title: SARS-CoV-2 RT-PCR profile in 298 Indian COVID-19 patients : a retrospective observational study

text: Background: Despite being in the 5th month of pandemic, knowledge with respect to viral dynamics, infectivity and RT-PCR positivity continues to evolve. Aim: To analyse the SARS CoV-2 nucleic acid RT-PCR profiles in COVID-19 patients. Design: It was a retrospective, observational study conducted at COVID facilities under AIIMS, New Delhi. Methods : Patients admitted with laboratory confirmed COVID-19 were eligible for enrolment. Patients with incomplete details, or only single PCR tests were excluded. Data regarding demographic details, comorbidities, treatment received and results of SARS-CoV-2 RT-PCR performed on nasopharyngeal and oropharyngeal swabs, collected at different time points, was retrieved from the hospital records. Results : 298 patients were included, majority were males (75.8%) with mean age of 39.07 years (0.6-88 years). The mean duration from symptom onset to first positive RT-PCR was 4.7 days (SD 3.67), while that of symptom onset to last positive test was 17.83 days (SD 6.22). Proportions of positive RT-PCR tests were 100%, 49%, 24%, 8.7% and 20.6% in the 1st, 2nd, 3rd, 4th & >4 weeks of illness. 12 symptomatic patients had prolonged positive test results even after 3 weeks of symptom onset. Age >= 60 years was associated with prolonged RT-PCR positivity (statistically significant). Conclusion : This study showed that the average period of PCR positivity is more than 2 weeks in COVID-19 patients; elderly patients have prolonged duration of RT-PCR positivity and requires further follow up.


docid: fkwskhfk

title: Impact of city and residential unit lockdowns on prevention and control of COVID-19

text: With respect to the asymptomatic transmission characteristics of the novel coronavirus that appeared in 2019 (COVID-19), a susceptible-asymptomatic-infected-recovered-death (SAIRD) model that considered human mobility was constructed in this study. The dissemination of COVID-19 was simulated using computational experiments to identify the mechanisms underlying the impact of city and residential lockdowns on controlling the spread of the epidemic. Results: The implementation of measures to lock down cities led to higher mortality rates in these cities, due to reduced mobility. Moreover, implementing city lockdown along with addition of hospital beds led to improved cure and reduced mortality rates. Stringent implementation and early lockdown of residential units effectively controlled the spread of the epidemic, and reduced the number of hospital bed requirements. Collectively, measures to lock down cities and residential units should be taken to prevent the spread of COVID-19. In addition, medical resources should be increased in cities under lockdown. Implementation of these measures would reduce the spread of the virus to other cities and allow appropriate treatment of patients in cities under lockdown.


title: Reduced inflammatory responses to SARS-CoV-2 infection in children presenting to hospital with COVID19 in China

text: Background Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in children is associated with better outcomes than in adults. The inflammatory response to COVID-19 infection in children remains poorly characterised. Methods We retrospectively analysed the medical records of 127 laboratory-confirmed COVID-19 patients aged 1 month to 16 years from Wuhan and Jingzhou of Hubei Province. Patients presented between January 25th and March 24th 2020. Information on clinical features, laboratory results, plasma cytokines/chemokines and lymphocyte subsets were analysed. Findings Children admitted to hospital with COVID-19 were more likely to be male (67.7%) and the median age was 7.3 [IQR 4.9] years. All but one patient with severe disease was aged under 2 and the majority (5/7) had significant co-morbidities. Despite 53% having viral pneumonia on CT scanning only 2 patients had low lymphocyte counts and no differences were observed in the levels of plasma proinflammatory cytokines, including interleukin (IL)-2, IL-4, IL-6, tumour necrosis factor (TNF)-alpha; and interferon (IFN)-gamma; between patients with mild, moderate or severe disease. Interpretations We demonstrated that the immune responses of children to COVID-19 infection is significantly different from that seen in adults. Our evidence suggests that SARS-CoV-2 does not trigger a robust inflammatory response or "cytokine storm" in children with COVID-19, and this may underlie the generally better outcomes seen in children with this disease. These data also imply anti-cytokine therapies may not be effective in children with moderate COVID-19.


title: Pooled testing with replication: a mass testing strategy for the COVID-19 pandemics

text: In absence of a vaccine or antiviral drugs for the COVID-19 pandemic, it becomes urgent to test for positiveness to the virus as many people as possible, in order to detect early outbreaks of the infection. Present testing solutions are based on the extraction of RNA from patients using oropharyngeal (OP) and nasopharyngeal (NP) swabs, and then testing with real-time PCR for the presence of specific RNA filaments identifying the virus. This approach is limited by the availability of reactants, trained technicians and laboratories. To speed up the testing procedures, some attempts have been done on group testing, which means that the swabs of multiple patients are grouped together and tested. Here we propose to use this technique in conjunction with a combinatorial replication scheme in which each patient is allocated in two or more groups to reduce total numbers of tests and to allow testing of even larger numbers of people. Under mild assumptions, a 13x average reduction of tests can be achieved.


Las buenas prácticas en la atención psicológica infanto-juvenil ante el COVID-19


docid: sokaqrkd

title: Hospitalization time and outcome in patients with Coronavirus Disease 2019 (COVID-19): analysis data from China

text: Objective: The mean hospitalization time and outcome among patients with coronavirus disease 2019 (COVID-19) was estimated with the purpose of providing evidence for decision-making in medical institutions and governments in epidemic areas. Method：The data of COVID-19 patients in china were collected from the websites of provincial and municipal health commissions. The mean hospitalization time and mortality in the mild or severe patients and the mean time from severe to mild illness were calculated by Gaussian mixture modeling. Results: The mean hospitalization time among mild patients in Hubei province, other areas except Hubei province, and the national areas was 20.71 ± 9.30, 16.86 ± 8.24, and 19.34 ± 9.29 days, respectively. The mean transition time from severe to mild illness in the above three areas were 15.00, 17.00, and 14.99 days, respectively. The death rate of mild and severe patients in Hubei province and the national areas were 1.10% and 18.14%, and 1.10% and 17.70%, respectively. Among those patients who died of COVID-19, the mean time from severe transition to death in Hubei province and the national areas was 6.22 ± 5.12 and 6.35 ± 5.27 days, respectively. Conclusion: There were regional differences in the average length of stay between Hubei province and other regions, which may be related to different medical configurations. For those severe patients who died of COVID-19, the average time from hospitalization to death was about one week, and proper and effective treatments in the first week were critical.


title: Distinct early IgA profile may determine severity of COVID-19 symptoms: an immunological case series

text: SARS-CoV-2 is the causative agent of COVID-19 and is a severe threat to global health. Patients infected with SARS-CoV-2 show a wide range of symptoms and disease severity, while limited data is available on its immunogenicity. Here, the kinetics of the development of SARS-CoV-2-specific antibody responses in relation to clinical features and dynamics of specific B-cell populations are reported. Immunophenotyping of B cells was performed by flow cytometry with longitudinally collected PBMCs. In parallel, serum samples were analyzed for the presence of SARS-CoV-2-specific IgA, IgG, and IgM antibodies using whole proteome peptide microarrays. Soon after disease onset in a mild case, we observed an increased frequency of plasmablasts concomitantly with a strong SARS-CoV-2-specific IgA response. In contrast, a case with more severe progression showed a delayed, but eventually very strong and broad SARS-CoV-2-specific IgA response. This case study shows that determining SARS-CoV-2-specific antibody epitopes can be valuable to monitor the specificity and magnitude of the early B-cell response, which could guide the development of vaccine candidates. Follow-up studies are required to evaluate whether the kinetics and strength of the SARS-CoV-2-specific IgA response could be potential prognostic markers of viral control.


title: Age-dependent progression of SARS-CoV-2 infection in Syrian hamsters

text: In late 2019, an outbreak of a severe respiratory disease caused by an emerging coronavirus, SARS-CoV-2, resulted in high morbidity and mortality in infected humans1. Complete understanding of COVID-19, the multi-faceted disease caused by SARS-CoV-2, requires suitable small animal models, as does the development and evaluation of vaccines and antivirals2. Because age-dependent differences of COVID-19 were identified in humans3, we compared the course of SARS-CoV-2 infection in young and aged Syrian hamsters. We show that virus replication in the upper and lower respiratory tract was independent of the age of the animals. However, older hamsters exhibited more pronounced and consistent weight loss. In situ hybridization in the lungs identified viral RNA in bronchial epithelium, alveolar epithelial cells type I and II, and macrophages. Histopathology revealed clear age-dependent differences, with young hamsters launching earlier and stronger immune cell influx than aged hamsters. The latter developed conspicuous alveolar and perivascular edema, indicating vascular leakage. In contrast, we observed rapid lung recovery at day 14 after infection only in young hamsters. We propose that comparative assessment in young versus aged hamsters of SARS-CoV-2 vaccines and treatments may yield valuable information as this small-animal model appears to mirror age-dependent differences in human patients.


title: Benefits and Risks of Chloroquine and Hydroxychloroquine in The Treatment of Viral Diseases: A Meta-Analysis of Placebo Randomized Controlled Trials

text: Background and Objective: Recently, in the scramble to find drugs to treat COVID-19, chloroquine (CQ) and its derivative hydroxychloroquine (HCQ) have rapidly gained the public attention. In this study, we conducted a meta-analysis of randomized clinical trials (RCTs) to evaluate the efficacy and safety of CQ and HCQ in the treatment of viral diseases. Methods: We searched PubMed, EMBASE, Cochrane Central, Web of Science, Clinical Trials Registries, CNKI, Wanfang Data, CQVIP, and Preprint Servers through April 4, 2020, for randomized controlled trials (RCTs) that examined the efficacy and safety of CQ and HCQ against viral infection. We analyzed pooled data on the overall efficacy, the relative risks over the placebo, and the prevalence of adverse events. Trial sequential analysis (TSA) was also performed to evaluate the random errors in the meta-analysis. Potential moderators of drug-placebo efficacy differences were analyzed by meta-regression. Results: The analysis included 11 RCTs with 2613 adult patients. Both the plasma viral load (standard mean difference: 0.29, 95% CI: -1.19 - 1.76, P = 0.70) and the improvement of clinical symptoms (odds ratio: 2.36, 95% CI: 0.81 - 6.92, P = 0.11) were not different between the intervention and placebo arm. There was significant heterogeneity for the efficacy assessment, which was primarily explained by the age of patients and the sample size. Compared to the placebo, CQ and HCQ had increased risk of mild adverse events (risk ratio: 1.51, 95% CI: 1.35 - 1.70, P < 0.05, TSA adjusted 95% CI: 1.31 - 2.19), which were statistically significant in nervous, integumentary, and gastrointestinal systems. The most common adverse events were observed in the nervous system, with the pooled prevalence of 31.4% (95% CI: 10.5% - 56.7%). Conclusions: Insufficient data were available to support the antiviral efficacy of CQ and HCQ due to the high heterogeneity caused by the age of patients. Mild side effects are expected for the current antiviral dose regimens of CQ and HCQ. Treatment outcomes may be enhanced by better-selected patients based on age and well-controlled adverse events.


