bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mesenchymal stromal cells for COVID-19: A living systematic review protocol
Authors: Rada Gabriel , Corbalán Javiera , Rojas Patricio ,   COVID-19 L·OVE Working Group
Published: April 2020

ABSTRACTObjectiveTo determine the impact of mesenchymal stromal cells outcomes important to patients with COVID-19.DesignThis is the protocol of a living systematic review.Data sourcesWe will conduct searches in PubMed/Medline, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), grey literature and in a centralised repository in L·OVE (Living OVerview of Evidence). L·OVE is a platform that maps PICO questions to evidence from Epistemonikos database. In response to the COVID-19 emergency, L·OVE was adapted to expand the range of evidence it covers and customised to group all COVID-19 evidence in one place. The search will cover the period until the day before submission to a journal.Eligibility criteria for selecting studies and methodsWe adapted an already published common protocol for multiple parallel systematic reviews to the specificities of this question.We will include randomised trials evaluating the effect of mesenchymal stromal cells versus placebo or no treatment in patients with COVID-19. Randomised trials evaluating other coronavirus infections, such as MERS-CoV and SARS-CoV, and non-randomised studies in COVID-19 will be searched in case we find no direct evidence from randomised trials, or if the direct evidence provides low- or very low-certainty for critical outcomes.Two reviewers will independently screen each study for eligibility, extract data, and assess the risk of bias. We will pool the results using meta-analysis and will apply the GRADE system to assess the certainty of the evidence for each outcome.A living, web-based version of this review will be openly available during the COVID-19 pandemic. We will resubmit it every time the conclusions change or whenever there are substantial updates.Ethics and disseminationNo ethics approval is considered necessary. The results of this review will be widely disseminated via peer-reviewed publications, social networks and traditional media.PROSPERO RegistrationSubmitted to PROSPERO (awaiting ID allocation).
A Rapidly Deployable Negative Pressure Enclosure for Aerosol-Generating Medical Procedures
Authors: Chahal Anthony M. , Van Dewark Kenneth , Gooch Robert , Fukushima Erin , Hudson Zachary M. 
Published: April 2020

AbstractBackgroundThe coronavirus disease 2019 (COVID-19) pandemic presents significant safety challenges to healthcare professionals. In some jurisdictions, over 10% of confirmed cases of COVID-19 have been found among healthcare workers. Aerosol-generating medical procedures (AGMPs) may increase the risk of nosocomial transmission, exacerbated by present global shortages of personal protective equipment (PPE). Improved methods for mitigating risk during AGMPs are therefore urgently needed.MethodsThe Aerosol Containment Enclosure (ACE) was constructed from acrylic with silicone gaskets for arm port seals and completed with a thin plastic sheet. Hospital wall suction generated negative pressure within the ACE. To evaluate protective capability, differential pressures were recorded under static conditions and during simulated AGMPs. Smoke flow patterns, fluorescence aerosolization, and sodium saccharin aerosolization tests were also conducted.ResultsNegative pressures of up to -47.7 mmH2O were obtained using the enclosure with two wall suction units (combined outflow of 70 L min-1), with inflow of O2 of 15 L min-1. Negative pressures between -10 and - 35 mmH2O were maintained during simulated AGMPs, including oxygen delivery by mask, airway suctioning, bag-mask manual ventilation and endotracheal intubation of a potential COVID-19 patient. The ACE effectively contained smoke, fluorescein aerosol, and sodium saccharin aerosol within the enclosure during use.ConclusionsThe ACE is capable of maintaining negative pressure during simulated AGMPs. In all cases, containment was improved relative to an identical enclosure with non-occluded ports at ambient pressure. During the current COVID-19 pandemic, the use of such a device may assist in reducing nosocomial infections among healthcare providers.
How important are parents in the development of child anxiety and depression? A genomic analysis of parent-offspring trios in the Norwegian Mother Father and Child Cohort Study (MoBa)
Authors: Cheesman Rosa , Eilertsen Espen Moen , Ahmadzadeh Yasmin I. , Gjerde Line C. , Hannigan Laurie J. , Havdahl Alexandra , Young Alexander I. , Eley Thalia C. , Njølstad Pål R. , Magnus Per , Andreassen Ole A. , Ystrom Eivind , McAdams Tom A. 
Published: April 2020

