Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Virology
Title: Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases
Abstract: The exported cases of 2019 novel coronavirus (COVID-19) infection that were confirmed outside China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number—the average number of secondary cases generated by a single primary case in a naïve population. We modeled epidemic growth either from a single index case with illness onset on 8 December 2019 (Scenario 1), or using the growth rate fitted along with the other parameters (Scenario 2) based on data from 20 exported cases reported by 24 January 2020. The cumulative incidence in China by 24 January was estimated at 6924 cases (95% confidence interval [CI]: 4885, 9211) and 19,289 cases (95% CI: 10,901, 30,158), respectively. The latest estimated values of the cCFR were 5.3% (95% CI: 3.5%, 7.5%) for Scenario 1 and 8.4% (95% CI: 5.3%, 12.3%) for Scenario 2. The basic reproduction number was estimated to be 2.1 (95% CI: 2.0, 2.2) and 3.2 (95% CI: 2.7, 3.7) for Scenarios 1 and 2, respectively. Based on these results, we argued that the current COVID-19 epidemic has a substantial potential for causing a pandemic. The proposed approach provides insights in early risk assessment using publicly available data.
Extracted statement — location: mainland China
Research field: Virology
Title: Estimating the Unreported Number of Novel Coronavirus (2019-nCoV) Cases in China in the First Half of January 2020: A Data-Driven Modelling Analysis of the Early Outbreak
Abstract: Background: In December 2019, an outbreak of respiratory illness caused by a novel coronavirus (2019-nCoV) emerged in Wuhan, China and has swiftly spread to other parts of China and a number of foreign countries. The 2019-nCoV cases might have been under-reported roughly from 1 to 15 January 2020, and thus we estimated the number of unreported cases and the basic reproduction number, R0, of 2019-nCoV. Methods: We modelled the epidemic curve of 2019-nCoV cases, in mainland China from 1 December 2019 to 24 January 2020 through the exponential growth. The number of unreported cases was determined by the maximum likelihood estimation. We used the serial intervals (SI) of infection caused by two other well-known coronaviruses (CoV), Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) CoVs, as approximations of the unknown SI for 2019-nCoV to estimate R0. Results: We confirmed that the initial growth phase followed an exponential growth pattern. The under-reporting was likely to have resulted in 469 (95% CI: 403–540) unreported cases from 1 to 15 January 2020. The reporting rate after 17 January 2020 was likely to have increased 21-fold (95% CI: 18–25) in comparison to the situation from 1 to 17 January 2020 on average. We estimated the R0 of 2019-nCoV at 2.56 (95% CI: 2.49–2.63). Conclusion: The under-reporting was likely to have occurred during the first half of January 2020 and should be considered in future investigation.
Extracted statement — location: mainland China
Research field: Virology
Title: Risk estimation and prediction by modeling the transmission of the novel coronavirus (COVID-19) in mainland China excluding Hubei province
Abstract: Background: In December 2019, an outbreak of coronavirus disease (COVID-19)was identified in Wuhan, China and, later on, detected in other parts of China. Our aim is to evaluate the effectiveness of the evolution of interventions and self-protection measures, estimate the risk of partial lifting control measures and predict the epidemic trend of the virus in mainland China excluding Hubei province based on the published data and a novel mathematical model. Methods: A novel COVID-19 transmission dynamic model incorporating the intervention measures implemented in China is proposed. We parameterize the model by using the Markov Chain Monte Carlo (MCMC) method and estimate the control reproduction number Rc, as well as the effective daily reproduction ratio Re(t), of the disease transmission in mainland China excluding Hubei province. Results: The estimation outcomes indicate that the control reproduction number is 3.36 (95% CI 3.20-3.64) and Re(t) has dropped below 1 since January 31st, 2020, which implies that the containment strategies implemented by the Chinese government in mainland China excluding Hubei province are indeed effective and magnificently suppressed COVID-19 transmission. Moreover, our results show that relieving personal protection too early may lead to the spread of disease for a longer time and more people would be infected, and may even cause epidemic or outbreak again. By calculating the effective reproduction ratio, we proved that the contact rate should be kept at least less than 30% of the normal level by April, 2020. Conclusions: To ensure the epidemic ending rapidly, it is necessary to maintain the current integrated restrict interventions and self-protection measures, including travel restriction, quarantine of entry, contact tracing followed by quarantine and isolation and reduction of contact, like wearing masks, etc. People should be fully aware of the real-time epidemic situation and keep sufficient personal protection until April. If all the above conditions are met, the outbreak is expected to be ended by April in mainland China apart from Hubei province.
