scholarly journals Forecasting COVID-19 infection trends and new hospital admissions in England due to SARS-CoV-2 Variant of Concern Omicron

2021 ◽  
Author(s):  
Alberto Giovanni Gerli ◽  
Stefano Centanni ◽  
Joan B Soriano ◽  
Julio Ancochea
Keyword(s):  
Social Distance ◽  
Prediction Models ◽  
Hospital Admissions ◽  
Moving Average ◽  
Severity Of Illness ◽  
Lag Time ◽  
Relative Increase ◽  
Degree Polynomial ◽  
Polynomial Curve ◽  
Epidemiological Trends

Objectives: On November 26, 2021, WHO designated the variant B.1.1.529 as a new SARS-CoV-2 variant of concern (VoC), named Omicron, originally identified in South Africa. Several mutations in Omicron indicate that it may have an impact on how it spreads, resistance to vaccination, or the severity of illness it causes. We used our previous modelling algorithms to forecast the spread of Omicron in England. Design: We followed EQUATOR TRIPOD guidance for multivariable prediction models. Setting: England. Participants: Not applicable. Interventions: Non-interventional, observational study with a predicted forecast of outcomes. Main outcome measures: Trends in daily COVID-19 cases with a 7-day moving average and of new hospital admissions. Methods: Modelling included a third-degree polynomial curve in existing epidemiological trends on the spread of Omicron and a new Gaussian curve to estimate a downward trend after a peak in England. Results: Up to February 15, 2022, we estimated a projection of 250,000 COVID-19 daily cases of Omicron spread in the worse scenario, and 170,000 in the best scenario. Omicron might represent a relative increase from the background daily rates of COVID-19 infection in England of mid December 2021 of 1.9 to 2.8-fold. With a 5-day lag-time, daily new hospital admissions would peak at around 5,063 on January 23, 2022 in the worse scenario. Conclusion: This warning of pandemic surge of COVID-19 due to Omicron is calling for further reinforcing in England and elsewhere of universal hygiene interventions (indoor ventilation, social distance, and face masks), and anticipating the need of new total or partial lockdowns in England.

scholarly journals Forecasting COVID-19 infection trends in the EU-27 countries, the UK and Switzerland due to SARS-CoV-2 Variant of Concern Omicron

2021 ◽  
Author(s):  
Alberto Giovanni Gerli ◽  
Stefano Centanni ◽  
Joan B Soriano ◽  
Julio Ancochea
Keyword(s):  
South Africa ◽  
Prediction Models ◽  
Moving Average ◽  
Severity Of Illness ◽  
Relative Increase ◽  
Background Rate ◽  
Sigmoidal Curve ◽  
The Uk ◽  
Epidemiological Trends ◽  
The Eu

Background: On November 26, 2021, WHO designated the variant B.1.1.529 as a new SARS-CoV-2 variant of concern (VoC), named Omicron, originally identified in South Africa. Several mutations in Omicron indicate that it may have an impact on how it spreads, resistance to vaccination, or the severity of illness it causes. Methods: We used our previous modelling algorithms to forecast the spread of Omicron aggregated in the EU-27 countries, the United Kingdom and Switzerland, and report trends in daily cases with a 7-day moving average. We followed EQUATOR TRIPOD guidance for multivariable prediction models. Modelling included a third-degree polynomial curve in existing epidemiological trends on the spread of Omicron in South Africa, a five-parameter logistic (5PL) asymmetrical sigmoidal curve following a parametric growth in Europe, and a new Gaussian curve to estimate a downward trend after a peak. Results: Up to January 15, 2022, we estimated a background rate projection in EU-27 countries, the UK and Switzerland of about 145,000 COVID-19 daily cases without Omicron, which increases up to 440,000 COVID-19 daily cases in the worst scenario of Omicron spread, and 375,000 in the best scenario. Therefore, Omicron might represent a relative increase from the background daily rates of COVID-19 infection in Europe of 1.03-fold or 2.03-fold, that is up to a 200% increase. Conclusion: This warning pandemic surge due to Omicron is calling for further reinforcing of COVID-19 universal hygiene interventions (indoor ventilation, social distance, and face masks), and anticipating the need of new lockdowns in Europe.

scholarly journals Predicting hospital admissions from individual patient data (IPD): an applied example to explore key elements driving external validity

