bluuebunny/crossref_metadata_2025 huggingface dataset:
Distinct systems serology features in children, elderly and COVID patients
Authors: Selva Kevin J. , van de Sandt Carolien E. , Lemke Melissa M. , Lee Christina Y. , Shoffner Suzanne K. , Chua Brendon Y. , Nguyen Thi H.O. , Rowntree Louise C. , Hensen Luca , Koutsakos Marios , Wong Chinn Yi , Jackson David C. , Flanagan Katie L. , Crowe Jane , Cheng Allen C. , Doolan Denise L. , Amanat Fatima , Krammer Florian , Chappell Keith , Modhiran Naphak , Watterson Daniel , Young Paul , Wines Bruce , Hogarth P. Mark , Esterbauer Robyn , Kelly Hannah G. , Tan Hyon-Xhi , Juno Jennifer A. , Wheatley Adam K. , Kent Stephen J. , Arnold Kelly B. , Kedzierska Katherine , Chung Amy W.
Published: May 2020

SARS-CoV-2, the pandemic coronavirus that causes COVID-19, has infected millions worldwide, causing unparalleled social and economic disruptions. COVID-19 results in higher pathogenicity and mortality in the elderly compared to children. Examining baseline SARS-CoV-2 cross-reactive coronavirus immunological responses, induced by circulating human coronaviruses, is critical to understand such divergent clinical outcomes. The cross-reactivity of coronavirus antibody responses of healthy children (n=89), adults (n=98), elderly (n=57), and COVID-19 patients (n=19) were analysed by systems serology. While moderate levels of cross-reactive SARS-CoV-2 IgG, IgM, and IgA were detected in healthy individuals, we identified serological signatures associated with SARS-CoV-2 antigen-specific Fcγ receptor binding, which accurately distinguished COVID-19 patients from healthy individuals and suggested that SARS-CoV-2 induces qualitative changes to antibody Fc upon infection, enhancing Fcγ receptor engagement. Vastly different serological signatures were observed between healthy children and elderly, with markedly higher cross-reactive SARS-CoV-2 IgA and IgG observed in elderly, whereas children displayed elevated SARS-CoV-2 IgM, including receptor binding domain-specific IgM with higher avidity. These results suggest that less-experienced humoral immunity associated with higher IgM, as observed in children, may have the potential to induce more potent antibodies upon SARS-CoV-2 infection. These key insights will inform COVID-19 vaccination strategies, improved serological diagnostics and therapeutics.
When Second Best Might be the Best: Using Hospitalization Data to Monitor the Novel Coronavirus Pandemic
Authors: Mallow Peter J. , Jones Michael
Published: May 2020

The novel coronavirus’ high rate of asymptomatic transmission combined with a lack of testing kits call for a different approach to monitor its spread and severity. We proposed the use of hospitalizations and hospital utilization data to monitor the spread and severity. A proposed threshold of a declining 7-day moving average over a 14-day period, “7&14” was set to communicate when a wave of the novel coronavirus may have passed. The state of Ohio was chosen to illustrate this threshold. While not the ideal solution for monitoring the spread of the epidemic, the proposed approach is an easy to implement framework accounting for limitations of the data inherent in the current epidemic. Hospital administrators and policy makers may benefit from incorporating this approach into their decision making.
Robot dance: a city-wise automatic control of Covid-19 mitigation levels
Authors: Silva Paulo J. S. , Pereira Tiago , Nonato Luis Gustavo
Published: May 2020

We develop an automatic control system to help to design efficient mitigation measures for the Covid-19 epidemic in cities. Taking into account parameters associated to the population of each city and the mobility among them, the optimal control framework suggests the level and duration of protective measures that must be implemented to ensure that the number of infected individuals is within a range that avoids the collapse of the health care system. Compared against other mitigation measures that are implemented simultaneously and in equal strength across cities our method has three major particularities when:

Accounts for city commute and health infrastructure: It takes into account the daily commute among cities to estimate the dynamics of infected people while keeping the number of infected people within a desired level at each city avoiding the collapse of its health care system.

City-specific control: It allows for orchestrating the control measures among cities so as to prevent all cities to face the same level control. The model tends to induce alternation between periods of stricter controls and periods of a more normal life in each city and among the cities.

Flexible scenarios: It is flexible enough to allow for simulating the impact of particular actions. For example, one can simulate the how the control all cities change when the number of care beds increases in specific places.

Therefore, our method creates an automatic dance adjusting mitigation levels within cities and alternating among cities as suggested in [9]. This automatic dance may help the city economy and orchestration of resources.

We provide case studies using the major cities of the state of São Paulo given by using estimates on the daily mobility among the cities their health care system capacity. We use official data in our case studies. However, sub-notification of infected people in Brazil is notoriously high. Hence the case study should not be considered as a real world policy suggestion. It high sub-notification is taken into account, the optimal control algorithm will suggest stricter mitigation measures, as also shown in the case studies. Surprisingly, the total duration of the protocol for the state is barely affected by the sub-notification, but the severity of such protocols is strengthened. This stresses a twofold implication, first, the protocol depends on high-quality data and, second, such optimal and orchestrated protocol is robust and can be adjusted to the demand.
Systematic Review and Meta-Analysis of Sex-Specific COVID-19 Clinical Outcomes
Authors: Galbadage Thushara , Peterson Brent M. , Awada Joseph , Buck Alison S. , Ramirez Danny A. , Wilson Jason , Gunasekera Richard S.
Published: May 2020

