bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Contribution to the Mathematical Modeling of the Corona/COVID-19 Pandemic
Authors: Bärwolff Günter 
Published: April 2020

AbstractThe responsible estimation of parameters is a main issue of mathematical pandemic models. Especially a good choice of β as the number of others that one infected person encounters per unit time (per day) influences the adequateness of the results of the model. For the example of the actual COVID-19 pandemic some aspects of the parameter choice will be discussed. Because of the incompatibility of the data of the Johns-Hopkins-University [3] to the data of the German Robert-Koch-Institut we use the COVID-19 data of the European Centre for Disease Prevention and Control [2] (ECDC) as a base for the parameter estimation. Two different mathematical methods for the data analysis will be discussed in this paper and possible sources of trouble will be shown.Parameters for several countries like UK, USA, Italy, Spain, Germany and China will be estimated and used in W. O. Kermack and A. G. McKendrick’s SIR model[1]. Strategies for the commencing and ending of social and economic shutdown measures are discussed.The numerical solution of the ordinary differential equation system of the modified SIR model is being done with a Runge-Kutta integration method of fourth order [4].At the end the applicability of the SIR model could be shown. Suggestions about appropriate points in time at which to commence with lockdown measures based on the acceleration rate of infections conclude the paper. This paper is an improved sequel of [5].
Case fatality rate in COVID-19: a systematic review and meta-analysis
Authors: Kahathuduwa Chanaka , Dhanasekara Chathurika , Chin Shao-Hua 
Published: April 2020

AbstractBackgroundEstimating the prevalence of severe or critical illness and case fatality of COVID-19 outbreak in December, 2019 remains a challenge due to biases associated with surveillance, data synthesis and reporting. We aimed to address this limitation in a systematic review and meta-analysis and to examine the clinical, biochemical and radiological risk factors in a meta-regression.MethodsPRISMA guidelines were followed. PubMed, Scopus and Web of Science were searched using pre-specified keywords on March 07, 2020. Peer-reviewed empirical studies examining rates of severe illness, critical illness and case fatality among COVID-19 patients were examined. Numerators and denominators to compute the prevalence rates and risk factors were extracted. Random-effects meta-analyses were performed. Results were corrected for publication bias. Meta-regression analyses examined the moderator effects of potential risk factors.ResultsThe meta-analysis included 29 studies representing 2,090 individuals. Pooled rates of severe illness, critical illness and case fatality among COVID-19 patients were 15%, 5% and 0.8% respectively. Adjusting for potential underreporting and publication bias, increased these estimates to 26%, 16% and 7.4% respectively. Increasing age and elevated LDH consistently predicted severe / critical disease and case fatality. Hypertension; fever and dyspnea at presentation; and elevated CRP predicted increased severity.ConclusionsRisk factors that emerged in our analyses predicting severity and case fatality should inform clinicians to define endophenotypes possessing a greater risk. Estimated case fatality rate of 7.4% after correcting for publication bias underscores the importance of strict adherence to preventive measures, case detection, surveillance and reporting.
Iterative community-driven development of a SARS-CoV-2 tissue simulator
Authors: Getz Michael , Wang Yafei , An Gary , Asthana Maansi , Becker Andrew , Cockrell Chase , Collier Nicholson , Craig Morgan , Davis Courtney L. , Faeder James R. , Ford Versypt Ashlee N. , Mapder Tarunendu , Gianlupi Juliano F. , Glazier James A. , Hamis Sara , Heiland Randy , Hillen Thomas , Hou Dennis , Islam Mohammad Aminul , Jenner Adrianne L. , Kurtoglu Furkan , Larkin Caroline I. , Liu Bing , Macfarlane Fiona , Maygrundter Pablo , Morel Penelope A , Narayanan Aarthi , Ozik Jonathan , Pienaar Elsje , Rangamani Padmini , Saglam Ali Sinan , Shoemaker Jason Edward , Smith Amber M. , Weaver Jordan J.A. , Macklin Paul 
Published: April 2020

