title: Trends in excess cancer and cardiovascular deaths in Scotland during the COVID-19 pandemic 30 December 2019 to 20 April 2020

text: Understanding the trends in causes of death for different diseases during the current COVID-19 pandemic is important to determine whether there are excess deaths beyond what is normally expected. Using the most recent report from National Records Scotland (NRS) on 29 April 2020, we examined the percentage difference in crude numbers of deaths in 2020 compared to the average for 2015-2019 by week of death within calendar year. To determine if trends were similar, suggesting underreporting/underdiagnosed COVID-19 related deaths, we also looked at the trends in % differences for cardiovascular disease deaths. From the first 17 weeks' of data, we found a peak in excess deaths between weeks 14 of 2020, about four weeks after the first case in Scotland was detected on 1 March 2020-- but by week 17 these excesses had diminished around the time lockdown in the UK began. Similar observations were seen for cardiovascular disease-related deaths. These observations suggest that the short-term increase in excess cancer and cardiovascular deaths might be associated with undetected/unconfirmed deaths related to COVID-19. Both of these conditions make patients more susceptible to infection and lack of widespread access to testing for COVID-19 are likely to have resulted in under-estimation of COVID-19 mortality. These data further suggest that the cumulative toll of COVID-19 on mortality is likely undercounted. More detailed analysis is needed to determine if these excesses were directly or indirectly related to COVID-19. Disease specific mortality will need constant monitoring for the foreseeable future as changes occur in increasing capacity and access to testing, reporting criteria, changes to health services and different measures are implemented to control the spread of the COVID-19. Multidisciplinary, multi-institutional, national and international collaborations for complementary and population specific data analysis is required to respond and mitigate adverse effects of the COVID-19 pandemic and to inform planning for future pandemics.


title: Podcast: Beating a killer coronavirus

text: As COVID-19 continues to spread, so does the effort to find treatment and vaccinations against SARS-CoV-2, the coronavirus that causes the disease Around the world, scientists are working nonstop on therapies they hope will stem the loss of life during this pandemic while trying to set us up to prevent future outbreaks What’s not clear is which of these treatments will work Much about SARS-CoV-2 remains unknown In this episode of Stereo Chemistry, we dig into the efforts to beat the novel coronavirus and why in some cases it’s like throwing spaghetti against the wall to see what sticks Learn more at http://cenm ag/coronapodcast


title: In Vitro Efficacy of Povidone-Iodine Nasal And Oral Antiseptic Preparations Against Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2)

text: Introduction:Improved antisepsis of human and non-human surfaces has been identified as a key feature of transmission reduction. There are no previous studies of povidone-iodine (PVP-I) against SARS-CoV-2. This study evaluated nasal and oral antiseptic formulations of povidone-iodine (PVP-I) for virucidal activity against SARS-CoV-2. This is the first report on the efficacy of PVP-I against the virus that causes COVID-19. Methods: PVP-I nasal antiseptic formulations and PVP-I oral rinse antiseptic formulations from 1-5% concentrations as well as controls were studied for virucidal efficacy against the SARS-CoV-2 virus. Test compounds were evaluated for ability to inactivate SARS-CoV-2 as measured in a virucidal assay. SARS-CoV-2 was exposed directly to the test compound for 60 seconds, compounds were then neutralized and surviving virus was quantified. Results: All concentrations of nasal antiseptics and oral rinse antiseptics evaluated completely inactivated the SARS-CoV-2 virus. Conclusions: Nasal and oral PVP-I antiseptic solutions are effective at inactivating the SARS-CoV-2 virus at a variety of concentrations after 60s exposure times. The formulations tested may help to reduce the transmission of SARS-CoV-2 if used for nasal decontamination, oral decontamination or surface decontamination in known or suspected cases of COVID-19.


title: Age Matters: COVID-19 Prevalence in a Vaping Adolescent Population - An Observational Study

text: Background: Currently, there is limited or no data demonstrating that vaping is associated with increased transmission or prevalence of coronavirus disease-2019 (COVID-19). Our study aims to investigate the relationship of vaping with the prevalence of COVID-19 infection across the United States and in the District of Columbia. Methods: COVID-19 case counts by state and the District of Columbia were obtained via the Worldometers website on 04/30/2020. Prevalence of COVID-19 cases per 100,000 residents were calculated using estimated 2019 population data from the US Census Department. Age ranges analyzed were: high school age children, Ages 18-24, Ages 25-44, and Ages 45-65. Spearman correlation analysis was conducted to determine if the rate of vaping was correlated with a higher prevalence of COVID-19 cases per 100,000 population. Findings: The Spearman correlation analysis demonstrated that persons vaping between 18 years and 24 years of age had a correlation coefficient of 0.278 with prevalence of COVID-19 infection (p=0.048). Vaping high school students had a correlation coefficient of 0.153 with prevalence of COVID-19 (p=0.328). Persons vaping in the age group 25-45 years had a correlation coefficient of 0.101 in association to COVID-19 prevalence (p=0.478). And finally, persons vaping between the age 45-65 years old had a correlation coefficient 0.130 with respect to COVID-19 prevalence (p=0.364). Interpretation: Increased COVID-19 prevalence is associated with vaping in the adolescent population between ages 18 and 24. Further prospective studies need to be performed in order investigate the severity of outcomes of vaping in association with COVID-19 infection. Funding: Nothing to disclose.


title: Stepping out of lockdown should start with school re-openings while maintaining distancing measures. Insights from mixing matrices and mathematical models.

text: Australia is one of a few countries which has managed to control COVID-19 epidemic before a major epidemic took place. Currently with just under 7000 cases and 100 deaths, Australia is seeing less than 20 new cases per day. This is a positive outcome, but makes estimation of current effective reproduction numbers difficult to estimate. Australia, like much of the world is poised to step out of lockdown and looking at which measures to relax first. We use age-based contact matrices, calibrated to Chinese data on reproduction numbers and difference in infectiousness and susceptibility of children to generate next generation matrices (NGMs) for Australia. These matrices have a spectral radius of 2.49, which is hence our estimated basic reproduction number for Australia. The effective reproduction number (Reff) for Australia during the April/May lockdown period is estimated by other means to be around 0.8. We simulate the impact of lockdown on the NGM by first applying observations through Google Mobility Report for Australia at 3 locations: home (increased contacts by 18%), work (reduced contacts by 34%) and other (reduced contacts by 40%), and we reduce schools to 3% reflecting attendance rates during lockdown. Applying macro-distancing to the NGM leads to a spectral radius of 1.76. We estimate that the further reduction of the reproduction number to current levels of Reff = 0.8 is achieved by a micro-distancing factor of 0.26. That is, in a given location, people are 26% as likely as usual to have an effective contact with another person. We apply both macro and micro-distancing to the NGMs to examine the impact of different exit strategies. We find that reopening schools is estimated to reduce Reff from 0.8 to 0.78. This is because increase in school contact is offset by decrease in home contact. The NGMs all estimate that adults aged 30-50 are responsible for the majority of transmission. We also find that micro-distancing is critically important to maintain Reff <1. There is considerable uncertainty in these estimates and a sensitivity and uncertainty analysis is presented.


title: Use of Corticosteroids in Coronavirus Disease 2019 Pneumonia: A Systematic Review of the Literature

text: The aim was to investigate the effectiveness of glucocorticoid therapy in patients with COVID-19. A systematic search of the literature across nine databases was conducted from inception until 15th March 2020, following the PRISMA guidelines. Patients with a validated diagnosis of COVID-19 and using corticosteroids were included, considering all health outcomes. Four studies with 542 Chinese participants were included. Two studies reported negative findings regarding the use of corticosteroids in patients with COVID-19, i.e., corticosteroids had a detrimental impact on clinical outcomes. One study reported no significant association between the use of corticosteroids and clinical outcomes. However, one study, on 201 participants with different stages of pneumonia due to COVID-19, found that in more severe forms, the administration of methylprednisolone significantly reduced the risk of death by 62%. The literature to date does not fully support the routine use of corticosteroids in COVID-19, but some findings suggest that methylprednisolone could lower mortality rate in more severe forms of the condition.


title: The Covid-19 epidemic in the UK

text: In this note we present some stylised facts about the Covid-19 epidemic in the UK using daily time-series data published by Public Health England and the UK Department of Health and Social Care. We model the data on confirmed new cases using standard count-data models estimated at the country and national levels using a fixed rolling window to capture changes in the model parameters over time. We then use the most recent estimated models to carry out a simple real-time forecasting exercise aimed at predicting the date when the number of confirmed new cases will be approximately zero.


title: Modeling the Stability of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) on Skin, Currency, and Clothing

text: A new coronavirus (SARS-CoV-2) emerged in the winter of 2019 in Wuhan, China, and rapidly spread around the world. The extent and efficiency of SARS-CoV-2 pandemic is far greater than previous coronaviruses that emerged in the 21st Century. Here, we modeled stability of SARS-CoV-2 on skin, paper currency, and clothing to determine if these surfaces may factor in the fomite transmission dynamics of SARS-CoV-2. Skin, currency, and clothing samples were exposed to SARS-CoV-2 under laboratory conditions and incubated at three different temperatures (4C, 22C, and 37C). Stability was evaluated at 0 hours (h), 4 h, 8 h, 24 h, 72 h, 96 h, 7 days, and 14 days post-exposure. SARS-CoV-2 was shown to be stable on skin through the duration of the experiment at 4C (14 days). Virus remained stable on skin for at least 96 h at 22C and for at least 8h at 37C. There were minimal differences between the tested currency samples. The virus remained stable on the $1 U.S.A. Bank Note for at least 96 h at 4C while viable virus was not detected on the $20 U.S.A. Bank Note samples beyond 72 h. The virus remained stable on both Bank Notes for at least 8 h at 22C and 4 h at 37C. Clothing samples were similar in stability to the currency with the virus being detected for at least 96 h at 4C and at least 4 h at 22C. No viable virus was detected on clothing samples at 37C after initial exposure. This study confirms the inverse relationship between virus stability and temperature. Furthermore, virus stability on skin demonstrates the need for continued hand hygiene practices to minimize fomite transmission both in the general population as well as workplaces where close contact is common.


