bluuebunny/crossref_metadata_2025_split huggingface dataset:
Increasing Virus Test Capacity via Recursive Pool Testing with an Application to SARS-CoV-2 Testing
Authors: Mutzel Petra , Bertram Alexander , Jünger Paul , Jünger Pauline , Krieger Horst , Schmitz Stephan , Jünger Michael 
Published: July 2020

AbstractIn the context of adequate reactions to the current Covid-19 pandemic, Seifried, Ciesek et al. [6, 5] have proposed the application of SARS-CoV-2 pool testing in the pursuit of increasing testing capacity. We show how this method can be substantially improved in realistic scenarios, and we point out a possible impact on the ongoing discussion concerning the need of increased testing as a complementary measure to relaxed restrictions.
A systematic review of the smartphone applications available for corona virus disease 2019 (COVID19) and their assessment using the mobile app rating scale (MARS)
Authors: Davalbhakta Samira , Advani Shailesh , Kumar Shobhit , Agarwal Vishwesh , Bhoyar Samruddhi , Fedirko Elizabeth , Misra Durga Prasanna , Goel Ashish , Gupta Latika , Agarwal Vikas 
Published: July 2020

AbstractThe global impact of COVID-19 pandemic has increased the need to rapidly develop and improve utilization of mobile applications across the healthcare continuum to address rising barriers of access to care due to social distancing challenges and allow continuity in sharing of health information, assist with COVID-19 activities including contact tracing, and providing useful information as needed. Here we provide an overview of mobile applications being currently utilized for COVID-19 related activities. We performed a systematic review of the literature and mobile platforms to assess mobile applications been currently utilized for COVID-19, and quality assessment of these applications using the Mobile Application Rating Scale (MARS) for overall quality, Engagement, Functionality, Aesthetics, and Information. Finally, we provide an overview of the key salient features that should be included in mobile applications being developed for future use. Our search identified 63 apps that are currently being used for COVID-19. Of these, 25 were selected from the Google play store and Apple App store in India, and 19 each from the UK and US. 18 apps were developed for sharing up to date information on COVID-19, and 8 were used for contact tracing while 9 apps showed features of both. On MARS Scale, overall scores ranged from 2.4 to 4.8 with apps scoring high in areas of functionality and lower in Engagement. Future steps should involve developing and testing of mobile applications using assessment tools like the MARS scale and the study of their impact on health behaviors and outcomes.
Tissue-specific tolerance in fatal Covid-19
Authors: Dorward David A , Russell Clark D , Um In Hwa , Elshani Mustafa , Armstrong Stuart D , Penrice-Randal Rebekah , Millar Tracey , Lerpiniere Chris EB , Tagliavini Giulia , Hartley Catherine S , Randle Nadine P , Gachanja Naomi N , Potey Philippe MD , Anderson Alison M , Campbell Victoria L , Duguid Alasdair J , Qsous Wael Al , BouHaidar Ralph , Baillie J Kenneth , Dhaliwal Kevin , Wallace William A , Bellamy Christopher OC , Prost Sandrine , Smith Colin , Hiscox Julian A , Harrison David J , Lucas Christopher D 
Published: July 2020