To successfully mitigate the extraordinary devastation caused by the Coronavirus disease 2019 (COVID-19) pandemic, it is crucial to identify important risk factors for this disease. One such neglected health determinant is the sex of the patient. This is an essential clinical characteristic, as it can factor into a patient’s clinical management and preventative measures. Some clinical studies have shown disparities in the proportion between males and females that have more severe clinical outcomes or, subsequently, die from this disease. However, this association has not been unequivocally established. Thus, the purpose of this investigation was to examine the association between male sex and COVID-19 severity. We systematically reviewed the literature, identified non-randomized studies that matched predetermined selection criteria, and performed a meta-analysis to evaluate the proportion of males among four disease severity categories. Appropriate assessment strategies were implemented to assess and minimize potential biases. The results of this meta-analysis indicated that males constituted a significantly higher proportion of those who had adverse clinical outcomes and died from COVID-19. As the coronavirus spread from the East to the West, male sex remained a consistent risk factor. Our results support the establishment of the male sex as an important risk factor for this disease. Early identification and appropriate medical care for males with lab-confirmed COVID-19 may substantially change the course of clinical prognosis, resulting in greater numbers of lives saved.
Estimating the Global Infection Fatality Rate of COVID-19
Authors: Grewelle Richard , De Leo Giulio
Published: May 2020

COVID-19 has become a global pandemic, resulting in nearly three hundred thousand deaths distributed heterogeneously across countries. Estimating the infection fatality rate (IFR) has been elusive due to the presence of asymptomatic or mildly symptomatic infections and lack of testing capacity. We analyze global data to derive the IFR of COVID-19. Estimates of COVID-19 IFR in each country or locality differ due to variable sampling regimes, demographics, and healthcare resources. We present a novel statistical approach based on sampling effort and the reported case fatality rate of each country. The asymptote of this function gives the global IFR. Applying this asymptotic estimator to cumulative COVID-19 data from 139 countries reveals a global IFR of 1.04% (CI: 0.77%,1.38%). Deviation of countries' reported CFR from the estimator does not correlate with demography or per capita GDP, suggesting variation is due to differing testing regimes or reporting guidelines by country. Estimates of IFR through seroprevalence studies and point estimates from case studies or sub-sampled populations are limited by sample coverage and cannot inform a global IFR, as mortality is known to vary dramatically by age and treatment availability. Our estimated IFR aligns with many previous estimates and is the first attempt at a global estimate of COVID-19 IFR.
Empirical Model of Spring 2020 Decrease in Daily Confirmed COVID-19 Cases in King County, Washington
Authors: Roach Jared C.
Published: May 2020

Projections of the near future of daily case incidence of COVID-19 are valuable for informing public policy. Near-future estimates are also useful for outbreaks of other diseases. Short-term predictions are unlikely to be affected by changes in herd immunity. In the absence of major net changes in factors that affect reproduction number (R), the two-parameter exponential model should be a standard model – indeed, it has been standard for epidemiological analysis of pandemics for a century but in recent decades has lost popularity to more complex compartmental models. Exponential models should be routinely included in reports describing epidemiological models as a reference, or null hypothesis. Exponential models should be fitted separately for each epidemiologically distinct jurisdiction. They should also be fitted separately to time intervals that differ by any major changes in factors that affect R. Using an exponential model, incidence-count half-life (t1/2) is a better statistic than R. Here an example of the exponential model is applied to King County, Washington during Spring 2020. During the pandemic, the parameters and predictions of this model have remained stable for intervals of one to four months, and the accuracy of model predictions has outperformed models with more parameters. The COVID pandemic can be modeled as a series of exponential curves, each spanning an interval ranging from one to four months. The length of these intervals is hard to predict, other than to extrapolate that future intervals will last about as long as past intervals.
Substantial underestimation of SARS-CoV-2 infection in the United States due to incomplete testing and imperfect test accuracy
Authors: Wu Sean L , Mertens Andrew , Crider Yoshika S , Nguyen Anna , Pokpongkiat Nolan N , Djajadi Stephanie , Seth Anmol , Hsiang Michelle S , Colford John M , Reingold Art , Arnold Benjamin F , Hubbard Alan , Benjamin-Chung Jade
Published: May 2020

Accurate estimates of the burden of SARS-CoV-2 infection are critical to informing pandemic response. Current confirmed COVID-19 case counts in the U.S. do not capture the total burden of the pandemic because testing has been primarily restricted to individuals with moderate to severe symptoms due to limited test availability. Using a semi-Bayesian probabilistic bias analysis to account for incomplete testing and imperfect diagnostic accuracy, we estimated 6,275,072 cumulative infections compared to 721,245 confirmed cases (1.9% vs. 0.2% of the population) as of April 18, 2020. Accounting for uncertainty, the number of infections was 3 to 20 times higher than the number of confirmed cases. 86% (simulation interval: 64-99%) of this difference was due to incomplete testing, while 14% (0.3-36%) was due to imperfect test accuracy. Estimates of SARS-CoV-2 infections that transparently account for testing practices and diagnostic accuracy reveal that the pandemic is larger than confirmed case counts suggest.
Perceived versus proven SARS-CoV-2 specific immune responses in health care workers
Authors: Behrens Georg MN , Cossmann Anne , Stankov Metodi V , Witte Torsten , Ernst Diana , Happle Christine , Jablonka Alexandra
Published: May 2020