Extracted statement — location: mainland China excluding Hubei province
Research field: Virology
Title: Characterizing the transmission and identifying the control strategy for COVID-19 through epidemiological modeling
Abstract: The outbreak of the novel coronavirus disease, COVID-19, originating from Wuhan, China in early December, has infected more than 70,000 people in China and other countries and has caused more than 2,000 deaths. As the disease continues to spread, the biomedical society urgently began identifying effective approaches to prevent further outbreaks. Through rigorous epidemiological analysis, we characterized the fast transmission of COVID-19 with a basic reproductive number 5.6 and proved a sole zoonotic source to originate in Wuhan. No changes in transmission have been noted across generations. By evaluating different control strategies through predictive modeling and Monte carlo simulations, a comprehensive quarantine in hospitals and quarantine stations has been found to be the most effective approach. Government action to immediately enforce this quarantine is highly recommended.
Extracted statement — Methods: Monte carlo simulation
Research field: Virology
Title: Alphacoronavirus in a Daubenton’s Myotis Bat (Myotis daubentonii) in Sweden.
Abstract: The ongoing COVID-19 pandemic has stimulated a search for reservoirs and species potentially involved in back and forth transmission. Studies have postulated bats as one of the key reservoirs of coronaviruses (CoVs), and different CoVs have been detected in bats. So far, CoVs have not been found in bats in Sweden and we therefore tested whether they carry CoVs. In summer 2020, we sampled a total of 77 adult bats comprising 74 Myotis daubentonii, 2 Pipistrellus pygmaeus, and 1 M. mystacinus bats in southern Sweden. Blood, saliva and feces were sampled, processed and subjected to a virus next-generation sequencing target enrichment protocol. An Alphacoronavirus was detected and sequenced from feces of a M. daubentonii adult female bat. Phylogenetic analysis of the almost complete virus genome revealed a close relationship with Finnish and Danish strains. This was the first finding of a CoV in bats in Sweden, and bats may play a role in the transmission cycle of CoVs in Sweden. Focused and targeted surveillance of CoVs in bats is warranted, with consideration of potential conflicts between public health and nature conservation required as many bat species in Europe are threatened and protected.
Extracted statement — Has Host: Myotis daubentonii
Research field: Virology
Title: Spread of SARS-CoV-2 in the Icelandic Population
Abstract: Abstract Background During the current worldwide pandemic, coronavirus disease 2019 (Covid-19) was first diagnosed in Iceland at the end of February. However, data are limited on how SARS-CoV-2, the virus that causes Covid-19, enters and spreads in a population. Methods We targeted testing to persons living in Iceland who were at high risk for infection (mainly those who were symptomatic, had recently traveled to high-risk countries, or had contact with infected persons). We also carried out population screening using two strategies: issuing an open invitation to 10,797 persons and sending random invitations to 2283 persons. We sequenced SARS-CoV-2 from 643 samples. Results As of April 4, a total of 1221 of 9199 persons (13.3%) who were recruited for targeted testing had positive results for infection with SARS-CoV-2. Of those tested in the general population, 87 (0.8%) in the open-invitation screening and 13 (0.6%) in the random-population screening tested positive for the virus. In total, 6% of the population was screened. Most persons in the targeted-testing group who received positive tests early in the study had recently traveled internationally, in contrast to those who tested positive later in the study. Children under 10 years of age were less likely to receive a positive result than were persons 10 years of age or older, with percentages of 6.7% and 13.7%, respectively, for targeted testing; in the population screening, no child under 10 years of age had a positive result, as compared with 0.8% of those 10 years of age or older. Fewer females than males received positive results both in targeted testing (11.0% vs. 16.7%) and in population screening (0.6% vs. 0.9%). The haplotypes of the sequenced SARS-CoV-2 viruses were diverse and changed over time. The percentage of infected participants that was determined through population screening remained stable for the 20-day duration of screening. Conclusions In a population-based study in Iceland, children under 10 years of age and females had a lower incidence of SARS-CoV-2 infection than adolescents or adults and males. The proportion of infected persons identified through population screening did not change substantially during the screening period, which was consistent with a beneficial effect of containment efforts. (Funded by deCODE Genetics–Amgen.)