ABSTRACTBackgroundTissue inflammation is associated with organ dysfunction and death in Covid-19. The efficacy of dexamethasone in preventing mortality in critical Covid-19 suggests that inflammation has a causal role in death. Whether this deleterious inflammation is a direct response to the presence of SARS-CoV-2, or an independent immuno-pathologic process, is unknown.MethodsTissue was acquired from detailed post-mortem examinations conducted on 11 well characterised hospitalised patients with fatal Covid-19. SARS-CoV-2 organotropism was mapped at an organ level by multiplex PCR and sequencing, with cellular resolution achieved by in situ viral spike (S) protein detection. Histological evidence of inflammation and organ injury was systematically examined, and the pulmonary immune response characterized with multiplex immunofluorescence.FindingsSARS-CoV-2 was detected across a wide variety of organs, most frequently in the respiratory tract but also in numerous extra-pulmonary sites. Minimal histological evidence of inflammation was identified in non-pulmonary organs despite frequent detection of viral RNA and protein. At a cellular level, viral protein was identified without adjacent inflammation in the intestine, liver and kidney. Severe inflammatory change was restricted to the lung and reticulo-endothelial system. Diffuse alveolar damage, pulmonary thrombi and a monocyte/myeloid-predominant vasculitis were the predominant pulmonary findings, though there was not a consistent association between viral presence and either the presence or nature of the inflammatory response within the lung. Immunophenotyping revealed an influx of macrophages, monocytes and T cells into pulmonary parenchyma. Bone marrow examination revealed plasmacytosis, erythroid dysplasia and iron-laden macrophages. Plasma cell excess was also present in lymph node, spleen and lung. These stereotyped reticulo-endothelial responses occurred largely independently of the presence of virus in lymphoid tissues.ConclusionsTissue inflammation and organ dysfunction in fatal Covid-19 do not map to the tissue and cellular distribution of SARS-CoV-2, demonstrating tissue-specific tolerance. We conclude that death in Covid-19 is primarily a consequence of immune-mediated, rather than pathogen-mediated, organ inflammation and injury.FundingThe Chief Scientist Office, LifeArc, Medical Research Scotland, UKRI (MRC).
Association of chronic heart failure and its comorbidities with loss of actuarially predicted life expectancy: a prospective cohort study
Authors: Drozd Michael , Relton Samuel D , Walker Andrew MN , Slater Thomas , Gierula John , Paton Maria F , Lowry Judith , Straw Sam , Koshy Aaron , McGinlay Melanie , Simms Alexander D , Gatenby V Kate , Sapsford Robert J , Witte Klaus K , Kearney Mark T , Cubbon Richard M 
Published: July 2020

AbstractBackgroundEstimating survival can aid care planning, but the use of absolute survival projections can be challenging for patients and clinicians to contextualize. We aimed to define how heart failure and its major comorbidities contribute to loss of actuarially predicted life expectancy.MethodsWe conducted an observational cohort study of 1794 adults with stable chronic heart failure and reduced left ventricular ejection fraction, recruited from cardiology outpatient departments of 4 United Kingdom (UK) hospitals. Data from an 11-year maximum (5-year median) follow-up period (999 deaths) was used to define how heart failure and its major comorbidities impact upon survival, relative to an age-sex matched control UK population, using a relative survival framework.ResultsAfter 10 years, mortality in the reference control population was 29%. In people with heart failure, this increased by an additional 37% (95% confidence interval 34-40%), equating to an additional 2.2-years of lost life, or a 2.4-fold (2.2-2.5) excess loss of life. This excess was greater in men than women (2.4 years [2.2-2.7] versus 1.6 years [1.2-2.0]; p<0.001). In patients without major comorbidity, men still experienced excess loss of life, whilst women experienced less and were non-significantly different from the reference population (1 year [0.6-1.5] versus 0.4 years [-0.3-1]; p<0.001). Accrual of comorbidity was associated with substantial increases in excess loss of life, particularly for chronic kidney and lung disease.ConclusionsComorbidity accounts for the majority of lost life expectancy in people with heart failure. Women, but not men, without comorbidity experience survival close to reference controls.
Using ECG Machine Learning for Detection of Cardiovascular Disease in African American Men and Women: the Jackson Heart Study
Authors: Pollard James D. , Haq Kazi T. , Lutz Katherine J. , Rogovoy Nichole M. , Paternostro Kevin A. , Soliman Elsayed Z. , Maher Joseph , Lima João A.C. , Musani Solomon , Tereshchenko Larisa G. 
Published: July 2020

AbstractBackgroundAlmost half of African American (AA) men and women have cardiovascular disease (CVD). Detection of prevalent CVD in barbershops would facilitate secondary prevention of CVD. We sought to investigate the cross-sectional association of prevalent CVD and sex with global electrical heterogeneity (GEH) and develop a tool for CVD detection.MethodsParticipants from the Jackson Heart Study (JHS) with analyzable ECGs (n=3,679; age, 62±12 years; 36% men) were included. QRS, T, and spatial ventricular gradient (SVG) vectors’ magnitude and direction, and traditional metrics were measured on 12-lead ECG. Linear regression and mixed linear models with random intercept were adjusted for cardiovascular risk factors, sociodemographic and anthropometric characteristics, type of median beat, and mean RR’ intervals. Random forests, convolutional neural network, and lasso models were developed in 80%, and validated in 20% samples.ResultsIn fully adjusted models, women had a smaller spatial QRS-T angle (−12.2(−19.4 to-5.1)°;P=0.001), SAI QRST (−29.8(−39.3 to −20.3) mV*ms;P<0.0001), and SVG elevation (−4.5(−7.5 to −1.4)°;P=0.004) than men, but larger SVG azimuth (+16.2(10.5-21.9)°;P<0.0001), with a significant random effect between families (+20.8(8.2-33.5)°;P=0.001). SAI QRST was larger in women with CVD as compared to CVD-free women or men (+15.1(3.8-26.4) mV*ms;P=0.009). Men with CVD had smaller T area [by 5.1 (95%CI 1.2-9.0) mV*ms] than CVD-free men, but there were no differences when comparing women with CVD to CVD-free women. Machine-learning detected CVD with ROC AUC 0.69-0.74; plug-in-based model included only age and QRS-T angle.ConclusionsGEH varies by sex. Sex modifies an association of GEH with CVD. Automated CVD detection is feasible.
Modeling the COVID-19 dissemination in the South Region of Brazil and testing gradual mitigation strategies
Authors: da Silva Rafael M. 
Published: July 2020