Uncertain rates of asymptomatic infections have raised concerns about potentially high rates of thus far undiagnosed SARS-CoV-2 infections. Serological testing for SARS-CoV-2 specific IgG can be helpful in identification of asymptomatic infections. We report baseline results of the CVOID-19 Contact (CoCo) Study, which follows 217 frontline healthcare workers at a university hospital and performs weekly SARS-CoV-2 specific serology (IgA/IgG). The majority of participants had direct contact to patients with infectious respiratory diseases. Study participants estimated their personal likelihood of having had a SARS-CoV-2 infection with a mean of 20.9% (range 0 to 90%). In contrast, anti-SARS-CoV-2-IgG prevalence was in the range of 1-2% among health care workers. The CoCo Study is not fully representative for other hospitals and the sensitivity of anti-SARS-CoV-2 serology in low prevalence conditions may require further improvement. Taken together, low rates of SARS-CoV-2 specific IgG in healthcare workers in Northern Germany are in sharp contrast to the high personal risk perception. Regular anti-SARS-CoV-2 IgG testing of health-care workers may aid in monitoring the pandemic, assessing the quality of immune responses, directing resources for protective measures, and assuring CVID-19 care in the long run.
Clinical assessment and validation of a rapid and sensitive SARS-CoV-2 test using reverse-transcription loop-mediated isothermal amplification
Authors: Anahtar Melis N. , McGrath Graham E.G. , Rabe Brian A. , Tanner Nathan A. , White Benjamin A. , Lennerz Jochen K.M. , Branda John A. , Cepko Constance L. , Rosenberg Eric S.
Published: May 2020

Amid the enduring COVID-19 pandemic, there is an urgent need for expanded access to rapid and sensitive SARS-CoV-2 testing worldwide. Here we present a simple clinical workflow that uses a sensitive and highly specific colorimetric reverse-transcription loop-mediated isothermal amplification (RT-LAMP) to detect SARS-CoV-2 and takes forty minutes from sample collection to result. This test requires no specialized equipment and costs a few dollars per sample. Nasopharyngeal samples collected in saline were added either directly (unprocessed) to RT-LAMP reactions or first inactivated by a combined chemical and heat treatment step to inhibit RNases and lyse virions and human cells. The specimens were then amplified with two SARS-CoV-2-specific primer sets and an internal specimen control; the resulting color change was visually interpreted. While direct addition of unprocessed specimens to RT-LAMP reactions could reliably detect samples with abundant SARS-CoV-2, the assay sensitivity markedly increased after the addition of an inactivation step. In 62 clinical samples with a wide range of SARS-CoV-2 nucleic acid concentrations, the assay had 87.5% sensitivity and 100% specificity with a limit of detection at least 25 copies/μL, making it an ideal test to rule in infection. To increase sensitivity, samples that tested negative for SARS-CoV-2 by direct sample addition could be reflexed to a purification step, to increase the effective per-reaction sample input volume. In 40 purified samples, the assay yielded a 90% sensitivity and 100% specificity, with a limit of detection comparable to commercially available real-time PCR-based diagnostics that have received Emergency Use Authorization (EUA) from the FDA. This test for SARS-CoV-2 can be performed in a range of settings for a fraction of the price of other available tests, with limited equipment, and without relying on over-burdened supply chains to increase overall testing capacity.
On the heterogeneity of infections, containment measures and the preliminary forecast of COVID-19 epidemic
Authors: Nakamoto Ichiro , Zhuang Weiqing , Wang Sheng , Guo Yan
Published: May 2020

As of May 1, 2020, there had been over three million of officially confirmed cases of novel coronavirus (COVID-19) infections reported worldwide. The pandemic originated from a severe acute respiratory syndrome coronavirus 2 (SARSCoV-2), a virus similar to severe acute respiratory syndrome (SARS). The dynamics of the pathogen incurred the incidence of the unidentified cases that were potentially substantial in magnitude. Unparalleled extensive measures, either in terms of medical quarantine or non-medical containment, were taken to deplete the growth of infected population and thereafter settle down the outbreak. We aimed to estimate the gap in sizes and peak dates between the confirmed and unconfirmed, and how containment measures impacted the dynamic trajectory of the COVID-19 in Japan. We performed simulations and desired to provide meaningful insight for the upcoming responses to the outbreak, for which much still remained to be unknown.
COVID-19 genomic susceptibility: Definition of ACE2 variants relevant to human infection with SARS-CoV-2 in the context of ACMG/AMP Guidance
Authors: Shovlin Claire L , Vizcaychipi Marcela P.
Published: May 2020

Background

Mortality remains very high and unpredictable in CoViD-19, with intense public protection strategies tailored to preceived risk. Males are at greater risk of severe CoViD-19 complications. Genomic studies are in process to identify differences in host susceptibility to SARS-CoV-2 infection.

Methods

Genomic structures were examined for the ACE2 gene that encodes angiotensin-converting enzyme 2, the obligate receptor for SARS-CoV-2. Variants in 213,158 exomes/genomes were integrated with ACE2 protein functional domains, and pathogenicity criteria from the American Society of Human Genetics and Genomics/Association for Molecular Pathology.