title: ESTIMATING UNDERDIAGNOSIS OF COVID-19 WITH NOWCASTING AND MACHINE LEARNING: EXPERIENCE FROM BRAZIL

text: Background: Brazil has the second largest COVID-19 number of cases, worldly. Even so, underdiagnosis in the country is massive. Nowcasting techniques have helped to overcome the underdiagnosis. Recent advances in machine learning techniques offer opportunities to refine the nowcasting. This study aimed to analyze the underdiagnosis of COVID-19, through nowcasting with machine learning, in a South of Brazil capital. Methods: The study has an observational ecological design. It used data from 3916 notified cases of COVID-19, from April 14th to June 02nd, 2020, in Florianopolis, Santa Catarina, Brazil. We used machine-learning algorithm to classify cases which had no diagnosis yet, producing the nowcast. To analyze the underdiagnosis, we compared the difference between the data without nowcasting and the median of the nowcasted projections for the entire period and for the six days from the date of onset of symptoms to diagnosis at the moment of data extraction. Results: The number of new cases throughout the entire period, without nowcasting, was 389. With nowcasting, it was 694 (UI95 496-897,025). At the six days period, the number without nowcasting was 19 and 104 (95% UI 60-142) with. The underdiagnosis was 37.29% in the entire period and 81.73% at the six days period. Conclusions: The underdiagnosis was more critical in six days from the date of onset of symptoms to diagnosis before the data collection than in the entire period. The use of nowcasting with machine learning techniques can help to estimate the number of new cases of the disease.


title: Clinical Characteristics of SARS-CoV-2 Pneumonia Compared to Controls in Chinese Han Population

text: Background In December 2019, novel coronavirus (SARS-CoV-2) infected pneumonia occurred in Wuhan, China. The number of cases has increased rapidly but information on the clinical characteristics of SARS-CoV-2 pneumonia without comorbidities compared to normal controls in Chinese Han population is limited. Our objective is to describe the epidemiological and clinical characteristics of SARS-CoV-2 pneumonia without comorbidities compared to normal controls in the Chinese Han population. Methods Retrospective, multi-center case series of the 69 consecutive hospitalized patients with confirmed SARS-CoV-2 pneumonia, from February 7 to February 28, 2020; final date of follow-up was February 29, 2020. Results The study population included 69 hospitalized patients with confirmed SARS-CoV-2 pneumonia without comorbidities and 14,117 normal controls. 50.7% patients were male and 49.3% were female; 1.5% patients were asymptomatic cases, 63.8% patients were mild cases, and 36.2% patients were severe or critical cases. Compared with mild patients (n = 44), severe or critical patients (n = 25) were significantly older (median age, 67 years [IQR, 58-79] vs. 49 years [IQR, 36-60]; P < 0.01). Fever was present in 98.6% of the patients. The second most common symptom was cough (62.3%), fatigue (58.0%), sputum (39.1%), and headache (33.3%). The median incubation period was 4 days (IQR, 2 to 7). Leukocyte count was 74.1% of normal controls and lymphocyte count was 45.9% of normal controls. The phenomenon of lymphocyte depletion (PLD) observed in severe or critical cases in 100%. Levels of lactate dehydrogenase, D-dimer, procalcitonin, and interleukin-6 were showed significant differences between mild and severe or critical cases. Chest computed tomographic scans showed bilateral patchy patterns (49.3%), local patchy shadowing (29.0%), and ground glass opacity (21.7%). 7.3% patients were diagnosed ARDS, 7.3% patients were diagnosed acute cardiac injury (troponin I >28 pg/mL) and 4.4% patients were diagnosed fungal infections or shock. 4.3% patients have been discharged; 1.5% patient had died; 1.5% patient had recovery. Conclusions In this multicenter case series of 69 patients without comorbidities, the full spectrum of asymptomatic, mild, severe, and critical cases is described. 50.7% patients were male and 49.3% were female; 1.5% patients were asymptomatic cases, 63.8% patients were mild cases, and 36.2% patients were severe or critical cases. 4.3% patients have been discharged; 1.5% patient had died; 1.5% patient had recovery. Among the 25 patients with severe or critical disease, 12.0% patients were underwent non-invasive mechanical ventilation, 8.0% patients underwent invasive mechanical ventilation, and 4.0% patients died.


title: Towards complete and error-free genome assemblies of all vertebrate species

text: High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are only available for a few non-microbial species1–4. To address this issue, the international Genome 10K (G10K) consortium5,6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling the most accurate and complete reference genomes to date. Here we summarize these developments, introduce a set of quality standards, and present lessons learned from sequencing and assembling 16 species representing major vertebrate lineages (mammals, birds, reptiles, amphibians, teleost fishes and cartilaginous fishes). We confirm that long-read sequencing technologies are essential for maximizing genome quality and that unresolved complex repeats and haplotype heterozygosity are major sources of error in assemblies. Our new assemblies identify and correct substantial errors in some of the best historical reference genomes. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an effort to generate high-quality, complete reference genomes for all ~70,000 extant vertebrate species and help enable a new era of discovery across the life sciences.


title: Department of Error

text: Cluver L, Lachman JM, Sherr L, et al. Parenting in a time of COVID-19. Lancet 2020; 395: e64—In this Correspondence, Gretchen Bachman's affiliation should have been “Department of Orphans and Vulnerable Children, United States Agency for International Development, Washington, DC, USA”. This correction has been made to the online version as of April 9, 2020.


title: A unifying structural and functional model of the coronavirus replication organelle: tracking down RNA synthesis

text: Zoonotic coronavirus (CoV) infections, like those responsible for the current SARS-CoV-2 epidemic, cause grave international public health concern. In infected cells, the CoV RNA-synthesizing machinery associates with modified endoplasmic reticulum membranes that are transformed into the viral replication organelle (RO). While double-membrane vesicles (DMVs) appear to be a pan-coronavirus RO element, studies to date describe an assortment of additional coronavirus-induced membrane structures. Despite much speculation, it remains unclear which RO element(s) accommodate viral RNA synthesis. Here we provide detailed 2D and 3D analyses of CoV ROs and show that diverse CoVs essentially induce the same membrane modifications, including the small open double-membrane spherules (DMSs) previously thought to be restricted to gamma- and delta-CoV infections and proposed as sites of replication. Metabolic labelling of newly-synthesized viral RNA followed by quantitative EM autoradiography revealed abundant viral RNA synthesis associated with DMVs in cells infected with the beta-CoVs MERS-CoV and SARS-CoV, and the gamma-CoV infectious bronchitis virus. RNA synthesis could not be linked to DMSs or any other cellular or virus-induced structure. Our results provide a unifying model of the CoV RO and clearly establish DMVs as the central hub for viral RNA synthesis and a potential drug target in coronavirus infection.


title: Multifocal transient cortical brain lesions: a consistent MRI finding in neuro-COVID-19 patients

text: We report four cases of subacute encephalopathy occurring in patients with SARS-CoV-2 infection. All patients have been intubated in the first week from onset of ARDS and presented neurological signs of agitation and spatial disorientation after weaning from mechanical ventilation. The MRI picture and the clinical features are described. MRI lesions characteristics are unusual but demonstrate a highly consistent pattern through all the four patients with similar neurological symptoms. They do not fulfill any typical criteria for a definite neuroradiological entity. Their predominantly parieto-occipital distribution recalls posterior reversible encephalopathy syndrome (PRES), although the prevalent cortical involvement and diffusion MRI pattern are not typical of PRES. We speculate that this pattern may be related to a possible transient dysregulation of vasomotor reactivity.


title: Bacteremia and Blood Culture Utilization During COVID-19 Surge in New York City

text: A surge of patients with coronavirus disease 2019 (COVID-19) presenting to New York City hospitals in March 2020 led to a sharp increase in the utilization of blood cultures, which overwhelmed the capacity of automated blood culture instruments. We sought to evaluate the utilization and diagnostic yield of blood cultures during the COVID-19 pandemic to determine prevalence and common etiologies of bacteremia, and to inform a diagnostic approach to relieve blood culture overutilization. We performed a retrospective cohort analysis of 88,201 blood cultures from 28,011 patients at a multicenter network of hospitals within New York City to evaluate order volume, positivity rate, time to positivity, and etiologies of positive cultures in COVID-19. Ordering volume increased by 34.8% in the second half of March 2020 compared to the first half of the month. The rate of bacteremia was significantly lower among COVID-19 patients (3.8%) than COVID-19 negative patients (8.0%) and those not tested (7.1%), p < 0.001. COVID-19 patients had a high proportion of organisms reflective of commensal skin microbiota, reducing the bacteremia rate to 1.6% when excluded. More than 98% of all positive cultures were detected within 4 days of incubation. Bloodstream infections are very rare for COVID-19 patients, which supports the judicious use of blood cultures in the absence of compelling evidence for bacterial co-infection. Clear communication with ordering providers is necessary to prevent overutilization of blood cultures during COVID-19 surges, and laboratories should consider shortening the incubation period from 5 days to 4 days to free additional capacity.