AbstractThis study aims to understand the features of the COVID-19 spread in the South Region of Brazil by estimating the Effective Reproduction Number (ERN)ℛefor the states of Paraná (PR), Rio Grande do Sul (RS), and Santa Catarina (SC). We used the SIRD (Susceptibles-Infectious-Recovered-Dead) model to describe the past data and to simulate strategies for the gradual mitigation of the epidemic curve by applying non-pharmacological measures. Besides the SIRD model does not include some aspects of COVID-19, as the symptomatic and asymptomatic subgroups of individuals and the incubation period, for example, in this work we intend to use a classical and easy to handle model to introduce a thorough method of adjustment that allows us to achieve reliable fitting for the real data and to obtain insights about the current trends for the pandemic in each locality. Our results demonstrate that for localities for which the ERN is about 2, only rigid measures are efficient to avoid overwhelming the health care system. These findings corroborate the relevance of keeping the value ofℛebelow 1 and applying containment measures early.
Nowcasting Influenza-like Illness Trends in Cameroon
Authors: Nsoesie Elaine O. , Oladeji Olubusola , Abah Aristide S. Abah , Ndeffo-Mbah Martial L. 
Published: July 2020

ABSTRACTAlthough acute respiratory infections are a leading cause of mortality in sub-Saharan Africa, surveillance of diseases such as influenza is mostly neglected. Evaluating the usefulness of influenza-like illness (ILI) surveillance systems and developing approaches for forecasting future trends is important for pandemic preparedness. We applied statistical and machine learning models to forecast 2012 to 2018 trends in ILI cases reported by the Cameroon Ministry of Health (MOH), using Google searches for influenza symptoms, treatments, natural or traditional remedies as well as, infectious diseases with a high burden (i.e., AIDS, malaria, tuberculosis). The variance explained by the models based on Google search data were 87.7%, 79.1% and 52.0% for the whole country, the Littoral and Centre regions respectively. Our study demonstrates the need for developing contextualized approaches when using digital data for disease surveillance and demonstrates the potential usefulness of search data for monitoring ILI in sub-Saharan African countries.
Dynamics of coagulopathy in patients with different COVID-19 severity
Authors: Kalinskaya Anna , Dukhin Oleg , Molodtsov Ivan , Maltseva Alexandra , Sokorev Denis , Elizarova Antonina , Sapozhnikova Olga , Glebova Ksenia , Stonogina Daria , Shakhidzhanov Soslan , Nikonov Evgeniy , Mazus Alexey , Spiridonov Ilia , Ataullakhanov Fazly , Margolis Leonid , Shpektor Alexander , Vasilieva Elena 
Published: July 2020

AbstractWith the progress of COVID-19 studies, it became evident that SARS-CoV-2 infection is often associated with thrombotic complications. The goal of our present study was to evaluate which component of clot formation process including endothelial function, platelets aggregation and plasma coagulation, as well as endogenous fibrinolysis in patients with COVID-19 correlates with the severity of the disease. We prospectively included 58 patients with COVID-19 and 47 healthy volunteers as a control group that we recruited before the pandemic started. It turns out that plasma coagulation with subsequent platelet aggregation, but not endothelial function, correlates with the severity of the COVID-19. IL-6 blockade may play a beneficial role in COVID-19 induced coagulopathy.
Laboratory findings that predict a poor prognosis in COVID-19 patients with diabetes: A meta-analysis
Authors: Lagunas-Rangel Francisco Alejandro , Chávez-Valencia Venice 
Published: July 2020

