bluuebunny/crossref_metadata_2025_split huggingface dataset:
A pragmatic model to forecast the COVID-19 epidemic in different countries and allowing for daily updates
Authors: Nordt Carlos , Herdener Marcus 
Published: April 2020

AbstractDue to high infections rates and a high death toll of the COVID-19 pandemic, it is important to have daily updated forecasted estimates for the next weeks in order to allocate the scare resources as good as possible. We propose a pragmatic model to forecast the COVID-19 epidemic by applying a mixture normal distribution to open accessible WHO data. We specified a simple joint model on data from 20 countries with number of confirmed COVID-19 infections and number of COVID-19 deaths. We found that the duration of an epidemic wave (99% of total size) was usually between 45 – 48 days. Using data up to April 6, 2020, we found in six of 20 counties two waves, spaced between 21 and 47 days. In China and Korea the first wave was bigger, and in Denmark, Iran, Japan, and Sweden the second wave was stronger. Lag time between time trends in confirmed infections and time trends in deaths varied between 3.1 and 9.5 days. We obtained a good fit between observed and modelled data in almost all countries. In about halve of the countries the highest peak of the COVID-19 epidemic had been reached until April 6, 2020. Among the 20 countries, it is predicted that the USA will reach the highest numbers of confirmed infections (653 683 – 802 205) and number of deaths (36 591 – 53 286). Taken together, for many countries reasonable and up-to-date forecasting seems to be feasible. This method therefore bears a high potential for assisting decision makers to adjust the measures aiming at reducing the spread of the virus appropriately.
Potential dissemination of epidemics based on Brazilian mobile geolocation data. Part I: Population dynamics and future spreading of infection in the states of São Paulo and Rio de Janeiro during the pandemic of COVID-19
Authors: Peixoto Pedro S. , Marcondes Diego , Peixoto Cláudia , Queiroz Lucas , Gouveia Rafael , Delgado Afonso , Oliva Sérgio M. 
Published: April 2020

AbstractMobile geolocation data is a valuable asset in the assessment of movement patterns of a population. Once a highly contagious disease takes place in a location the movement patterns aid in predicting the potential spatial spreading of the disease, hence mobile data becomes a crucial tool to epidemic models. In this work, based on millions of anonymized mobile visits data in Brazil, we investigate the most probable spreading patterns of the COVID-19 within states of Brazil. The study is intended to help public administrators in action plans and resources allocation, whilst studying how mobile geolocation data may be employed as a measure of population mobility during an epidemic. The first part of the study focus on the states of São Paulo and Rio de Janeiro during the period of March 2020, when the disease first started to spread in these states. Metapopulation models for the disease spread were simulated in order to evaluate the risk of infection of each city within the states, by ranking them according to the time the disease will take to infect each city. We observed that, although the high risk regions are those closer to the capital cities, where the outbreak has started, there are also cities in the countryside with great risk.
ACE-inhibitors and Angiotensin-2 Receptor Blockers are not associated with severe SARS-COVID19 infection in a multi-site UK acute Hospital Trust
Authors: Bean Daniel M , Kraljevic Zeljko , Searle Thomas , Bendayan Rebecca , O’Gallagher Kevin , Pickles Andrew , Folarin Amos , Roguski Lukasz , Noor Kawsar , Shek Anthony , Zakeri Rosita , Shah Ajay M , Teo James TH , Dobson Richard JB 
Published: April 2020