BMJ Open ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. e045572
Author(s):  
Andreas Daniel Meid ◽  
Ana Isabel Gonzalez-Gonzalez ◽  
Truc Sophia Dinh ◽  
Jeanet Blom ◽  
Marjan van den Akker ◽  
...  
Keyword(s):  
Prognostic Model ◽  
Prediction Models ◽  
Hospital Admissions ◽  
Absolute Risk ◽  
External Validation ◽  
Baseline Risk ◽  
Study Heterogeneity ◽  
Related Quality ◽  
Individual Participant ◽  
Risk Predictor

ObjectiveTo explore factors that potentially impact external validation performance while developing and validating a prognostic model for hospital admissions (HAs) in complex older general practice patients.Study design and settingUsing individual participant data from four cluster-randomised trials conducted in the Netherlands and Germany, we used logistic regression to develop a prognostic model to predict all-cause HAs within a 6-month follow-up period. A stratified intercept was used to account for heterogeneity in baseline risk between the studies. The model was validated both internally and by using internal-external cross-validation (IECV).ResultsPrior HAs, physical components of the health-related quality of life comorbidity index, and medication-related variables were used in the final model. While achieving moderate discriminatory performance, internal bootstrap validation revealed a pronounced risk of overfitting. The results of the IECV, in which calibration was highly variable even after accounting for between-study heterogeneity, agreed with this finding. Heterogeneity was equally reflected in differing baseline risk, predictor effects and absolute risk predictions.ConclusionsPredictor effect heterogeneity and differing baseline risk can explain the limited external performance of HA prediction models. With such drivers known, model adjustments in external validation settings (eg, intercept recalibration, complete updating) can be applied more purposefully.Trial registration numberPROSPERO id: CRD42018088129.

scholarly journals Impact of COVID-19 pandemic on stroke admissions in Qatar

2021 ◽  
Vol 3 (1) ◽  
pp. e000084
Author(s):  
Naveed Akhtar ◽  
Salman Al Jerdi ◽  
Ziyad Mahfoud ◽  
Yahia Imam ◽  
Saadat Kamran ◽  
...  
Keyword(s):  
Hospital Admissions ◽  
Small Vessel Disease ◽  
Tertiary Care ◽  
Relative Increase ◽  
Large Vessel ◽  
Tertiary Care Centre ◽  
Transient Ischaemic Attacks ◽  
Stroke Mimics ◽  
Coronary Syndromes ◽  
The Impact

IntroductionThe COVID-19 pandemic has resulted in a dramatic unexplained decline in hospital admissions due to acute coronary syndromes and stroke. Several theories have emerged aiming to explain this decline, mostly revolving around the fear of contracting the disease and thus avoiding hospital visits.AimsIn this study, we aim to examine the impact of the COVID-19 pandemic on stroke admissions to a tertiary care centre in Qatar.MethodsThe Hamad General Hospital stroke database was interrogated for stroke admissions between September 2019 and May 2020. The number of stroke admissions, stroke subtypes and short-term outcomes was compared between the ‘pre-COVID-19’ period (September 2019 to February 2020) and the COVID-19 pandemic period (March to May 2020).ResultsWe observed a significant decline in monthly admissions in March (157), April (128) and May (135) compared with the pre-COVID-19 6-month average (229) (p=0.024). The reduction in admissions was most evident in functional stroke mimics. The average admissions decreased from 87 to 34 per month (p=0.0001). Although there were no significant differences in admissions due to ischaemic stroke (IS), intracranial haemorrhage or transient ischaemic attacks between the two periods, we noted a relative decrease in IS due to small vessel disease and an increase in those due to large vessel atherosclerosis in March to May 2020.ConclusionsThe decline in overall stroke admissions during the COVID-19 pandemic is most likely related to concerns of contracting the infection, evidenced mainly by a decline in admissions of stroke mimics. However, a relative increase in large vessel occlusions raises suspicion of pathophysiological effects of the virus, and requires further investigation.

Molecular Epidemiology and Risk Factors for Colonization by Vancomycin-ResistantEnterococcusin Patients with Hematologic Malignancies

2011 ◽  
Vol 32 (5) ◽  
pp. 490-496 ◽  
Author(s):  
N. G. Almyroudis ◽  
A. J. Lesse ◽  
T. Hahn ◽  
G. Samonis ◽  
P. A. Hazamy ◽  
...  
Keyword(s):  
Risk Factors ◽  
Molecular Epidemiology ◽  
Hospital Admissions ◽  
Severity Of Illness ◽  
Hematologic Malignancies ◽  
Observation Time ◽  
Patient Specific ◽  
Common Source ◽  
Retrospective Case ◽  
Hematopoietic Stem

