bluuebunny/crossref_metadata_2025_split huggingface dataset:
A New Approach to the Dynamic Modeling of an Infectious Disease
Authors: Shayak B , Sharma Mohit M 
Published: November 2020

ABSTRACTIn this work we propose a delay differential equation as a lumped parameter or compartmental infectious disease model featuring high descriptive and predictive capability, extremely high adaptability and low computational requirement. Whereas the model has been developed in the context of COVID-19, it is general enough to be applicable mutatis mutandis to other diseases as well. Our fundamental modeling philosophy consists of a decoupling of public health intervention effects, immune response effects and intrinsic infection properties into separate terms. All parameters in the model are directly related to the disease and its management; we can measure or calculate their values a priori basis our knowledge of the phenomena involved, instead of having to extrapolate them from solution curves. Our model can accurately predict the effects of applying or withdrawing interventions, individually or in combination, and can quickly accommodate any newly released information regarding, for example, the infection properties and the immune response to an emerging infectious disease. After demonstrating that the baseline model can successfully explain the COVID-19 case trajectories observed all over the world, we systematically show how the model can be expanded to account for heterogeneous transmissibility, detailed contact tracing drives, mass testing endeavours and immune responses featuring different combinations of limited-time sterilizing immunity, severity-reducing immunity and antibody dependent enhancement.
Modeling-based UV-C decontamination of N95 masks optimized to avoid undertreatment
Authors: Sears Adam P. , Ohayon Jacques , Shutov Anton D. , Pettigrew Roderic I. 
Published: November 2020

AbstractAs the Coronavirus 2019 pandemic creates worldwide shortages of personal protective equipment, hospitals have increasingly turned to sterilization and re-use protocols, often without significant data supporting the specific methodologies. When using UV-C irradiation, previously shown to be effective for decontaminating hard surfaces, modeling shows the importance of accounting for the porosity and non-uniform curvature of the N95 masks in decontamination procedures. Data shows a standard incident dose of 1 J/cm2 delivered to both front and back surfaces is more than 500x higher than the known kill dose. However, modeling indicates this would undertreat 40% of the mask material due to the curvature, path-length attenuation and scatter. Multidirectional UV-C irradiation employing dose calibrated exposures can adjust for this loss and best decontaminate masks. Such protocols can be rapidly implemented in thousands of hospitals across the world equipped with UV-C irradiation lamps without the need for additional capital equipment purchases.
Literature study on the return on investment concerning the implementation of a computerized clinical decision support in a hospital information system
Authors: Kuotu Gérard Christian , Moukam Lower Bride Barth 
Published: November 2020

AbstractBackgroundThe objective of this study was to carry out a bibliographic study on the return on investment concerning the implementation of a computerized clinical decision support in a hospital information system.MethodsA bibliographic search was carried out using the PubMed and Google Scholar bibliographic databases. The articles obtained were selected by combining the elements: outlook, net benefits, comparability, types of costs, discount rate, sensitivity analyzes, and measurement of effectiveness. This enabled us to review 498 articles published during our study period, of which 56 were selected.ResultsThe most commonly available tools are return on investment estimation methods. The data in the literature on the return on investment concerning the implementation of clinical decision support, although documented, are quite mixed.ConclusionEvaluations such as the econometric approach can be considered to determine if these investments are justified.
Investigating the effects of absolute humidity and human encounters on transmission of COVID-19 in the United States
Authors: Lin Gary , Hamilton Alisa , Gatalo Oliver , Haghpanah Fardad , Igusa Takeru , Klein Eili ,   For the CDC MInD-Healthcare Network
Published: November 2020