title: Estimating seroprevalence with imperfect serological tests: exploiting cutoff-free approaches

text: Large-scale serological testing in the population is essential to determine the true extent of the current Coronavirus pandemic. Serological tests measure antibody responses against pathogens and define cutoff levels that dichotomize the quantitative test measures into sero-positives and negatives. With the imperfect tests that are currently available to test for past SARS-CoV-2 infection, the fraction of seropositive individuals in serosurveys is a biased estimator of seroprevalence and is usually corrected post-hoc to account for the sensitivity and specificity. Here we use a likelihood-based inference method — previously called mixture models — for the estimation of the seroprevalence that does not require to define cutoffs by integrating the quantitative test measures directly into the statistical inference procedure. We confirm that this likelihood-based method outperforms the methods based on cutoffs and post-hoc corrections leading to less variation in point-estimates of the seroprevalence and its temporal trend. We illustrate how the likelihood-based method can be used to optimize the design of serosurveys with imperfect serological tests. We also provide guidance on the number of control and case sera that are required to quantify the test’s ambiguity sufficiently to enable the reliable estimation of the seroprevalence. Lastly, we show how this approach can be used to identify classes of case sera with an unknown distribution of quantitative test measures that have not been used for test validation. An R-package with the likelihood and power analysis functions is provided. Our study advocates to using serological tests without cutoffs, especially if they are used to determine parameters characterizing populations rather than individuals. This approach circumvents some of the shortcomings of cutoff-based methods with post-hoc correction at exactly the low seroprevalence levels and test accuracies that we are currently facing in COVID-19 serosurveys. Author Summary As other pathogens, SARS-CoV-2 elicits antibody responses in infected people that can be detected in their blood serum as early as a week after the infection until long after recovery. The presence of SARS-CoV-2 specific antibodies can therefore be used as a marker of past infection, and the prevalence of seropositive people, i.e. people with specific antibodies, is a key measure to determine the extent of the Coronavirus pandemic. The serological tests, however, are usually not perfect, yielding false positive and negative results. Here we exploit an approach that refrains from classifying people as seropositive or negative, but rather compares the antibody level to that of confirmed cases and controls. This approach leads to more reliable seroprevalence estimates, especially for the low prevalence and low test accuracies that we face during the current Coronavirus pandemic. We also show how this approach can be extended to infer the presence of cases that have not been used for validating the test, such as people that underwent a mild or even asymptomatic infection.


title: D(2)EA: Depict the Epidemic Picture of COVID-19

text: The outbreak of coronavirus disease 2019 (COVID-19) has aroused a global alert. To release social panic and guide future schedules, this article proposes a novel mathematical model, the Delay Differential Epidemic Analyzer (D(2)EA), to analyze the dynamics of epidemic and forecast its future trends. Based on the traditional Susceptible-Exposed-Infectious-Recovered (SEIR) model, the D(2)EA model innovatively introduces a set of quarantine states and applies both ordinary differential equations and delay differential equations to describe the transition between two states. Potential variations of practical factors are further considered to reveal the true epidemic picture. In the experiment part, we use the D(2)EA model to simulate the epidemic in Hubei Province. Fitting to the collected real data as non-linear optimization, the D(2)EA model forecasts that the accumulated confirmed infected cases in Hubei Province will reach the peak at the end of February and then steady down. We also evaluate the effectiveness of the quarantine measures and schedule the date to reopen Hubei Province.


title: Modeling the Transmission of Respiratory Infectious Diseases in Mass Transportation Systems

text: Mass transportation is one of the areas that are badly hit by respiratory infectious disease outbreaks due to moderate to high exposure risk to pathogens brought about by the interaction among commuters. Here, we formulate agent-based models that simulate the spread of a respiratory infectious disease in a train wagon in the Manila Light Rail Transit System, and in a 49-seater public utility bus. We consider preventive measures such as implementation of social distancing, and limitation of interaction or movement among the commuters to investigate how these measures will inhibit disease transmission. We also consider the effect of protective gears and practices, crowd density, and prevalence of disease in the community on the possible number of newly-infected individuals. Our simulations show that (i) individuals must have protection with more than 90% effectiveness to inhibit transmission of the disease; (ii) social or physical distancing by more than 1m distance reduces the risk of being infected; (iii) minimizing movement or interaction with other passengers reduces the risk of transmission by 50%; (iv) passenger capacity should be less than 10-50% of the maximum seating capacity to reduce the number of infections depending on the level of imposed social distancing and passenger interaction; (v) vehicles with greater number of occupied seating capacity generate higher number of infections but vehicles with smaller dimensions have faster disease transmissions; and (vi) ideal set-up for a 24-seater train wagon (49-seater bus) is to allow a maximum of 12 (24) passengers, with little to no interaction among passengers, with social distancing of more than 1m distance apart, and each person has a protection with 90% effectiveness as much as possible. These results can aid policy makers in determining optimal strategies to minimize infections while maintaining transportation services during pandemics or disease outbreaks.


The covid-19 outbreak: a Chinese school student’s life in isolation for 73 days


title: Review and methodological analysis of trials currently testing treatment and prevention options for the novel coronavirus disease (COVID-19) globally.

text: Background: As novel coronavirus disease (COVID-19) cases continue to steeply rise globally within an unprecedented short period of time, solid evidence from large randomised controlled trials is still lacking. Currently, numerous trials testing potential treatment and preventative options are undertaken globally. Objectives: We summarised all currently registered clinical trials examining treatment and prevention options for COVID-19 pneumonia. Additionally, we evaluated the quality of the retrieved interventional studies. Data sources: The ClinicalTrials.gov, the Chinese Clinical Trial Registry and the European Union Clinical Trials Register were systematically searched. Study eligibility criteria: Registered clinical trials examining treatment and/or prevention options for COVID-19 were included. No language, country or study design restrictions were applied. Withdrawn, cancelled studies and trials not reporting therapeutic or preventative strategies for COVID-19 were excluded. Participants and interventions: No restrictions in terms of participants' age and medical background or type of intervention were enforced. Methods: The registries were searched using the term "coronavirus" or "COVID-19" from their inception until 26th March 2020. Additional manual search of the registries was also performed. Eligible studies were summarised and tabulated. Interventional trials were methodologically analysed, excluding expanded access studies and trials testing Traditional Chinese Medicine. Results: In total, 309 trials evaluating therapeutic management options, 23 studies assessing preventive strategies and 3 studies examining both were retrieved. Interventional treatment studies were mostly randomised (n=150, 76%) and open-label (n=73, 37%) with a median number of planned inclusions of 90 (IQR 40-200). Major categories of interventions that are currently being investigated are discussed. Conclusion: Numerous clinical trials have been registered since the onset of the COVID-19 pandemic. Summarised data on these trials will assist physicians and researchers to promote patient care and guide future research efforts for COVID-19 pandemic containment. However, up to the end of March, 2020, significant information concerning reported trials was lacking.


docid: iisugydg

title: Certified Coronavirus Immunity as a Resource and Strategy to Cope with Pandemic Costs

text: A pandemic is not only a biological event and a public health disaster, but it also generates impacts that are worth understanding from economic, societal, historical, and cultural perspectives. In this contribution, we argue that as the disease spreads, we are able to harness a valuable key resource_ people who have immunity to coronavirus. This vital resource must be effectively employed, it must be certified, it must be searched for, it must be found, and it may even be actively produced. We discuss why this needs to be done and how this can be achieved. Our arguments not only apply to the current pandemic but also to any future rapidly spreading, infectious disease epidemics. In addition, we argue for high awareness of a major secondary, nonbiological crisis arising from the side effects of societal and economic pandemic reactions to actual or imagined health risks. There is a risk that the impacts of the secondary crisis could outweigh that of the biological event.


title: Design of potent membrane fusion inhibitors against SARS-CoV-2, an emerging coronavirus with high fusogenic activity

text: The coronavirus disease COVID-19, caused by emerging SARS-CoV-2, has posed serious threats to global public health, economic and social stabilities, calling for the prompt development of therapeutics and prophylactics. In this study, we firstly verified that SARS-CoV-2 uses human ACE2 as a cell receptor and its spike (S) protein mediates high membrane fusion activity. Comparing to that of SARS-CoV, the heptad repeat 1 (HR1) sequence in the S2 fusion protein of SARS-CoV-2 possesses markedly increased α-helicity and thermostability, as well as a higher binding affinity with its corresponding heptad repeat 2 (HR1) site. Then, we designed a HR2 sequence-based lipopeptide fusion inhibitor, termed IPB02, which showed highly poent activities in inibibiting the SARS-CoV-2 S protein-mediated cell-cell fusion and pseudovirus infection. IPB02 also inhibited the SARS-CoV pseudovirus efficiently. Moreover, the strcuture and activity relationship (SAR) of IPB02 were characterzized with a panel of truncated lipopeptides, revealing the amino acid motifs critical for its binding and antiviral capacities. Therefore, the presented results have provided important information for understanding the entry pathway of SARS-CoV-2 and the design of antivirals that target the membrane fusion step.


title: There are asymptomatic and pre-symptomatic patients infected with COVID-19. So what? Pandemic response implications

text: Abstract Asymptomatic but infectious people have been reported in many infectious diseases. Asymptomatic and pre-symptomatic carriers would be a hidden reservoir of COVID-19. Aim This review identifies primary empirical evidence about the ability of asymptomatic carriers to infect others with COVID-19 pandemic and reflects on the implications for control measures. Methods A systematic review is followed by a narrative report and commentary inclusion criteria were: studies reporting primary data on asymptomatic or pre-symptomatic patients, who were considered to have passed on COVID-19 infection; and published in indexed journals or in peer review between January 1 and March 31, 2020. Results Nine articles reported on 83 asymptomatic or pre-symptomatic persons. Conclusions The evidence confirms COVID-19 transmission from people who were asymptomatic at the time. A series of implications for health service response are laid out. Keywords: Covid-19, Asymptomatic, Pre-symptomatic, Public Health


title: Low doses of radiation therapy increase the immunosuppressive profile of lung macrophages via IL-10 production and IFNγ/IL-6 suppression: a therapeutic strategy to counteract lung inflammation?