title: Quantifying Effects, Forecasting Releases, and Herd Immunity of the Covid-19 Epidemic in S. Paulo, Brazil

text: A simple and well known epidemiological deterministic model was selected to estimate the main results for the basic dynamics of the Covid-19 epidemic breakout in the city of S. Paulo, Brazil. The methodology employed the SEIR Model to characterize the epidemics outbreak and future outcomes. A time-dependent incidence weight on the SEIR reproductive basic number accounts for local Mitigation Policies (MP). The insights gained from analysis of these successful interventions were used to quantify shifts and reductions on active cases, casualties, and estimatives on required medical facilities (ITU). This knowledge can be applied to other Brazilian areas. The analysis was applied to forecast the consequences of releasing the MP over specific periods of time. Herd Immunity (HI) analysis allowed estimating how far we are from reaching the HI threshold value, and the price to be paid.


title: Multimorbidity, Polypharmacy, and COVID-19 infection within the UK Biobank cohort.

text: BACKGROUND: It is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on the influence of multimorbidity ([≥]2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors. METHODS AND FINDINGS: We studied data from UK Biobank (428,199 participants; aged 37-73; recruited 2006-2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96-1.30)), whereas those with [≥]2 LTCs had 48% higher risk; RR 1.48 (1.28-1.71). Compared with no cardiometabolic LTCs, having 1 and [≥]2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12-1.46) and 1.77 (1.46-2.15), respectively. Polypharmacy was associated with a dose response increased risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI [≥]40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09-3.78); 2.79 (2.00-3.90); 2.66 (1.88-3.76); 2.13 (1.46-3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population. CONCLUSIONS: Increasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19.


title: Restarting after COVID-19: A Data-driven Evaluation of Opening Scenarios

text: To contain the COVID-19 pandemic, several governments introduced strict Non-Pharmaceutical Interventions (NPI) that restricted movement, public gatherings, national and international travel, and shut down large parts of the economy. Yet, the impact of the enforcement and subsequent loosening of these policies on the spread of COVID-19 is not well understood. Accordingly, we measure the impact of NPI on mitigating disease spread by exploiting the spatio-temporal variations in policy measures across the 16 states of Germany. This quasi-experiment identifies each policy's effect on reducing disease spread. We adapt the SEIR (Susceptible-Exposed-Infected-Recovered) model for disease propagation to include data on daily confirmed cases, intra- and inter-state movement, and social distancing. By combining the model with measures of policy contributions on mobility reduction, we forecast scenarios for relaxing various types of NPIs. Our model finds that, in Germany, policies that mandated contact restrictions (e.g., movement in public space limited to two persons or people co-living), initial business closures (e.g., restaurant closures), stay-at-home orders (e.g., prohibition of non-essential trips), non-essential services (e.g., florists, museums) and retail outlet closures led to the sharpest drops in movement within and across states. Contact restrictions were the most effective at lowering infection rates, while border closures had only minimal effects at mitigating the spread of the disease, even though cross-border travel might have played a role in seeding the disease in the population. We believe that a deeper understanding of the policy effects on mitigating the spread of COVID-19 allows a more accurate forecast of the disease spread when NPIs are (partially) loosened, and thus also better informs policymakers towards making appropriate decisions.


title: Changes in non-linear and time-domain heart rate variability indices between critically ill COVID-19 and all-cause sepsis patients -a retrospective study

text: Objective: To measure heart rate variability metrics in critically ill COVID-19 patients with comparison to all-cause critically ill sepsis patients. Design and patients: Retrospective analysis of COVID-19 patients admitted to an ICU for at least 24h at any of Emory Healthcare ICUs between March and April 2020. The comparison group was a cohort of all-cause sepsis patients prior to COVID-19 pandemic. Interventions: none. Measurements: Continuous waveforms were captured from the patient monitor. The EKG was then analyzed for each patient over a 300 second (s) observational window, that was shifted by 30s in each iteration from admission till discharge. A total of 23 HRV metrics were extracted in each iteration. We use the Kruskal-Wallis and Steel-Dwass tests (p < 0.05) for statistical analysis and interpretations of HRV multiple measures. Results: A total of 141 critically-ill COVID-19 patients met inclusion criteria, who were compared to 208 patients with all-cause sepsis. Demographic parameters were similar apart from a high proportion of African-Americans in the COVID-19 cohort. Three non-linear markers, including SD1:SD2, sample entropy, approximate entropy and four linear features mode of Beat-to-Beat interval (NN), Acceleration Capacity (AC), Deceleration Capacity (DC), and pNN50, were statistical significance between more than one binary combinations of the sub-groups (comparing survivors and non-survivors in both the COVID-19 and sepsis cohorts). The three nonlinear features and AC, DC, and NN (mode) were statistically significant across all four combinations. Temporal analysis of the main markers showed low variability across the 5 days of analysis, compared with sepsis patients. Conclusions: Heart rate variability is broadly implicated across patients infected with SARS-CoV-2, and admitted to the ICU for critical illness. Comparing these metrics to patients with all-cause sepsis suggests a unique set of expressions that differentiate this viral phenotype. This finding could be investigated further as a potential biomarker to predict poor outcome in this patient population, and could also be a starting point to measure potential autonomic dysfunction in COVID-19.


title: Significant non-existence of sequences in genomes and proteomes

text: Nullomers are minimal-length oligomers absent from a genome or proteome. Although research has shown that artificially synthesized nullomers have deleterious effects, there is still a lack of a strategy for the prioritisation and classification of non-occurring sequences as potentially malicious or benign. In this work, by using Markovian models with multiple-testing correction, we reveal significant absent oligomers which are statistically expected to exist. This strongly suggests that their absence is due to negative selection. We survey genomes and proteomes covering the diversity of life, and find thousands of significant absent sequences. Common significant nullomers are often mono- or dinucleotide tracts, or palindromic. Significant viral nullomers are often restriction sites, and may indicate unknown restriction motifs. Surprisingly, significant mammal genome nullomers are often present, but rare, in other mammals, suggesting that they are suppressed but not completely forbidden. Significant human nullomers are rarely present in human viruses, indicating viral mimicry of the host. More than 1/4 of human proteins are one substitution away from containing a significant nullomer. We provide a web-based, interactive database of significant nullomers across genomes and proteomes.


title: The work of culture and C-19

text: This article offers some initial commentary on the cultural impacts of COVID-19. It first considers how the pandemic might already have shifted the focus - or challenged our capacities - for cultural studies scholarship. However, the article is more centrally concerned with how measures designed to combat COVID-19 have begun to transform patterns of cultural consumption, production and work. The article considers the current status of cultural workers, in the midst of (yet further) crisis, and poses questions of what might culture be or become, in and beyond the current state of emergency.


title: Real-Time Radar-Based Gesture Detection and Recognition Built in an Edge-Computing Platform

text: In this paper, a real-time signal processing frame-work based on a 60 GHz frequency-modulated continuous wave (FMCW) radar system to recognize gestures is proposed. In order to improve the robustness of the radar-based gesture recognition system, the proposed framework extracts a comprehensive hand profile, including range, Doppler, azimuth and elevation, over multiple measurement-cycles and encodes them into a feature cube. Rather than feeding the range-Doppler spectrum sequence into a deep convolutional neural network (CNN) connected with recurrent neural networks, the proposed framework takes the aforementioned feature cube as input of a shallow CNN for gesture recognition to reduce the computational complexity. In addition, we develop a hand activity detection (HAD) algorithm to automatize the detection of gestures in real-time case. The proposed HAD can capture the time-stamp at which a gesture finishes and feeds the hand profile of all the relevant measurement-cycles before this time-stamp into the CNN with low latency. Since the proposed framework is able to detect and classify gestures at limited computational cost, it could be deployed in an edge-computing platform for real-time applications, whose performance is notedly inferior to a state-of-the-art personal computer. The experimental results show that the proposed framework has the capability of classifying 12 gestures in real-time with a high F1-score.


title: Exit strategies: optimising feasible surveillance for detection, elimination and ongoing prevention of COVID-19 community transmission

text: Background Following successful implementation of strong containment measures by the community, Australia is now close to the point of eliminating detectable community transmission of COVID-19. We aimed to develop an efficient, rapid and scalable surveillance strategy for detecting all remaining COVID-19 community transmission through exhaustive identification of every active transmission chain. We also identified measures to enable early detection and effective management of any reintroduction of transmission once containment measures are lifted to ensure strong containment measures do not need to be reinstated. Methods We compared efficiency and sensitivity to detect community transmission chains through testing of: hospital cases; primary care fever and cough patients; or asymptomatic community members, using surveillance evaluation methods and mathematical modelling, varying testing capacities and prevalence of COVID-19 and non-COVID-19 fever and cough, and the reproduction number. System requirements for increasing testing to allow exhaustive identification of all transmission chains, and then enable complete follow-up of all cases and contacts within each chain, were assessed per million population. Findings Assuming 20% of cases are asymptomatic and all symptomatic COVID-19 cases present to primary care, with high transmission (R=2.2) there are a median of 13 unrecognised community cases (5 infectious) when a transmission chain is identified through hospital surveillance versus 3 unrecognised cases (1 infectious) through primary care surveillance. 3 unrecognised community upstream community cases themselves are estimated to generate a further 22-33 contacts requiring follow-up. The unrecognised community cases rise to 5 if only 50% of symptomatic cases present to primary care. Screening for asymptomatic disease in the community cannot exhaustively identify all transmission under any of the scenarios assessed. The additional capacity required to screen all fever and cough primary care patients would be approximately 2,000 tests/million population per week using 1/16 pooling of samples. Interpretation Screening all syndromic fever and cough primary care presentations, in combination with exhaustive and meticulous case and contact identification and management, enables appropriate early detection and elimination of community transmission of COVID-19. If testing capacity is limited, interventions such as pooling allow increased case detection, even given reduced test sensitivity. Wider identification and testing of all upstream contacts, (i.e. potential sources of infection for identified cases, and their related transmission chains) is critical, and to be done exhaustively requires more resources than downstream contact tracing. The most important factor in determining the performance of such a surveillance system is community participation in screening and follow up, and as such, appropriate community engagement, messaging and support to encourage presentation and compliance is essential. We provide operational guidance on implementing such a system.