AbstractAimsThe SARS-Cov2 virus binds to the ACE2 receptor for cell entry. It has been suggested that ACE-inhibitors (ACEi) and Angiotensin-2 Blockers (ARB), which are commonly used in patients with hypertension or diabetes and may raise ACE2 levels, could increase the risk of severe COVID19 infection.Methods and ResultsWe evaluated this hypothesis in a consecutive cohort of 1200 acute inpatients with COVID19 at two hospitals with a multi-ethnic catchment population in London (UK). The mean age was 68±17 years (57% male) and 74% of patients had at least 1 comorbidity. 415 patients (34.6%) reached the primary endpoint of death or transfer to a critical care unit for organ support within 21-days of symptom onset. 399 patients (33.3 %) were taking ACEi or ARB. Patients on ACEi/ARB were significantly older and had more comorbidities. The odds ratio (OR) for the primary endpoint in patients on ACEi and ARB, after adjustment for age, sex and co-morbidities, was 0.63 (CI 0.47-0.84, p<0.01).ConclusionsThere was no evidence for increased severity of COVID19 disease in hospitalised patients on chronic treatment with ACEi or ARB. A trend towards a beneficial effect of ACEi/ARB requires further evaluation in larger meta-analyses and randomised clinical trials.
Non-specific Primers Reveal False-negative Risk in Detection of COVID-19
Authors: Liu Wei 
Published: April 2020

SummaryBackgroundA novel coronavirus disease 2019 (COVID-19) broke out in Wuhan of Hubei province and had spread throughout the world since December 2019. Because the clinically diagnosed cases in Hubei province were reported for the first time on February 13, 2020, a very high peak of new cases in China was observed. The reason why so many clinically diagnosed cases appeared was not clear.MethodsAll data of new cases in China were acquired from WHO situation reports. Linear fitting was used to infer the ability to detect COVID-19 infections. Primer-BLAST and nucleotide blast were applied to check the specificity of primers. Expression data of human mRNA in different tissues was obtained from Human Protein Atlas.FindingsBased on the data and analysis of changes of new laboratory-confirmed cases and new clinically diagnosed cases, it was inferred that there were many false-negative results in all clinically diagnosed cases in Hubei province. There were eight non-specific primers in dozens of primers used in clinical or research detection of COVID-19. Among them, a pair of primer for the ORF1ab regions of SARS-CoV-2 genome well matched some human mRNAs such as Cathepsin C transcripts. Compared to other transcripts, Cathepsin C mRNA had a high abundance in tonsil, lung and small intestine.InterpretationSome non-specific RT-PCR primers could cause the serious interference during RT-PCR amplification so as to increase the risk of false-negative diagnoses for COVID-19 infections.FundingKey Research Project of the Higher Education of Henan ProvinceResearch in contextEvidence before this studyThe author searched PubMed on April 15, 2020, for papers that describe false-negative RT-PCR detection of COVID-19 by using the search terms “COVID-19”, “false-negative” and “RT-PCR”, with no language or time restrictions. Eleven investigations only presented the rate of false-negative detection or the importance of positive chest CT finding. There were no reports referring the primer problems of false-negative detection in COVID-19 infections.Added value of this studyThe author had found that some primers could amplify the human mRNA in specimens, which mixed SARS-CoV-2 viral particles and other tissue cells. A pair of primer provided by China CDC could vastly match the sequences of human CTSC transcripts with high abundance. That could lead to false-negative results in detection of COVID-19 infections.Implications of all the available evidenceAlthough there were so many false-negative results in detection of COVID-19 infections in China, the exact reason was not clear. Problems in sampling and test condition were discussed thoroughly, but conclusions were usually contradictory. Therefore, the work could promote the verification of the false-negative detection of COVID-19 infections in China.
SARS-CoV-2 and human milk: what is the evidence?
Authors: Lackey Kimberly A. , Pace Ryan M. , Williams Janet E. , Bode Lars , Donovan Sharon M. , Järvinen Kirsi M. , Seppo Antti E. , Raiten Daniel J. , Meehan Courtney L. , McGuire Mark A. , McGuire Michelle K. 
Published: April 2020