Objective.To study the molecular epidemiology of vancomycin-resistantEnterococcus(VRE) colonization and to identify modifiable risk factors among patients with hematologic malignancies.Setting.A hematology-oncology unit with high prevalence of VRE colonization.Participants.Patients with hematologic malignancies and hematopoietic stem cell transplantation recipients admitted to the hospital.Methods.Patients underwent weekly surveillance by means of perianal swabs for VRE colonization and, if colonized, were placed in contact isolation. We studied the molecular epidemiology in fecal and blood isolates by pulsed-field gel electrophoresis over a 1-year period. We performed a retrospective case-control study over a 3-year period. Cases were defined as patients colonized by VRE, and controls were defined as patients negative for VRE colonization. Case patients and control patients were matched by admitting service and length of observation time.Results.Molecular genotyping demonstrated the primarily polyclonal nature of VRE isolates. Colonization occurred at a median of 14 days. Colonized patients were characterized by longer hospital admissions. Previous use of ceftazidime was associated with VRE colonization (P< .001), while use of intravenous vancomycin and antibiotics with anaerobic activity did not emerge as a risk factor. There was no association with neutropenia or presence of colonic mucosal disruption, and severity of illness was similar in both groups.Conclusion.Molecular studies showed that in the majority of VRE-colonized patients the strains were unique, arguing that VRE acquisition was sporadic rather than resulting from a common source of transmission. Patient-specific factors, including prior antibiotic exposure, rather than breaches in infection control likely predict for risk of fecal VRE colonization.

Incorporating gout guideline advice into urate reports is associated with reduced hospital admissions: results of an observational study

Rheumatology ◽  
2021 ◽  
Author(s):  
Philip L Riches ◽  
Laura Downie ◽  
Carol Thomson
Keyword(s):  
Hospital Admissions ◽  
Relative Rate ◽  
Primary Diagnosis ◽  
Relative Increase ◽  
Local Data ◽  
Improved Outcomes ◽  
Significant Difference ◽  
Prescription Rates ◽  
The Impact ◽  
Health Boards

Abstract Objective To evaluate the impact of incorporating treatment guidance into reporting of urate test results. Methods Urate targets for clinically confirmed gout were added to urate results above 0.36 mmol/l requested after September 2014 within NHS Lothian. Scotland-wide data on urate-lowering therapy prescriptions and hospital admissions with gout were analysed between 2009 and 2020. Local data on urate tests were analysed between 2014 and 2015. Results Admissions with a primary diagnosis of gout in Lothian reduced modestly following the intervention from 111/year in 2010–2014 to 104/year in 2015–2019, a non-significant difference (P = 0.32). In contrast there was a significant increase in admissions to remaining NHS Scotland health boards (556/year vs 606/year, P &lt; 0.01). For a secondary diagnosis of gout the number of admissions in NHS Lothian reduced significantly (58/year vs 39/year, P &lt; 0.01) contrasting with a significant increase in remaining Scottish health boards (220/year vs 290/year, P &lt; 0.01). The relative rate of admissions to NHS Lothian compared with remaining Scottish boards using a 2009 baseline were significantly reduced for both primary diagnosis of gout (1.06 vs 1.25, P &lt; 0.001) and secondary diagnoses of gout (0.64 compared with 1.4, P &lt; 0.001) after the intervention; however, there was no difference before the intervention. A relative increase in the prescription rates of allopurinol 300 mg tablets and febuxostat 120 mg tablets may have contributed to the improved outcomes seen. Conclusion Incorporation of clinical guideline advice into routine reporting of urate results was associated with reduced rates of admission with gout in NHS Lothian, in comparison with other Scottish health boards.

HOSPITAL Score, LACE Index and LACE+ Index as predictors of 30-day readmission in patients with heart failure

2019 ◽  
Vol 25 (5) ◽  
pp. 166-167 ◽  
Author(s):  
Abdisamad M Ibrahim ◽  
Cameron Koester ◽  
Mohammad Al-Akchar ◽  
Nitin Tandan ◽  
Manjari Regmi ◽  
...  
Keyword(s):  
Heart Failure ◽  
Length Of Stay ◽  
Patient Population ◽  
Prediction Models ◽  
Hospital Admissions ◽  
Diastolic Heart Failure ◽  
Hospital Readmissions ◽  
Medical Patients ◽  
Readmission Rates ◽  
C Statistic