text: Patients with severe COVID-19 have a marked inflammatory state characterized by a cytokine storm syndrome. Severe pneumonia and acute respiratory distress syndrome (ARDS) have been described in 14% of the reported cases. Several therapeutic approaches are under investigation but safety and potential efficacy remain to be determined. Chest irradiation at equivalent doses below 1 Gy has been used successfully in the past to treat pneumonia. However, after the onset of effective antimicrobial agents, the use of low doses in the treatment of patients has been discontinued and the involved mechanism remained unknown. The objective of this study was to determine the mechanism by which low doses of radiation therapy (RT) protect the lung from inflammation. Nerve- and airway-associated macrophages (NAMs) and the pro-versus anti-inflammatory cytokine balance (IL6-IFNγ/IL-10) were recently shown to regulate lung inflammation. Here, we used Toll-like receptor 3 (TLR3) ligand polyinosinic:polycytidylic acid [Poly(I:C)] and lipopolysaccharide (LPS) in human lung macrophages and murine model of lung inflammation for functional assays. Our results show that irradiation of Poly(I:C)-stimulated human lung macrophages in vitro using low doses of RT (0.5-1 Gy) increased IL-10 secretion and decreased IFNγ production in the culture supernatant. The percentage of human lung macrophages producing IL-6 was also decreased in vitro with low doses of RT. Furthermore, using experimental models (LPS- and Poly(I :C)-induced lung inflammation), we showed that chest irradiation using low doses of RT significantly increased the percentage of NAMs producing IL-10, leading to lung protection from inflammation. Altogether, our data highlight one of the mechanisms by which low doses of RT regulate lung inflammation and positively favor anti-inflammatory cytokine secretion by lung macrophages. These data strongly suggest that low doses of RT could be used in order to mitigate lung inflammatory processes in situations such as COVID-19-induced ARDS.


title: Epidemiological impact of SARS-CoV-2 vaccination: mathematical modeling analyses

text: Background: Several SARS-CoV-2 vaccine candidates are currently in the pipeline. This study aims to inform SARS-CoV-2 vaccine development, licensure, decision-making, and implementation by determining key preferred vaccine product characteristics and associated population-level impact. Methods: Vaccination impact was assessed at various efficacies using an age-structured mathematical model describing SARS-CoV-2 transmission and disease progression, with application for China. Results: A prophylactic vaccine with efficacy against acquisition (VEs) of ≥70% is needed to eliminate this infection. A vaccine with VEs <70% will still have a major impact, and may control the infection if it reduces infectiousness or infection duration among those vaccinated who acquire the infection, or alternatively if supplemented with a moderate social-distancing intervention (<20% reduction in contact rate), or complemented with herd immunity. Vaccination is cost-effective. For a vaccine with VEs of 50%, number of vaccinations needed to avert one infection is only 2.4, one severe disease case is 25.5, one critical disease case is 33.2, and one death is 65.1. Gains in effectiveness are achieved by initially prioritizing those ≥60 years. Probability of a major outbreak is virtually zero with a vaccine with VEs ≥70%, regardless of number of virus introductions. Yet, an increase in social contact rate among those vaccinated (behavior compensation) can undermine vaccine impact. Conclusions: Even a partially-efficacious vaccine can offer a fundamental solution to control SARS-CoV-2 infection and at high cost-effectiveness. In addition to the primary endpoint on infection acquisition, developers should assess natural history and disease progression outcomes and/or proxy biomarkers, since such secondary endpoints may prove critical in licensure, decision-making, and vaccine impact.


title: Clinical Manifestations of Children with COVID-19: a Systematic Review

text: Context: The coronavirus disease 2019 (COVID-19) outbreak is an unprecedented global public health challenge, leading to thousands of deaths every day worldwide. Despite the epidemiological importance, clinical patterns of children with COVID-19 remain unclear. Objective: To describe the clinical, laboratorial and radiological characteristics of children with COVID-19. Data Sources: The Medline database was searched between December 1st 2019 and March 30th 2020. Study Selection: Inclusion criteria were: (1) studied patients younger than 18 years old; (2) presented original data from cases of COVID-19 confirmed by reverse-transcription polymerase chain reaction; and (3) contained descriptions of clinical manifestations, laboratory tests or radiological examinations. Data Extraction: Number of cases, gender, age, clinical manifestations, laboratory tests, radiological examinations and outcomes. Results: A total of 34 studies (1,118 cases) were included. From all the cases, 1,111 had their severity classified: 14.3% were asymptomatic, 36.4% were mild, 46.0% were moderate, 2.2% were severe and 1.2% were critical. The most prevalent symptom was fever (16.3%), followed by cough (14.4%), nasal symptoms (3.6%), diarrhea (2.7%) and nausea/vomiting (2.5%). One hundred forty-five (12.9%) children were diagnosed with pneumonia and 43 (3.8%) upper airway infections were reported. Reduced lymphocyte count were reported in 13.1% of cases. Abnormalities on computed tomography was reported in 62.7% of cases. The most prevalent abnormalities reported were ground glass opacities, patchy shadows and consolidations. Only one death was reported. Conclusions: Clinical manifestations of children with COVID-19 differ widely from adults cases. Fever and respiratory symptoms should not be considered a hallmark of COVID-19 in children.


title: Comprehensive Testing Highlights Racial, Ethnic, and Age Disparities in the COVID-19 Outbreak

text: The United States (US), which is currently the epicenter for the COVID-19 pandemic, is a country whose demographic composition differs from that of other highly-impacted countries. US-based descriptions of SARS-CoV-2 infections have, for the most part, focused on patient populations with severe disease, captured in areas with limited testing capacity. The objective of this study is to compare characteristics of positive and negative SARS-CoV-2 patients, in a population primarily comprised of mild and moderate infections, identified from comprehensive population-level testing. Here, we extracted demographics, comorbidities, and vital signs from 20,088 patients who were tested for SARS-CoV-2 at University of Utah Health clinics, in Salt Lake County, Utah; and for a subset of tested patients, we performed manual chart review to examine symptoms and exposure risks. To determine risk factors for testing positive, we used logistic regression to calculate the odds of testing positive, adjusting for symptoms and prior exposure. Of the 20,088 individuals, 1,229 (6.1%) tested positive for SARS-CoV-2. We found that Non-White persons were more likely to test positive compared to non-Hispanic Whites (adjOR=1.1, 95% CI: 0.8, 1.6), and that this increased risk is more pronounced among Hispanic or Latino persons (adjOR=2.0, 95%CI: 1.3, 3.1). However, we did not find differences in the duration of symptoms nor type of symptom presentation between non-Hispanic White and non-White individuals. We found that risk of hospitalization increases with age (adjOR=6.9 95% CI: 2.1, 22.5 for age 60+ compared to 0-19), and additionally show that younger individuals (aged 0-19), were underrepresented both in overall rates of testing as well as rates of testing positive. We did not find major race/ethnic differences in hospitalization rates. In this analysis of predominantly non-hospitalized individuals tested for SARS-CoV-2, enabled by expansive testing capacity, we found disparities in both testing and SARS-CoV-2 infection status by race/ethnicity and by age. Further work on addressing racial and ethnic disparities, particularly among Hispanic/Latino communities (where SARS-CoV-2 may be spreading more rapidly due to increased exposure and comparatively reduced testing), will be needed to effectively combat COVID-19 in the US.


title: From Community Acquired Pneumonia to COVID-19: A Deep Learning Based Method for Quantitative Analysis of COVID-19 on thick-section CT Scans

text: Background: Thick-section CT scanners are more affordable for the developing countries. Considering the widely spread COVID-19, it is of great benefit to develop an automated and accurate system for quantification of COVID-19 associated lung abnormalities using thick-section chest CT images. Purpose: To develop a fully automated AI system to quantitatively assess the disease severity and disease progression using thick-section chest CT images. Materials and Methods: In this retrospective study, a deep learning based system was developed to automatically segment and quantify the COVID-19 infected lung regions on thick-section chest CT images. 531 thick-section CT scans from 204 patients diagnosed with COVID-19 were collected from one appointed COVID-19 hospital from 23 January 2020 to 12 February 2020. The lung abnormalities were first segmented by a deep learning model. To assess the disease severity (non-severe or severe) and the progression, two imaging bio-markers were automatically computed, i.e., the portion of infection (POI) and the average infection HU (iHU). The performance of lung abnormality segmentation was examined using Dice coefficient, while the assessment of disease severity and the disease progression were evaluated using the area under the receiver operating characteristic curve (AUC) and the Cohen's kappa statistic, respectively. Results: Dice coefficient between the segmentation of the AI system and the manual delineations of two experienced radiologists for the COVID-19 infected lung abnormalities were 0.74 {+/-} 0.28 and 0.76 {+/-} 0.29, respectively, which were close to the inter-observer agreement, i.e., 0.79 {+/-} 0.25. The computed two imaging bio-markers can distinguish between the severe and non-severe stages with an AUC of 0.9680 (p-value < 0.001). Very good agreement ({kappa} = 0.8220) between the AI system and the radiologists were achieved on evaluating the changes of infection volumes. Conclusions: A deep learning based AI system built on the thick-section CT imaging can accurately quantify the COVID-19 associated lung abnormalities, assess the disease severity and its progressions.


title: Predictors of Anxiety Regarding The COVID-19 Pandemic Among Health-care Workers in a Hospital Not Assigned to Manage COVID-19 Patients in Nepal.

text: Introduction: We studied the levels and severity of anxiety caused by COVID-19 amongst frontline health-care workers (HCWs) in a tertiary care neurological hospital in Nepal, not assigned to manage COVID-19 cases. Methods: A cross-sectional study was conducted on 100 frontline Health Care Workers (HCWs) using a 10-point subjective assessment tool, the Anxiety Level Index (ALI), and the Zung Self Rating Anxiety Score (SAS), to assess the level of anxiety regarding COVID-19. Results: On ALI 55% of HCWs were found to have marked severe anxiety (6-9), however, on SAS 44% of HCWs reported anxiety. The majority HCWs were female (n=78) with nurses forming 62% of the sample size. The mean age was 26.8 years (SD 8.17). Factors associated with significantly higher levels of anxiety regarding COVID-19 on ALI were age (p=0.002), sex (p=0.001), receiving regular COVID-19 updates via social media (p=0.011) and a high frequency of checking for COVID-19 information authenticity (p=0.039). Work experience (p=0.026) and frequency of checking for information authenticity (p=0.029) were factors found to increase SAS measured anxiety and were found to be associated with significantly higher levels of anxiety. Multivariate logistic regression analysis showed that respondents with work experience of less than or equal to 2 years were 0.380 (95% CI 0.158 to 0.910) times less likely to have anxiety than those with work experience of more than 2 years. Similarly, the odds of having anxiety among those who checked information authenticity less frequently was 0.377 (95% CI 0.153 to 0.931) times less than those who often did. Conclusion: The COVID-19 outbreak has caused a substantial impact on the mental health of frontline HCWs in a hospital not assigned to manage COVID-19 patients. Length of time of worked in healthcare and the frequency of checking for COVID-19-related information were significant predictors of anxiety.