Extracted statement — has study design: population screening
Research field: Virology
Title: Viral load dynamics and disease severity in patients infected with SARS-CoV-2 in Zhejiang province, China, January-March 2020: retrospective cohort study
Abstract: Abstract Objective To evaluate viral loads at different stages of disease progression in patients infected with the 2019 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the first four months of the epidemic in Zhejiang province, China. Design Retrospective cohort study. Setting A designated hospital for patients with covid-19 in Zhejiang province, China. Participants 96 consecutively admitted patients with laboratory confirmed SARS-CoV-2 infection: 22 with mild disease and 74 with severe disease. Data were collected from 19 January 2020 to 20 March 2020. Main outcome measures Ribonucleic acid (RNA) viral load measured in respiratory, stool, serum, and urine samples. Cycle threshold values, a measure of nucleic acid concentration, were plotted onto the standard curve constructed on the basis of the standard product. Epidemiological, clinical, and laboratory characteristics and treatment and outcomes data were obtained through data collection forms from electronic medical records, and the relation between clinical data and disease severity was analysed. Results 3497 respiratory, stool, serum, and urine samples were collected from patients after admission and evaluated for SARS-CoV-2 RNA viral load. Infection was confirmed in all patients by testing sputum and saliva samples. RNA was detected in the stool of 55 (59%) patients and in the serum of 39 (41%) patients. The urine sample from one patient was positive for SARS-CoV-2. The median duration of virus in stool (22 days, interquartile range 17-31 days) was significantly longer than in respiratory (18 days, 13-29 days; P=0.02) and serum samples (16 days, 11-21 days; P<0.001). The median duration of virus in the respiratory samples of patients with severe disease (21 days, 14-30 days) was significantly longer than in patients with mild disease (14 days, 10-21 days; P=0.04). In the mild group, the viral loads peaked in respiratory samples in the second week from disease onset, whereas viral load continued to be high during the third week in the severe group. Virus duration was longer in patients older than 60 years and in male patients. Conclusion The duration of SARS-CoV-2 is significantly longer in stool samples than in respiratory and serum samples, highlighting the need to strengthen the management of stool samples in the prevention and control of the epidemic, and the virus persists longer with higher load and peaks later in the respiratory tissue of patients with severe disease.
Extracted statement — Material: respiratory sample
Research field: Virology
Title: Enterovirus inhibiting activities of two lupane triterpenoids and anthraquinones from senna siamea stem bark against three serotypes of echovirus
Abstract: Echovirus 7, 13 and 19 are part of the diseases-causing enteroviruses identified in Nigeria. Presently, no treatment modality is clinically available against these enteric viruses. Herein, we investigated the ability of two anthraquinones (physcion and chrysophanol) and two lupane triterpenoids (betulinic acid and lupeol), isolated from the stem bark of Senna siamea, to reduce the viral-induced cytopathic effect on rhabdomyosarcoma cells using MTT (3-[4,5-dimethylthiazol–2-yl]-2,5diphenyltetrazolium bromide) colorimetric method. Viral-induced CPE by E7 and E19 was inhibited in the presence of all tested compounds, E13 was resistant to all the compounds except betulinic acid. Physcion was the most active with IC50 of 0.42 and 0.33 μg/mL on E7 and E19, respectively. We concluded that these compounds from Senna siamea possess anti-enteroviral activities and betulinic acid may represent a potential therapeutic agent to control E7, E13, and E19 infections, especially due its ability to inhibit CPE caused by the impervious E13.
