Scalable Computational Algorithms for Geo-spatial Covid-19 Spread in High Performance Computing

A nonlinear partial differential equation (PDE) based compartmental model of COVID-19 provides a continuous trace of infection over space and time. Finer resolutions in the spatial discretization, the inclusion of additional model compartments and model stratifications based on clinically relevant categories contribute to an increase in the number of unknowns to the order of millions. We adopt a parallel scalable solver allowing faster solutions for these high fidelity models. The solver combines domain decomposition and algebraic multigrid preconditioners at multiple levels to achieve the desired strong and weak scalability. As a numerical illustration of this general methodology, a five-compartment susceptible-exposed-infected-recovered-deceased (SEIRD) model of COVID-19 is used to demonstrate the scalability and effectiveness of the proposed solver for a large geographical domain (Southern Ontario). It is possible to predict the infections up to three months for a system size of 92 million (using 1780 processes) within 7 hours saving months of computational effort needed for the conventional solvers

Hubungan Status Gizi Dengan Usia Menarche Pada Remaja Putri Di SMP Negeri 6 Tidore Kepulauan

. Background : Adolescence isatransition periodbetweenchildhoodandadulthood,is a time ofphysical maturity, cognitive, social andemotional. In young women, pubertyis oftenmarked bymenarche.Menarcheisthefirstmenstruationoccurs, whichis the hallmark ofmaturity ofa woman who ishealthyandnot pregnant. Menarcheusuallyoccurs at age11-13years. There are manyfactors that affectthe age ofmenarche,one of them isnutritionalstatus. This research was aimed to know the relationship nutritional status with age of menarche in young women at 6 Junior High School of Tidore Islands. The research methodsanalytical survey usingcross sectionaldesign. This research was conducted in 6 Junior High School of Tidore Islands on November 30 - December 8, 2015. Population is 97 students.Sampling technique is the total sampling with a sample size of 97 students. The instrument of this research used questionnaire, scales and height measuring devices.The data analysis is done with using the chi-square test, at the 95% significance level (á 0.05) showed the value of ñ=0.000, this value is smaller than á = 0.05. Conclusion : there is a relationship of nutritional status with age of menarche in young women at 6 Junior High School of Tidore Islands.Advice for young women to maintain normal nutritional status to achieve the normal age of menarche

Scalable computational algorithms for geospatial COVID-19 spread using high performance computing

A nonlinear partial differential equation (PDE) based compartmental model of COVID-19 provides a continuous trace of infection over space and time. Finer resolutions in the spatial discretization, the inclusion of additional model compartments and model stratifications based on clinically relevant categories contribute to an increase in the number of unknowns to the order of millions. We adopt a parallel scalable solver that permits faster solutions for these high fidelity models. The solver combines domain decomposition and algebraic multigrid preconditioners at multiple levels to achieve the desired strong and weak scalabilities. As a numerical illustration of this general methodology, a five-compartment susceptible-exposed-infected-recovered-deceased (SEIRD) model of COVID-19 is used to demonstrate the scalability and effectiveness of the proposed solver for a large geographical domain (Southern Ontario). It is possible to predict the infections for a period of three months for a system size of 186 million (using 3200 processes) within 12 hours saving months of computational effort needed for the conventional solvers

Melatonin and Human Cardiovascular Disease

The possible therapeutic role of melatonin in the pathophysiology of coronary artery disorder (CAD) is increasingly being recognized. In humans, exogenous melatonin has been shown to decrease nocturnal hypertension, improve systolic and diastolic blood pressure, reduce the pulsatility index in the internal carotid artery, decrease platelet aggregation, and reduce serum catecholamine levels. Low circulating levels of melatonin are reported in individuals with CAD, arterial hypertension, and congestive heart failure. This review assesses current literature on the cardiovascular effects of melatonin in humans. It can be concluded that melatonin deserves to be considered in clinical trials evaluating novel therapeutic interventions for cardiovascular disorders.Fil: Pandi Perumal, Seithikurippu R.. King Saud University; Arabia SauditaFil: BaHammam, Ahmed S.. King Saud University; Arabia SauditaFil: Ojike, Nwakile I.. King Saud University; Arabia SauditaFil: Akinseye, Oluwaseun A.. University of New York; Estados UnidosFil: Kendzerska, Tetyana. Sunnybrook Health Sciences Center; CanadáFil: Buttoo, Kenneth. Sleep Disorders Center; CanadáFil: Dhandapany, Perundurai S.. Oregon Health And Science University; Estados UnidosFil: Brown, Gregory M.. University of Toronto; CanadáFil: Cardinali, Daniel Pedro. Pontificia Universidad Católica Argentina ; Argentin