title: 44 GHz methanol masers: Observations toward 95 GHz methanol masers

text: We report a simultaneous 44 and 95 GHz class I methanol maser survey toward 144 sources from the 95 GHz class I methanol maser catalog. The observations were made with the three telescopes of the Korean very long baseline interferometry network operating in single-dish mode. The detection rates are 89% at 44 GHz and 77% at 95 GHz. There are 106 new discoveries at 44 GHz. Comparing the previous 95 GHz detections with new observations of the same transitions made using the Purple Mountain Observatory 13.7 m radio telescope shows no clear evidence of variability on a timescale of six years. Emission from the 44 and 95 GHz transitions shows strong correlations in peak velocity, peak flux density, and integrated flux density, indicating that they are likely cospatial. We found that the peak flux density ratio Spk,95/Spk,44 decreases as the 44 GHz peak flux density increases. We found that some class I methanol masers in our sample could be associated with infrared dark clouds, while others are associated with H II regions, indicating that some sources occur at an early stage of high-mass star formation, while others are located toward more evolved sources.


title: How COVID-19 changed our food systems and food security paradigms

text: [Figure: see text]


docid: viwochvv

title: Modelling strategies to organize healthcare workforce during pandemics: application to COVID-19

text: Protection of healthcare workforce is of paramount relevance for the care of infected and non-infected patients in the setting of a pandemic such as coronavirus disease 2019 (COVID-19). Healthcare workers are at increased risk to become infected because of contact to infected patients, infected co-workers and their community outside the hospital. The ideal organisational strategy to protect the healthcare workforce in a situation in which social distancing cannot be maintained at the workplace remains to be determined. In this study, we have mathematically modelled strategies for the employment of hospital workforce with the goal to simulate health and productivity of the workers. Therefore, deterministic models were extended to account for stochastic influences potentially occurring in rather small populations. The models were also designed to determine if desynchronization of medical teams by dichotomizing the workers may protect the workforce. Our studies model workforce productivity depending on the infection rate, the presence of reinfection and the efficiency of home office. As an application example, we apply our theory to the case of coronavirus disease 2019 (COVID-19). The results of the models reveal that a desynchronization strategy in which two medical teams work alternating for 7 days reduces the infection rate of the healthcare workforce. In case of immunity to the infectious agent this affect is mainly relevant at early stages of the pandemic. This effect is independent on infection rates and increases the overall workforce productivity under certain situations.


title: On Leadership: Responding to COVID-19: Short- and long-term challenges

text: In the early days of the COVID-19 outbreak, school district leaders’ most immediate priority was to ensure that students have access to regular meals. However, efforts to provide a range of other social services must follow close behind. As a start, superintendents can look to their data systems to help them identify those students and families that are most likely to need social services to make it through this phase and beyond. But even while racing to ensure students’ health and safety, they cannot afford to ignore the longer-term challenges that their districts will face, given not just the need to move instruction online but also given that COVID-19 is all but guaranteed to do serious damage to state and local economies.


title: The end of the social confinement in Spain and the COVID-19 re-emergence risk

text: After the spread of SARS-CoV-2 epidemic out of China, the world approaches the 2 million declared infected cases and death toll rises well above the 100 thousand. The course of pandemic evolution has shown great differences among countries and not much is yet known about the level of generated immunity, which might appear not to be long-lasting. In this situation, management of a recurrent disease seems to be a plausible scenario that countries worldwide will have to face, before effective drugs or a vaccine appear. Spain in Europe, appears to be the first country deciding to partly lift the strict social distancing regulations imposed. Whether this action may lead to further epidemic recrudescence, to a following second wave of cases or conversely, help return to previous normality, is a subject of great debate and interest to all other countries affected by COVID-19. Here we applied a modified SEIR compartmental model accounting for the spread of infection during the latent period, in which we had also incorporated effects of social confinement. We now modify this previous model configuration to mimic potential post-confinement scenarios, by simulating from instant massive liberation of different portions of the confined population, up to a more gradual incorporation of people to work. Results show how current lockdown conditions should be extended at least two weeks more to prevent a new escalation in cases and deaths, as well as a larger second wave occurring in just a few months. Conversely, best-case scenario in terms of lower COVID-19 incidence and casualties should gradually incorporate workers back in a daily proportion at most 30 percent higher than that of previous confinement. The former should begin not earlier than by the end of April and it would represent approximately 600 thousand people or a 3.75% rate for the whole of Spain.


title: Development and Utilization of a Rapid and Accurate Epidemic Investigation Support System for COVID-19

text: OBJECTIVES: In this pandemic situation caused by a novel coronavirus disease in 2019 (COVID-19), an electronic support system that can rapidly and accurately perform epidemic investigations, is needed. It would systematically secure and analyze patients’ data (who have been confirmed to have the infection), location information, and credit card usage. METHODS: The “Infectious Disease Prevention and Control Act” in South Korea, established a legal basis for the securement, handling procedure, and disclosure of information required for epidemic investigations. The Epidemic Investigation Support System (EISS) was developed as an application platform on the Smart City data platform. RESULTS: The EISS performed the function of inter-institutional communication which reduced the processing period of patients’ data in comparison to other methods. This system automatically marked confirmed cases’ tracking data on a map and hot-spot analysis which lead to the prediction of areas where people may be vulnerable to infection. CONCLUSION: The EISS was designed and implemented for use during an epidemic investigation to prevent the spread of an infectious disease, by specifically tracking confirmed cases of infection.


title: CIRD-F: Spread and Influence of COVID-19 in China

text: The outbreak of coronavirus disease 2019 (COVID-19) has been spreading rapidly in China and the Chinese government took a series of policies to control the epidemic. Therefore, it will be helpful to predict the tendency of the epidemic and analyze the influence of official policies. Existing models for prediction, such as cabin models and individual-based models, are either oversimplified or too meticulous, and the influence of the epidemic was studied much more than that of official policies. To predict the epidemic tendency, we consider four groups of people, and establish a propagation dynamics model. We also create a negative feedback to quantify the public vigilance to the epidemic. We evaluate the tendency of epidemic in Hubei and China except Hubei separately to predict the situation of the whole country. Experiments show that the epidemic will terminate around 17 March 2020 and the final number of cumulative infections will be about 78 191 (prediction interval, 74 872 to 82 474). By changing the parameters of the model accordingly, we demonstrate the control effect of the policies of the government on the epidemic situation, which can reduce about 68% possible infections. At the same time, we use the capital asset pricing model with dummy variable to evaluate the effects of the epidemic and official policies on the revenue of multiple industries.


title: DIAGNOSTICO Y TRATAMIENTO LOCORREGIONAL DE LAS PACIENTES CON CANCER DE MAMA DURANTE LA PANDEMIA DE LA COVID-19

text: Resumen Nos enfrentamos a una pandemia que afecta a una parte importante de la población. A finales de abril de 2020, en el mundo hay cerca de 3.000.000 de casos, con 205.000 muertes y 860.000 pacientes recuperados La respuesta a esta pandemia en muchos casos ha supuesto modificaciones importantes en el cuidado diario de las pacientes con cáncer, dependiendo el buen resultado en buena parte del ajuste de los protocolos a las circunstancias especiales y a los tratamientos multidisciplinarios Presentamos una revisión del tratamiento quirúrgico y radioterapia junto con las recomendaciones de los autores basadas en su experiencia personal a la hora del diagnóstico y tratamiento locorregional del cáncer de mama durante la pandemia del COVID-19 Los comités multidisciplinarios deben seguir reuniéndose semanalmente en formato de videoconferencia. Todos las intervenciones quirúrgicas e irradiaciones deben ser llevadas a cabo con la máxima seguridad tanto para las pacientes como para el personal sanitario que participa. El hipofraccionamiento debe ser el tratamiento radioterápico estándar. En algunos casos se utilizará tratamiento sistémico primario o incluso radioterapa preoperatoria. Es esencial una coordinación importante entre los equipos quirúrgicos y los oncológicos, tanto radioterápicos como médicos. Abstract We are facing a pandemic that is going to affect a significant part of the population. At the end of April in the world there are about 3,000,000 cases, with 205,000 deaths and 860,000 patients recovered. The response to this pandemic has in many cases led to a significant change in the daily work of caring for cancer patients, the good results of which depend largely on time-adjusted protocols and multidisciplinary treatments. We present a review of local, surgical and radiotherapy treatment together with authors' recommendations made from personal experience on ways to act in the diagnosis and surgical treatment of breast cancer during the COVID-19 pandemic. The multidisciplinary Breast Committees must continue to meet weekly in videoconference format. All surgical actions and irradiations must be carried out with maximum safety for both the patients and the participating teams. Hypofractionation in radiation therapy should be the standard treatment. Sometimes it is recommended to apply a primary systemic treatment or even a primary irradiation. Great coordination between the surgical and oncology teams, both medical and radiotherapeutic, is essential.


title: Functional alteration of innate T cells in critically ill Covid-19 patients

text: Covid-19 can induce lung infection ranging from mild pneumonia to life-threatening acute respiratory distress syndrome (ARDS). Dysregulated host immune response in the lung is a key feature in ARDS pathophysiology. However, cellular actors in Covid-19-driven ARDS are poorly understood. Here, we dynamically analyzed the biology of innate T cells, a heterogeneous class (MAIT, {gamma}{delta}T and iNKT cells) of T lymphocytes, presenting potent anti-infective and regulatory functions. Patients presented a compartmentalized lung inflammation paralleled with a limited systemic inflammation. Circulating innate T cells of critically ill Covid-19 patients presented a profound and persistent phenotypic and functional alteration. Highly activated innate T cells were detected in airways of patients suggesting a recruitment to the inflamed site and a potential contribution in the regulation of the local inflammation. Finally, the expression of the CD69 activation marker on blood iNKT and MAIT cells at inclusion was predictive of disease severity. Thus, patients present an altered innate T cell biology that may account for the dysregulated immune response observed in Covid-19-related acute respiratory distress syndrome.