How can the COVID-19 response advance global mental health?


title: A Multi-hospital Study in Wuhan, China：Protective Effects of Non-menopause and Female Hormones on SARS-CoV-2 infection

text: Objective To determine the correlation between menstruation status/sex hormones and prognosis of COVID-19, and to identify potential protective factors for female patients. Design, Setting, and Participants A cross-sectional study of COVID-19 patients who were hospitalized at Tongji and Mobile Cabin Hospitals from Jan 28, 2020 to March 8, 2020. Sex differences in severity and composite endpoints (admission to intensive care unit (ICU), use of mechanical ventilation, or death) of COVID-19 patients were compared. The correlation analysis and cox/logistic regression modeling of menstruation status/sex hormones and prognosis were conducted. Correlation between cytokines related to immunity and inflammation and disease severity or estradiol (E2) was revealed.Results Chi square test indicated significant differences in distribution of composite endpoints (p<0.01) and disease severity (p=0.05) between male and female patients (n=1902). 435 female COVID-19 patients with menstruation records were recruited. By the end of Mar 8, 111 patients recovered and discharged (25.3%). Multivariate Cox regression model adjusted for age and severity indicated that post-menopausal patients show the greater risk of hospitalization time than non-menopausal patients (relative hazard [RH], 1.91; 95% confidence interval [CI], 1.06-3.46)Logistic regression model showed that higher AMH as a control for age increases the risk of severity of COVID-19 (HR=0.146, 95%CI= (0.026-0.824) p=0.029). E2 showed protective effect against disease severity (HR=0.335, 95%CI= (0.105-1.070), p=0.046).In the Mann-Whitney U test, the higher levels of IL6 and IL8 were found in severe group (p=0.040, 0.033).The higher levels of IL2R, IL6, IL8 and IL10 were also observed in patients with composite end points(p＜0.001,＜0.001, =0.009, = 0.040).E2 levels were negatively correlated with IL2R, IL6, IL8 and TNFα in luteal phase (Pearson Correlation=-0.592, -0.558, -0.545, -0.623; p=0.033, 0.048, 0.054, 0.023) and with C3 in follicular phase (Pearson Correlation=-0.651; p=0.030). Conclusions and Relevance Menopause is an independent risk factor for COVID-19. E2 and AMH are negatively correlated with COVID-19 severity probably due to their regulation of cytokines related to immunity and inflammation.


title: SARS-CoV-2 infection does not significantly cause acute renal injury: an analysis of 116 hospitalized patients with COVID-19 in a single hospital, Wuhan, China

text: Summary Background Whether the patients with COVID-19 infected by SARS-CoV-2 would commonly develop acute renal function damage is a problem worthy of clinical attention. This study aimed to explore the effects of SARS-CoV-2 infection on renal function through analyzing the clinical data of 116 hospitalized COVID-19-confirmed patients. Methods 116 hospitalized COVID-19-confirmed patients enrolled in this study were hospitalized in the Department of Infectious Diseases, Renmin Hospital of Wuhan University from January 14 to February 13, 2020. The recorded information includes demographic data, medical history, contact history, potential comorbidities, symptoms, signs, laboratory test results, chest computer tomography (CT) scans, and treatment measures. SARS-CoV-2 RNA in 53 urine sediments of enrolled patients was examined by real-time RT-PCR. Findings 12 (10.8%) and 8 (7.2%) patients showed mild elevation of blood urea nitrogen or creatinine, and trace or 1+ albuminuria respectively in 111 COVID-19-confirmed patients without basic kidney disease. In addition, 5 patients with chronic renal failure (CRF) were undergone regular continuous renal replacement therapy (CRRT) were confirmed infection of SARS-CoV-2, and diagnosed as COVID-19. Beside the treatment of COVID-19, CRRT was also applied three times weekly. The course of treatment, the renal function indicators showed stable, without exacerbation of CRF, and pulmonary inflammation was gradually absorbed. All 5 patients with CRF were survived. Moreover, SARS-CoV-2 RNA in urine sediments was positive only in 3 patients from 48 cases without renal illness before, and one patient had a positive for SARS-CoV-2 ORF 1ab from 5 cases with CRF. Interpretation Acute renal impairment was uncommon in COVID-19. SARS-CoV-2 infection does not significantly cause obvious acute renal injury, or aggravate CRF in the COVID-19 patients.


title: Quantifying the effect of quarantine control in Covid-19 infectious spread using machine learning

text: Since the first recording of what we now call Covid-19 infection in Wuhan, Hubei province, China on Dec 31, 2019, the disease has spread worldwide and met with a wide variety of social distancing and quarantine policies. The effectiveness of these responses is notoriously difficult to quantify as individuals travel, violate policies deliberately or inadvertently, and infect others without themselves being detected. Moreover, the publicly available data on infection rates are themselves unreliable due to limited testing and even possibly under-reporting. In this paper, we attempt to interpret and extrapolate from publicly available data using a mixed first-principles epidemiological equations and data-driven neural network model. Leveraging our neural network augmented model, we focus our analysis on four locales: Wuhan, Italy, South Korea and the United States of America, and compare the role played by the quarantine and isolation measures in each of these countries in controlling the effective reproduction number Rt of the virus. Our results unequivocally indicate that the countries in which rapid government interventions and strict public health measures for quarantine and isolation were implemented were successful in halting the spread of infection and prevent it from exploding exponentially. In the case of Wuhan especially, where the available data were earliest available, we have been able to test the predicting ability of our model by training it from data in the January 24 till March 3 window, and then matching the predictions up to April 1. Even for Italy and South Korea, we have a buffer window of one week (25 March - 1 April) to validate the predictions of our model. In the case of the US, our model captures well the current infected curve growth and predicts a halting of infection spread by 20 April 2020. We further demonstrate that relaxing or reversing quarantine measures right now will lead to an exponential explosion in the infected case count, thus nullifying the role played by all measures implemented in the US since mid March 2020.


Undetected cases


title: More than just smell - COVID-19 is associated with severe impairment of smell, taste, and chemesthesis

text: Recent anecdotal and scientific reports have provided evidence of a link between COVID-19 and chemosensory impairments such as anosmia. However, these reports have downplayed or failed to distinguish potential effects on taste, ignored chemesthesis, generally lacked quantitative measurements, and were mostly restricted to data from single countries. Here, we report the development, implementation and initial results of a multi-lingual, international questionnaire to assess self-reported quantity and quality of perception in three distinct chemosensory modalities (smell, taste, and chemesthesis) before and during COVID-19. In the first 11 days after questionnaire launch, 4039 participants (2913 women, 1118 men, 8 other, ages 19-79) reported a COVID-19 diagnosis either via laboratory tests or clinical assessment. Importantly, smell, taste and chemesthetic function were each significantly reduced compared to their status before the disease. Difference scores (maximum possible change {+/-}100) revealed a mean reduction of smell (-79.7{+/-}28.7, mean{+/-}SD), taste (-69.0{+/-}32.6), and chemesthetic (-37.3{+/-}36.2) function during COVID-19. Qualitative changes in olfactory ability (parosmia and phantosmia) were relatively rare and correlated with smell loss. Importantly, perceived nasal obstruction did not account for smell loss. Furthermore, chemosensory impairments were similar between participants in the laboratory test and clinical assessment groups. These results show that COVID-19-associated chemosensory impairment is not limited to smell, but also affects taste and chemesthesis. The multimodal impact of COVID-19 and lack of perceived nasal obstruction suggest that SARS-CoV-2 infection may disrupt sensory-neural mechanisms.


title: The Nucleocapsid Protein of SARS-CoV-2 Abolished Pluripotency in Human Induced Pluripotent Stem Cells

text: The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is raging across the world, leading to a global mortality rate of 3.4% (estimated by World Health Organization in March 2020). As a potential vaccine and therapeutic target, the nucleocapsid protein of SARS-CoV-2 (nCoVN) functions in packaging the viral genome and viral self-assembly. To investigate the biological effects of nCoVN to human stem cells, genetically engineered human induced pluripotent stem cells (iPSC) expressing nCoVN (iPSC-nCoVN) were generated by lentiviral expression systems, in which the expression of nCoVN could be induced by the doxycycline. The proliferation rate of iPSC-nCoVN was decreased. Unexpectedly, the morphology of iPSC started to change after nCoVN expression for 7 days. The pluripotency marker TRA-1-81 were not detectable in iPSC-nCoVN after a four-day induction. Meanwhile, iPSC-nCoVN lost the ability for differentiation into cardiomyocytes with a routine differentiation protocol. The RNA-seq data of iPSC-nCoVN (induction for 30 days) and immunofluorescence assays illustrated that iPSC-nCoVN were turning to fibroblast-like cells. Our data suggested that nCoVN disrupted the pluripotent properties of iPSC and turned them into other types of cells, which provided a new insight to the pathogenic mechanism of SARS-CoV-2.


title: Visual analytics for networked-guarantee loans risk management

text: Groups of enterprises guarantee each other and form complex guarantee networks when they try to obtain loans from banks. Such secured loan can enhance the solvency and promote the rapid growth in the economic upturn period. However, potential systemic risk may happen within the risk binding community. Especially, during the economic down period, the crisis may spread in the guarantee network like a domino. Monitoring the financial status, preventing or reducing systematic risk when crisis happens is highly concerned by the regulatory commission and banks. We propose visual analytics approach for loan guarantee network risk management, and consolidate the five analysis tasks with financial experts: i) visual analytics for enterprises default risk, whereby a hybrid representation is devised to predict the default risk and developed an interface to visualize key indicators; ii) visual analytics for high default groups, whereby a community detection based interactive approach is presented; iii) visual analytics for high defaults pattern, whereby a motif detection based interactive approach is described, and we adopt a Shneiderman Mantra strategy to reduce the computation complexity. iv) visual analytics for evolving guarantee network, whereby animation is used to help understanding the guarantee dynamic; v) visual analytics approach and interface for default diffusion path. The temporal diffusion path analysis can be useful for the government and bank to monitor the default spread status. It also provides insight for taking precautionary measures to prevent and dissolve systemic financial risk. We implement the system with case studies on a real-world guarantee network. Two financial experts are consulted with endorsement on the developed tool. To the best of our knowledge, this is the first visual analytics tool to explore the guarantee network risks in a systematic manner.


