ii) organisations owning existing Crisis-Critical IP, described as incumbents in Crisis-Critical Sectors (CC-Sectors), (iii) manufacturing firms from other sectors normally not producing CC-Products suddenly rushing into CC-Sectors to support the manufacturing of CC-Products (new entrants), and (iv) voluntary grassroot initiatives that are formed during a pandemic. This paper discusses IP challenges related to the development and manufacturing of technologies and products for (i) prevention (of spread), (ii) diagnosis of infected patients and (iii) the development of treatments. We offer an initial discussion of potential response measures to reduce IP associated risks among industrial stakeholders during a pandemic.


Researchers are using algorithms to tackle the coronavirus test shortage: The scramble to develop new test kits that deliver faster results - [Spectral Lines]


title: When is SARS-CoV-2 in your shopping list?

text: The pandemic of coronavirus disease 2019 (COVID-19) has caused, by May 24th 2020, more than 5.3 million confirmed cases worldwide. The necessity of keeping open and accessible public commercial establishments such as supermarkets or pharmacies increases during the pandemic provided that distancing rules and crowd control are satisfied. Herein, using agent-based models, we explore the potential spread of the novel SARS-CoV-2 considering the case of a small size supermarket. For diverse distancing rules and number of simultaneous users (customers), we question flexible and limited movement policies, guiding the flow and interactions of users in place. Results indicate that a guided, limited in movement and well-organized policy combined with a distance rule of at least 1 m between users and a small number of them (15) may aid in the mitigation of potential new contagions in more than 90% compared to the usual policy of flexible movement with more users (30) which may reach up to 64% of mitigation of potential new infections under the same distancing conditions. This study may guide novel strategies for the mitigation of the current COVID-19 pandemic, at any stage, and prevention of future outbreaks of SARS-CoV-2 or related viruses.


title: Agency Insight from Portugal’s Autoridade da Concorrência

text: 2020 will be a landmark year for reasons that had not been anticipated But it is also a critical year for the implementation, by national legislators in the European Union, of the ECN+ Directive This will grant competition agencies stronger means of enforcement and will consecrate independence of enforcement decisions based on the pursuit of consumer welfare protection Another developing topic in 2020 is industrial policy in the EU and its coexistence with competition policy While the EU needs to remain pragmatic, it need not — must not, I would argue - lose its distinctive economic features


title: Anesthesia management of thoracic surgery in a patient with suspected/confirmed COVID-19: Interim Saudi Anesthesia Society guidelines

text: The Saudi Anesthesia Society (SAS) has developed interim guidelines on perioperative care of COVID-19 patients who undergo surgery and anesthesia. [1]Patients with ' suspected/confirmed' COVID-19 might be scheduled for emergency thoracic procedures either during the acute or convalescence phases of the disease. There is a demanding need to develop the SAS recommendations on the perioperative care of thoracic surgery patients during the COVID-19 outbreak. There are no relevant publications on perioperative care of thoracic surgery in COVID-19 patients. These recommendations were developed from the previous experience of management of patients during the MERS-CoV outbreak in 2012-2013 and literature available on the general airway and anesthesia care for patients with COVID-19, SARS, MERS-CoV.