AbstractBackgroundMany studies detect associations between parent behaviour and child symptoms of anxiety and depression. However, most do not account for shared genetic risk. Quantitative genetic designs provide a means of controlling for shared genes, but rely on observed putative exposure variables, and require data from highly specific family structures.MethodsThe intergenerational genomic method, Relatedness Disequilibrium Regression (RDR), indexes environmental effects of parents on child traits using measured genotypes. RDR estimates how much the parent genome influences the child indirectly via the environment, over and above effects of genes acting directly in the child. This ‘genetic nurture’ effect is agnostic to parent phenotype and captures unmeasured heritable parent behaviours. We applied RDR in a sample of 11,598 parent-offspring trios from the Norwegian Mother, Father and Child Cohort Study (MoBa) to estimate parental genetic nurture separately from direct child genetic effects on anxiety and depression symptoms at age 8. We also tested for mediation of genetic nurture via maternal emotional symptoms. Results were compared to a complementary non-genomic pedigree model.ResultsParental genetic nurture significantly influenced depression symptoms at age 8, explaining 14% of the phenotypic variance. Subsequent analyses suggested that maternal anxiety and depression partially mediated the parental genetic nurture effect. The genetic nurture effect was mirrored by the finding of shared family environmental influence in our complementary pedigree model. In contrast, variance in anxiety symptoms was not significantly influenced by common genetic variation in children or parents, despite a moderate pedigree heritability.ConclusionsGenomic methods like RDR represent new opportunities for genetically sensitive family research in humans, which until now has been largely confined to adoption, twin and other pedigree designs. Our results are relevant to debates about the role of parents in the development of emotional problems in children, and possibly where to intervene to reduce problems.
Estimating the end of the first wave of epidemic for COVID-19 outbreak in mainland China
Authors: Griette Quentin , Liu Zhihua , Magal Pierre 
Published: April 2020

AbstractOur main aim is to estimate the end of the first wave epidemic of COVID-19 outbreak in mainland China. We developed mathematical models to predict reasonable bounds on the date of end of the COVID-19 epidemics in mainland China with strong quarantine and testing measures for a sufficiently long time. We used reported data in China from January 20, 2020 to April 9, 2020. We firstly used a deterministic approach to obtain a formula to compute the probability distribution of the extinction date by combining the models and continuous-time Markov processes. Then we present the individual based model (IMB) simulations to compare the result by deterministic approach and show the absolute difference between the estimated cumulative probability distribution computed by simulations and formula. We provide the predictions of the end of the first wave epidemic for different fractions f of asymptomatic infectious that become reported symptomatic infectious.
Estimate of Covid prevalence using imperfect data
Authors: Rudnicki Witold R. , Piliszek Radosław 
Published: April 2020

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

ABSTRACTBackgroundFaced with the global pandemic of COVID-19, declared by World Health Organization (WHO) on March 11th2020, and the need to better understand the seasonal behavior of the virus, our team conducted this systematic review to describe current knowledge about the emergence and replicability of the virus and its correlation with different weather factors such as temperature and relative humidity.MethodsThe review was registered with the PROSPERO database. The electronic databases PubMed, Scopus, Web of Science, Cochrane Library, LILACS, OpenGrey and Google Scholar were examined with the searches restricted to the years 2019 and 2020. Risk of bias assessment was performed using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist tool. The GRADE tool was used to assess the quality of the evidence.ResultsThe initial screening identified 517 articles. After examination of the full texts, seventeen studies met the review’s eligibility criteria. Great homogeneity was observed in the findings regarding the effect of temperature and humidity on the seasonal viability and transmissibility of COVID-19. Cold and dry conditions were potentiating factors on the spread of the virus. After quality assessment, four studies had a high risk of bias and thirteen studies were scored as moderate risk of bias. The certainty of evidence was graded as low for both outcomes evaluated.ConclusionConsidering the existing scientific evidence, warm and wet climates seem to reduce the spread of COVID-19. The certainty of the evidence generated was graded as low. However, these variables alone could not explain most of the variability in disease transmission.
Novel Coronavirus in Nigeria: Epidemiological analysis of the first 45 days of the pandemic
Authors: Adegboye Oyelola A. , Adekunle Adeshina I. , Gayawan Ezra 
Published: April 2020