title: Impact of self-imposed prevention measures and short-term government intervention on mitigating and delaying a COVID-19 epidemic

text: Background: With new cases of COVID-19 surging around the world, many countries have to prepare for moving beyond the containment phase. Prediction of the effectiveness of non-case-based interventions for mitigating, delaying or preventing the epidemic is urgent, especially for countries affected by the ongoing seasonal influenza activity. Methods: We developed a transmission model to evaluate the impact of self-imposed prevention measures (handwashing, mask-wearing, and social distancing) due to the spread of COVID-19 awareness and of short-term government-imposed social distancing on the peak number of diagnoses, attack rate and time until the peak number of diagnoses. Findings: For fast awareness spread in the population, self-imposed measures can significantly reduce the attack rate, diminish and postpone the peak number of diagnoses. A large epidemic can be prevented if the efficacy of these measures exceeds 50%. For slow awareness spread, self-imposed measures reduce the peak number of diagnoses and attack rate but do not affect the timing of the peak. Early implementation of short-term government interventions can only delay the peak (by at most 7 months for a 3-month intervention). Interpretation: Handwashing, mask-wearing and social distancing as a reaction to information dissemination about COVID-19 can be effective strategies to mitigate and delay the epidemic. We stress the importance of rapidly spreading awareness on the use of these self-imposed prevention measures in the population. Early-initiated short-term government-imposed social distancing can buy time for healthcare systems to prepare for an increasing COVID-19 burden. Keywords: SARS-CoV-2, COVID-19, mathematical model, prevention measures, mitigation, epidemic control, disease awareness, social distancing, handwashing, mask-wearing


title: Effect of Hydroxychloroquine in Hospitalized Patients with COVID-19: Preliminary results from a multi-centre, randomized, controlled trial.

text: Background: Hydroxychloroquine and chloroquine have been proposed as treatments for coronavirus disease 2019 (COVID-19) on the basis of in vitro activity, uncontrolled data, and small randomized studies. Methods: The Randomised Evaluation of COVID-19 therapy (RECOVERY) trial is a randomized, controlled, open-label, platform trial comparing a range of possible treatments with usual care in patients hospitalized with COVID-19. We report the preliminary results for the comparison of hydroxychloroquine vs. usual care alone. The primary outcome was 28-day mortality. Results: 1561 patients randomly allocated to receive hydroxychloroquine were compared with 3155 patients concurrently allocated to usual care. Overall, 418 (26.8%) patients allocated hydroxychloroquine and 788 (25.0%) patients allocated usual care died within 28 days (rate ratio 1.09; 95% confidence interval [CI] 0.96 to 1.23; P=0.18). Consistent results were seen in all pre-specified subgroups of patients. Patients allocated to hydroxychloroquine were less likely to be discharged from hospital alive within 28 days (60.3% vs. 62.8%; rate ratio 0.92; 95% CI 0.85-0.99) and those not on invasive mechanical ventilation at baseline were more likely to reach the composite endpoint of invasive mechanical ventilation or death (29.8% vs. 26.5%; risk ratio 1.12; 95% CI 1.01-1.25). There was no excess of new major cardiac arrhythmia. Conclusions: In patients hospitalized with COVID-19, hydroxychloroquine was not associated with reductions in 28-day mortality but was associated with an increased length of hospital stay and increased risk of progressing to invasive mechanical ventilation or death.


title: Features of 16,749 hospitalised UK patients with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol

text: Objective: To characterize the clinical features of patients with severe COVID-19 in the UK. Design: Prospective observational cohort study with rapid data gathering and near real-time analysis, using a pre-approved questionnaire adopted by the WHO. Setting: 166 UK hospitals between 6th February and 18th April 2020. Participants: 16,749 people with COVID-19. Interventions: No interventions were performed, but with consent samples were taken for research purposes. Many participants were co-enrolled in other interventional studies and clinical trials. Results: The median age was 72 years [IQR 57, 82; range 0, 104], the median duration of symptoms before admission was 4 days [IQR 1,8] and the median duration of hospital stay was 7 days [IQR 4,12]. The commonest comorbidities were chronic cardiac disease (29%), uncomplicated diabetes (19%), non-asthmatic chronic pulmonary disease (19%) and asthma (14%); 47% had no documented reported comorbidity. Increased age and comorbidities including obesity were associated with a higher probability of mortality. Distinct clusters of symptoms were found: 1. respiratory (cough, sputum, sore throat, runny nose, ear pain, wheeze, and chest pain); 2. systemic (myalgia, joint pain and fatigue); 3. enteric (abdominal pain, vomiting and diarrhoea). Overall, 49% of patients were discharged alive, 33% have died and 17% continued to receive care at date of reporting. 17% required admission to High Dependency or Intensive Care Units; of these, 31% were discharged alive, 45% died and 24% continued to receive care at the reporting date. Of those receiving mechanical ventilation, 20% were discharged alive, 53% died and 27% remained in hospital. Conclusions: We present the largest detailed description of COVID-19 in Europe, demonstrating the importance of pandemic preparedness and the need to maintain readiness to launch research studies in response to outbreaks. Trial documentation: Available at https://isaric4c.net/protocols . Ethical approval in England and Wales (13/SC/0149), and Scotland (20/SS/0028). ISRCTN (pending).


title: An Interpretable Machine Learning Framework for Accurate Severe vs Non-severe COVID-19 Clinical Type Classification

text: Effectively and efficiently diagnosing COVID-19 patients with accurate clinical type is essential to achieve optimal outcomes of the patients as well as reducing the risk of overloading the healthcare system. Currently, severe and non-severe COVID-19 types are differentiated by only a few clinical features, which do not comprehensively characterize complicated pathological, physiological, and immunological responses to SARS-CoV-2 invasion in different types. In this study, we recruited 214 confirmed COVID-19 patients in non-severe and 148 in severe type, from Wuhan, China. The patients' comorbidity and symptoms (26 features), and blood biochemistry (26 features) upon admission were acquired as two input modalities. Exploratory analyses demonstrated that these features differed substantially between two clinical types. Machine learning random forest (RF) models using features in each modality were developed and validated to classify COVID-19 clinical types. Using comorbidity/symptom and biochemistry as input independently, RF models achieved >90% and >95% predictive accuracy, respectively. Input features' importance based on Gini impurity were further evaluated and top five features from each modality were identified (age, hypertension, cardiovascular disease, gender, diabetes; D-Dimer, hsTNI, neutrophil, IL-6, and LDH). Combining top 10 multimodal features, RF model achieved >99% predictive accuracy. These findings shed light on how the human body reacts to SARS-CoV-2 invasion as a unity and provide insights on effectively evaluating COVID-19 patient's severity and developing treatment plans accordingly. We suggest that symptoms and comorbidities can be used as an initial screening tool for triaging, while biochemistry and features combined are applied when accuracy is the priority.


title: Fear of exponential growth in Covid19 data of India and future sketching

text: We have attempted to interpret existing n-cov positive data in India with respect to other countries - Italy, USA, China and South Korea. We have mainly zoomed in the exponential growth in a particular zone of time axis, which is well followed in the data profile of India and Italy but not in others. A deviation from exponential growth to Sigmoid function is analyzed in the data profile of China and South Korea. Projecting that pattern to time dependent data of total number and new cases in India, we have drawn three possible Sigmoid functions, which saturate to cases 10 4 , 10 5 , 10 6 . Ongoing data has doubtful signal of those possibilities and future hope is probably in extension of lock-down and additional imposition of interventions.


title: No evidence for increased transmissibility from recurrent mutations in SARS-CoV-2

text: The COVID-19 pandemic is caused by the coronavirus SARS-CoV-2, which jumped into the human population in late 2019 from a currently uncharacterised reservoir. Due to this extremely recent association with humans, SARS-CoV-2 may not yet be fully adapted to its human host. This has led to speculations that some lineages of SARS-CoV-2 may be evolving towards higher transmissibility. The most plausible candidate mutations under putative natural selection are those which have emerged repeatedly and independently (homoplasies). Here, we formally test whether any of the recurrent mutations that have been observed in SARS-CoV-2 to date are significantly associated with increased viral transmission. To do so, we developed a phylogenetic index to quantify the relative number of descendants in sister clades with and without a specific allele. We apply this index to a carefully curated set of recurrent mutations identified within a dataset of over 23,000 SARS-CoV-2 genomes isolated from patients worldwide. We do not identify a single recurrent mutation in this set convincingly associated with increased viral transmission. Instead, recurrent SARS-CoV-2 mutations currently in circulation appear to be evolutionary neutral. Recurrent mutations also seem primarily induced by the human immune system via host RNA editing, rather than being signatures of adaption to the novel human host. We find no evidence at this stage for the emergence of more transmissible lineages of SARS-CoV-2 due to recurrent mutations.