ABSTRACTThe novel coronavirus SARS-CoV-2 has emerged as one of the most compelling and concerning public health challenges of our time. To address the myriad issues generated by this pandemic, an interdisciplinary breadth of research, clinical, and public health communities has rapidly engaged to collectively find answers and solutions. One area of active inquiry is understanding the mode(s) of SARS-CoV-2 transmission. While respiratory droplets are a known mechanism of transmission, other mechanisms are likely. Of particular importance to global health is the possibility of vertical transmission from infected mothers to infants through breastfeeding or consumption of human milk. However, there is limited published literature related to vertical transmission of any human coronaviruses (including SARS-CoV-2) via human milk and/or breastfeeding. Results of the literature search reported here (finalized on April 17, 2020) revealed a single study providing some evidence of vertical transmission of human coronavirus 229E; a single study evaluating presence of SARS-CoV in human milk (it was negative); and no published data on MERS-CoV and human milk. We identified 12 studies reporting human milk tested for SARS-CoV-2; one study detected the virus in one milk sample, and another study detected SARS-CoV-2 specific IgG in milk. Importantly, none of the studies on coronaviruses and human milk report validation of their collection and analytical methods for use in human milk. These reports are evaluated here, and their implications related to the possibility of vertical transmission of coronaviruses (in particular, SARS-CoV-2) during breastfeeding are discussed.
HOW THE COVID-19 PANDEMIA IS SPREADING IN ITALY
Authors: Salvatoni Alessandro 
Published: April 2020

AbstractIn this short paper we describe a simple technique aimed to forecast the course of the spreading of Covid-19 virus infection in Italy. Data released every day by the Italian “Protezione Civile” organization have been processed with reference of the the SIR classical mathematical model by Kermack and McKendrick. The model provides a rough estimate of the time needed to completely block virus spread. The above assumptions will be valid if Covid-19 will not be recognized as capable of establishing a chronic productive infection in significant fraction of the population.
Modeling the COVID-19 pandemic - parameter identification and reliability of predictions
Authors: Hackl Klaus 
Published: April 2020

AbstractIn this paper, we try to identify the parameters for two elementary epidemic models, the so-called SI- and SIS-models, via non-linear regression using data of the COVID-19 pandemic. This is done based on the data for the number of daily infections. Studying the history of predictions made, we attempt to estimate their reliability concerning the future course of the epidemic. We validate this procedure using data for the case numbers in China and South Korea. Then we apply it in order to find predictions for Germany, Italy and the United States. The results are encouraging, but no final judgment on the validity of the procedure can yet be made.
A model to predict COVID-19 epidemics with applications to South Korea, Italy, and Spain
Authors: Liu Z. , Magal P. , Seydi Ousmane , Webb Glenn 
Published: April 2020

1AbstractIn this work, our team develops a differential equations model of COVID-19 epidemics. Our goal is to predict forward in time the future number of cases from early reported case data in regions throughout the world. Our model incorporates the following important elements of COVID-19 epidemics: (1) the number of asymptomatic infectious individuals (with very mild or no symptoms), (2) the number of symptomatic reported infectious individuals (with severe symptoms) and (3) the number of symptomatic unreported infectious individuals (with less severe symptoms). We apply our model to COVID-!9 epidemics in South Korea, Italy and Spain.
LabWAS: novel findings and study design recommendations from a meta-analysis of clinical labs in two independent biobanks
Authors: Goldstein Jeffery A. , Weinstock Joshua S. , Bastarache Lisa A. , Larach Daniel B. , Fritsche Lars G. , Schmidt Ellen M. , Brummett Chad M. , Kheterpal Sachin , Abecasis Goncalo R. , Denny Joshua C. , Zawistowski Matthew 
Published: April 2020