Extracted statement — Source name: Senna siamea
Research field: Virology
Title: Estimating the generation interval for COVID-19 based on symptom onset data
Abstract: Background: Estimating key infectious disease parameters from the COVID-19 outbreak is quintessential for modelling studies and guiding intervention strategies. Whereas different estimates for the incubation period distribution and the serial interval distribution have been reported, estimates of the generation interval for COVID-19 have not been provided. Methods: We used outbreak data from clusters in Singapore and Tianjin, China to estimate the generation interval from symptom onset data while acknowledging uncertainty about the incubation period distribution and the underlying transmission network. From those estimates we obtained the proportions pre-symptomatic transmission and reproduction numbers. Results: The mean generation interval was 5.20 (95%CI 3.78-6.78) days for Singapore and 3.95 (95%CI 3.01-4.91) days for Tianjin, China when relying on a previously reported incubation period with mean 5.2 and SD 2.8 days. The proportion of pre-symptomatic transmission was 48% (95%CI 32-67%) for Singapore and 62% (95%CI 50-76%) for Tianjin, China. Estimates of the reproduction number based on the generation interval distribution were slightly higher than those based on the serial interval distribution. Conclusions: Estimating generation and serial interval distributions from outbreak data requires careful investigation of the underlying transmission network. Detailed contact tracing information is essential for correctly estimating these quantities.
Extracted statement — Method: serial interval
Research field: Virology
Title: Estimating the generation interval for COVID-19 based on symptom onset data
Abstract: Background: Estimating key infectious disease parameters from the COVID-19 outbreak is quintessential for modelling studies and guiding intervention strategies. Whereas different estimates for the incubation period distribution and the serial interval distribution have been reported, estimates of the generation interval for COVID-19 have not been provided. Methods: We used outbreak data from clusters in Singapore and Tianjin, China to estimate the generation interval from symptom onset data while acknowledging uncertainty about the incubation period distribution and the underlying transmission network. From those estimates we obtained the proportions pre-symptomatic transmission and reproduction numbers. Results: The mean generation interval was 5.20 (95%CI 3.78-6.78) days for Singapore and 3.95 (95%CI 3.01-4.91) days for Tianjin, China when relying on a previously reported incubation period with mean 5.2 and SD 2.8 days. The proportion of pre-symptomatic transmission was 48% (95%CI 32-67%) for Singapore and 62% (95%CI 50-76%) for Tianjin, China. Estimates of the reproduction number based on the generation interval distribution were slightly higher than those based on the serial interval distribution. Conclusions: Estimating generation and serial interval distributions from outbreak data requires careful investigation of the underlying transmission network. Detailed contact tracing information is essential for correctly estimating these quantities.