title: 68 Consecutive patients assessed for COVID-19 infection; experience from a UK regional infectious disease unit

text: Clinical assessment of possible infection with SARS-CoV-2, the novel coronavirus responsible for the outbreak of COVID-19 respiratory illness, has been a major activity of infectious diseases services in the UK and elsewhere since the first report of cases in December 2019. We report our case series of 68 patients, reviewed by Infectious Diseases Consultants at a Regional Infectious Diseases Unit in the UK. We prospectively evaluated our service between the 29th Jan 2020 and 24th Feb 2020. Demographic, clinical, epidemiological and laboratory data were collected. We have compared clinical features and subsequent diagnosis between well patients not requiring admission for clinical reasons or antimicrobials with those assessed as needing either admission or antimicrobial treatment. Final microbiological diagnoses included SARS-CoV-2 (COVID-19), Mycoplasma pneumonia, influenza A, RSV, non SARS/MERS coronaviruses, rhinovirus/enterovirus. 9/68 were treated with antimicrobials, 15/68 were admitted to a negative pressure room of whom 5/68 were admitted solely due to an inability to isolate at home. Patients requiring either admission on clinical grounds or antimicrobials (14/68) were similar to those not requiring admission or antimicrobials, with modestly more fever and shortness of breath in the clinically admitted / antimicrobial group. The most commonly prescribed antimicrobials were doxycycline, moxifloxacin and oseltamivir. The majority of patients had mild illness which did not require a clinical intervention to manage. This finding supports a community testing approach supported by clinicians to review the proportion of more unwell patients.


title: Untangling factors associated with country-specific COVID-19 incidence, mortality and case fatality rates during the first quarter of 2020

text: At early stages of the COVID-19 pandemic which we are experiencing, the publicly reported incidence, mortality and case fatality rates (CFR) vary significantly between countries. Here we aim to untangle factors that are associated with the differences during the first quarter of the year 2020. Number of performed COVID-19 tests has a strong correlation with country-specific incidence (p <2×10-16) and mortality rate (p = 5.1×10-8). Using multivariate linear regression we show that incidence and mortality rates correlate significantly with GDP per capita (p = 2.6×10-15 and 7.0×10-4, respectively), country-specific duration of the outbreak (2.6×10-4 and 0.0019), fraction of citizens over 65 years old (p = 0.0049 and 3.8×10-4) and level of press freedom (p = 0.021 and 0.019) which cumulatively explain 80% of variability of incidence and more than 60% of variability of mortality of the disease during the period analyzed. Country hemisphere demonstrated significant correlation only with mortality (p = 0.17 and 0.036) whereas population density (p = 0.94 and p = 0.75) and latitude (p = 0.61 and 0.059) did not reach significance in our model. Case fatality rate is shown to rise as the outbreak progresses (p = 0.028). We rank countries by COVID-19 mortality corrected for incidence and the factors that were shown to affect it, and by CFR corrected for outbreak duration, yielding very similar results. Among the countries where the outbreak started after the 15th of February and with at least 1000 registered patients during the period analyzed, the lowest corrected CFR are seen in Israel, South Africa and Chile. The ranking results should be considered with caution as they do not consider all confounding factors or data reporting biases.


title: Geo temporal distribution of 1,688 Chinese healthcare workers infected with COVID-19 in severe conditions, a secondary data analysis

text: Introduction The COVID 19 outbreak is posing an unprecedented challenge to healthcare workers. This study analyzes the geo temporal effects on disease severity for the 1,688 Chinese healthcare workers infected with COVID 19. Method Using the descriptive results recently reported by the Chinese CDC, we compare the percentage of infected healthcare workers in severe conditions over time and across three areas in China, and the fatality rate of infected healthcare workers with all the infected individuals in China aged 22 to 59 years. Results Among the infected Chinese healthcare workers whose symptoms onset appeared during the same ten day period, the percentage of those in severe conditions decreased statistical significantly from 19.7% (Jan 11 to 20) to 14.4% (Jan 21 to 31) to 8.7% (Feb 1 to 11). Across the country, there was also a significant difference in the disease severity among patients symptoms onset during the same period, with Wuhan being the most severe (17%), followed by Hubei Province (10.4%), and the rest of China (7.0%). The case fatality rate for the 1,688 infected Chinese healthcare workers was significantly lower than that for the 29,798 infected patients aged 20 to 59 years 0.3% (5/1,688) vs. 0.65% (193/29,798), respectively. Conclusion The disease severity improved considerably over a short period of time in China. The more severe conditions in Wuhan compared to the rest of the country may be attributable to the draconian lockdown. The clinical outcomes of infected Chinese healthcare workers may represent a more accurate estimation of the severity of COVID 19 for those who have access to quality healthcare.


title: A Model of Workflow in the Hospital During a Pandemic to Assist Management

text: We present a computational model of workflow in the hospital during a pandemic. The objective is to assist management in anticipating the load of each care unit, such as the ICU, or ordering supplies, such as personal protective equipment, but also to retrieve key parameters that measure the performance of the health system facing a new crisis. The model was fitted with good accuracy to France's data set that gives information on hospitalized patients and is provided online by the French government. The goal of this work is both practical in offering hospital management a tool to deal with the present crisis of COVID-19 and offering a conceptual illustration of the benefit of computational science during a pandemic.


title: Dynamic profile of severe or critical COVID-19 cases

text: In December 2019, a cluster of acute respiratory illness, now known as SARS-CoV-2 pneumonia, occurred in Wuhan, China. World Health Organization (WHO) declared the rapidly spreading coronavirus outbreak a pandemic on March 11, 2020, acknowledging what has seemed clear for some time-the virus will likely spread to all countries on the globe. As of February 11, 2020, the Chinese Center for Disease Control and Prevention (China CDC) has officially reported that there are 2.0% (889) asymptomatic cases, 2.3% (1,023) death cases, and 80.9% mild cases among 44,672 confirmed cases. 51.4% (22,981) were male and 48.6% (21,691) were female. Lymphopenia, in particular T lymphopenia, was common among patients with SARS-COV-2 in the observation. A notable drop in CD4 and CD8 lymphocyte counts occurred early in the course of the syndrome and was associated with adverse outcomes. The appearing a phenomenon of lymphocyte depletion (PLD) suggested severe adverse outcomes. The outcome observed: 60% had discharged and 20% had die.


title: Laboratory-based surveillance of COVID-19 in the Greater Helsinki area, Finland, February-June 2020

text: Laboratory registry data (80,791 specimens, 70,517 individuals) was used to characterise age- and sex-specific SARS-CoV-2 RT-PCR sampling frequency and positivity rate, and laboratory capacity building in Greater Helsinki, Finland during February-June 2020. While the number of positive cases was similar in males and females, the positivity rate was significantly higher in males. The highest incidence/100,000 was observed in those aged [≥]80 years. The proportion of young adults in positive cases increased in late May 2020.


title: COVID-19 und die Niere

text: The drastic consequences that emerging infectious diseases can have for people and society are currently being demonstrated by coronavirus disease 2019 (COVID-19). Since its initial description in December 2019 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has dominated current scientific and public interest.


title: Chest low-dose CT in auxiliary diagnosis of corona virus disease 2019/ 胸部低剂量CT辅助诊断新型冠状病毒肺炎

text: Objective: To observe the clinical application value of chest low-dose CT (LDCT) in auxiliary diagnosis of corona virus disease 2019 (COVID-19). Methods: Totally 50 COVID-19 patients with positive 2019 novel coronavirus nucleic acid test of pharynx swabs were selected. All patients underwent routine dose chest CT examination on the first time (routine dose group), and followed chest LDCT for the review examination after treatment (LD group). The image quality of was evaluated by 2 imaging doctors. Kappa test was used to analyze the consistency of the image quality Results: of 2 groups evaluated by the two physicians. The X-ray radiation dose of the two CT scanning schemes were compared. Results: The consistency of image quality scores of 2 groups evaluated by 2 physicians was relatively high (Kappa=0.65, P<0.05). There was no significant difference of image quality between LD group and routine dose group (Z=-0.93, P=0.35). The effective radiation dose (ED)in LD group ([2.43±0.66]mSv) reduced by 39.55% (t=0.85, P<0.01) compared with that of the routine dose group ([4.02±1.03]mSv). Conclusion: Chest LDCT scan can be used for clinical screening and auxiliary diagnosis of COVID-19, which can ensure the image quality, meet clinical diagnosis requirements and reduce the dose of X-ray radiation.


title: When the storm is the strongest: The health conditions and job satisfaction of Healthcare staff and their associated predictors during the epidemic peak of COVID-19

text: This study reports the physical health, mental health, anxiety, depression, distress, and job satisfaction of healthcare staff in Iran when the country faced its highest number of total active COVID-19 cases. In a sample of 304 healthcare staff (doctors, nurses, radiologists, technicians, etc.), we found a sizable portion reached the cutoff levels of disorders in anxiety (28.0%), depression (30.6%), and distress (20.1%). Age, gender, education, access to PPE (personal protective equipment), healthcare institutions (public vs. private), and individual status of COVID-19 infection each predicted some but not all the outcome variables of SF-12, PHQ-4, K6, and job satisfaction. The healthcare workers varied greatly in their access to PPE and in their status of COVID-19 infection: negative (69.7%), unsure (28.0%), and positive (2.3%). The predictors were also different from those identified in previous studies of healthcare staff during the COVID-19 crisis in China. This study helps to identify the healthcare staff in need to enable more targeted help as healthcare staff in many countries are facing peaks in their COVID-19 cases.


title: Efferent Synaptic Transmission at the Vestibular Type II Hair Cell Synapse

text: In the vestibular peripheral organs, type I and type II hair cells (HCs) transmit incoming signals via glutamatergic quantal transmission onto afferent nerve fibers. Additionally, type I HCs transmit via ‘non-quantal’ transmission to calyx afferent fibers, by accumulation of glutamate and potassium in the synaptic cleft. Vestibular efferent inputs originating in the brainstem contact type II HCs and vestibular afferents. Here, we aimed at characterizing the synaptic efferent inputs to type II HCs using electrical and optogenetic stimulation of efferent fibers combined with in vitro whole-cell patch clamp recording from type II HCs in the rodent vestibular crista. Properties of efferent synaptic currents in type II HCs were similar to those found in cochlear hair cells and mediated by activation of α9/α10 nicotinic acetylcholine receptors (AChRs) and SK potassium channels. While efferents showed a low probability of release at low frequencies of stimulation, repetitive stimulation resulted in facilitation and increased probability of release. Notably, the membrane potential of type II HCs measured during optogenetic stimulation of efferents showed a strong hyperpolarization even in response to single pulses and was further enhanced by repetitive stimulation. Such efferent-mediated inhibition of type II HCs can provide a mechanism to adjust the contribution of signals from type I and type II HCs to vestibular nerve fibers. As a result, the relative input of type I hair cells to vestibular afferents will be strengthened, emphasizing the phasic properties of the incoming signal that are transmitted via fast non-quantal transmission. New and Noteworthy Type II vestibular hair cells (HCs) receive inputs from efferent fibers originating in the brainstem. We used in vitro optogenetic and electrical stimulation of efferent fibers to study their synaptic inputs to type II HCs. Efferent inputs inhibited type II HCs, similar to cochlear efferent effects. We propose that efferent inputs adjust the contribution of signals from type I and type II HCs that report different components of the incoming signal to vestibular nerve fibers.