Results

483 variants were identified in the 19 exons of ACE2 on the X chromosome. All variants were rare, including nine loss-of-function (potentially SARS-CoV-2 protective) alleles present only in female heterozygotes. Unopposed variant alleles were more common in males (262/3596 [7.3%] nucleotides) than females (9/3596 [0.25%] nucleotides, p<0.0001). 37 missense variants substituted amino acids in SARS-CoV-2 interacting regions or critical domains for transmembrane ACE2 expression. Four upstream open reading frames with 31 associated variants were identified. Excepting loss-of-function alleles, variants would not meet minimum criteria for classification as ‘Likely Pathogenic/beneficial’ if differential frequencies emerged in patients with CoViD-19.

Conclusions

Males are more exposed to consequences from a single variant ACE2 allele. Common risk/beneficial alleles are unlikely in regions subject to evolutionary constraint. ACE2 upstream open reading frames may have implications for aminoglycoside use in SARS-CoV-2-infected patients. For this SARS-CoV-2-interacting protein with pre-identified functional domains, pre-emptive functional and computational studies are encouraged to accelerate interpretations of genomic variation for personalised and public health use.
Multi-center Clinical Study Using Optical Coherence Tomography for Evaluation of Cervical Lesions In-vivo
Authors: Ren Chenchen , Zeng Xianxu , Shi Zhongna , Wang Chunyan , Wang Huifen , Wang Xiuqin , Zhang Baoping , Jiang Zhaoning , Ma Huan , Hu Hao , Piao Haozhe , Zhang Xiaoan , Wang Baojin
Published: May 2020

Objective

In this prospective study of an in-vivo cervical examination using optical coherence tomography (OCT), we evaluated the diagnostic value of non-invasive and real-time OCT in cervical precancerous lesions and cancer diagnosis, and determined the characteristics of OCT images.

Methods

733 patients from 5 Chinese hospitals were inspected with OCT and colposcopy-directed biopsy. The OCT images were compared with the histological sections to find out the characteristics of various categories of lesions. The OCT images were also interpreted by 3 investigators to make a 2-class classification, and the results were compared against the pathological results.

Results

Various structures of the cervical tissue were clearly observed in OCT images, which matched well with the corresponding histological sections. The OCT diagnosis results delivered a sensitivity of 87.0% (95% confidence interval, CI, 82.2%-90.7%), a specificity of 84.1% (95% CI, 80.3%-87.2%), and an overall accuracy of 85.1%.

Conclusion

Both good consistency of OCT images and histological images and satisfactory diagnosis results were provided by OCT. Due to its features of non-invasion, real-time, and accuracy, OCT is valuable for the in-vivo evaluation of cervical lesions and has the potential to be one of the routine cervical diagnosis methods.
The medical education level of the administrators of the local health committees in China
Authors: Zhao Faming , Yin Kaili , Wang Yu , Li Juan , Zhang Guo
Published: May 2020

The outbreak of coronavirus disease 2019 (COVID-19) caused by the recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a serious challenge for the healthcare system worldwide. We collected information, which were posted online as of February 25, 2020, on demographic characteristics of the directors of provincial and municipal health committees in China, and analyzed the education level and medical education background according to geographic region or GPD per capita. We found that the overall information disclosure rate is insufficient (63.39%). The mean age of the directors of provincial and municipal health committee was ~54 years. Among the 277 officials whose information is available, those in economically less-developed regions or remote areas had significantly poorer educational background. Regardless of economic status, the proportion of officials with a background of medical education in most regions was low. This might hinder the efficiency of healthcare and public health administration, which requires personnel with a background of medical training.
Molecular conservation and Differential mutation on ORF3a gene in Indian SARS-CoV2 genomes
Authors: Hassan Sk. Sarif , Choudhury Pabitra Pal , Basu Pallab , Jana Siddhartha Sankar
Published: May 2020

A global emergency due to the COVID-19 pandemic demands various studies related to genes and genomes of the SARS-CoV2. Among other important proteins, the role of accessory proteins are of immense importance in replication, regulation of infections of the coronavirus in the hosts. The largest accessory proteins in the SARS-CoV2 genome is ORF3a which modulates the host response to the virus infection and consequently it plays an important role in pathogenesis. In this study, an attempt is made to decipher the conservation of nucleotides, dimers, codons and amino acids in the ORF3a genes across thirty two genomes of Indian patients. ORF3a gene possesses single and double point mutations in Indian SARS-CoV2 genomes suggesting the change of SARS-CoV2’s virulence property in Indian patients. We find that the parental origin of the ORF3a gene over the genomes of SARS-CoV2 and Pangolin-CoV is same from the phylogenetic analysis based on conservations of nucleotides and so on. This study highlights the accumulation of mutation on ORF3a in Indian SARS-CoV2 genomes which may provide the designing therapeutic approach against SARS-CoV2.
Evaluation of the US governors decision when to issue stay-at-home orders [Running title: When to shut down: the Weber-Fechner law describes the timing of U. S. governors decisions to issue stay-at-home orders]
Authors: Djulbegovic Benjamin , Weiss David J , Hozo Iztok
Published: May 2020

Objectives To evaluate if the US governors decision to issue the stay-at-home orders reflects the classic Weber-Fechner law of psychophysics, the amount by which a stimulus (such as number of cases or deaths) must increase in order to be noticed-the just noticeable difference- as a fraction of the intensity of that stimulus.

Design A prospective observational study using data on the daily number of infected patients and deaths from the New York Times daily database.