title: Infection and mortality of healthcare workers worldwide from COVID-19: a scoping review

text: Objectives To estimate COVID-19 infections and deaths in healthcare workers (HCWs) from a global perspective. Design Scoping review. Methods Two parallel searches of academic bibliographic databases and grey literature were undertaken. Governments were also contacted for further information where possible. Due to the time-sensitive nature of the review and the need to report the most up-to-date information for an ever-evolving situation, there were no restrictions on language, information sources utilised, publication status, and types of sources of evidence. The AACODS checklist was used to appraise each source of evidence. Outcome measures Publication characteristics, country-specific data points, COVID-19 specific data, demographics of affected HCWs, and public health measures employed Results A total of 152,888 infections and 1413 deaths were reported. Infections were mainly in women (71.6%) and nurses (38.6%), but deaths were mainly in men (70.8%) and doctors (51.4%). Limited data suggested that general practitioners and mental health nurses were the highest risk specialities for deaths. There were 37.17 deaths reported per 100 infections for healthcare workers aged over 70. Europe had the highest absolute numbers of reported infections (119628) and deaths (712), but the Eastern Mediterranean region had the highest number of reported deaths per 100 infections (5.7). Conclusions HCW COVID-19 infections and deaths follow that of the general world population. The reasons for gender and speciality differences require further exploration, as do the low rates reported from Africa and India. Although physicians working in certain specialities may be considered high-risk due to exposure to oronasal secretions, the risk to other specialities must not be underestimated. Elderly HCWs may require assigning to less risky settings such as telemedicine, or administrative positions. Our pragmatic approach provides general trends, and highlights the need for universal guidelines for testing and reporting of infections in HCWs.


title: shani mutation in mouse affects splicing of Spata22 and leads to impaired meiotic recombination

text: Recombination is crucial for chromosome pairing and segregation during meiosis. SPATA22, along with its direct binding partner and functional collaborator, MEIOB, is essential for the proper repair of double-strand breaks (DSBs) during meiotic recombination. Here we describe a novel point-mutated allele (shani) of mouse Spata22 that we isolated in a forward genetic screen. shani mutant mice phenocopy Spata22-null and Meiob-null mice: mutant cells appear to form DSBs and initiate meiotic recombination, but are unable to complete DSB repair, leading to meiotic prophase arrest, apoptosis and sterility. shani mutants show precocious loss of DMC1 foci and improper accumulation of BLM-positive recombination foci, reinforcing the requirement of SPATA22-MEIOB for the proper progression of meiotic recombination events. The shani mutation lies within a Spata22 coding exon and molecular characterization shows that it leads to incorrect splicing of the Spata22 mRNA, ultimately resulting in no detectable SPATA22 protein. We propose that the shani mutation alters an exonic splicing enhancer element (ESE) within the Spata22 transcript. The affected DNA nucleotide is conserved in most tetrapods examined, suggesting that the splicing regulation we describe here may be a conserved feature of Spata22 regulation.


title: Genitourinary cancer management during a severe pandemic: Utility of rapid communication tools and evidence‐based guidelines

text: Objectives: To determine the usefulness of social media for rapid communication with experts to discuss strategies for prioritization and safety of deferred treatment for urologic malignancies during COVID‐19 pandemic, and to determine whether the discourse and recommendations made through discussions on social media (Twitter) were consistent with the current peer‐reviewed literature regarding the safety of delayed treatment. Methods: We reviewed and compiled the responses to our questions on Twitter regarding the management and safety of deferred treatment in the setting of COVID‐19 related constraints on non‐urgent care. We chronicled the guidance published on this subject by various health authorities and professional organizations. Further, we analyzed peerreviewed literature on the safety of deferred treatment (surgery or systemic therapy) to make made evidence‐based recommendations. Results: Due to the rapidly changing information about epidemiology and infectious characteristics of COVID‐19, the health authorities and professional societies guidance required frequent revisions which by design take days or weeks to produce. Several active discussions on Twitter provided real‐time updates on the changing landscape of the restrictions being placed on non‐urgent care. For separate discussion threads on prostate cancer and bladder cancer, dozens of specialists with expertise in treating urologic cancers could be engaged in providing their expert opinions as well as share evidence to support their recommendations. Our analysis of published studies addressing the safety and extent to which delayed cancer care does not compromise oncological outcome revealed that most prostate cancer care and certain aspects of the bladder and kidney cancer care can be safely deferred for 2‐6 months. Urothelial bladder cancer and advanced kidney cancer require a higher priority for timely surgical care. We did not find evidence to support the idea of using nonsurgical therapies, such as hormone therapy for prostate cancer or chemotherapy for bladder cancer for safer deferment of previously planned surgery. We noted that the comments and recommendations made by the participants in the Twitter discussions were generally consistent with our evidence‐based recommendations for safely postponing cancer care for certain types of urologic cancers. Conclusion: The use of social media platforms, such as Twitter, where the comments and recommendations are subject to review and critique by other specialists is not only feasible but quite useful in addressing the situations requiring urgent resolution, often supported by published evidence. In circumstances such as natural disasters, this may be a preferable approach than the traditional expert panels due to its ability to harness the collective intellect to available experts to provide responses and solutions in real‐time. These real‐time communications via Twitter provided sound guidance which was readily available to the public and participants, and was generally in concordance with the peerreviewed data on safety of deferred treatment.


title: Assessing the Tendency of 2019-nCoV (COVID-19) Outbreak in China

text: Since December 8, 2019, the spread of COVID-19 is increasing every day. It is particularly important to predict the trend of the epidemic for the timely adjustment of the economy and industries. We proposed a Flow-SEHIR model in this paper, based on which we further analyzed the trends of 2019-nCoV (COVID-19) in China. The results show that the basic reproductive numbers R0 of COVID-19 is 3.56 (95% CI: 2.31-4.81). The number of daily confirmed new cases reaches the inflection point on Feb. 6-10 outside Hubei. For the maximum of infected cases number, the predicted peak value in China except Hubei was estimated to be 13806 (95% CI: 11926-15845). The peak arrival time is on March 3-9. The temporal number of patients in most areas of China outside Hubei will peak from March 12 to March 15. The peak values of more than 73.5% provinces or regions in China will be controlled within 1000. According to Flow-SEHIR model and estimations from the data of evacuation of nationals from Wuhan, the peak cumulative number of patients in Hubei was estimated to be 403481 (95% CI: 143284-1166936).


title: Optimized qRT-PCR approach for the detection of intra- and extra-cellular SARS-CoV-2 RNAs

text: The novel coronavirus SARS-CoV-2 is the causative agent of the acute respiratory disease COVID-19 which has become a global concern due to its rapid spread. Meanwhile, increased demand in testing has led to shortage of reagents, supplies, and compromised the performance of diagnostic laboratories in many countries. Both the world health organization (WHO) and the Center for Disease Control and Prevention (CDC) recommend multi-step RT-PCR assays using multiple primer and probe pairs, which might complicate interpretation of the test results especially for borderline cases. In this study, we describe an alternative RT-PCR approach for the detection of SARS-CoV-2 RNA that can be used for the probe-based detection of clinical isolates in the diagnostics as well as in research labs using a low cost SYBR green method. For the evaluation, we used samples from patients with confirmed SARS-CoV-2 infection and performed RT-PCR assays along with successive dilutions of RNA standards to determine the limit of detection. We identified an M-gene binding primer and probe pair highly suitable for quantitative detection of SARS-CoV-2 RNA for diagnostic and research purposes.


title: Liver Function in Novel Coronavirus Disease (COVID-19): A Systematic Review and Meta-Analysis

text: Introduction:The outbreak of new coronavirus has become a global public health challenge. Given a consequential liver function, and the high risk of death coming from liver disorders, the assessment of Novel Coronavirus Disease on liver function is importance. Hence, we carried out this meta-analysis to heightening insight into the occult features of COVID 19, which is likely to affect liver function. Method:This study was performed using databases of Web of Science, Scopus, and PubMed. We considered English cross-sectional and case-series papers, which reported available findings on the association between liver injury and COVID-19 infection. We used the STATA v.11 and random effect model for data analysis. Result:In this present meta-analysis, 52 papers, including 8,463 COVID-19 patients, were studied. The prevalence of increased liver enzymes among the patients, including Alanine aminotransferase, Aspartate aminotransferase, were 30% and 21% in non-severe patients, respectively, which were 38% and 48% in severe patients. The prevalence of increasing C-reactive protein, Lactate dehydrogenase, D-dimer, and Bilirubin were 55%, 39%, 28%, and 10% in non-severe patients respectively, which were 78%, 75%, 79% and 17% in sever patients.The prevalence of liver toxicity as a complication of COVID-19 was 20%.Also patients who have severe condition are 5.54, 4.22, 4.96, 4.13 and 4.34 times more likely to have elevated CRP, ALT, AST, LDH, D-dimer enzymes retrospectively. Conclusion:Elevation of some liver markers were higher in patients with severe COVID-19 infection. All to gather, we assumed that abnormal liver markers could act as a prognostic factor for a better survey of COVID-19.


title: Twitter activity about treatments during the COVID-19 pandemic: case studies of remdesivir, hydroxychloroquine, and convalescent plasma.

text: Since the COVID-19 pandemic started, the public has been eager for news about promising treatments, and social media has played a large role in information dissemination. In this paper, our objectives are to characterize the public discussion of treatments on Twitter, and demonstrate the utility of these discussions for public health surveillance. We pulled tweets related to three promising COVID-19 treatments (hydroxychloroquine, remdevisir and convalescent plasma), between the dates of February 28th and May 22nd using the Twitter public API. We characterize treatment tweet trends over this time period. Most major tweet/retweet/sentiment trends correlated to public announcement made by the white house and/or to new clinical trial evidence about treatments. Most of the websites people shared in treatment-related tweets were non-scientific media sources that leaned conservative. Hydroxychloroquine was the most discussed treatment on Twitter, and over 10% of hydroxychloroquine tweets mentioned an adverse drug reaction. There is a gap between the public attention/discussion around COVID-19 treatments and their evidence. Twitter data can and should be used public health surveillance during this pandemic, as it is informative for monitoring adverse drug reactions, especially as many people avoid going to hospitals/doctors.


title: Chloroquine and hydroxychloroquine in the context of COVID-19

text: Chloroquine and closely related structural analogs, employed initially for the treatment of malaria, are now gaining worldwide attention due to the rapidly spreading pandemic caused by severe acute respiratory syndrome-coronavirus-2, named coronavirus disease (COVID) of 2019 (COVID-19). Although much of this attention has a mechanistic basis, the hard efficacy data for chloroquine/hydroxychloroquine in the management of the clinical syndrome of COVID-19 have been limited thus far. This review aims to present the available in vitro and clinical data for the role of chloroquine/hydroxychloroquine in COVID-19 and attempts to put them into perspective, especially in relation to the different risks/benefits particular to each patient who may require treatment.