Extracted statement — Methods: serial interval
Research field: Virology
Title: Viral load dynamics and disease severity in patients infected with SARS-CoV-2 in Zhejiang province, China, January-March 2020: retrospective cohort study
Abstract: Abstract Objective To evaluate viral loads at different stages of disease progression in patients infected with the 2019 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the first four months of the epidemic in Zhejiang province, China. Design Retrospective cohort study. Setting A designated hospital for patients with covid-19 in Zhejiang province, China. Participants 96 consecutively admitted patients with laboratory confirmed SARS-CoV-2 infection: 22 with mild disease and 74 with severe disease. Data were collected from 19 January 2020 to 20 March 2020. Main outcome measures Ribonucleic acid (RNA) viral load measured in respiratory, stool, serum, and urine samples. Cycle threshold values, a measure of nucleic acid concentration, were plotted onto the standard curve constructed on the basis of the standard product. Epidemiological, clinical, and laboratory characteristics and treatment and outcomes data were obtained through data collection forms from electronic medical records, and the relation between clinical data and disease severity was analysed. Results 3497 respiratory, stool, serum, and urine samples were collected from patients after admission and evaluated for SARS-CoV-2 RNA viral load. Infection was confirmed in all patients by testing sputum and saliva samples. RNA was detected in the stool of 55 (59%) patients and in the serum of 39 (41%) patients. The urine sample from one patient was positive for SARS-CoV-2. The median duration of virus in stool (22 days, interquartile range 17-31 days) was significantly longer than in respiratory (18 days, 13-29 days; P=0.02) and serum samples (16 days, 11-21 days; P<0.001). The median duration of virus in the respiratory samples of patients with severe disease (21 days, 14-30 days) was significantly longer than in patients with mild disease (14 days, 10-21 days; P=0.04). In the mild group, the viral loads peaked in respiratory samples in the second week from disease onset, whereas viral load continued to be high during the third week in the severe group. Virus duration was longer in patients older than 60 years and in male patients. Conclusion The duration of SARS-CoV-2 is significantly longer in stool samples than in respiratory and serum samples, highlighting the need to strengthen the management of stool samples in the prevention and control of the epidemic, and the virus persists longer with higher load and peaks later in the respiratory tissue of patients with severe disease.
Extracted statement — Material: serum sample
Research field: Virology
Title: Statistics based predictions of coronavirus 2019-nCoV spreading in mainland China
Abstract: Background. The epidemic outbreak cased by coronavirus 2019-nCoV is of great interest to researches because of the high rate of spread of the infection and the significant number of fatalities. A detailed scientific analysis of the phenomenon is yet to come, but the public is already interested in the questions of the duration of the epidemic, the expected number of patients and deaths. For long time predictions, the complicated mathematical models are necessary which need many efforts for unknown parameters identification and calculations. In this article, some preliminary estimates will be presented. Objective. Since the reliable long time data are available only for mainland China, we will try to predict the epidemic characteristics only in this area. We will estimate some of the epidemic characteristics and present the most reliable dependences for victim numbers, infected and removed persons versus time. Methods. In this study we use the known SIR model for the dynamics of an epidemic, the known exact solution of the linear equations and statistical approach developed before for investigation of the children disease, which occurred in Chernivtsi (Ukraine) in 1988-1989. Results. The optimal values of the SIR model parameters were identified with the use of statistical approach. The numbers of infected, susceptible and removed persons versus time were predicted. Conclusions. Simple mathematical model was used to predict the characteristics of the epidemic caused by coronavirus 2019-nCoV in mainland China. The further research should focus on updating the predictions with the use of fresh data and using more complicated mathematical models.
Extracted statement — Method: SIR model
Research field: Virology
Title: Structure-Based Design, Synthesis, and Biological Evaluation of a Series of Novel and Reversible Inhibitors for the Severe Acute Respiratory Syndrome−Coronavirus Papain-Like Protease
Abstract: We describe here the design, synthesis, molecular modeling, and biological evaluation of a series of small molecule, nonpeptide inhibitors of SARS-CoV PLpro. Our initial lead compound was identified via high-throughput screening of a diverse chemical library. We subsequently carried out structure-activity relationship studies and optimized the lead structure to potent inhibitors that have shown antiviral activity against SARS-CoV infected Vero E6 cells. Upon the basis of the X-ray crystal structure of inhibitor 24-bound to SARS-CoV PLpro, a drug design template was created. Our structure-based modification led to the design of a more potent inhibitor, 2 (enzyme IC(50) = 0.46 microM; antiviral EC(50) = 6 microM). Interestingly, its methylamine derivative, 49, displayed good enzyme inhibitory potency (IC(50) = 1.3 microM) and the most potent SARS antiviral activity (EC(50) = 5.2 microM) in the series. We have carried out computational docking studies and generated a predictive 3D-QSAR model for SARS-CoV PLpro inhibitors.
Extracted statement — has role: small molecule