ABSTRACTPhenotypes extracted from Electronic Health Records (EHRs) are increasingly prevalent in genetic studies. EHRs contain hundreds of distinct clinical laboratory test results, providing a trove of health data beyond diagnoses. Such lab data is complex and lacks a ubiquitous coding scheme, making it more challenging than diagnosis data. Here we describe the first large-scale cross-health system genome-wide association study (GWAS) of EHR-based quantitative lab measurements. We meta-analyzed 70 labs matched between the BioVU cohort from the Vanderbilt University Health System and the Michigan Genomics Initiative (MGI) cohort from Michigan Medicine. We show high replication of known association for these labs, validating EHR-based measurements as high-quality phenotypes for genetic analysis. Notably, our analysis provides the first replication for 700 previous GWAS associations across 46 different labs. We discovered 31 novel associations at genome-wide significance for 22 distinct labs, including the first reported associations for two labs. We replicated 22 of these novel associations in an independent tranche of BioVU samples. The summary statistics for all association tests are available through an interactive webtool to benefit other researchers. Finally, we performed mirrored analyses in BioVU and MGI to assess competing analytic practices for lab data. We find that using the mean of all available lab measurements provides a robust summary value, but alternate summarizations can improve power in certain labs. This study provides a proof-of-principle for cross health system GWAS and is a framework for future studies of quantitative traits in EHRs.
Prediction on Covid-19 epidemic for different countries: Focusing on South Asia under various precautionary measures
Authors: Paul Abhijit , Chatterjee Samrat , Bairagi Nandadulal 
Published: April 2020

ABSTRACTThe coronavirus disease 2019 (COVID-19), which emerged from Wuhan, China, is now a pandemic, affecting across the globe. Government of different countries have developed and adopted various policies to contain this epidemic and the most common were the social distancing and lockdown. We proposed a SEIR epidemic model that accommodates the effects of lockdown and individual based precautionary measures and used it to estimate model parameters from the epidemic data up to 2nd April, 2020, freely available in GitHub repository for COVID-19, for nine developed and developing countries. We used the estimated parameters to predict the disease burden in these countries with special emphasis on India, Bangladesh and Pakistan. Our analysis revealed that the lockdown and recommended individual hygiene can slow down the outbreak but unable to eradicate the disease from the society. With the current human-to-human transmission rate and existing level of personal precautionary, the number of infected individuals in India will be increasing at least for the next 3 months and the peak will come in 5 months. We can, however, reduce the epidemic size and prolong the time to arrive epidemic peak by seriously following the measures suggested by the authorities. We need to wait for another one month to obtain more data and epidemiological parameters for giving a better prediction about the pandemic. It is to be mentioned that research community is working for drugs and/ or vaccines against COVID19 and the presence of such pharmaceutical interventions will significantly alter the results.
Exercising caution in correlating COVID-19 incidence and mortality rates with BCG vaccination policies due to variable rates of SARS CoV-2 testing
Authors: Hensel Janine , McAndrews Kathleen M. , McGrail Daniel J. , Dowlatshahi Dara P. , LeBleu Valerie S. , Kalluri Raghu 
Published: April 2020

ABSTRACTThe Bacillus Calmette-Guerin (BCG) vaccine provides protection against tuberculosis (TB), and is proposed to provide protection to non-TB infectious diseases. The COVID-19 outbreak results from infection with the novel coronavirus SARS-CoV-2 (CoV-2) and was declared a pandemic on March 11th, 2020. We queried whether the BCG vaccine offers protection against CoV-2 infection. We observed that countries with a current universal BCG vaccination policy have a significantly lower COVID-19 incidence than countries which never had a universal BCG policy or had one in the past. However, population density, median age, TB incidence, urban population, and, most significantly, CoV-2 testing rate, were also connected with BCG policy and could potentially confound the analysis. By limiting the analysis to countries with high CoV-2 testing rates, defined as greater than 2,500 tests per million inhabitants, these parameters were no longer statistically associated with BCG policy. When analyzing only countries with high testing rates, there was no longer a significant association between the number of COVID-19 cases per million inhabitants and the BCG vaccination policy. Although preliminary, our analyses indicate that the BCG vaccination may not offer protection against CoV-2 infection. While reporting biases may confound our observations, our findings support exercising caution in determining potential correlation between BCG vaccination and COVID-19 incidence, in part due significantly lower rates of CoV-2 testing per million inhabitants in countries with current universal BCG vaccination policy.
Prognostic factors for severity and mortality in patients infected with COVID-19: A living systematic review protocol
Authors: Izcovich Ariel , Ragusa Martín , Sanguine Verónica , Tortosa Fernando , Espinosa Federico , Agnoletti Camila , Lavena Marzio María Andrea , Ceirano Agustina , Bengolea Agustín , Saavedra Ezequiel , Catalano Hugo N. , Rada Gabriel ,   COVID-19 L·OVE Working Group
Published: April 2020