AbstractBackgroundMounting evidence suggests that the primary mode of transmission of SARS-CoV-2 is aerosolized transmission from close contact with infected individuals. Even though transmission is a direct result of human encounters, environmental conditions, such as lower humidity, may enhance aerosolized transmission risks similar to other respiratory viruses such as influenza.MethodsWe utilized dynamic time warping to cluster all 3,137 counties in the United States based on temporal data on absolute humidity from March 10 to September 29, 2020. We then used a multivariate generalized additive model (GAM) combining data on human mobility derived from mobile phone data with humidity data to identify the potential effect of absolute humidity and mobility on new daily cases of COVID-19 while considering the temporal differences between seasons.ResultsThe clustering analysis found ten groups of counties with similar humidity levels. We found a significant negative effect between increasing humidity and new cases of COVID-19 in most regions, particularly in the period from March to July. The effect was greater in regions with generally lower humidity in the Western, Midwest, and Northeast regions of the US. In the two regions with the largest effect, a 1 g/m3 increase of absolute humidity resulted in a 0.21 and 0.15 decrease in cases. The effect of mobility on cases was positive and significant across all regions in the July-Sept time period, though the relationship in some regions was more mixed in the March to June period.ConclusionsWe found that increasing humidity played an important role in falling cases in the spring, while increasing mobility in the summer contributed more significantly to increases in the summer. Our findings suggest that, similar to other respiratory viruses, the decreasing humidity in the winter is likely to lead to an increase in COVID-19 cases. Furthermore, the fact that mobility data were positively correlated suggests that efforts to counteract the rise in cases due to falling humidity can be effective in limiting the burden of the pandemic.
SARS-CoV-2 Infection Hospitalization Rate and Infection Fatality Rate among the Non-Congregant Population in Connecticut
Authors: Mahajan Shiwani , Caraballo César , Li Shu-Xia , Dong Claire , Chen Lian , Huston Sara K. , Srinivasan Rajesh , Redlich Carrie A. , Ko Albert I. , Faust Jeremy S. , Forman Howard P. , Krumholz Harlan M. 
Published: November 2020

ABSTRACTImportanceCOVID-19 case fatality and hospitalization rates, calculated using the number of confirmed cases of COVID-19, have been described widely in the literature. However, the number of infections confirmed by testing underestimates the total infections as it is biased based on the availability of testing and because asymptomatic individuals may remain untested. The infection fatality rate (IFR) and infection hospitalization rate (IHR), calculated using the estimated total infections based on a representative sample of a population, is a better metric to assess the actual toll of the disease.ObjectiveTo determine the IHR and IFR for COVID-19 using the statewide SARS-CoV-2 seroprevalence estimates for the non-congregate population in Connecticut.DesignCross-sectional.SettingAdults residing in a non-congregate setting in Connecticut between March 1 and June 1, 2020.ParticipantsIndividuals aged 18 years or above.ExposureEstimated number of adults with SARS-CoV-2 antibodies.Main Outcome and MeasuresCOVID-19-related hospitalizations and deaths among adults residing in a non-congregate setting in Connecticut between March 1 and June 1, 2020.ResultsOf the 2.8 million individuals residing in the non-congregate settings in Connecticut through June 2020, 113,515 (90% CI 56,758–170,273) individuals had SARS-CoV-2 antibodies. There were a total of 9425 COVID-19-related hospitalizations and 4071 COVID-19-related deaths in Connecticut between March 1 and June 1, 2020, of which 7792 hospitalizations and 1079 deaths occurred among the non-congregate population. The overall COVID-19 IHR and IFR was 6.86% (90% CI, 4.58%–13.72%) and 0.95% (90% CI, 0.63%–1.90%) among the non-congregate population. Older individuals, men, non-Hispanic Black individuals and those belonging to New Haven and Litchfield counties had a higher burden of hospitalization and deaths, compared with younger individuals, women, non-Hispanic White or Hispanic individuals, and those belonging to New London county, respectively.Conclusion and RelevanceUsing representative seroprevalence estimates, the overall COVID-19 IHR and IFR were estimated to be 6.86% and 0.95% among the non-congregate population in Connecticut. Accurate estimation of IHR and IFR among community residents is important to guide public health strategies during an infectious disease outbreak.
Mapping the human helminthiases: a systematic review of geospatial tools in medical parasitology
Authors: Schluth Catherine G. , Standley Claire J. , Bansal Shweta , Carlson Colin J. 
Published: November 2020