AbstractThe 2019 novel coronavirus, SARS-CoV-2, is a pathogen of critical significance to international public health. Knowledge of the interplay between molecular-scale virus-receptor interactions, single-cell viral replication, intracellular-scale viral transport, and emergent tissue-scale viral propagation is limited. Moreover, little is known about immune system-virus-tissue interactions and how these can result in low-level (asymptomatic) infections in some cases and acute respiratory distress syndrome (ARDS) in others, particularly with respect to presentation in different age groups or pre-existing inflammatory risk factors. Given the nonlinear interactions within and among each of these processes, multiscale simulation models can shed light on the emergent dynamics that lead to divergent outcomes, identify actionable “choke points” for pharmacologic interventions, screen potential therapies, and identify potential biomarkers that differentiate patient outcomes. Given the complexity of the problem and the acute need for an actionable model to guide therapy discovery and optimization, we introduce and iteratively refine a prototype of a multiscale model of SARS-CoV-2 dynamics in lung tissue. The first prototype model was built and shared internationally as open source code and an online interactive model in under 12 hours, and community domain expertise is driving regular refinements. In a sustained community effort, this consortium is integrating data and expertise across virology, immunology, mathematical biology, quantitative systems physiology, cloud and high performance computing, and other domains to accelerate our response to this critical threat to international health. More broadly, this effort is creating a reusable, modular framework for studying viral replication and immune response in tissues, which can also potentially be adapted to related problems in immunology and immunotherapy.
LY6E Restricts the Entry of Human Coronaviruses, including the currently pandemic SARS-CoV-2
Authors: Zhao Xuesen , Zheng Shuangli , Chen Danying , Zheng Mei , Li Xinglin , Li Guoli , Lin Hanxin , Chang Jinhong , Zeng Hui , Guo Ju-Tao 
Published: April 2020

ABSTRACTC3A is a sub-clone of human hepatoblastoma HepG2 cell line with the strong contact inhibition of growth. We fortuitously found that C3A was more susceptible to human coronavirus HCoV-OC43 infection than HepG2, which was attributed to the increased efficiency of virus entry into C3A cells. In an effort to search for the host cellular protein(s) mediating the differential susceptibility of the two cell lines to HCoV-OC43 infection, we found that ADAP2, GILT and LY6E, three cellular proteins with known activity of interfering virus entry, expressed at significantly higher levels in HepG2 cells. Functional analyses revealed that ectopic expression of LY6E, but not GILT or ADAP2, in HEK 293 cells inhibited the entry of HCoV-OC43. While overexpression of LY6E in C3A and A549 cells efficiently inhibited the infection of HCoV-OC43, knockdown of LY6E expression in HepG2 significantly increased its susceptibility to HCoV-OC43 infection. Moreover, we found that LY6E also efficiently restricted the entry mediated by the envelope spike proteins of other human coronaviruses, including the currently pandemic SARS-CoV-2. Interestingly, overexpression of serine protease TMPRSS2 or amphotericin treatment significantly neutralized the IFITM3 restriction of human coronavirus entry, but did not compromise the effect of LY6E on the entry of human coronaviruses. The work reported herein thus demonstrates that LY6E is a critical antiviral immune effector that controls CoV infection and pathogenesisviaa distinct mechanism.ImportanceVirus entry into host cells is one of the key determinants of host range and cell tropism and is subjected to the control by host innate and adaptive immune responses. In the last decade, several interferon inducible cellular proteins, including IFITMs, GILT, ADAP2, 25CH and LY6E, had been identified to modulate the infectious entry of a variety of viruses. Particularly, LY6E was recently identified as host factors to facilitate the entry of several human pathogenic viruses, including human immunodeficiency virus, influenza A virus and yellow fever virus. Identification of LY6E as a potent restriction factor of coronaviruses expands the biological function of LY6E and sheds new light on the immunopathogenesis of human coronavirus infection.
Analytical Validation of a COVID-19 qRT-PCR Detection Assay Using a 384-well Format and Three Extraction Methods
Authors: Nelson Andrew C. , Auch Benjamin , Schomaker Matthew , Gohl Daryl M. , Grady Patrick , Johnson Darrell , Kincaid Robyn , Karnuth Kylene E. , Daniel Jerry , Fiege Jessica K. , Fay Elizabeth J. , Bold Tyler , Langlois Ryan A. , Beckman Kenneth B. , Yohe Sophia 
Published: April 2020