AbstractBackgroundOn December 31, 2019, the World Health Organization (WHO) was notified of a novel coronavirus in China that was later named COVID-19. On March 11, 2020, the outbreak of COVID-19 was declared a pandemic. The first instance of the virus in Nigeria was documented on February 27, 2020.MethodsThis study provides a preliminary epidemiological analysis of the first 45 days of COVID-19 outbreak in Nigeria quantifying. We estimated the early transmissibility via time-varying reproduction number based on Bayesian method that incorporates uncertainty in the distribution of serial interval (time interval between symptoms onset in an infected individual and the infector) and adjusted for disease importation.FindingsBy April 11, 2020, 318 confirmed cases and 10 deaths from COVID-19 have occurred in Nigeria. At day 45, the exponential growth rate was 0.07 (95% Confidence Interval (CI): 0.05 – 0.10) with doubling time of 9.84 days (95% CI: 7.28 – 15.18). Separately for travel related and local cases the doubling time was 12.88 days and 2.86 days, respectively. Furthermore, we estimated the reproduction number for each day of the outbreak using three-weekly window while adjusting for travel related cases. The estimated reproduction number was 4.98 (95% CrI: 2.65 – 8.41) at day 22 (March 19, 2020), peaking at 5.61 (95% CrI: 3.83 –7.88) at day 25 (March 22, 2020). The median reproduction number over the study period was 2.71 and the latest value at April 11, 2020 was 1.42 (95% CI: 1.26 – 1.58).InterpretationThese 45-day estimates suggested that cases of COVID-19 in Nigeria have been remarkably lower than expected and the preparedness to detect needs to be shifted to stop local transmission.FundingNone
Multinational modeling of SARS-CoV-2 spreading dynamics: Insights on the heterogeneity of COVID-19 transmission and its potential healthcare burden
Authors: Martinez-Loran Erick R. , Jesús Naveja J. , Bello-Chavolla Omar Y. , Contreras-Torres Flavio F. 
Published: April 2020

SummaryBackgroundModelling and projections of COVID-19 using a single set of transmission parameters can be an elaborated because the application of different levels of containment measures at different stages of the worldwide COVID-19 outbreak.MethodsWe developed a piecewise fitting SEIR methodology to fit the progress of the COVID-19 that can be applied on any of the 185 countries listed in John Hopkins Coronavirus Resource Center. The contagious contact rate, the rate of removal and the initially exposed population were obtained at three different stages of the pandemic for a set of 18 countries, and globally for the total number of cases worldwide. The active number of infections and the removed populations were fitted simultaneously to validate the SEIR model against the available time series reports on the number of confirmed infections, recoveries and deaths. We evaluate the effect of a reduction of contagious contact rate on the level of burden put on local healthcare infrastructure considering different levels of intervention. As a guideline for future public health interventions, we also estimated the maximum number of future cases and its potential peak date.FindingsWe project that the peak in the number of infections worldwide will take place after the third quarter of 2020 with a decline rate that might extend beyond 2020. For 12 out of the 18 countries analyzed, we observe that, following the trend at the date of this study, the number of severe infections will surpass their healthcare capacity. For a 90% reduction scenario of the contagious contact rate, four out of the 18 countries analyzed will undergo a significant delay in the peak of infection, extending the course of the epidemic further than our simulation window (365 days).InterpretationWe identify three stages for the COVID-19 transmission dynamics, which suggest that it is highly heterogeneous between countries and its contagious contact rate, is currently affected by both local responses of the public health interventions and to the population’s adherence to the measures.FundingNo funding received.
Refined compartmental models, asymptomatic carriers and COVID-19
Authors: Oliveira Gonçalo 
Published: April 2020

AbstractThe goal of this article is to analyze some compartmental models specially designed to model the spread of a disease whose transmission has the same features as COVID-19. The major contributions of this article are: (1) Rigorously find sufficient conditions for the outbreak to only have one peak, i.e. for no second wave of infection to form; (2) Investigate the formation of other waves of infection when such conditions are not met; (3) Use numerical simulations to analyze the different roles asymptomatic carriers can have. We also argue that dividing the population into non-interacting groups leads to an effective reduction of the transmission rates.As in any compartmental model, the goal of this article is to provide qualitative understanding rather than exact quantitative predictions.
The Easter and Passover Blip in New York City: How exceptions can cause detrimental effects in pandemic times
Authors: Vierlboeck Maximilian , Nilchiani Roshanak R. , Edwards Christine M. 
Published: April 2020