This study aimed to evaluate the accuracy of the HOSPITAL Score (Haemoglobin level at discharge, Oncology at discharge, Sodium level at discharge, Procedure during hospitalization, Index admission, number of hospital admissions, Length of stay) LACE index (Length of stay, Acute/emergent admission, Charlson comorbidy index score, Emerency department visits in previous 6 months) and LACE+ index in predicting 30-day readmission in patients with diastolic dysfunction. Heart failure remains one of the most common hospital readmissions in adults, leading to significant morbidity and mortality. Different models have been used to predict 30-day hospital readmissions. All adult medical patients discharged from the SIU School of Medicine Hospitalist service from 12 June 2016 to 12 June 2018 with an International Classification of Disease, 10th Revision, Clinical Modification diagnosis of diastolic heart failure were studied retrospectively to evaluate the performance of the HOSPITAL Score, LACE index and LACE+ index readmission risk prediction tools in this patient population. Of the 730 patient discharges with a diagnosis of heart failure with preserved ejection fraction (HFpEF), 692 discharges met the inclusion criteria. Of these discharges, 189 (27%) were readmitted to the same hospital within 30 days. A receiver operating characteristic evaluation showed C-statistic values to be 0.595 (95% CI 0.549 to 0.641) for the HOSPITAL Score, 0.551 (95% CI 0.503 to 0.598) for the LACE index and 0.568 (95% CI 0.522 to 0.615) for the LACE+ index, indicating poor specificity in predicting 30-day readmission. The result of this study demonstrates that the HOSPITAL Score, LACE index and LACE+ index are not effective predictors of 30-day readmission for patients with HFpEF. Further analysis and development of new prediction models are needed to better estimate the 30-day readmission rates in this patient population.

scholarly journals Regression analysis between sediment transport rates and stream discharge for the Nestos River, Greece

2013 ◽  
Vol 14 (3) ◽  
pp. 362-370
Keyword(s):  
Sediment Transport ◽  
Suspended Load ◽  
Bed Load ◽  
Regression Curve ◽  
Degree Polynomial ◽  
Stream Discharge ◽  
Nestos River ◽  
Polynomial Curve ◽  
Load Transport ◽  
Bed Load Transport

Systematic measurements of sediment transport rates and water discharge were conducted in the Nestos River (Greece), at a place located between the outlet of Nestos River basin and the river delta. This basin area is about 838 km2 and lies downstream of the Platanovrysi Dam. Separate measurements of bed load transport and suspended load transport were performed at certain cross sections of the Nestos River. In this study, relationships between sediment transport rates and stream discharge for the Nestos River are presented. A nonlinear regression curve (4th degree polynomial curve; r2 equals 0.62) between bed load transport rates and stream discharge, on the basis of 63 measurements, was developed. In addition, a nonlinear regression curve (5th degree polynomial curve; r2 equals 0.95) between suspended load transport rates and stream discharge, on the basis of 65 measurements, was developed. The relatively high r2 values indicate that both bed load transport rates and, especially, suspended load transport rates can be predicted as a function of the stream discharge in the Nestos River. However, the reliability of the regression equations would have been higher if more measured data were available.

scholarly journals Assessment of the outbreak risk, mapping and infestation behavior of COVID-19: Application of the autoregressive and moving average (ARMA) and polynomial models

2020 ◽  
Author(s):  
Hamid Reza Pourghasemi ◽  
Soheila Pouyan ◽  
Zakariya Farajzadeh ◽  
Nitheshnirmal Sadhasivam ◽  
Bahram Heidari ◽  
...  
Keyword(s):  
High Risk ◽  
Moving Average ◽  
Maximum Temperature ◽  
Support Vector ◽  
Good Prediction ◽  
Fars Province ◽  
Arma Models ◽  
Degree Polynomial ◽  
The Third ◽  
The World