AbstractThe COVID-19 global pandemic is an unprecedented health emergency. Insufficient access to testing has hampered effective public health interventions and patient care management in a number of countries. Furthermore, the availability of regulatory-cleared reagents has challenged widespread implementation of testing. We rapidly developed a qRT-PCR SARS-CoV-2 detection assay using a 384-well format and tested its analytic performance across multiple nucleic acid extraction kits. Our data shows robust analytic accuracy on residual clinical biospecimens. Limit of detection sensitivity and specificity was confirmed with currently available commercial reagents. Our methods and results provide valuable information for other high-complexity laboratories seeking to develop effective, local, laboratory-developed procedures with high-throughput capability to detect SARS-CoV-2.
Public perspectives on social distancing and other protective measures in Europe: a cross-sectional survey study during the COVID-19 pandemic
Authors: Meier Karien , Glatz Toivo , Guijt Mathijs C , Piccininni Marco , van der Meulen Merel , Atmar Khaled , Jolink Anne-Tess C , Kurth Tobias , Rohmann Jessica L , Najafabadi Amir H Zamanipoor 
Published: April 2020

ABSTRACTObjectivesThe extent to which people implement government-issued protective measures is critical in preventing further spread of coronavirus disease 2019 (COVID-19) caused by coronavirus SARS-CoV-2. Our study aimed to evaluate the public belief in the effectiveness of protective measures, the reported implementation of these measures in daily life, and to identify communication channels used to acquire relevant information on COVID-19 in European countries.DesignA cross-sectional online survey available in multiple languages was disseminated on social media starting March 19th, 2020. After five days, we computed descriptive statistics for countries with more than 500 respondents. Each day, we compiled and categorized community containment measures enacted in each country by stringency (stage I-IV). Response collection continued for one week to explore possible dynamics as containment strategies intensified.ParticipantsIn total, 9,796 adults responded, of whom 8,611 resided in the Netherlands (stage III), 604 in Germany (stage III), and 581 in Italy (stage IV). An additional 1,365 respondents completed the survey in the following week.ResultsParticipants indicated support for governmental measures related to avoiding social gatherings, selective closure of public places, and hand hygiene and respiratory measures (range for all measures: 95.0%-99.7%). Respondents from the Netherlands were less likely to consider a complete social lockdown effective (59.2%), compared to respondents in Germany (76.6%) or Italy (87.2%). Italian residents did not only apply enforced social distancing measures more frequently (range: 90.2%-99.3%, German and Dutch residents: 67.5%-97.0%), but also self-initiated hygienic and social distancing behaviors (range: 36.3%-96.6%, German and Dutch residents: 28.3%-95.7%). Respondents largely reported being sufficiently informed about the COVID-19 outbreak and about behaviors to avoid infection (range across countries: 90.2%-91.1%). Information channels most commonly reported included television (range: 53.0%-82.0%), newspapers (range: 31.0%-63.0%), official health websites (range: 39.0%-54.1%), and social media (range: 40.0%-55.8%). We observed no major changes in answers over time.ConclusionsIn European countries, the degree of public belief in the effectiveness of protective measures was high and residents reported to be sufficiently informed by various communication channels. In March 2020, implementation of enacted and self-initiated measures differed between countries and were highest among Italian respondents, who were subjected to the most elaborate measures of social lockdown and greatest COVID-19 burden in Europe.
Surge capacities and predicted demands of Brazil’s health system associated with severe COVID-19 cases
Authors: Cavalcante Eric Luis Barroso , Ferreira Juliana Cristina Cardoso 
Published: April 2020