AbstractHelminthiases are a class of neglected tropical diseases that affect at least one billion people worldwide, with a disproportionate impact in resource-poor areas with limited disease surveillance. Geospatial methods can offer valuable insights into the burden of these infections, particularly given that many are subject to strong ecological influences on the environmental, vector-borne, or zoonotic stages of their life cycle. In this study, we screened 6,829 abstracts and analyzed 485 studies that use maps to document, infer, or predict transmission patterns for over 200 species of parasitic worm. We found that quantitative mapping methods are increasingly used in medical parasitology, drawing on One Health surveillance data from the community scale to model geographic distributions and burdens up to the regional or global scale. However, we found that the vast majority of the human helminthiases may be entirely unmapped, with research effort focused disproportionately on a half-dozen infections that are targeted by mass drug administration programs. Entire regions were also surprisingly under-represented in the literature, particularly southern Asia and the Neotropics. We conclude by proposing a shortlist of possible priorities for future research, including several neglected helminthiases with a burden that may be substantially underestimated.
Personalized Prescription of ACEI/ARBs for Hypertensive COVID-19 Patients
Authors: Bertsimas Dimitris , Borenstein Alison , Mingardi Luca , Nohadani Omid , Orfanoudaki Agni , Stellato Bartolomeo , Wiberg Holly , Sarin Pankaj , Varelmann Dirk J. , Estrada Vicente , Macaya Carlos , Núñez Gil Iván J. 
Published: November 2020

AbstractThe COVID-19 pandemic has prompted an international effort to develop and repurpose medications and procedures to effectively combat the disease. Several groups have focused on the potential treatment utility of angiotensin-converting–enzyme inhibitors (ACEIs) and angiotensin-receptor blockers (ARBs) for hypertensive COVID-19 patients, with inconclusive evidence thus far. We couple electronic medical record (EMR) and registry data of 3,643 patients from Spain, Italy, Germany, Ecuador, and the US with a machine learning framework to personalize the prescription of ACEIs and ARBs to hypertensive COVID-19 patients. Our approach leverages clinical and demographic information to identify hospitalized individuals whose probability of mortality or morbidity can decrease by prescribing this class of drugs. In particular, the algorithm proposes increasing ACEI/ARBs prescriptions for patients with cardiovascular disease and decreasing prescriptions for those with low oxygen saturation at admission. We show that personalized recommendations can improve patient outcomes by 1.0% compared to the standard of care when applied to external populations. We develop an interactive interface for our algorithm, providing physicians with an actionable tool to easily assess treatment alternatives and inform clinical decisions. This work offers the first personalized recommendation system to accurately evaluate the efficacy and risks of prescribing ACEIs and ARBs to hypertensive COVID-19 patients.Highlights−This paper introduces a data-driven approach for personalizing the prescription of ACE inhibitors (ACEIs) and angiotensin-receptor blockers (ARBs) for hypertensive COVID-19 patients.−Leveraging an international cohort of more than 3,500 patients, we identify clinical and demographic characteristics that may affect the effectiveness of ACEIs/ARBs for COVID-19 patients, such as low oxygen saturation at admission.−We developed a user-friendly online application that is available to physicians to facilitate interpretation and communication of the results of the algorithm.
Concentration of the cellular material in the nasopharyngeal swabs increases the clinical sensitivity of SARS-CoV2 RT-PCR
Authors: Kannian Priya , Mahanathi Pasuvaraj , Ashwini Veeraraghavan 
Published: November 2020