title: A DISSYMMETRY IN THE FIGURES RELATED TO THE COVID-19 PANDEMIC IN THE WORLD: WHAT FACTORS EXPLAIN THE DIFFERENCE BETWEEN AFRICA AND THE REST OF THE WORLD?

text: Humanity has experienced outbreaks for millennia, from epidemics limited to pandemics that have claimed many victims and changed the course of civilizations. The advent of vaccines has eradicated some of the serious pathogens and reduced many others. However, pandemics are still part of our modern world, as we continue to have pandemics as devastating as HIV and as alarming as severe acute respiratory syndrome, Ebola and the Middle East respiratory syndrome. The Covid-19 epidemic with 0-exponential contamination curves reaching 3 million confirmed cases should not have come as a surprise, nor should it have been the last pandemic in the world. In this article, we try to summarize the lost opportunities as well as the lessons learned, hoping that we can do better in the future. The objective of this study is to relate the situation of Covid-19 in African countries with those of the countries most affected by the pandemic. It also allows us to verify how, according to the observed situation, the African ecosystem seems to be much more resilient compared to that of other continents where the number of deaths is in the thousands. To verify this, the diagnosed morbidity and mortality reported for different states of the world are compared to the ages of life and the average annual temperature of these states. The results show that the less dramatic balance of the African continent compared to other continents is partly linked to the relatively high temperatures on the continent but also to the relatively young character of its population.


title: Systematic investigations of COVID-19 in 283 cancer patients

text: Background: Cancer patients are considered to be highly susceptible to viral infections, however, the comprehensive features of COVID-19 in these patients remained largely unknown. The present study aimed to assess the clinical characteristics and outcomes of COVID-19 in a large cohort of cancer patients. Design, Setting, and Participants: Data of consecutive cancer patients admitted to 33 designated hospitals for COVID-19 in Hubei province, China from December 17, 2019 to March 18, 2020 were retrospectively collected. The follow-up cutoff date was April 02, 2020. The clinical course and survival status of the cancer patients with COVID-19 were measured, and the potential risk factors of severe events and death were assessed through univariable and multivariable analyses. Results: A total of 283 laboratory confirmed COVID-19 patients (50% male; median age, 63.0 years [IQR, 55.0 to 70.0]) with more than 20 cancer types were included. The overall mortality rate was 18% (50/283), and the median hospitalization stay for the survivors was 26 days. Amongst all, 76 (27%) were former cancer patients with curative resections for over five years without recurrence. The current cancer patients exhibited worse outcomes versus former cancer patients (overall survival, HR=2.45, 95%CI 1.10 to 5.44, log-rank p=0.02; mortality rate, 21% vs 9%). Of the 207 current cancer patients, 95 (46%) have received recent anti-tumor treatment, and the highest mortality rate was observed in the patients receiving recent chemotherapy (33%), followed by surgery (26%), other anti-tumor treatments (19%), and no anti-tumor treatment (15%). In addition, a higher mortality rate was observed in patients with lymphohematopoietic malignancies (LHM) (53%, 9/17), and all seven LHM patients with recent chemotherapy died. Multivariable analysis indicated that LHM (p=0.001) was one of the independent factors associating with critical illness or death. Conclusions: This is the first systematic study comprehensively depicting COVID-19 in a large cancer cohort. Patients with tumors, especially LHM, may have poorer prognosis of COVID-19. Additional cares are warranted and non-emergency anti-tumor treatment should be cautiously used for these patients under the pandemic.


title: Making sense of the Global Coronavirus Data: The role of testing rates in understanding the pandemic and our exit strategy

text: The Coronavirus disease 2019(COVID-19) outbreak has caused havoc across the world. Subsequently, research on COVID-19 has focused on number of cases and deaths and predicted projections have focused on these parameters. We propose that the number of tests performed is a very important denominator in understanding the COVID-19 data. We analysed the number of diagnostic tests performed in proportion to the number of cases and subsequently deaths across different countries and projected pandemic outcomes. We obtained real time COVID-19 data from the reference website Worldometer at 0900 BST on Saturday 4th April, 2020 and collated the information obtained on the top 50 countries with the highest number of COVID 19 cases. We analysed this data according to the number of tests performed as the main denominator. Country wise population level pandemic projections were extrapolated utilising three models - 1) inherent case per test and death per test rates at the time of obtaining the data (4/4/2020 0900 BST) for each country; 2) rates adjusted according to the countries who conducted at least 100000 tests and 3) rates adjusted according to South Korea. We showed that testing rates impact on the number of cases and deaths and ultimately on future projections for the pandemic across different countries. We found that countries with the highest testing rates per population have the lowest death rates and give us an early indication of an eventual COVID-19 mortality rate. It is only by continued testing on a large scale that will enable us to know if the increasing number of patients who are seriously unwell in hospitals across the world are the tip of the iceberg or not. Accordingly, obtaining this information through a rapid increase in testing globally is the only way which will enable us to exit the COVID-19 pandemic and reduce economic and social instability.


title: Integrated genomic view of SARS-CoV-2 in India

text: India first detected SARS-CoV-2, causal agent of COVID-19 in late January-2020, imported from Wuhan, China. March-2020 onwards; importation of cases from rest of the countries followed by seeding of local transmission triggered further outbreaks in India. We used ARTIC protocol based tiling amplicon sequencing of SARS-CoV-2 (n=104) from different states of India using a combination of MinION and MinIT from Oxford Nanopore Technology to understand introduction and local transmission. The analyses revealed multiple introductions of SARS-CoV-2 from Europe and Asia following local transmission. The most prevalent genomes with patterns of variance (confined in a cluster) remain unclassified, here, proposed as A4-clade based on its divergence within A-cluster. The viral haplotypes may link their persistence to geo-climatic conditions and host response. Despite the effectiveness of non-therapeutic interventions in India, multipronged strategies including molecular surveillance based on real-time viral genomic data is of paramount importance for a timely management of the pandemic.


title: On the Spread of Coronavirus Infection. A Mechanistic Model to Rate Strategies for Disease Management

text: Effective policy making based on ongoing COVID-19 pandemic is an urgent issue. We present a mathematical model describing the viral infection dynamics, which reveals two transmissibility parameters influenced by the management strategies in the area for control of the current pandemic. The parameters readily yield the peak infection rate and means for flattening the curve. Model parameters are shown to be correlated to different management strategies by employing machine learning enabling the comparison among different strategies. Treatment of population data with the model shows that restricted non-essential business closure, school closing and strictures on mass gathering influence the spread of infection. While a rational strategy for initiation of an economic reboot would call for a wider perspective of the local economics, the model can speculate on its timing based on the status of the infection as reflected by its potential for an unacceptably renewed viral onslaught.


title: Inequalities in air pollution exposure are increasing in the United States

text: Exposure to ambient air pollution contributes substantially to the global burden of disease, and in 2015, ambient exposure to PM2.5 (fine particles with a mass median aerodynamic diameter of less than 2.5 m) was the fifth-ranking risk factor of mortality globally. We analyzed data from the US zip code tabulation areas (N=32047) for 2000-2016 and found strong evidence of inequalities in exposure to PM2.5 among both racial/ethnic and income groups. Most alarming, we found that these inequalities have been increasing over time. From 2010 to 2016 inequalities in the exposure to PM2.5 levels above 8 g/m3 across racial/ethnic, and income groups increased by factors of 1.6 and 4.0 respectively. As shown in our powerful map visualizations, these results indicate that air pollution regulations must not only decrease PM2.5 concentration levels nationwide but also prioritize reducing environmental injustice across the US.


title: Structural variability, expression profile and pharmacogenetics properties of TMPRSS2 gene as a potential target for COVID-19 therapy

text: The human serine protease TMPRSS2 gene is involved in the priming of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins being one of the possible targets for COVID-19 therapy. TMPRSS2 gene is possibly co-expressed with SARS-CoV-2 cell receptor genes ACE2 and BSG, but only TMPRSS2 demonstrates tissue-specific expression in alveolar cells according to single cell RNA sequencing data. Our analysis of the structural variability of the TMPRSS2 gene based on genome-wide data of 76 human populations demonstrates that functionally significant missense mutation in exon 6/7 in TMPRSS2 gene, was found in many human populations in relatively high frequency, featuring region-specific distribution patterns. The frequency of the missense mutation encoded by the rs12329760, which previously was found to be associated with prostate cancer, is ranged between 10% and 63% being significantly higher in populations of Asian origin compared to European populations. In addition to SNPs, two copy numbers variants (CNV) were detected in the TMPRSS2 gene. Number of microRNAs have been predicted to regulate TMPRSS2 and BSG expression levels, but none of them is enriched in lung or respiratory tract cells. Several well studied drugs can downregulate the expression of TMPRSS2 in human cells, including Acetaminophen (Paracetamol) and Curcumin. Thus TMPRSS2 interaction with the SARS-CoV-2, its structural variability, gene-gene interactions, and expression regulation profiles, and pharmacogenomics properties characterize this gene as a potential target for COVID-19 therapy.


title: A mathematical model to predict the porosity of nickel pillars manufactured by localized electrochemical deposition under pulsed voltage conditions

text: Abstract Metal parts manufactured with engineered porosity offer advantages over traditional parts as they have excellent specific mechanical properties at a lower weight. This is especially of interest in the aerospace and automobile industries. Additive manufacturing allows for creating parts with computer aided design (CAD) modeled lattice structures that offer lightweight parts. However, there is a need for porous structures at the micron scale (<50 µm) which cannot be achieved in a controlled manner using traditional powder-bed based metal additive manufacturing processes. Electrochemical Additive Manufacturing (ECAM) is a novel non-thermal metal additive manufacturing process capable of producing metal 3D parts with engineered porosity at the micron scale. There is a lack of understanding of the cause of porosity and controlling the porosity generated in the parts created using this process. In this paper, the effects of the electrical parameters of deposition, such as the pulse duty cycle and pulse frequency during electrodeposition, on the porosity of the manufactured parts were mathematically modeled. The model predicts that higher frequency electrodeposition leads to more porous structures. The model developed in this study can be used to predict the process parameters needed to deposit nickel microstructures with desired levels of porosity between 20 and 55 %. These model predictions were also validated by experiments. Two mechanisms for the cause of porosity in the deposits were identified. The diffusion-limited deposition phenomenon causing a lack of availability of cations results in larger sized pores and hollow structures to form on the part. The crystal growth and the nucleation process cause micron-scale pores.