AbstractObjectiveTo estimate surge capacities and demands of Brazil’s health system in view of severe cases of the novel coronavirus disease.MethodsThree types of hospital equipments demanded by severe COVID-19 patients are considered: available intensive care unit (ICU) beds, existing surgery operating rooms and respirators located in other hospital areas. They are taken into account on a cumulative basis forming three levels of hospital equipment usage. Based on a mean duration of hospitalization for the disease, it is estimated the daily admission capacity of infected patients per state and for the entire country for each level of hospital equipment usage. Furthermore, an exponential regression model is fitted by means of the daily national number of new documented patients. The prediction intervals for the number of new patients for certain days in the immediate future are then calculated and compared to the admissible daily demand for the three incremental groups of equipments. The data are made publicly available by the Brazilian federal government and are gathered and analyzed by means of the Python programming language.Results41% of the (adult) ICU beds in Brazil were available during 2019, indicating that this hospital equipment has not been on average operating near capacity in national numbers. Nevertheless, there is a marked heterogeneity in the absolute and relative numbers of available and existing ICU beds and existing surgery operating rooms and extra respirators between its states.ConclusionsThe remarkable differences between states’ hospital resources directly reflect into the number of possible daily admissions of COVID-19 patients with respiratory failure for the three considered levels of hospital equipment usage. In national numbers, Brazil’s health system is estimated to be capable of daily admitting 693, 1243 and 2166 severe patients under the three studied scenarios. The fitted model predicted that only the first limit, if any, would be reached.
Explaining national differences in the mortality of Covid-19: individual patient simulation model to investigate the effects of testing policy and other factors on apparent mortality
Authors: Michaels Jonathan A , Stevenson Matt D 
Published: April 2020

ABSTRACTThere has been extensive speculation on the apparent differences in mortality between countries reporting on the confirmed cases and deaths due to Covid-19. A number of explanations have been suggested, but there is no clear evidence about how apparent fatality rates may be expected to vary with the different testing regimes, admission policies and other variables. An individual patient simulation model was developed to address this question. Parameters and sensitivity analysis based upon recent international data sources for Covid-19 and results were averaged over 100 iterations for a simulated cohort of over 500,000 patients.Different testing regimes for Covid-19 were considered; testing admitted patients only, various rates of community testing of symptomatic cases and active contact-tracing and screening.In the base case analysis, apparent mortality ranged from 10.5% under a policy of testing only admitted patients to 0.4% with intensive contact tracing and community testing. These findings were sensitive to assumptions regarding admission rates and the rate of spread, with more selective admission policies and suppression of spread increasing the apparent mortality and the potential for apparent mortality rates to exceed 18% under some circumstances. Under all scenarios the proportion of patients tested in the community had the greatest impact on apparent mortality.Whilst differences in mortality due to health service and demographic factors cannot be excluded, the current international differences in reported mortality are all consistent with differences in practice regarding screening, community testing and admission policies.
Dynamics of COVID-19 epidemics: SEIR models underestimate peak infection rates and overestimate epidemic duration
Authors: Grant Alastair 
Published: April 2020