ABSTRACTObjectiveThe objective of our systematic review is to identify prognostic factors that can potentially be used in decision-making related to the care of patients infected 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 covered and customised to group all COVID-19 evidence in one place. The search will continue until the day before submission to a journal.Eligibility criteria for selecting studies and methodsWe will follow a common protocol for multiple parallel systematic reviews, already published and submitted to PROSPERO (awaiting ID allocation).We will include studies that assess patients with confirmed or suspected SARS-CoV-2 infection and inform the relation between potential prognostic factors and death or disease severity. Two groups of two reviewers will independently screen studies for eligibility, extract data and assess the risk of bias. We will perform meta-analyses and use GRADE to assess the certainty of evidence for each prognostic factor and outcome.A living, web-based version of this review will be openly available during the COVID-19 pandemic. We will resubmit it if the conclusions change or 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).
Epidemiological characteristics of COVID-19 cases in Italy and estimates of the reproductive numbers one month into the epidemic
Authors: Riccardo Flavia , Ajelli Marco , Andrianou Xanthi D , Bella Antonino , Del Manso Martina , Fabiani Massimo , Bellino Stefania , Boros Stefano , Urdiales Alberto Mateo , Marziano Valentina , Rota Maria Cristina , Filia Antonietta , D’Ancona Fortunato Paolo , Siddu Andrea , Punzo Ornella , Trentini Filippo , Guzzetta Giorgio , Poletti Piero , Stefanelli Paola , Castrucci Maria Rita , Ciervo Alessandra , Di Benedetto Corrado , Tallon Marco , Piccioli Andrea , Brusaferro Silvio , Rezza Giovanni , Merler Stefano , Pezzotti Patrizio ,   for the COVID-19 working group
Published: April 2020

SUMMARYBackgroundIn February 2020, a locally-acquired COVID-19 case was detected in Lombardia, Italy. This was the first signal of ongoing transmission of SARS-CoV-2 in the country. The outbreak rapidly escalated to a national level epidemic, amid the WHO declaration of a pandemic.MethodsWe analysed data from the national case-based integrated surveillance system of all RT-PCR confirmed COVID-19 infections as of March 24th 2020, collected from all Italian regions and autonomous provinces. Here we provide a descriptive epidemiological summary on the first 62,843 COVID-19 cases in Italy as well as estimates of the basic and net reproductive numbers by region.FindingsOf the 62,843 cases of COVID-19 analysed, 71.6% were reported from three Regions (Lombardia, Veneto and Emilia-Romagna). All cases reported after February 20th were locally acquired. Estimates of R0 varied between 2.5 (95%CI: 2.18-2.83) in Toscana and 3 (95%CI: 2.68-3.33) in Lazio, with epidemic doubling time of 3.2 days (95%CI: 2.3-5.2) and 2.9 days (95%CI: 2.2-4.3), respectively. The net reproduction number showed a decreasing trend starting around February 20-25, 2020 in Northern regions. Notably, 5,760 cases were reported among health care workers. Of the 5,541 reported COVID-19 associated deaths, 49% occurred in people aged 80 years or above with an overall crude CFR of 8.8%. Male sex and age were independent risk factors for COVID-19 death.InterpretationThe COVID-19 infection in Italy emerged with a clustering onset similar to the one described in Wuhan, China and likewise showed worse outcomes in older males with comorbidities. Initial R0 at 2.96 in Lombardia, explains the high case-load and rapid geographical spread observed. Overall Rt in Italian regions is currently decreasing albeit with large diversities across the country, supporting the importance of combined non-pharmacological control measures.Fundingroutine institutional funding was used to perform this work.