Pet dog confirmed to have coronavirus.


title: Serial Interval Distribution of SARS-CoV-2 Infection in Brazil

text: Using 65 transmission pairs of SARS-CoV-2 reported to the Brazilian Ministry of Health we estimate the mean and standard deviation for the serial interval to be 2.97 and 3.29 days respectively. We also present a model for the serial interval probability distribution using only two parameters.


title: SARS-CoV-2 Spike protein binds to bacterial lipopolysaccharide and boosts proinflammatory activity

text: There is a well-known and established link between high lipopolysaccharide (LPS) levels in blood and the metabolic syndrome (MS). MS is a risk factor for developing severe COVID-19 and acute respiratory distress syndrome (ARDS). Here we define an interaction between SARS-CoV-2 Spike (S) protein and LPS and its link to aggravated inflammation in vitro and in vivo. Electrophoresis under native conditions demonstrated that SARS-CoV-2 S protein binds to Escherichia coli LPS, forming high molecular weight aggregates. Microscale thermophoresis analysis further defined the interaction, having a KD of ~47 nM, similar to the observed affinity between LPS and the human receptor CD14. Moreover, S protein, when combined with low levels of LPS, boosted nuclear factor-kappa B (NF-κB) and cytokine responses in monocytic THP-1 cells and human blood, respectively. In an experimental model of localized inflammation, employing NF-κB reporter mice and in vivo bioimaging, S protein in conjunction with LPS significantly increased the inflammatory response when compared with S protein and LPS alone. Apart from providing information on LPS as a ligand for S protein, our results are of relevance for studies on comorbidities involving bacterial endotoxins, such as the MS, or co-existing acute and chronic infections in COVID-19 patients.


title: Development of a COVID-19 vaccine based on the receptor binding domain displayed on virus-like particles

text: The recently ermerging disease COVID-19 is caused by the new SARS-CoV-2 virus first detected in the city of Wuhan, China. From there it has been rapidly spreading inside and outside China. With initial death rates around 4%, COVID-19 patients at longer distances from Wuhan showed reduced mortality as was previously observed for the SARS coronavirus. However, the new coronavirus spreads more strongly, as it sheds long before onset of symptoms or may be transmitted by people without symptoms. Rapid development of a protective vaccine against COVID-19 is therefore of paramount importance. Here we demonstrate that recombinantly expressed receptor binding domain (RBD) of the spike protein homologous to SARS binds to ACE2, the viral receptor. Higly repetitive display of RBD on immunologically optimized virus-like particles derived from cucumber mosaic virus resulted in a vaccine candidate (RBD-CuMVTT) that induced high levels of specific antibodies in mice which were able to block binding of spike protein to ACE2 and potently neutralized the SARS-CoV-2 virus in vitro.


title: DREIMT: a drug repositioning database and prioritization tool for immunomodulation

text: Motivation Drug immunomodulation modifies the response of the immune system and can be therapeutically exploited in pathologies such as cancer and autoimmune diseases. Results DREIMT is a new hypothesis-generation web tool which performs drug prioritization analysis for immunomodulation. DREIMT provides significant immunomodulatory drugs targeting up to 70 immune cells subtypes through a curated database that integrates 4,960 drug profiles and ~2,6K immune gene expression signatures. The tool also suggests potential immunomodulatory drugs targeting user-supplied gene expression signatures. Final output includes drug-signature association scores, FDRs and downloadable plots and results tables. Availability http://www.dreimt.org Contact falshahrour@cnio.es; ggomez@cnio.es


title: Preliminary evidence that higher temperatures are associated with lower incidence of COVID-19, for cases reported globally up to 29th February 2020

text: Seasonal variation in COVID-19 incidence could impact the trajectory of the pandemic. Using global line-list data on COVID-19 cases reported until 29th February 2020 and global gridded temperature data, and after adjusting for surveillance capacity and time since first imported case, higher average temperature was strongly associated with lower COVID-19 incidence for temperatures of 1°C and higher. However, temperature explained a relatively modest amount of the total variation in COVID-19 incidence. These preliminary findings support stringent containment efforts in Europe and elsewhere.


title: A Very Flat Peak: Exponential growth phase of COVID-19 is mostly followed by a prolonged linear growth phase, not an immediate saturation

text: When actively taking measures to control an epidemic, an important indicator of success is crossing the "peak" of daily new infections. The peak is a positive sign which marks the end of the exponential phase of infection spread and a transition into a phase that is a manageable. Most countries or provinces with similar but independent growth trajectories had taken drastic measures for containing the COVID-19 pandemic and are eagerly waiting to cross the peak. However, the data after many weeks of strict measures suggests that most provinces instead enter a phase where the infections are in a linear growth. While the transition out of an exponential phase is relieving, the roughly constant number of daily new infections differ widely, range from around 50 in Singapore to around 2000 just in Lombardy (Italy), and 7600 in Spain. The daily new infection rate of a region seems to depend heavily on the time point in the exponential evolution when the restrictive measures were adopted, rather than on the population of the region. It is not easy to point the critical source of these persistent infections. We attempt to interpret this data using a simple model of newer infections mediated by asymptomatic patients, which underscores the importance of actively identifying any potential leakages in the quarantine. Given the novelty of the virus, it is hard to predict too far into the future and one needs to be observant to see if a plan B is needed as a second round of interventions. So far, the peak achieved by most countries with the first round of intervention is extremely flat.


title: Shrinking the gHAT map: identifying target regions for enhanced control of gambiense human African trypanosomiasis in the Democratic Republic of Congo

text: Gambiense human African trypanosomiasis (gHAT) is a disease targeted for elimination of transmission (EOT) by 2030, however the likelihood of achieving it is unknown. We utilised modelling to study the impact of currently-available intervention methods on transmission across the Democratic Republic of Congo (DRC) - which accounts for [~] 70% of global burden - and highlight regions requiring intensified interventions. A model previously fitted to case data in DRC was used to predict cases and new infections under four future strategies in 168 health zones. The strategies comprise of medical interventions - active and passive screening (AS and PS) - and some include large-scale vector control (VC). In each health zone, we estimate the median year of EOT and the probability of EOT by 2030 under each and compute the least ambitious strategy predicted to achieve EOT by 2030. The model predicts 42 health zones are very likely to achieve EOT (> 90% probability) using medical-only strategies continued at mean coverage levels; this increases to 52 when AS coverage is increased to maximum previous coverage. In all VC strategies, health zones are predicted to meet EOT by 2030, although there are several where increasing low AS coverage could achieve this. This analysis provides a priority list for consideration for supplementary VC implementation (Bagata, Bandundu, Bolobo, Kikongo, Kwamouth and Masi Manimba in former Bandundu province) in conjunction with the recent AS coverage.


title: Changing travel patterns in China during the early stages of the COVID-19 pandemic

text: Understanding changes in human mobility in the early stages of the COVID-19 pandemic is crucial for assessing the impacts of travel restrictions designed to reduce disease spread. Here, relying on data from mainland China, we investigated the spatio-temporal characteristics of human mobility between 1st January and 1st March 2020 and discussed their public health implications. An outbound travel surge from Wuhan before travel restrictions were implemented was also observed across China due to the Lunar New Year, indicating that holiday travel may have played a larger role in mobility changes compared to impending travel restrictions. Holiday travel also shifted healthcare pressure related to COVID-19 towards locations with lower access to care. Network analyses showed no sign of major changes in the transportation network after Lunar New Year. Changes observed were temporary and have not yet led to structural reorganisation of the transportation network at the time of this study.


title: Data From the COVID-19 Epidemic in Florida Suggest That Younger Cohorts Have Been Transmitting Their Infections to Less Socially Mobile Older Adults

text: We analyzed the daily incidence of newly reported COVID-19 cases among adults aged 20-39 years, 40-59 years, and 60 or more years in the sixteen most populous counties of the state of Florida from March 1 through June 27, 2020. In all 16 counties, an increase in reported COVID-19 case incidence was observed in all three age groups soon after the governor-ordered Full Phase 1 reopening went into effect. Trends in testing, hospitalization and mortality do not support the hypothesis that the observed increase in case incidence was merely the result of liberalization of testing criteria. Parameter estimates from a parsimonious two-group heterogeneous SIR model strongly support the hypothesis that younger persons, having first acquired their infections through increasing social contact with their peers, then transmitted their infections to older, less socially mobile individuals.


title: Reinforcing the Impact of Statistics on Society

text: What does statistics have to offer science and society, in this age of massive data, machine learning algorithms, and multiple online sources of tools for data analysis? I recall a few situations where statistics made a real difference and reinforced the impact of our discipline on society. Sometimes the difference lay in the insightful analysis and inference enabled by ground-breaking methods in our field like hypothesis testing, likelihood ratios, Bayesian models, jackknife, and bootstrap. But perhaps more often, the impacts came from thoughtful analyses before data were collected, and the questions that arose after the statistical analysis. The impact of understanding the problem, designing the experiment and data collections, conducting the pilot surveys, and raising important questions, is substantial. Through sensible explorations following formal statistical procedures, statisticians have made contributions in many domains. In this presentation, I recall some examples which made a long-lasting impact. Some of them, like randomization in clinical trials, known and familiar to all, are so ingrained in our practice that the role of statistics has been forgotten. Others may be less familiar but nonetheless benefited greatly from the critical input of statisticians. All remind us that our field remains today not only relevant but critical to science and society.