AbstractCompartment models of infectious diseases, such as SEIR, are being used extensively to model the COVID-19 epidemic. Transitions between compartments are modelled either as instantaneous rates in differential equations, or as transition probabilities in discrete time difference or matrix equations. These models give accurate estimates of the position of equilibrium points, when the rate at which individuals enter each stage is equal to the rate at which they exit from it. However, they do not accurately capture the distribution of times that an individual spends in each compartment, so do not accurately capture the transient dynamics of epidemics. Here we show how matrix models can provide a straightforward route to accurately model stage durations, and thus correctly reproduce epidemic dynamics. We apply this approach to modelling the dynamics of a COVID-19 epidemic. We show that a SEIR model underestimates peak infection rates (by a factor of three using published parameter estimates based on the progress of the epidemic in Wuhan) and substantially overestimates epidemic persistence after the peak has passed.
COVID-19 scenario modelling for the mitigation of capacity-dependent deaths in intensive care: computer simulation study
Authors: Wood Richard M , McWilliams Christopher J , Thomas Matthew J , Bourdeaux Christopher P , Vasilakis Christos 
Published: April 2020

BackgroundManaging healthcare demand and capacity is especially difficult in the context of the COVID-19 pandemic, where limited intensive care resources can be overwhelmed by a large number of cases requiring admission in a short space of time. If patients are unable to access this specialist resource, then death is a likely outcome. The aim of this study is to estimate the extent to which such capacity-dependent deaths can be mitigated through demand-side initiatives involving non-pharmaceutical interventions and supply-side measures to increase surge capacity or reduce length of stay.MethodsA stochastic discrete event simulation model is developed to represent the key dynamics of the intensive care admissions process for COVID-19 patients. Model inputs are aligned to levers available to planners with key outputs including duration of time at maximum capacity (to inform workforce requirements), peak daily deaths (for mortuary planning), and total deaths (as an ultimate marker of intervention efficacy). The model - freely available - is applied to the COVID-19 response at a large hospital in England for which the effect of a number of possible interventions are simulated.ResultsCapacity-dependent deaths are closely associated with both the nature and effectiveness of non-pharmaceutical interventions and availability of intensive care beds. For the hospital considered, results suggest that capacity-dependent deaths can be reduced five-fold through a combination of isolation policies, a doubling of bed capacity, and 25% reduced length of stay.ConclusionsWithout treatment or vaccination there is little that can be done to reduce deaths occurring when patients have otherwise been treated in the most appropriate hospital setting. Healthcare planners should therefore focus on minimising the capacity-dependent deaths that are within their influence.
Therapeutic Management of COVID-19 Patients: A systematic review
Authors: Tobaiqy Mansour , Qashqary Mohammed , Al-Dahery Shrooq , Mujallad Alaa , Hershan Almonther Abdullah , Kamal Mohammad Azhar , Helmi Nawal 
Published: April 2020

AbstractBackgroundSARS-CoV-2 is the cause of the COVID-19 that has been declared a global pandemic by the WHO in 2020. The COVID-19 treatment guidelines vary in each country, and yet there is no approved therapeutic for COVID-19.Aims of the studythis review aimed to report any evidence of therapeutics used for the management of COVID-19 patients in clinical practice since the emergence of the virus.MethodsA systematic review protocol was developed based on PRISMA Statement. Articles for review were selected from electronic databases (Embase, Medline and Google Scholar). Readily accessible peer-reviewed full articles in English published from December 1 st, 2019 to March 26 th, 2020 were included. The search terms included combinations of: COVID, SARS-COV-2, glucocorticoids, convalescent plasma, antiviral, antibacterial. There were no restrictions on the type of study design eligible for inclusion.ResultsAs of March 26, 2020, of the initial manuscripts identified (n=449) articles. Forty-one studies were included, of which clinical trials (n=3), (case reports n=7), case series (n=10), retrospective (n=11) and prospective (n=10) observational studies. Thirty-six studies were conducted in China (88%).The most common mentioned and reported medicine in this systematic review was corticosteroids (n=25), followed by Lopinavir (n=21) and oseltamivir (n=16).ConclusionsThis is the first systematic review up to date related to the therapeutics used in COVID-19 patients. Only forty-one research articles on COVID-19 and therapeutics were found eligible to be included, most conducted in China, corticosteroid therapy was found to be the most used medicine in these studies.