Reaction Engineering during corona times/ Reaktionstechnik in Corona-Zeiten


docid: hhpnewdt

title: Global Infodemiology of COVID-19: Focus on Google web searches and Instagram hashtags

text: Background: Several studies have been conducted using 'infodemiological' methods in COVID-19 research, but studies focusing to examine the extent of infodemic monikers (misinformation) on the internet is very limited. Aim: We aimed to investigate the internet search behavior related to COVID-19 and the extent of infodemic monikers circulating in Google and Instagram during the pandemic period in the world. Methods: Using Google Trends and Instagram hashtags (#), we explored the internet search activities and behaviors related to COVID-19 pandemic all over the world from February 20, 2020, to May 06, 2020. Briefly, we investigated the names used to identify the virus, health and risk perception, life during the lockdown, and also information related to the adoption of infodemic monikers related to COVID-19. We computed the average peak volume (APC) with a 95% confidence interval (CI) during the study period. Results: The top five COVID-19 related terms used in Google searches were "coronavirus", "corona", "COVID", "virus", "corona virus", and "COVID-19". Countries with a higher number of COVID-19 cases have greater Google searches queries related to COVID-19. "coronavirus ozone", "coronavirus laboratory", "coronavirus 5G", "coronavirus conspiracy" and "coronavirus bill gates" are widely circulated infodemic monikers on the internet. Searches related to 'tips and cures' to COVID-19 spiked when the US president suggested an unproven drug as a 'miracle cure' and suggested injecting disinfectant to treat COVID-19. Around two-thirds (66.1%) of the Instagram users use "COVID-19", and "coronavirus" hashtags to disperse the information related to COVID-19. Conclusion: Globally, there is a growing interest in COVID-19 and a large number of infodemic monikers are circulating on the internet. Therefore, mass media regulators and health organizers should be vigilant to diminish the infodemic monikers dispersing on the internet and also should take serious actions against those spreading misinformation in social media.


title: Fully automatic deep convolutional approaches for the analysis of Covid-19 using chest X-ray images

text: Covid-19 is a new infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Given the seriousness of the situation, the World Health Organization declared a global pandemic as the Covid-19 rapidly around the world. Among its applications, chest X-ray images are frequently used for an early diagnostic/screening of Covid-19 disease, given the frequent pulmonary impact in the patients, critical issue to prevent further complications caused by this highly infectious disease. In this work, we propose complementary fully automatic approaches for the classification of chest X-ray images under the analysis of 3 different categories: Covid-19, pneumonia and healthy cases. Given the similarity between the pathological impact in the lungs between Covid-19 and pneumonia, mainly during the initial stages of both lung diseases, we performed an exhaustive study of differentiation considering different pathological scenarios. To face these classification tasks, we exploited and adapted to this topic a densely convolutional network architecture, which connects each layer to every other layer in a feed-forward fashion. To validate the designed approaches, several representative experiments were performed using images retrieved from different public chest X-ray images datasets. Overall, satisfactory results were obtained from the designed experiments, facilitating the doctors' work and allowing better an early diagnostic/screening and treatment of this relevant pandemic pathology.


title: Heat inactivation of the Severe Acute Respiratory Syndrome Coronavirus 2

text: Supernatants of cells infected with SARS-CoV-2, nasopharyngeal and sera samples containing SARS-CoV-2 were submitted to heat inactivation for various periods of time, ranging from 30 seconds to 60 minutes. Our results showed that SARS-CoV-2 could be inactivated in less than 30 minutes, 15 minutes and 3 minutes at 56°C, 65°C and 95°C respectively. These data could help laboratory workers to improve their protocols with handling of the virus in biosafety conditions.


title: A Model for the Testing and Tracing Needed to Suppress COVID-19

text: This paper presents a simple mathematical model that answers how much testing and tracing we need to do to suppress new surges of COVID-19 infections after reopening. We derived the model by modifying the SEIR model taking into the effects of testing and tracing. The following equation is one of the essential outcomes of the model: {rho}>(R0S/N-1)/(D(1+{eta}R0)) Where {rho} is the percentage of infectious people that have to be detected per day, R0 is the basic reproduction number, S/N is the percentage of the susceptible population over the entire population, D is the length of the infectious period, and {eta} is the percentage of close contacts that have to be traced. If the above equation is satisfied, we can bring the effective reproduction number Re to below 1 to get the transmission suppressed. This model demonstrates that together with social-distancing measures such as wearing masks in public, with a reasonable amount of testing and tracing, we may suppress the COVID-19 transmission for good. For example, if social distancing measures can bring R0 to below 1.2, for D being 10 days, in places where 15% people have developed antibodies, we can suppress the transmission by detecting only 0.13% of the infectious population daily while tracing 50% of their close contacts. The model provides intuitive insights and quantitative guidance for policymakers and public health practitioners to deploy the testing and tracing resources optimally.


title: Population simulations of COVID-19 outbreaks provide tools for risk assessment and continuity planning

text: Essential industrial sectors, healthcare systems, and government agencies must continue operations despite the risk of COVID-19 infection. They need tools to assess risks associated with operations, so they can devise emergency plans. We developed a population-based simulator to study COVID-19 outbreaks in enclosed environments and evaluate the effectiveness of preventative measures and action plans, such as pre-dispatch quarantine and removal of symptomatic cases.


title: State-of-the-art tools to identify druggable protein ligand of SARS-CoV-2

text: INTRODUCTION: The SARS-CoV-2 (previously 2019-nCoV) outbreak in Wuhan, China and other parts of the world affects people and spreads coronavirus disease 2019 (COVID-19) through human-to-human contact, with a mortality rate of > 2%. There are no approved drugs or vaccines yet available against SARS-CoV-2. MATERIAL AND METHODS: State-of-the-art tools based on in-silico methods are a cost-effective initial approach for identifying appropriate ligands against SARS-CoV-2. The present study developed the 3D structure of the envelope and nucleocapsid phosphoprotein of SARS-CoV-2, and molecular docking analysis was done against various ligands. RESULTS: The highest log octanol/water partition coefficient, high number of hydrogen bond donors and acceptors, lowest non-bonded interaction energy between the receptor and the ligand, and high binding affinity were considered for the best ligand for the envelope (mycophenolic acid: log P = 3.00; DG = –10.2567 kcal/mol; pKi = 7.713 µM) and nucleocapsid phosphoprotein (1-[(2,4-dichlorophenyl)methyl]pyrazole-3,5-dicarboxylic acid: log P = 2.901; DG = –12.2112 kcal/mol; pKi = 7.885 µM) of SARS-CoV-2. CONCLUSIONS: The study identifies the most potent compounds against the SARS-CoV-2 envelope and nucleocapsid phosphoprotein through state-of-the-art tools based on an in-silico approach. A combination of these two ligands could be the best option to consider for further detailed studies to develop a drug for treating patients infected with SARS-CoV-2, COVID-19.


title: Angiotensin-converting enzyme 2 (ACE2) expression increases with age in patients requiringmechanical ventilation.

text: Mortality due to Covid-19 is highly associated with advanced age, owing in large part to severe lower respiratory tract infection. SARS-CoV-2 utilizes the host ACE2 receptor for infection. Whether ACE2 abundance in the lung contributes to age-associated vulnerability is currently unknown. We set out to characterize the RNA and protein expression profiles of ACE2 in aging human lung in the context of phenotypic parameters likely to affect lung physiology. Examining publicly available RNA sequencing data, we discovered that mechanical ventilation is a critical variable affecting lung ACE2 levels. Therefore, we investigated ACE2 protein abundance in patients either requiring mechanical ventilation or spontaneously breathing. ACE2 distribution and expression were determined in archival lung samples by immunohistochemistry (IHC). Tissues were selected from the specimen inventory at a large teaching hospital collected between 2010-2020. Twelve samples were chosen from patients receiving mechanical ventilation for acute hypoxic respiratory failure (AHRF). Twenty samples were selected from patients not requiring ventilation. We compared samples across age, ranging from 40-83 years old in the ventilated cohort and 14-80 years old in the non-ventilated cohort. Within the alveolated parenchyma, ACE2 expression is predominantly observed in type II pneumocytes (or alveolar type II / AT2 cells) and alveolar macrophages. All 12 samples from our ventilated cohort showed histologic features of diffuse alveolar damage including reactive, proliferating AT2 cells. In these cases, ACE2 was strongly upregulated with age when normalized to lung area (p = 0.004) or cellularity (p = 0.003), associated with prominent expression in AT2 cells. In non-ventilated individuals, AT2 cell reactive changes were not observed and ACE2 expression did not change with age when normalized to lung area (p = 0.231) or cellularity (p = 0.349). Additionally, we observed prominent pulmonary endothelial ACE2 expression in 2 patients on either an angiotensin-converting enzyme inhibitor (ACEI) or angiotensin receptor blocker (ARB). In summary, ACE2 expression increases with age in the setting of alveolar damage observed in patients on mechanical ventilation, providing a potential mechanism for higher Covid-19 mortality in the elderly.