SummarySevere acute respiratory syndrome - coronavirus 2 (SARS-CoV2) is detected by a highly sensitive molecular method, reverse transcriptase-polymerase chain reaction (RT-PCR) from nasopharyngeal swab (NPS) samples collected in 2-3ml of viral transport medium (VTM). Unlike body fluids, NPS samples are undermined by high variability in the amount of cells that get suspended into the VTM. Hence, the cell density used for RNA extraction becomes an important analytical variable that contributes to the overall sensitivity of the RT-PCR. In this study, we compared the sensitivity of SARS-CoV2 RT-PCR in 50 NPS samples collected from in-patients of the COVID wards using the concentration and direct methods. The concentration method detected the viral RNA in all 50 samples, while the direct method was positive in only 41 (82%) samples (p=0.003). Additionally, the Ct values were lower in the direct method compared to concentration method among the 41 positive samples (p=0.03 for N gene and p=0.04 for RdRp gene). The mean CV% was also ≥10%. Thus, the concentration of the cells prior to RNA extraction drastically improves the sensitivity of detection of SARS-CoV2 in NPS samples.
A Benchmark Dose Analysis for Maternal Pregnancy Urine-Fluoride and IQ in Children
Authors: Grandjean Philippe , Hu Howard , Till Christine , Green Rivka , Bashash Morteza , Flora David , Tellez-Rojo Martha Maria , Song Peter , Lanphear Bruce , Budtz-Jørgensen Esben 
Published: November 2020

AbstractAs a safe exposure level for fluoride in pregnancy has not been established, we used data from two prospective studies for benchmark dose modeling. We included mother-child pairs from the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) cohort in Mexico and the Maternal-Infant Research on Environmental Chemicals (MIREC) cohort in Canada. Children were assessed for IQ at age 4 (n=211) and between 6 and 12 years (n=287) in the ELEMENT cohort and between ages 3 and 4 years (n=512) in the MIREC cohort. We calculated covariate-adjusted regression coefficients and their standard errors to explore the concentration-effect function for maternal urinary fluoride with children’s IQ, including possible sex-dependence. Assuming a benchmark response of 1 IQ point, we derived benchmark concentrations (BMCs) of maternal urinary fluoride and benchmark concentration levels (BMCLs). No deviation from linearity was detected from the results of the two studies. Using a linear slope, the BMC for maternal urinary fluoride associated with a 1-point decrease in IQ scores of preschool-aged boys and girls was 0.29 mg/L (BMCL, 0.18 mg/L). The BMC was 0.30 mg/L (BMCL, 0.19 mg/L) when pooling the IQ scores from the older ELEMENT children and the MIREC cohort. Boys showed slightly lower BMC values compared with girls. Relying on two prospective studies, maternal urine-fluoride exposure at levels commonly occurring in the general population, the joint data showed BMCL results about 0.2 mg/L. These results can be used to guide decisions on preventing excess fluoride exposure in vulnerable populations.
What is the efficacy and safety of rapid exercise tests for exertional desaturation in Covid-19: A rapid review protocol
Authors: Kalin Asli , Javid Babak , Knight Matthew , Inada-Kim Matt , Greenhalgh Trisha 
Published: November 2020

AbstractBackgroundEven when resting pulse oximetry is normal in the patient with acute Covid-19, hypoxia can manifest on exertion. We sought to summarise the literature on the performance of different rapid tests for exertional desaturation.Research questionWhat tests have been formally evaluated for the rapid assessment of exertional hypoxia? What is the evidence for their accuracy, practicability and safety in the context of suspected acute Covid-19? To what extent will these tests help identify patients with evidence of either silent or hidden hypoxia leading to earlier recognition of those at risk of severe outcomes?MethodWe aim to review three independent searches of AMED, CINAHL, EMBASE MEDLINE, Cochrane and PubMed using LitCovid, Scholar and Google databases until 24thSeptember 2020. Screening, data abstraction, and quality appraisal of full-text papers will be completed independently by two reviewers including a topic expert and a review expert. Studies will be tabulated and assessed for risk of bias using QUADAS 2 tool.DiscussionThis rapid review aims to produce key findings relevant to the assessment of exertional desaturation in patients with suspected Covid-19. Establishing a validated tool to assess exertional desaturation will help to ensure that future research on this topic can be undertaken in a consistent way. An exertional desaturation test should be used in combination with a comprehensive clinical evaluation and only on patients whose resting oximetry reading is 96% or above unless in a supervised care setting. It should be terminated if the patient experiences adverse effects.
A publicly available score for evaluating hospital financial standing
Authors: Zinoviev Radoslav , Krumholz Harlan , Ciccarone Richard A. , Antle Rick , Forman Howard 
Published: November 2020