Trends in outpatient and inpatient visits for separate ambulatory-care-sensitive conditions during the first year of the COVID-19 pandemic: a province-based study

BackgroundThe COVID-19 pandemic led to global disruptions in non-urgent health services, affecting health outcomes of individuals with ambulatory-care-sensitive conditions (ACSCs).MethodsWe conducted a province-based study using Ontario health administrative data (Canada) to determine trends in outpatient visits and hospitalization rates (per 100,000 people) in the general adult population for seven ACSCs during the first pandemic year (March 2020–March 2021) compared to previous years (2016–2019), and how disruption in outpatient visits related to acute care use. ACSCs considered were chronic obstructive pulmonary disease (COPD), asthma, angina, congestive heart failure (CHF), hypertension, diabetes, and epilepsy. We used time series auto-regressive integrated moving-average models to compare observed versus projected rates.ResultsFollowing an initial reduction (March–May 2020) in all types of visits, primary care outpatient visits (combined in-person and virtual) returned to pre-pandemic levels for asthma, angina, hypertension, and diabetes, remained below pre-pandemic levels for COPD, and rose above pre-pandemic levels for CHF (104.8 vs. 96.4, 95% CI: 89.4–104.0) and epilepsy (29.6 vs. 24.7, 95% CI: 22.1–27.5) by the end of the first pandemic year. Specialty visits returned to pre-pandemic levels for COPD, angina, CHF, hypertension, and diabetes, but remained above pre-pandemic levels for asthma (95.4 vs. 79.5, 95% CI: 70.7–89.5) and epilepsy (53.3 vs. 45.6, 95% CI: 41.2–50.5), by the end of the year. Virtual visit rates increased for all ACSCs. Among ACSCs, reductions in hospitalizations were most pronounced for COPD and asthma. CHF-related hospitalizations also decreased, albeit to a lesser extent. For angina, hypertension, diabetes, and epilepsy, hospitalization rates reduced initially, but returned to pre-pandemic levels by the end of the year.ConclusionThis study demonstrated variation in outpatient visit trends for different ACSCs in the first pandemic year. No outpatient visit trends resulted in increased hospitalizations for any ACSC; however, reductions in rates of asthma, COPD, and CHF hospitalizations persisted

Comprehensive compartmental model and calibration algorithm for the study of clinical implications of the population-level spread of COVID-19 : a study protocol

Introduction: The complex dynamics of the coronavirus disease 2019 (COVID-19) pandemic has made obtaining reliable long-term forecasts of the disease progression difficult. Simple mechanistic models with deterministic parameters are useful for short-term predictions but have ultimately been unsuccessful in extrapolating the trajectory of the pandemic because of unmodelled dynamics and the unrealistic level of certainty that is assumed in the predictions. Methods and analysis: We propose a 22-compartment epidemiological model that includes compartments not previously considered concurrently, to account for the effects of vaccination, asymptomatic individuals, inadequate access to hospital care, post-acute COVID-19 and recovery with long-term health complications. Additionally, new connections between compartments introduce new dynamics to the system and provide a framework to study the sensitivity of model outputs to several concurrent effects, including temporary immunity, vaccination rate and vaccine effectiveness. Subject to data availability for a given region, we discuss a means by which population demographics (age, comorbidity, socioeconomic status, sex and geographical location) and clinically relevant information (different variants, different vaccines) can be incorporated within the 22-compartment framework. Considering a probabilistic interpretation of the parameters allows the model’s predictions to reflect the current state of uncertainty about the model parameters and model states. We propose the use of a sparse Bayesian learning algorithm for parameter calibration and model selection. This methodology considers a combination of prescribed parameter prior distributions for parameters that are known to be essential to the modelled dynamics and automatic relevance determination priors for parameters whose relevance is questionable. This is useful as it helps prevent overfitting the available epidemiological data when calibrating the parameters of the proposed model. Population-level administrative health data will serve as partial observations of the model states. Ethics and dissemination: Approved by Carleton University's Research Ethics Board-B (clearance ID: 114596). Results will be made available through future publication