title: Predictive usefulness of PCR testing in different patterns of Covid-19 symptomatology - Analysis of a French cohort of 12,810 outpatients

text: Polymerase Chain reaction (PCR) is a key tool to diagnose Covid-19. Yet access to PCR is often limited. In this paper, we develop a clinical strategy for prescribing PCR to patients based on data from COVIDOM, a French cohort of 54,000 patients with clinically suspected Covid-19 including 12,810 patients tested by PCR. Using a machine learning algorithm (a decision tree), we show that symptoms alone are sufficient to predict PCR outcome with a mean average precision of 86%. We identify combinations of symptoms that are predictive of PCR positivity (90% for anosmia/ageusia) or negativity (only 30% of PCR+ for a subgroup with cardiopulmonary symptoms): in both cases, PCR provides little added diagnostic value. We deduce a prescribing strategy based on clinical presentation that can improve the global efficiency of PCR testing.


title: The Seattle Flu Study: a multi-arm community-based prospective study protocol for assessing influenza prevalence, transmission, and genomic epidemiology

text: Introduction. Influenza epidemics and pandemics cause significant morbidity and mortality. An effective response to a potential pandemic requires the infrastructure to rapidly detect, characterize, and potentially contain new and emerging influenza strains at a population level. The objective of this study is to use data gathered simultaneously from community and hospital sites to develop a model of how influenza enters and spreads in a population. Methods and Analysis. Starting in the 2018-19 season, we have been enrolling individuals with acute respiratory illness from community sites throughout the Seattle metropolitan area, including clinics, childcare facilities, Seattle-Tacoma International Airport, workplaces, college campuses, and homeless shelters. At these sites, we collect clinical data and mid-nasal swabs from individuals with at least two acute respiratory symptoms. Additionally, we collect residual nasal swabs and data from individuals who seek care for respiratory symptoms at four regional hospitals. Samples are tested using a multiplex molecular assay, and influenza whole genome sequencing is performed for samples with influenza detected. Geospatial mapping and computational modeling platforms are in development to characterize the regional spread of influenza and other respiratory pathogens. Ethics and Dissemination. The study was approved by the University of Washington's Institutional Review Board. Results will be disseminated through talks at conferences, peer-reviewed publications, and on the study website (www.seattleflu.org).


title: Assessing the risks of "infodemics" in response to COVID-19 epidemics

text: Our society is built on a complex web of interdependencies whose effects become manifest during extraordinary events such as the COVID-19 pandemic, with shocks in one system propagating to the others to an exceptional extent. We analyzed more than 100 millions Twitter messages posted worldwide in 64 languages during the epidemic emergency due to SARS-CoV-2 and classified the reliability of news diffused. We found that waves of unreliable and low-quality information anticipate the epidemic ones, exposing entire countries to irrational social behavior and serious threats for public health. When the epidemics hit the same area, reliable information is quickly inoculated, like antibodies, and the system shifts focus towards certified informational sources. Contrary to mainstream beliefs, we show that human response to falsehood exhibits early-warning signals that might be mitigated with adequate communication strategies.


title: Clinical onset serial interval and diagnostic serial interval of SARS-CoV-2/COVID-19 in South Korea

text: BACKGROUND The clinical onset serial interval, or the time between the onset of symptoms in successive cases in a chain of infection, is often used as a measurable proxy for the transmission serial interval of an infectious disease. Current estimates of the mean clinical onset serial interval of COVID-19 range from 3.96 to 7.5 days. In this article, we define the diagnostic serial interval as the time between the diagnosis dates of the infector and infectee. We study and compare the clinical onset and diagnostic serial intervals of SARS-CoV-2/COVID-19 in South Korea. METHODS Analyzing the DS4C project data which summarize information on SARS-CoV-2/COVID-19 cases reported by regional governments in South Korea, we estimate the means of the clinical onset serial interval, the diagnostic serial interval and the difference between the two. We use the balanced cluster bootstrap method to construct 95% bootstrap confidence intervals. RESULTS The mean clinical onset serial interval and mean diagnostic serial interval were estimated to be 3.58 days (95% CI: 2.62, 4.53) and 3.68 days (95% CI: 3.14, 4.22), respectively. A matched sample analysis showed that the diagnostic serial interval was significantly shorter than the clinical onset serial interval (estimated mean difference -1.17 days, 95% CI: -2.26, -0.09). CONCLUSIONS The short diagnostic serial interval of SARS-CoV-2/COVID-19 in South Korea may explain why South Korea was able to contain the COVID-19 outbreak and avoid high mortality. We conjecture that the mean diagnostic serial interval may serve as a predictor for the success of a country's containment efforts.


title: COVID-19 Evolution and Alternative Medicine A Review

text: The current global health emergency, COVID-19, is not the first time that coronaviruses have posed a threat to human world shrinking our numbers by thousands Before this SARS-CoV in 2003 and MERSCoV in 2013 have caused epidemics Four months in existence, and it has already affected 1,995,983 people and taken over 131,037 lives worldwide, yet we do not have any specific treatment available with us and the management is purely empirical Looking at the similarities between SARS-CoV and SARS-CoV-2 in origin, genomics, pathogenesis and epidemiology, we can bring the researches done for SARS-CoV in use which can be our guide in finding an effective management strategy against SARS-CoV-2 There are various researches and studies reporting the use and effect of various phytochemical compounds in SARS-CoV treatment Already, the thought has been put into action and in-silico screening for various natural plant compounds have been done to find a potential candidate compound One such example is of curcumin, a secondary metabolite of turmeric, which is found to be effective against COVID-19 protease by molecular docking analysis


title: Drug repurposing clinical trials in the search for life-saving COVID-19 therapies;research targets and methodological and ethical issues

text: Introduction: So far, there is no vaccine, nor are there effective drugs to treat COVID-19, an emerging viral respiratory infection deadlier than influenza Objective: To take a snapshot picture of planned and ongoing clinical research addressing drugs potentially useful for treating SAR-CoV-2 infections Method: A search was conducted (20 April 2020) in an international registry of clinical studies (https://ClinicalTrials gov, US NIH) After excluding observational studies and other interventions that fell outside the scope of this study, 294 research protocols (out of 516 retrieved protocols) were selected for analysis Results: Of 294 included trials, 249 were Randomized Controlled Trials (RCT), 118 of which were double-, triple- or quadruple-blinded studies The interventions (drug therapies) were compared with "standard-of-care" (SOC) or with the placebo plus SOC, or yet with presumed "active" comparators RCT focused on the primary treatment of the disease (inhibitors of viral replication) or on the therapy for resolution of hyperinflammation in pneumonia/Acute Respiratory Distress Syndrome (ARDS) and thromboembolism associated with SARS-CoV-2 The trials found in the database involve existing antiviral compounds and drugs with multiple modes of antiviral action Antiparasitic drugs, which inhibited viral replication in cell-culture assays, are being tested as well Regarding the adjunctive immunomodulatory, anti-inflammatory and antithrombotic therapies, a number of drugs with distinct pharmacological targets are under investigation in trials enrolling patients with severe COVID-19 Conclusions: Although many clinical studies of drugs for COVID-19 are planned or in progress, only a minority of them are sufficiently large, randomized and placebo-controlled trials with masking and concealment of allocation Owing to methodological limitations, only a few clinical trials found in the registry are likely to yield robust evidence of effectiveness and safety of drugs repurposable for COVID-19


Off-label therapy targeting pathogenic inflammation in COVID-19


title: A surprising formula for the spread of Covid-19 under aggressive management

text: We propose an algebraic-type formula that describes with high accuracy the spread of Covid-19 pandemic under aggressive management for the periods of the intensive growth of the total number of infections. The formula can be used as a powerful forecasting tool. The parameters of the theory are the transmission rate, reflecting the viral fitness and "normal" frequency of contacts in the infected areas, and the intensity of prevention measures. The duration of the period of intensive growth is essentially inversely proportional to the square root of the intensity of hard measures. A more precise formula is based on Bessel functions. The data for the USA, UK, Sweden, Israel are provided.


title: Emergency calls are early indicators of ICU bed requirement during the COVID-19 epidemic

text: Background: Although the number of intensive care unit (ICU) beds is crucial during the COVID-19 epidemic caring for the most critically ill infected patients, there is no recognized early indicator to anticipate ICU bed requirements. Methods: In the Ile-de-France region, from February 20 to May 5, 2020, emergency medical service (EMS) calls and the response provided (ambulances) together the percentage of positive reverse transcriptase polymerase chain reaction (RT-PCR) tests, general practitioner (GP) and emergency department (ED) visits, and hospital admissions of COVID-19 patients were recorded daily and compared to the number of COVID-19 ICU patients. Correlation curve analysis was performed to determine the best correlation coefficient (R), depending on the number of days the indicator has been shifted. A delay [≥]7 days was considered as an early alert, and a delay [≥]14 days a very early alert. Findings: EMS calls, percentage of positive RT-PCR tests, ambulances used, ED and GP visits of COVID-19 patients were strongly associated with COVID-19 ICU patients with an anticipation delay of 23, 15, 14, 13, and 12 days respectively. Hospitalization did not anticipate ICU bed requirement. Interpretation: The daily number of COVID19-related telephone calls received by the EMS and corresponding dispatch ambulances, and the proportion of positive RT-PCR tests were the earliest indicators of the number of COVID19 patients requiring ICU care during the epidemic crisis in the Ile-de-France region, rapidly followed by ED and GP visits. This information may help health authorities to anticipate a future epidemic, including a second wave of COVID19 or decide additional social measures. Funding: Only institutional funding was provided.


title: Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data

text: Promoter-anchored chromatin interactions (PAIs) play a pivotal role in transcriptional regulation. Current high-throughput technologies for detecting PAIs, such as promoter capture Hi-C, are often limited in sample size due to the complexity of the experiments. Here, we present an analytical approach that uses summary-level data from DNA methylation (DNAm) quantitative trait locus (mQTL) studies to predict PAIs. Using mQTL data from human peripheral blood (n=1,980), we predicted 34,797 PAIs which showed strong overlap with the chromatin contacts identified by experimental assays. The promoter-interacting DNAm sites were enriched in enhancers or near expression QTLs. Genes whose promoters were involved in PAIs were more actively expressed, and gene pairs with promoter-promoter interactions were enriched for co-expression. Integration of the predicted PAIs with GWAS data highlighted interactions among 601 DNAm sites associated with 15 complex traits. This study demonstrates the use of mQTL data to predict PAIs and provide insights into the role of PAIs in complex trait variation.