A.AbstractObjectivesTo create a straightforward scoring procedure based on widely available, inexpensive financial data that provides an assessment of the financial health of a hospital.DesignMethodological study.SettingMulticenter study.ParticipantsAll hospitals and health systems reporting the required financial metrics in 2017 were included for a total of 1,075 participants.InterventionsWe examined a list of 232 hospital financial indicators and used existing models and financial literature to select 30 metrics that sufficiently describe hospital operations. In a set of hospital financial data from 2017, we used Principal Coordinate Analysis to assess collinearity among variables and eliminated redundant variables. We isolated 10 unique variables, each assigned a weight equal to the share of its coefficient in a regression onto Moody’s Credit Rating, our predefined gold standard. The sum of weighted variables is a single composite score named the Yale Hospital Financial Score (YHFS).Primary Outcome MeasuresAbility to reproduce both financial trends from a “gold standard” metric and known associations with non-fiscal data.ResultsThe validity of the YHFS was evaluated by: (1) assessing its reproducibility with previously excluded data; (2) comparing it to existing models; and, (3) replicating known associations with non-fiscal data. Ten percent of the initial dataset had been reserved for validation and was not used in creating the model; the YHFS predicts 96.7% of the variation in this reserved sample, demonstrating reproducibility. The YHFS predicts 90.5% and 88.8% of the variation in Moody’s and Standard and Poor’s bond ratings, respectively, supporting its validity. As expected, larger hospitals had higher YHFS scores whereas a greater share of Medicare discharges correlated with lower YHFS scores.ConclusionsWe created a reliable and publicly available composite score of hospital financial stability.B.Article SummaryStrengths and Limitations of This StudyThere is a lack of models for assessing the financial state of hospitals in a robust and systematic way using publicly available data.We created the Yale Hospital Financial Score, a compound financial ranking of hospitals using a diverse collection of hospital financial metrics.The score ranks hospitals from 0 to 100 and was validated by showing reproducibility on a pre-excluded sample and strong correlation with “gold standard” metricsThis score has been developed to aid health policy researchers and has not yet been validated in studies of longitudinal financial outcomes
Cohorting of Non-Critically Ill COVID-19 Patients: A Multicenter Survey Study (COVID-COHORT)
Authors: Purohit Ushma , Fralick Mike 
Published: November 2020

AbstractThe COVID-19 pandemic has posed novel infection-control challenges for hospitals around the globe. One infection-control strategy that has been widely used in the context of other outbreaks is patient cohorting. This strategy refers to the placement of all patients exposed to the same laboratory-confirmed infectious agent in one location within the hospital. Little is known about the current utilization of this strategy with non-critically ill COVID-19 patients. An international multicenter, survey study was conducted to identify what strategies are planned or in place for patients with COVID-19 who are not critically ill. The survey was distributed from March 23-29th, 2020 to GIM physicians in Canada, USA, Denmark, Singapore, Hong Kong, and England. Of the 31 hospitals, 29 (94%) indicated that they plan on cohorting all GIM patients with COVID-19 to one location in the hospital. Among these 29 hospitals, 23 (79%) had implemented the plan at the time of the survey. The primary reasons for this decision were to limit the spread of COVID-19 and conserve PPE use. In conclusion, in the face of a novel virus there is near unanimity in the practice of patient cohorting as a potential mitigation strategy.