Setting 50 States and the District of Columbia

Participants All individuals judged to be positive for the coronavirus or to have died from COVID19.
Main outcome measures Number of people diagnosed with or died from COVID19.

Results We found that the decision to issue the state-at-home order reflects the Weber-Fechner law of psychophysics. Both the number of infections (p=<0.0001; R2=0.79) and deaths (p<0.0001; R2=0.63) were highly statistically significantly associated with the decision to issue the stay-at-home orders. The results indicate that for each doubling of infections or deaths within their state, an additional four to six governors will issue the stay-at-home order. We also observed a clear dose-response relationship in the Cox model: the larger the number of cases, or deaths, the higher the probability that the stay-at-home order will be made. When the number of deaths reached 256 or the number of infected people was greater than 16,384, the probability of issuing a stay-at-home order was close to 100%.

Conclusions When there are not clearly articulated rules to follow, decision-makers in times of crisis such as COVID19 resort to use of simple heuristics consistent with the Weber-Fechner law of psychophysics. The findings are important for the public to understand how their elected officials make important public health decisions.
Age-dependence of mortality from novel coronavirus disease (COVID-19) in highly exposed populations: New York transit workers and residents and Diamond Princess passengers
Authors: Leffler Christopher T. , Hogan Matthew C.
Published: May 2020

Background

Populations heavily exposed to the novel coronavirus provide an opportunity to estimate the mortality from COVID-19 in different age groups.

Methods

The mortality reported by May 13 from COVID-19 among Diamond Princess cruise ship passengers, and New York residents and Metropolitan Transit Authority (MTA) workers was estimated based on publicly available information.

Results

The mortality among children (age 0 to 17 yrs) in New York City was 1 in 172,692. The mortality in New York state was 1 in 322,217 for ages 10-19 yrs., and 1 in 36,725 for ages 20-29 yrs. The mortality among New York transit workers was estimated to be 1 in 7,329 for ages 30-39 years; 1 in 1,075 for ages 40-49 yrs.; 1 in 343 for ages 50-59 yrs.; and 1 in 178 for ages 60-69 yrs. Among Diamond Princess passengers, the mortality was estimated to be 1 in 145 for ages 70-79, and 1 in 54 for ages 80-89.

Conclusions

Mortality among populations exposed to the novel coronavirus increases with age, ranging from about 1 in 170,000 below the age of 18 years, to 1 in 54 above the age of 80 years.
Decline in Emergent and Urgent Care during the COVID-19 Pandemic
Authors: Kazi Dhruv S. , Wadhera Rishi K. , Shen Changyu , Ho Kalon K. L. , Patell Rushad , Selim Magdy H. , Urwin John , Zeidel Mark L. , Zimetbaum Peter , Tabb Kevin , Yeh Robert W.
Published: May 2020

Due to the ongoing coronavirus disease (COVID-19) pandemic, there are concerns that patients may be avoiding care for emergent and urgent health conditions due to fear of contagion or as an unintentional consequence of government orders to postpone “non-essential” services. We therefore sought to evaluate the effect of the COVID-19 pandemic on the number of patient encounters for select emergent or urgent diagnoses at a large tertiary-care academic medical center in Boston. Inpatient diagnoses included acute myocardial infarction (MI) and stroke, and outpatient but urgent diagnoses included new referrals for breast and hematologic malignancies. For each condition, we used a “difference-in-differences” approach to estimate the proportional change in number of encounters during the pandemic (March – April 2020) compared with earlier in the same year (January – February 2020), using equivalent periods in 2019 as a control. After the onset of the pandemic, we observed significant reductions in hospitalizations for MI (difference-in-differences estimate, 0.67; 95%CI, 0.46-0.96; P=0.04) and stroke (difference-in-differences estimate, 0.42; 95%CI, 0.28-0.65; P<0.001) (Table). In the ambulatory setting, there was a reduction in referrals for breast cancer and hematologic cancers, but this did not reach statistical significance until the month after the onset of the pandemic. Our findings suggest an urgent need for public health messaging to ensure that patients continue to seek care for acute emergencies. In addition, decisions by health systems regarding when to reinitiate non-emergent care should carefully factor in the harms of delayed diagnosis and treatment occurring during the COVID-19 pandemic.
PREDICTORS OF MORTALITY AND CLINICAL CHARACTERISTICS AMONG CARBAPENEM-RESISTANT OR CARBAPENEMASE-PRODUCING ENTEROBACTERIACEAE BLOODSTREAM INFECTION IN SPANISH CHILDREN
Authors: Ara Montojo Maria Fatima , Escosa Garcia Luis , Alguacil Marina , Seara Nieves , Zozaya Carlos , Plaza Diego , Schuffelmann-Gutierrez Cristina , De la Vega Angela , Fernandez-Camblor Carlota , Ramos-Boluda Esther , Romero-Gomez Maria Pilar , Ruiz-Carrascoso Guillermo , Losantos-Garcia Itsaso , Mellado Maria Jose , Gomez-Gil Rosa
Published: May 2020

Background: Carbapenem-resistant Enterobacteriaceae (CRE) are a growing problem in pediatric population worldwide with high mortality rates (18.5-52%) in bloodstream infection (BSI).
Objectives: The aim of this study is to evaluate predictors of 30-day mortality in CRE BSI in a pediatric cohort.