AbstractDiabetes is one of the main comorbidities in patients infected with the SARS-CoV-2 virus, the causative agent of the new coronavirus disease 2019 (COVID-19). Because the presence of diabetes and COVID-19 in the same patient is related to a poor clinical prognosis and a high probability of death, it is necessary to determine what findings allow us to predict a good or bad resolution of the disease in order to opt for a traditional treatment or a more incisive one. In this way, in the present work we analyze which laboratory parameters showed differences in patients with COVID-19 and diabetes who recovered and in those who had complications or died.
Stroke survivors experience elevated levels of loneliness: a multi-year analysis of the National Survey for Wales
Authors: Byrne Christopher , Saville Christopher W. N. , Coetzer Rudi , Ramsey Richard 
Published: July 2020

AbstractDespite clinical observation that stroke survivors frequently experience loneliness, there is no large-scale empirical evidence to support this observation. To address this issue, we completed two pre-registered analyses of a nationally representative annual survey that included a self-report measure of loneliness (N>21000). Across two separate cohorts, the results consistently showed that human stroke survivors report higher levels of loneliness compared to healthy individuals, and this relationship could not be accounted for by demographic factors (e.g., age, sex) or objective measures of social isolation (e.g., marital status, number of household members). These findings demonstrate that elevated levels of loneliness post-stroke are robust in that they replicate in large nationally representative samples and cannot be reduced to objective measures of social isolation. The work has clinical and societal relevance by suggesting that loneliness post-stroke is unlikely to be adequately “treated” if only the quantity and not the quality of social experiences are considered.
How was the Mental Health of Colombian people on March during Pandemics Covid19?
Authors: Chire Saire Josimar E. 
Published: July 2020

ABSTRACTActual pandemic started with first cases in China and fast spread in Europe, Asia and the next continents became a global concern from March, so the most of countries ordered a lockdown to decrease infection rate forced people to stay at home. The first confirmed case was on March 6, during the next days more cases were confirmed by Minster of Health, the first death was on March 21, one day after of the announcement of lockdown in Colombia. During this period of waiting for what is going to happen people can develop mental stress as fear, sleep disorders so to analyze how was the behaviour on the population the present study is conducted using a Social Network as Twitter, Natural Language algorithms and Data Mining criterion’s. The findings confirmed the interest of covid19 was increasing daily, people was experimenting fear, anxiety, mental stress.
Prevalence of IgG and IgM antibodies to SARS-CoV-2 among clinic staff and patients
Authors: Asuquo Marcus Inyama , Effa Emmanuel , Otu Akaninyene , Ita Okokon , Udoh Ubong , Umoh Victor , Gbotosho Oluwabukola , Ikpeme Anthonia , Ameh Soter , Egbe William , Etok Margaret , Guck Jochen , Ekpenyong Andrew 
Published: July 2020

ABSTRACTThe coronavirus disease 2019 (COVID-19) is now a pandemic with devastating social and economic consequences. The extent of the spread of COVID-19 within populations is uncertain since diagnostic tests have not been carried out on all eligible persons and doing such diagnostic tests on everyone is much less feasible in developing countries such as Nigeria. Tests for antibodies to SARS-CoV-2, the virus that causes COVID-19, are more affordable, readily available, and require minimal training than current diagnostic tests. Employing a seroepidemiological strategy, serological tests were conducted on 66 volunteering staff and patients at the University of Calabar Teaching Hospital (UCTH), a Federal Government owned tertiary healthcare facility, to determine the extent of exposure to SARS-CoV-2, from 17th to 25th June 2020. Using a COVID-19 IgG/IgM Rapid Test Cassette with emergency use authorization (EUA) from the Food and Drug Administration (FDA) of the United States, it was observed that of the 66 samples tested, 5 (7.6%) were both IgG and IgM positive and 17 (26%) were IgG positive. Moreover, for 44 of the 66 participants, simultaneous tests were carried out using a rapid test kit from a different manufacturer but without FDA-EUA and all the results completely matched with the FDA-EUA kit, except one case where the FDA-EUA kit showed positive for both IgG and IgM while the other kit was positive only for IgM. The 26% positive IgG indicates a high exposure rate for the hospital staff and patients and points to community transmission where the facility is situated. Hence, immediate activation of WHO guidelines for controlling community transmission is called for. These results can further serve as a pilot study to guide public health policies in response to COVID-19 pandemic in both the general population and in healthcare settings.
Forecasting COVID-19 cases using Machine Learning models
Authors: Tian Yuan , Luthra Ishika , Zhang Xi 
Published: July 2020