A Risk Stratification Model for Adult Patients with Obstructive Sleep Apnea: Development and Evaluation

Despite emerging evidence that obstructive sleep apnea (OSA) may cause cardio-metabolic disturbances independently of known risk factors, the strength and significance of this association remains unclear. This thesis is comprised of three studies assessing the long term-consequences of OSA, and specifically the prognostic value of OSA-related variables for cardiovascular (CV) events, all-cause mortality and incident diabetes. Methods: The first study is a systematic review of longitudinal studies, from 1999 to 2011. Quality was assessed using published guidelines. Studies two and three linked a clinical sleep database to Ontario health administrative databases for the period of 1991 to 2011 to examine the relationship between OSA variables and a composite CV outcome and incident diabetes. For the latter, we assembled a cohort free of diabetes at baseline, as defined by health administrative data. Cox regression models were used to investigate the association between of OSA-related predictors and outcomes of interest, controlling for potential confounders. Study one identified significant relationships between OSA and all-cause mortality and composite CV outcome in men; associations with other outcomes remain uncertain. Among OSA-related variables, only apnea-hypopnea index (AHI) was a consistent predictor. Limitations of the clinically-based studies were small numbers of events, weak definitions of outcomes, and inconsistency in polysomnographic scoring criteria over time. Study two found that 1,172 (11.5%) of 10,149 participants experienced our composite CV event over a median follow-up of 68 months. In a fully adjusted model, the following OSA-related variables were significant independent predictors: time spent with oxygen saturation (SaO2) < 90%, sleep time, awakenings, periodic leg movements, heart rate, and presence of daytime sleepiness. In study three, of 8,678 cohort participants without diabetes at baseline, 1,017 (11.7%) developed incident diabetes over a median follow-up of 67 months. In fully-adjusted models, patients with AHI > 30 had a 30% higher hazard of developing diabetes than those with AHI < 5. Among other OSA-related variables, REM-AHI, and SaO2<90%, heart rate and neck circumference were associated with incident diabetes. Conclusions: Based on these studies, we demonstrated that OSA-related predictors significantly and independently contribute to the risk for occurrence of composite CV outcome and incidence diabetes.Ph

Self-report instruments for assessing sleep dysfunction in an adult traumatic brain injury population: a systematic review

Objectives: To review the number and characteristics of self-reported sleep measures used to evaluate impaired sleep/wakefulness in traumatic brain injury (TBI) populations. Methods: We conducted a comprehensive peer-reviewed literature search of Medline, Embase, PsycINFO, CINAHL, and various bibliographies. Only standardized self-report measures for evaluating sleep dysfunction and its signs were taken into consideration. Results: Sixteen self-report measures used in TBI research and clinical practices were identified. Five were generic, five symptom-related, and six were condition-specific measures. The Pittsburgh sleep quality index and Epworth sleepiness scale were partially validated in post-acute TBI. Conclusion: Although no instrument has been specifically developed for TBI patients, there are scientific benefits to using the existing measures. However, additional research is needed to examine their applicability to the TBI population. The design and introduction of a new instrument able to triage sleep-related complaints between depressive, other medical, and primary sleep disorders—with a section for caregiver reports—might assist in the identification of the etiology of sleep dysfunction in persons with TBI. In choosing or developing a sleep measure, researchers and clinicians must consider the specific domains they want to screen, diagnose, or monitor. Polysomnography is recommended for diagnosing specific sleep disorders that cannot be diagnosed solely using a self-report measure