Methods: Retrospective observational single-center study (December 2005 - August 2018) was conducted. CRE BSI in children 0 to 16 years were included. Microbiological identification (MALDI Biotyper) and antimicrobial susceptibility testing (Vitek2 and MicroScan panel NBC44) according to current EUCAST breakpoints were performed. PCR OXVIKP was used to confirm carbapenemases genes (OXA-48, VIM, KPC, NDM). Demographic characteristics, underlying diseases, source of bacteremia, antimicrobial therapy and outcomes were collected from medical records. Survival analysis to establish predictors of 30 day-mortality was performed.

Results: Thirty-eight cases were included, 76.3% hospital-acquired infections and 23.7% related to healthcare. All patients had underlying comorbidity and 52.6% had received a transplant. VIM-carbapenemase was the predominant mechanism (92%). Previous CRE colonization or infection rate was 52.6%. Gut (26%) and vascular catheter (21%) were the predominant sources of infection. Crude mortality within 30 days was 18.4% (7/38); directly related 30-day mortality was 10.5%. Conditions associated with an increment in 30-day mortality were intensive care admission and inadequate empiric therapy (p<0.05). Combination antibiotic targeted treatment and a low meropenem MIC were not related to improved survival.

Conclusions: CRE BSI mortality rate is high. The most important factor related to 30-day survival in our CRE BSI cohort in children was success in empiric treatment with at least one active antibiotic.
Bounding the Predictive Values of COVID-19 Antibody Tests
Authors: Manski Charles F.
Published: May 2020

COVID-19 antibody tests have imperfect accuracy. There has been lack of clarity on the meaning of reported rates of false positives and false negatives. For risk assessment and clinical decision making, the rates of interest are the positive and negative predictive values of a test. Positive predictive value (PPV) is the chance that a person who tests positive has been infected. Negative predictive value (NPV) is the chance that someone who tests negative has not been infected. The medical literature regularly reports different statistics, sensitivity and specificity. Sensitivity is the chance that an infected person receives a positive test result. Specificity is the chance that a non-infected person receives a negative result. Knowledge of sensitivity and specificity permits one to predict the test result given a person's true infection status. These predictions are not directly relevant to risk assessment or clinical decisions, where one knows a test result and wants to predict whether a person has been infected. Given estimates of sensitivity and specificity, PPV and NPV can be derived if one knows the prevalence of the disease, the rate of illness in the population. There is considerable uncertainty about the prevalence of COVID-19. This paper addresses the problem of inference on the PPV and NPV of COVID-19 antibody tests given estimates of sensitivity and specificity and credible bounds on prevalence. I explain the methodological problem, show how to estimate bounds on PPV and NPV, and apply the findings to some tests authorized by the FDA.
Prevalence, intensity and control strategies of soil-transmitted helminth infections among pre-school age children after 10 years of preventive chemotherapy in Gamo Gofa zone, Southern Ethiopia: A call for action
Authors: Asfaw Mekuria Asnakew , Gezmu Tigist , Wegayehu Teklu , Bekele Alemayehu , Hailemariam Zeleke , Masresha Nebiyu , Gebre Teshome
Published: May 2020

Background: Soil-transmitted helminths (STH) (Ascaris lumbricoides, Trichuris trichiura and hookworm) are among the most prevalent neglected tropical diseases (NTDs) in Ethiopia. Pre-school age children (PSAC) pay high morbidity toll associated with STH infections. Site specific operational evidence is lacking on prevalence, intensity and control strategies of STH among PSAC in Ethiopia. This study is, therefore, aimed to fill that missing knowledge gap.
Methods: We did a community-based cross-sectional study in five districts of Gamo Gofa zone; from December 2018 to January 2019. Data were collected using pre-tested questionnaire, and the Kato-Katz technique was used to diagnose parasites egg in stool. Then data were edited, coded and entered into EpiData 4.4.2, and exported to SPSS software (IBM, version 25) for analysis.
Results: A total of 2462 PSAC participated in this study. Overall, the prevalence of STH was 23.5% (578/2462). Ascaris lumbricoides was the most prevalent, 18.6% (457/2462), followed by Trichuris trichiura, 9.2% (226/2462), and hookworm, 3.1% (76/2462). The prevalence of STH in Chencha, Dita, Deremalo, Bonke and Demba Gofa districts were 33.8% (210/622), 26.4% (109/413), 21.3% (88/414), 20.6% (128/621), and 11% (43/392), respectively. Of the total, 7.4% (181/2462) PSAC were infected with two STH species. Ascaris lumbricodes infections had moderate intensity (15%), and the rest had low infections intensity. It is found that 68.7% of PSAC were treated with Albendazole. This study also revealed households level data as, 39.4% used water from hand-dug well, 52.5% of need to move ≥30minutes to collect water, 77.5% did not treat water, and 48.9% not had hand washing facility.
Conclusion: This study showed that a significant proportion of pre-school age children are suffering from STH infections across districts in the study area despite preventive chemotherapy distribution for more than 10 years. Further, gaps in control strategies of STH were highlighted, which calls for action.
Is it Just About Physical Health? An Online Cross-Sectional Study Exploring the Psychological Distress Among University Students in Jordan in the midst of COVID-19 Pandemic
Authors: Al-Tammemi Ala’a B. , Akour Amal , Alfalah Laith
Published: May 2020

Background

Since the spread of COVID-19 on a global scale, most of efforts at national and international levels were directed to mitigate the spread of the disease and its physical harm, paying less attention to the psychological impacts of COVID-19 on global mental health especially at early stages of the pandemic.