title: Appendix I Additional Notes on Taxonomy

text: Unknown


title: Climate & BCG: Effects on COVID-19 DeathGrowth Rates

text: Multiple studies have suggested the spread of COVID-19 is affected by factors such as climate, BCG vaccinations, pollution and blood type. We perform a joint study of these factors using the death growth rates of 40 regions worldwide with both machine learning and Bayesian methods. We find weak, non-significant (< 3 sigma) evidence for temperature and relative humidity as factors in the spread of COVID-19 but little or no evidence for BCG vaccination prevalence or PM2.5 pollution. The only variable detected at a statistically significant level (> 3 sigma) is the rate of positive COVID-19 tests, with higher positive rates correlating with higher daily growth of deaths.


title: Is hemoglobin the missing link in the pathogenesis of COVID-19?

text: This editorial considers studies which establish our current understanding of SARSCoV-2 and the indicated direction for treatment of COVID-19 patients and future research. Recent modelling studies point to the effect of SARS-CoV-2 on hemoglobin as a key element in understanding the pathogenesis of COVID-19. This would suggest that the focus of treatment of COVID-19 would need to shift towards maintaining the oxygen carrying capacity of blood; potentially with blood transfusions and super-oxygenation, perhaps including hyperbaric oxygen therapy. Further, early prevention of thromboembolism, and suppression of the immune response due to hemoglobin damage, may help contain the clinical course.


title: Drug treatments affecting ACE2 in COVID-19 infection: a systematic review protocol

text: Abstract Background: The SARS-CoV-2 virus causing COVID-19 binds human angiotensin-converting enzyme 2 (ACE2) receptors in human tissues. ACE2 expression may be associated with COVID-19 infection and mortality rates. Routinely prescribed drugs which up- or down-regulate ACE2 expression are therefore of critical research interest as agents which might promote or reduce risk of COVID-19 infection in a susceptible population. Aim: To review evidence on routinely prescribed drug treatments in the UK that could up- or down-regulate ACE2 and potentially affect COVID-19 infection. Design and setting: Systematic review of studies published in MEDLINE, EMBASE, CINAHL, the Cochrane Library and Web of Science from inception to April 1st 2020. Method: A systematic review will be conducted in line with PRISMA guidelines. Inclusion criteria will be: i) assess effect of drug exposure on ACE2 level; ii) drug is included in British National Formulary (BNF) and therefore available to prescribe in UK; iii) a control, placebo or sham group is included as comparator. Exclusion criteria will be: i) ACE2 measurement in utero; ii) ACE2 measurement in children under 18 years; iii) drug not in BNF; iv) review article. Quality will be assessed using the Cochrane risk of bias tool for human studies, and the SYRCLE risk of bias tool for animal studies. Results: Data will be reported in summary tables and narrative synthesis. Conclusion: This systematic review will identify drug therapies which may increase or decrease ACE2 expression. This might identify medications increasing risk of COVID-19 transmission, or as targets for intervention in mitigating transmission.


title: Development of a dual-gene loop-mediated isothermal amplification (LAMP) detection assay for SARS-CoV-2: A preliminary study

text: Severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) has emerged as a rapidly spreading global pathogen stressing the need for development of rapid testing protocols ever than before. The aim of present study was to develop a SARS-CoV-2 detection protocol which can be performed within minimal resources and timeframe. For this purpose, we implemented the reverse transcription loop-mediated isothermal amplification (RT-LAMP) methodology for the qualitative detection of SARS-CoV-2 RNA. In order to improve the detection capability, the RT-LAMP assay was developed to simultaneously amplify two viral genes: ORF1a and N. A total of 45 SARS-CoV-2 associated coronavirus disease 2019 (COVID-19) cases were enrolled. Viral RNA was extracted from the nasopharyngeal swab samples and analyzed simultaneously using PCR and RT-LAMP protocols. Overall, our SARS-CoV-2 dual gene RT-LAMP assay was found to be 95% accurate in detecting positive cases and showed no cross-reactivity or false-positive result in non-COVID-19 samples. Further evaluation on larger and multi-centric cohorts is currently underway to establish the diagnostic accuracy and subsequent implementation into clinical practice and at point-of-care settings.


title: Statistical Issues and Lessons Learned from COVID-19 Clinical Trials with Lopinavir-Ritonavir and Remdesivir

text: Background: Since the outbreak of the novel coronavirus disease 2019 (COVID-19) in December 2019, it has rapidly spread in more than 200 countries or territories with over 8 million confirmed cases and 440,000 deaths by June 17, 2020. Recently, three randomized clinical trials on COVID-19 treatments were completed, one for lopinavir-ritonavir and two for remdesivir. One trial reported that remdesivir was superior to placebo in shortening the time to recovery, while the other two showed no benefit of the treatment under investigation. However, several statistical issues in the original design and analysis of the three trials are identified, which might shed doubts on their findings and the conclusions should be evaluated with cautions. Objective: From statistical perspectives, we identify several issues in the design and analysis of three COVID-19 trials and reanalyze the data from the cumulative incidence curves in the three trials using more appropriate statistical methods. Methods: The lopinavir-ritonavir trial enrolled 39 additional patients due to insignificant results after the sample size reached the planned number, which led to inflation of the type I error rate. The remdesivir trial of Wang et al. failed to reach the planned sample size due to a lack of eligible patients, while the bootstrap method was used to predict the quantity of clinical interest conditionally and unconditionally if the trial had continued to reach the originally planned sample size. Moreover, we used a terminal (or cure) rate model and a model-free metric known as the restricted mean survival time or the restricted mean time to improvement (RMTI) in this context to analyze the reconstructed data due to the existence of death as competing risk and a terminal event. The remdesivir trial of Beigel et al. reported the median recovery time of the remdesivir and placebo groups and the rate ratio for recovery, while both quantities depend on a particular time point representing local information. We reanalyzed the data to report other percentiles of the time to recovery and adopted the bootstrap method and permutation test to construct the confidence intervals as well as the P values. The restricted mean time to recovery (RMTR) was also computed as a global and robust measure for efficacy. Results: For the lopinavir-ritonavir trial, with the increase of sample size from 160 to 199, the type I error rate was inflated from 0.05 to 0.071. The difference of terminal rates was -8.74% (95% CI [-21.04, 3.55]; P=.16) and the hazards ratio (HR) adjusted for terminal rates was 1.05 (95% CI [0.78, 1.42]; P=.74), indicating no significant difference. The difference of RMTIs between the two groups evaluated at day 28 was -1.67 days (95% CI [-3.62, 0.28]; P=.09) in favor of lopinavir-ritonavir but not statistically significant. For the remdesivir trial of Wang et al., the difference of terminal rates was -0.89% (95% CI [-2.84, 1.06]; P=.19) and the HR adjusted for terminal rates was 0.92 (95% CI [0.63, 1.35]; P=.67). The difference of RMTIs at day 28 was -0.89 day (95% CI [-2.84, 1.06]; P=.37). The planned sample size was 453, yet only 236 patients were enrolled. The conditional prediction shows that the HR estimates would reach statistical significance if the target sample size had been maintained, and both conditional and unconditional prediction delivered significant HR results if the trial had continued to double the target sample size. For the remdesivir trial of Beigel et al., the difference of RMTRs between the remdesivir and placebo groups up to day 30 was -2.7 days (95% CI [-4.0, -1.2]; P<.001), confirming the superiority of remdesivir. The difference in recovery time at the 25th percentile (95% CI [-3, 0]; P=.65) was insignificant, while the differences manifested to be statistically significant at larger percentiles. Conclusions: Based on the statistical issues and lessons learned from the recent three clinical trials on COVID-19 treatments, we suggest more appropriate approaches for the design and analysis for ongoing and future COVID-19 trials.


title: Imaging auxiliary diagnosis of corona virus disease 2019/ 影像学辅助诊断新型冠状病毒肺炎

text: Corona virus disease 2019 (COVID-2019) is an acute respiratory tract infectious disease caused by infection with 2019 novel coronavirus(2019-nCoV), which is mainly characterized with pulmonary inflammatory lesions, strong infectivity and long incubation period. At present, the gold standard for diagnosis of COVID-2019 is positive nucleic acid test result. However, nucleic acid test Results: of some patients are false negative, and the number of patients need to be screened is so large. For asymptomatic patients and the large number of patients needed to be screened, imaging examinations are particularly important. The main points of CT and ultrasonic examination in auxiliary diagnosis of COVID-2019, the advantages of ultrasonic examination and protective specifications were reviewed in this article.


title: QT Interval Prolongation and Torsade De Pointes in Patients with COVID-19 treated with Hydroxychloroquine/Azithromycin

text: Background: The emergence of the COVID-19 pandemic has resulted in over two million affected and over 150 thousand deaths to date. There is no known effective therapy for the disease. Initial reports suggesting the potential benefit of Hydroxychloroquine/Azithromycin (HY/AZ) have resulted in massive adoption of this combination worldwide. However, while the true efficacy of this regimen is unknown, initial reports have raised concerns regarding the potential risk of QT prolongation and induction of torsade de pointes (TdP). Methods: This is a multicenter retrospective study of 251 patients with COVID-19 treated with HY/AZ. We reviewed ECG tracings from baseline and until 3 days after completion of therapy to determine the progression of QTc and incidence of arrhythmia and mortality. Results: QTc prolonged in parallel with increasing drug exposure and incompletely shortened after its completion. Extreme new QTc prolongation to > 500 ms, a known marker of high risk for TdP had developed in 15.9% of patients. One patient developed TdP requiring emergent cardioversion. Seven patients required premature termination of therapy. The baseline QTc of patients exhibiting QTc prolongation of > 60 ms was normal. Conclusion: The combination of HY/AZ significantly prolongs the QTc in patients with COVID-19. This prolongation may be responsible for life threating arrhythmia in the form of TdP. This risk mandates careful consideration of HY/AZ therapy in lights of its unproven efficacy. Strict QTc monitoring should be performed if the regimen is given.