Abstract and Executive SummaryWhen it comes to pandemics such as the currently present COVID-19 [1], various issues and problems arise for infrastructures and institutions. Due to possible extreme effects, such as hospitals potentially running out of beds or medical equipment, it is essential to lower the infection rate to create enough space to attend to the affected people and allow enough time for a vaccine to be developed. Unfortunately, this requires that measures put into place are upheld long enough to reduce the infection rate sufficiently.In this paper, we describe research simulating the influences of the contact rate on the spread of the pandemic using New York City as an example (Section IV) and especially already observed effects of contact rate increases during holidays [2-4] (Section V). In multiple simulations scenarios for Passover and Easter holidays, we evaluated 25%, 50%, 75%, and 100% temporary increases in contact rates using a scenario close to the currently reported numbers as reference and contact rates based on bioterrorism research as a “normal” baseline for NYC.The first general finding from the simulations is that singular events of increased visits/contacts amplify each other disproportionately if they are happening in close proximity (time intervals) together. The second general observation was that contact rate spikes leave a permanently increased and devastating infection rate behind, even after the contact rate returns to the reduced one. In case of a temporary sustained increase of contact rate for just three days in a row, the aftermath results in an increase of infection rate up to 40%, which causes double the fatalities in the long run.In numbers, given that increases of 25% and 50% seem to be most likely given the data seen in Germany for the Easter weekend for example [2, 3], our simulations show the following increases (compared to the realistic reference run): for a temporary 25% surge in contact rate, the total cases grew by 215,880, the maximum of required hospitalizations over time increased to 63,063, and the total fatalities climbed by 8,844 accumulated over 90 days. As for the 50% surge, we saw the total number of cases rise by 461,090, the maximum number of required hospitalizations increase to 79,733, and the total number of fatalities climb by 19,125 over 90 days in NYC.All in all, we conclude that even very short, temporary increases in contact rates can have disproportionate effects and result in unrecoverable phenomena that can hardly be reversed or managed later. The numbers show possible phenomena before they might develop effects in reality. This is important because phenomena such as the described blip can impact the hospitals in reality. Therefore, we warn that a wave of infections due to increased contact rates during Passover/Easter might come as a result!
Estimate of COVID-19 case prevalence in India based on surveillance data of patients with severe acute respiratory illness
Authors: Venkatesan Padmanaban 
Published: April 2020

AbstractIn absence of extensive testing for SARS-CoV-2, true prevalence of COVID-19 cases in India remain unknown. In this study, a conservative estimate of prevalence of COVID-19 is calculated based on the age wise COVID-19 positivity rate among patients with severe respiratory illness as reported by Indian Council of Medical Research. Calculations in the study estimates a cumulative number of 17151 COVID-19 positive cases by the end of April 2, 2020.
Clinical academic research in the time of Corona: a simulation study in England and a call for action
Authors: Banerjee Amitava , Katsoulis Michail , Lai Alvina G. , Pasea Laura , Treibel Thomas A. , Manisty Charlotte , Denaxas Spiros , Quarta Giovanni , Hemingway Harry , Cavalcante Joao , Noursadeghi Mahdad , Moon James C 
Published: April 2020

AbstractBackgroundCoronavirus (COVID-19) poses health system challenges in every country. As with any public health emergency, a major component of the global response is timely, effective science. However, particular factors specific to COVID-19 must be overcome to ensure that research efforts are optimised. We aimed to model the impact of COVID-19 on the clinical academic response in the UK, and to provide recommendations for COVID-related research.MethodsWe constructed a simple stochastic model to determine clinical academic capacity in the UK in four policy approaches to COVID-19 with differing population infection rates: “Italy model” (6%), “mitigation” (10%), “relaxed mitigation” (40%) and “do-nothing” (80%) scenarios. The ability to conduct research in the COVID-19 climate is affected by the following key factors: (i) infection growth rate and population infection rate (from UK COVID-19 statistics and WHO); (ii) strain on the healthcare system (from published model); and (iii) availability of clinical academic staff with appropriate skillsets affected by frontline clinical activity and sickness (from UK statistics).FindingsIn “Italy model”, “mitigation”, “relaxed mitigation” and “do-nothing” scenarios, from 5 March 2020 the duration (days) and peak infection rates (%) are 95(2.4%), 115(2.5%), 240(5.3%) and 240(16.7%) respectively. Near complete attrition of academia (87% reduction, <400 clinical academics) occurs 35 days after pandemic start for 11, 34, 62, 76 days respectively – with no clinical academics at all for 37 days in the “do-nothing” scenario. Restoration of normal academic workforce (80% of normal capacity) takes 11,12, 30 and 26 weeks respectively.InterpretationPandemic COVID-19 crushes the science needed at system level. National policies mitigate, but the academic community needs to adapt. We highlight six key strategies: radical prioritisation (eg 3-4 research ideas per institution), deep resourcing, non-standard leadership (repurposing of key non-frontline teams), rationalisation (profoundly simple approaches), careful site selection (eg protected sites with large academic backup) and complete suspension of academic competition with collaborative approaches.