Objectives

This study aimed to assess and explore (i) The levels of psychological distress and its correlates (ii) Motivation for distance learning (iii) Coping activities and pandemic related concerns, among university students in Jordan in the midst of COVID-19 pandemic

Methods

A cross-sectional study was conducted using an online self-administered questionnaire. The measure of psychological distress was obtained using the 10-item Kessler Psychological Distress Scale,while other questions have explored our study’s second and third aims.

Results

A total of 381 completed questionnaires were included in the analysis. Female participants slightly predominated the sample (n=199, 52.2%). The respondents aged 18-38 years (mean 22.6 years, SD: 3.16). Concerning distress severity, most of respondents were regarded as having severe psychological distress (n=265, 69.5%). 209 students (54.9%) reported that they had no motivation for distance learning. Ordinal logistic regression revealed a significant correlation between distress severity and many predictors. Among the predictors that were found to act as a protective factors against higher levels of distress included older age (aOR=0.64, P=0.022; 95% CI: 0.44 - 0.94), and having a strong motivation for distance learning (aOR=0.10, P=0.048 ; 95% CI: 0.01 - 0.96). In contrary, being a current smoker (aOR=1.99, P=0.049 ; 95% CI: 1.10 - 3.39), and having no motivation for distance learning (aOR=2.49, P=0.007; 95% CI: 1.29 - 4.80) acted as risk factors for having higher levels of psychological distress among the students. The most common coping activity reported was spending more time on social media platforms (n=269, 70.6%), and 209 students (54.9%) reported distance learning was their most distressing concern.

Conclusion

The COVID-19 pandemic and related control measures could impact the mental health of individuals, including students. We recommend a nationwide psychological support program to be incorporated into Jordan’s preparedness plan and response strategy in combating the COVID-19 pandemic.
Investigation of somatic mutations in human brains targeting genes associated with Parkinson’s disease
Authors: Leija-Salazar Melissa , Pittman Alan , Mokretar Katya , Morris Huw , Schapira Anthony H. , Proukakis Christos
Published: May 2020

Background

Somatic mutations occur in neurons but their role in synucleinopathies is unknown.

Aim

We aimed to identify disease-relevant low-level somatic single nucleotide variants (SNVs) in brains from sporadic patients with synucleinopathies and a monozygotic twin carrying LRRK2 G2019S, whose penetrance could be explained by somatic variation.

Methods and Results

We included different brain regions from 26 Parkinson’s disease (PD), 1 Incidental Lewy body, 3 multiple system atrophy cases and 12 controls. The whole SNCA locus and exons of other genes associated with PD and neurodegeneration were deeply sequenced using molecular barcodes to improve accuracy. We selected 21 variants at 0.33-5% allele frequencies for validation using accurate methods for somatic variant detection.

Conclusions

We could not detect disease-relevant somatic SNVs, however we cannot exclude their presence at earlier stages of degeneration. Our results support that coding somatic SNVs in neurodegeneration are rare, but other types of somatic variants may hold pathological consequences in synucleinopathies.
Urinary viral shedding of COVID-19 and its clinical associations: A Systematic Review and Meta-analysis of Observational Studies
Authors: Kashi Amir H , de la Rosette Jean , Amini Erfan , Abdi Hamidreza , Fallah-karkan Morteza , Vaezjalali Maryam
Published: May 2020

Objectives

To review the current literature on the presence of COVID-19 virus in the urine of infected patients and to explore the clinical features that can predict the presence of COVID-19 in urine.

Materials and Methods

A systematic review of published literature between 30th December 2019 and 21st June 2020 was conducted on Pubmed, Google Scholar, Ovid, Scopus, and ISI web of science. Studies investigating urinary viral shedding of COVID-19 in infected patients were included. Two reviewers selected relative studies and performed quality assessment of individual studies. Meta-analysis was performed on the pooled case reports and cohort with a sample size of 9.

Results

Thirty-nine studies were finally included in the systematic review; 12 case reports, 26 case series, and one cohort study. Urinary samples from 533 patients were investigated. Fourteen studies reported the presence of COVID-19 in the urinary samples from 24 patients. The crude overall rate of COVID-19 detection in urinary samples was 4.5%. Considering case series and cohorts with a sample size of ≥ 9, the estimated viral shedding frequency was 1.18 % (CI 95%: 0.14 – 2.87) in the meta-analysis. In adult patients, urinary shedding of COVID-19 was commonly detected in patients with moderate to severe disease (16 adult patients with moderate or severe disease versus two adult patients with mild disease). In children, urinary viral shedding of COVID-19 was reported in 4 children who all suffered from mild disease. Urinary viral shedding of COVID-19 was detected from day 1 to day 52 after disease onset. The pathogenicity of virus isolated from urine has been demonstrated in cell culture media in one study while another study failed to reveal replication of isolated viral RNA in cell cultures. Urinary symptoms were not attributed to urinary viral shedding.