AbstractAs of April 26, 2020, more than 2,994,958 cases of COVID-19 infection have been confirmed globally, raising a challenging public health issue. A predictive model of the disease would help allocate medical resources and determine social distancing measures more efficiently. In this paper, we gathered case data from Jan 22, 2020 to April 14 for 6 countries to compare different models’ proficiency in COVID-19 cases prediction. We assessed the performance of 3 machine learning models including hidden Markov chain model (HMM), hierarchical Bayes model, and long-short-term-memory model (LSTM) using the root-mean-square error (RMSE). The LSTM model had the consistently smallest prediction error rates for tracking the dynamics of incidents cases in 4 countries. In contrast, hierarchical Bayes model provided the most realistic prediction with the capability of identifying a plateau point in the incidents growth curve.
Firearm Purchasing and Firearm Violence in the First Months of the Coronavirus Pandemic in the United States
Authors: Schleimer Julia P. , McCort Christopher D. , Pear Veronica A. , Shev Aaron , Tomsich Elizabeth , Asif-Sattar Rameesha , Buggs Shani , Laqueur Hannah S. , Wintemute Garen J. 
Published: July 2020

ABSTRACTImportanceFirearm violence is a significant public health and safety problem in the United States. A surge in firearm purchases following the onset of the coronavirus pandemic may increase rates of firearm violence.ObjectiveTo estimate the association between changes in firearm purchasing and interpersonal firearm violence during the coronavirus pandemic.DesignCross-sectional time series study. We estimate the difference between observed rates of firearm purchases and those predicted by seasonal autoregressive integrated moving average models. Using negative binomial models, we then estimate the association between excess firearm purchases and rates of interpersonal firearm violence within states, controlling for confounders.SettingThe 48 contiguous states and the District of Columbia. Hawaii and Alaska are excluded due to missing or incomplete data.ExposureThe difference between observed and expected rates of firearm purchases in March through May 2020, approximated by National Instant Criminal Background Check System records.Main Outcome and MeasureFatal and nonfatal injuries from interpersonal firearm violence, recorded in the Gun Violence Archive.ResultsWe estimate that there were 2.1 million excess firearm purchases from March through May 2020—a 64.3% increase over expected volume, and an increase of 644.4 excess purchases per 100,000 population. We estimate a relative rate of death and injury from firearm violence of 1.015 (95% Confidence Interval (CI): 1.005 to 1.025) for every 100 excess purchases per 100,000, in models that incorporate variation in purchasing across states and control for effects of the pandemic common to all states. This reflects an increase of 776 fatal and nonfatal injuries (95% CI: 216 to 1,335) over the number expected had no increase in purchasing occurred.Conclusions and RelevanceWe find a significant increase in firearm violence in the United States associated with the coronavirus pandemic-related surge in firearm purchasing. Our findings are consistent with existing research. Firearm violence prevention strategies may be particularly important during the pandemic.KEY POINTSQuestionIs the coronavirus-related surge in firearm purchasing associated with changes in rates of interpersonal firearm violence?FindingsThis cross-sectional time series study suggests the recent increase in firearm purchases—an estimated 2.1 million excess purchases nationally between March and May 2020—is associated with a statistically significant increase in firearm violence. We estimate an increase of 776 fatal and nonfatal injuries (95% CI: 216 to 1,335) in the US over the number expected for those months had there been no increase in purchasing.MeaningDuring the coronavirus pandemic, an acute increase in firearm access is associated with an increase in firearm violence.
Profiling cases with non-respiratory symptoms and asymptomatic SARS-CoV-2 infections in Mexico City
Authors: Bello-Chavolla Omar Yaxmehen , Antonio-Villa Neftali Eduardo , Vargas-Vázquez Arsenio , Fermín-Martínez Carlos A. , Márquez-Salinas Alejandro , Bahena-López Jessica Paola 
Published: July 2020

ABSTRACT (50 WORDS)We profiled cases with non-respiratory symptoms (NRS) and asymptomatic SARS-CoV-2 assessed within Mexico City’s Epidemiological Surveillance System. We show that initially asymptomatic or NRS cases have decreased risk of adverse COVID-19 outcomes compared to cases with respiratory symptoms. Comorbidity and age influence likelihood of developing symptoms in initially asymptomatic cases.