AbstractInfectious disease outbreaks pose a significant threat to human health worldwide. The outbreak of pandemic coronavirus disease 2019 (COVID-2019) has caused a global health emergency. Identification of regions with high risk for COVID-19 outbreak is a major priority of the governmental organizations and epidemiologists worldwide. The aims of the present study were to analyze the risk factors of coronavirus outbreak and identify areas with a high risk of human infection with virus in Fars Province, Iran. A geographic information system (GIS)-based machine learning algorithm (MLA), support vector machine (SVM), was used for the assessment of the outbreak risk of COVID-19 in Fars Province, Iran. The daily observations of infected cases was tested in the third-degree polynomial and the autoregressive and moving average (ARMA) models to examine the patterns of virus infestation in the province and in Iran. The results of disease outbreak in Iran were compared with the data for Iran and the world. Sixteen effective factors including minimum temperature of coldest month (MTCM), maximum temperature of warmest month (MTWM), precipitation in wettest month (PWM), precipitation of driest month (PDM), distance from roads, distance from mosques, distance from hospitals, distance from fuel stations, human footprint, density of cities, distance from bus stations, distance from banks, distance from bakeries, distance from attraction sites, distance from automated teller machines (ATMs), and density of villages – were selected for spatial modelling. The predictive ability of an SVM model was assessed using the receiver operator characteristic – area under the curve (ROC-AUC) validation technique. The validation outcome reveals that SVM achieved an AUC value of 0.786 (March 20), 0.799 (March 29), and 86.6 (April 10) a good prediction of change detection. The growth rate (GR) average for active cases in Fars for a period of 41 days was 1.26, whilst it was 1.13 in country and the world. The results of the third-degree polynomial and ARMA models revealed an increasing trend for GR with an evidence of turning, demonstrating extensive quarantines has been effective. The general trends of virus infestation in Iran and Fars Province were similar, although an explosive growth of the infected cases is expected in the country. The results of this study might assist better programming COVID-19 disease prevention and control and gaining sorts of predictive capability would have wide-ranging benefits.

scholarly journals Lymphopenia in hospitalized patients and its relationship with severity of illness and mortality

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256205
Author(s):  
Juan Carlos Andreu-Ballester ◽  
Aurelio Pons-Castillo ◽  
Antonio González-Sánchez ◽  
Antonio Llombart-Cussac ◽  
María José Cano ◽  
...  
Keyword(s):  
Hospital Stay ◽  
Hospital Admissions ◽  
Severity Of Illness ◽  
Absolute Lymphocyte Count ◽  
Hospitalized Patients ◽  
Time To Death ◽  
Extreme Risk ◽  
Four Levels ◽  
Time Of Admission ◽  
Relationship Of

Background Lymphopenia is associated with various pathologies such as sepsis, burns, trauma, general anesthesia and major surgeries. All these pathologies are clinically expressed by the so-called Systemic Inflammatory Response Syndrome which does not include lymphopenia into defining criteria. The main objective of this work was to analyze the diagnosis of patients admitted to a hospital related to lymphopenia during hospital stay. In addition, we investigated the relationship of lymphopenia with the four levels of the Severity of Illness (SOI) and the Risk of Mortality (ROM). Method and findings Lymphopenia was defined as Absolute Lymphocyte Count (ALC) <1.0 x109/L. ALC were analyzed every day since admission. The four levels (minor, moderate, major and extreme risk) of both SOI and ROM were assessed. A total of 58,260 hospital admissions were analyzed. More than 41% of the patients had lymphopenia during hospital stay. The mean time to death was shorter among patients with lymphopenia on admission 65.6 days (CI95%, 57.3–73.8) vs 89.9 (CI95%, 82.4–97.4), P<0.001. Also, patients with lymphopenia during hospital stay had a shorter time to the mortality, 67.5 (CI95%, 61.1–73.9) vs 96.9 (CI95%, 92.6–101.2), P<0.001. Conclusions Lymphopenia had a high prevalence in hospitalized patients with greater relevance in infectious pathologies. Lymphopenia was related and clearly predicts SOI and ROM at the time of admission, and should be considered as clinical diagnostic criteria to define SIRS.

Complete Solution to the Eight-Point Path Generation of Slider-Crank Four-Bar Linkages

2010 ◽  
Vol 132 (8) ◽  
Author(s):  
Hafez Tari ◽  
Hai-Jun Su
Keyword(s):  
Complete Solution ◽  
Solution Process ◽  
Polynomial Equations ◽  
Homotopy Methods ◽  
Degree Polynomial ◽  
Fourth Degree ◽  
Augmented System ◽  
Polynomial Curve ◽  
Four Bar Linkage ◽  
Classical Homotopy

We study the synthesis of a slider-crank four-bar linkage whose coupler point traces a set of predefined task points. We report that there are at most 558 slider-crank four-bars in cognate pairs passing through any eight specified task points. The problem is formulated for up to eight precision points in polynomial equations. Classical elimination methods are used to reduce the formulation to a system of seven sixth-degree polynomials. A constrained homotopy technique is employed to eliminate degenerate solutions, mapping them to solutions at infinity of the augmented system, which avoids tedious post-processing. To obtain solutions to the augmented system, we propose a process based on the classical homotopy and secant homotopy methods. Two numerical examples are provided to verify the formulation and solution process. In the second example, we obtain six slider-crank linkages without a branch or an order defect, a result partially attributed to choosing design points on a fourth-degree polynomial curve.

Sign in / Sign up

Export Citation Format

Share Document