Conclusions

While COVID-19 is rarely detected in urine of infected individuals, infection transmission through urine still remains possible. In adult patients, infected urine is more likely in the presence of moderate or severe disease. Therefore, caution should be exerted when dealing with COVID-19 infected patients during medical interventions like endoscopy and urethral catheterization.
Forecasting COVID-19 pandemic Severity in Asia
Authors: Aviv-Sharon Elinor , Aharoni Asaph
Published: May 2020

Four months into the ongoing novel coronavirus disease 2019 (COVID-19) pandemic, this work provides a simple and direct projection of the outbreak spreading potential and the pandemic cessation dates in China, Iran, the Philippines and Taiwan, using the generalized logistic model (GLM). The short-term predicted number of cumulative COVID-19 cases matched the confirmed reports of those who were infected across the four countries, suggesting GLM as a valuable tool for characterizing the transmission dynamics process and the trajectory of COVID-19 pandemic along with the impact of interventions.
Belief loads of assumptions impact brain networks underlying logical reasoning: A machine learning approach
Authors: Ziaei Maryam , Bonyadi Mohammad Reza , Reutens David
Published: May 2020

Prior knowledge and beliefs influence our reasoning in daily life and may lead us to draw unwarranted conclusions with undesirable consequences. The underlying neural correlates of the interaction between belief and logic, prior to making logical decisions, are largely unknown. In this study, we aimed to identify brain regions important in distinguishing belief load of assumptions in logical decision making. Thirty-one healthy volunteers (18-29 years old) participated in an fMRI study and were asked to respond to a series of syllogistic arguments in which assumptions were either congruent (believable) or incongruent (unbelievable) with common knowledge. An interpretable machine learning algorithm, an L1 regularized Support Vector Machine, was used to explain the discriminatory pattern of conditions given the brain activation patterns. Behavioral results confirmed that believable premises were incorrectly endorsed more than unbelievable ones. Imaging results revealed that several connectivity patterns anchored around the insula, amygdala, and IFG were important in distinguishing believable from unbelievable assumptions at different time points preceding logical decisions. Our convergent behavioral and imaging results underscore the importance of the belief loads of ourassumptionsfor a logically sound decision. Our results provide new insights into neural and potential cognitive mechanisms underlying the interaction between belief and logic systems, with important practical implications for social, complex decisions.

Highlights

Belief load of premises impact logical decisions

Regional importance in distinguishing belief load changes in different TRs

Belief load of assumptions elicits emotional and salience responses

Regional connectivity changes as the reasoning process evolves at different TRs

Insula, caudate, amygdala, and IFG were among highly connected hubs during the task

Significance

It has been experimentally shown that decision-makers often ignore given assumptions in favor of their own beliefs, potentially leading them towards a subjective rather than a logical decision. Consider “Carbon emission tax” given the assumption of “global warming”. If a decision-maker does not believe in “global warming”, the final decision on “Carbon emission tax” is not driven by factual premises but by the personal belief of the decision-maker. Understanding neural mechanisms underlying the interaction between the decision-makers’ beliefs and factual premises sheds light on factors driving belief bias and potential interventions to circumvent it. The main contribution of this study is to investigate neural mechanisms in a logical reasoning task in which the belief load of the assumptions was manipulated.
A simple and efficient method for in vitro site-directed mutagenesis
Authors: Palis Dave , Huang Frank
Published: May 2020

This paper has been withdrawn by bioRxiv because its content, including the author names, was fabricated and fraudulently submitted in what may have been an attempt to game citation statistics or other metrics.
Interpretable Artificial Intelligence for COVID-19 Diagnosis from Chest CT Reveals Specificity of Ground-Glass Opacities
Authors: Warman Anmol , Warman Pranav I. , Sharma Ayushman , Parikh Puja , Warman Roshan , Viswanadhan Narayan , Chen Lu , Mohapatra Subhra , Mohapatra Shyam S , Sapiro Guillermo
Published: May 2020

1

1.1

Background

The use of CT imaging enhanced by artificial intelligence to effectively diagnose COVID-19, instead of or in addition to reverse transcription-polymerase chain reaction (RT-PCR), can improve widespread COVID-19 detection and resource allocation.

1.2

Methods

904 axial lung window CT slices from 338 patients in 17 countries were collected and labeled. The data included 606 images from COVID-19 positive patients (confirmed via RT-PCR), 224 images of a variety of other pulmonary diseases including viral pneumonias, and 74 images of normal patients. We developed, trained, validated, and tested an object detection model which detects features in three categories: ground-glass opacities (GGOs) for COVID-19, GGOs for non-COVID-19 diseases, and features that are inconsistent with a COVID-19 diagnosis. These collected features are passed into an interpretable decision tree model to make a suggested diagnosis.

1.3

Results

On an independent test of 219 images from COVID-19 positive, a variety of pneumonia, and healthy patients, the model predicted COVID-19 diagnoses with an accuracy of 96.80 % (95% confidence interval [CI], 96.75 to 96.86), AUC-ROC of 0.9664 (95% CI, 0.9659 to 0.9671), sensitivity of 98.33% (95% CI, 98.29 to 98.40), precision of 95.93% (95% CI, 95.83 to 95.99), and specificity of 94.95% (95% CI, 94.84 to 95.05). On an independent test of 34 images from asymptomatic COVID-19 positive patients, our model achieved an accuracy of 97.06% (95% CI, 96.81 to 97.06) and a sensitivity of 96.97% (95% CI, 96.71 to 96.97). Similarly high performance was also obtained for out-of-sample countries, and no significant performance difference was obtained between genders.

1.4

Conclusion

We present an interpretable artificial intelligence CT analysis tool to diagnose COVID-19 in both symptomatic and asymptomatic patients. Further, our model is able to differentiate COVID-19 GGOs from similar pathologies suggesting that GGOs can be disease-specific.