A Bayesian model calibration framework for stochastic compartmental models with both time-varying and time-invariant parameters.

We consider state and parameter estimation for compartmental models having both time-varying and time-invariant parameters. In this manuscript, we first detail a general Bayesian computational framework as a continuation of our previous work. Subsequently, this framework is specifically tailored to the susceptible-infectious-removed (SIR) model which describes a basic mechanism for the spread of infectious diseases through a system of coupled nonlinear differential equations. The SIR model consists of three states, namely, the susceptible, infectious, and removed compartments. The coupling among these states is controlled by two parameters, the infection rate and the recovery rate. The simplicity of the SIR model and similar compartmental models make them applicable to many classes of infectious diseases. However, the combined assumption of a deterministic model and time-invariance among the model parameters are two significant impediments which critically limit their use for long-term predictions. The tendency of certain model parameters to vary in time due to seasonal trends, non-pharmaceutical interventions, and other random effects necessitates a model that structurally permits the incorporation of such time-varying effects. Complementary to this, is the need for a robust mechanism for the estimation of the parameters of the resulting model from data. To this end, we consider an augmented state vector, which appends the time-varying parameters to the original system states whereby the time evolution of the time-varying parameters are driven by an artificial noise process in a standard manner. Distinguishing between time-varying and time-invariant parameters in this fashion limits the introduction of artificial dynamics into the system, and provides a robust, fully Bayesian approach for estimating the time-invariant system parameters as well as the elements of the process noise covariance matrix. This computational framework is implemented by leveraging the robustness of the Markov chain Monte Carlo algorithm permits the estimation of time-invariant parameters while nested nonlinear filters concurrently perform the joint estimation of the system states and time-varying parameters. We demonstrate performance of the framework by first considering a series of examples using synthetic data, followed by an exposition on public health data collected in the province of Ontario.

Restrictive Spirometric Pattern and Preserved Ratio Impaired Spirometry in a Population 50-64 Years.

RATIONALE: Knowledge regarding prevalence and shared and unique characteristics of Restrictive spirometric pattern (RSP) and Preserved ratio impaired spirometry (PRISm) is lacking for a general population investigated with post-bronchodilator spirometry and computed tomography of the lungs. OBJECTIVES: To investigate shared and unique features for RSP and PRISm. METHODS: In the Swedish CArdioPulmonary bioImage Study (SCAPIS), a general population sample of 28,555 people aged 50 - 64 years (including 14,558 never-smokers) was assessed. The participants answered a questionnaire and underwent computed tomography of the lungs, post-bronchodilator spirometry, and coronary artery calcification score (CACS). Odds ratios (OR) with 95% confidence intervals (CI) were calculated using adjusted logistic regression. RSP was defined as FEV1/FVC≥0.70 and FVC<80%. PRISm was defined as FEV1/FVC≥0.70 and FEV1<80%. A local reference equation was applied. MEASUREMENTS AND RESULTS: The prevalence of RSP and PRISm were 5.1% (95% CI 4.9 - 5.4) and 5.1% (95% CI 4.8 - 5.3), respectively, with similar values seen in never-smokers. For RSP and PRISm, shared features were current smoking, dyspnea, chronic bronchitis, rheumatic disease, diabetes, ischemic heart disease (IHD), bronchial wall thickening, interstitial lung abnormalities (ILA), and bronchiectasis. Emphysema was uniquely linked to PRISm (OR 1.69, 1.36-2.10) vs 1.10 (0.84-1.43) for RSP. CACS≥300 was related to PRISm, but not among among never-smokers. CONCLUSIONS: PRISm and RSP have respiratory, cardiovascular, and metabolic conditions as shared features. Emphysema is only associated with PRISm. Coronary atherosclerosis may be associated with PRISm. Our results indicate that RSP and PRISm may share more features than not. This article is open access and distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

Evaluating the benefit of virtual surgical planning on bony union rates in head and neck reconstructive surgery.

OBJECTIVES: Virtual surgical planning (VSP) has gained acceptance because of its benefits in obtaining adequate resection, achieving cephalometric accuracy, and reducing operative time. The aim of this study is to compare the rate of union between VSP and free-hand surgery (FHS), identify predictors of non-union and evaluate the difference in operative time. METHODS: Post-operative CT were retrospectively reviewed for 123 patients who underwent maxillary or mandibular reconstruction between 2014 and 2021 using either VSP or FHS. Each apposition was graded as complete, partial or non-union. The rate of union, risk difference and inter-rater reliability were calculated. The difference in operative time was assessed. Predictors of non-union were identified using logistic regression. RESULTS: A total of 326 appositions were graded (VSP n = 150; FHS n = 176). The rates of complete and partial union were higher with VSP than FHS (74.7% vs. 65.3%; 18% vs. 15.9%, respectively, p = 0.01). Non-union was found at a higher rate with FHS than with VSP (18.7% vs. 7.3%). The non-union risk difference was 11.4. FHS, major complications and apposition at the native bone were predictors of non-union (OR 2.9, p = 0.02; OR 3.4, p = 0.01; OR 2.5, p = 0.05, respectively). The mean surgical time was shorter with VSP than with FHS (265.3 vs. 381.5 min, p < 0.001). The inter-rater agreement was high (k = 0.85; ICC = 0.86). CONCLUSION: VSP demonstrated significantly higher bony union rates and shorter operative time. FHS, development of major complications and apposition with native bone correlated with non-union.

Learning analytics for enhanced professional capital development: a systematic review.

Background/Motivation: This article presents a systematic review aimed at examining the utilization of learning analytics (LA) to enhance teachers' professional capital. Aim: The study focuses on three primary research questions: (1) exploring the characteristics and approaches of LA in professional capital, (2) investigating suggestions from LA for assessing and improving professional capital, and (3) examining variables studied in enhancing the most intricate dimension of professional capital using LA. Methodology: To address the research objectives, a systematic review was conducted focusing on the key concepts "learning analytics" and "professional capital." Following the procedures outlined encompassed in four stages: identification, screening, inclusion, and adequacy. The PRISMA 2009 protocol guided the systematic review process. Principal findings: The findings of the study underscore the efficacy of LA as a catalyst for improving professional capital, particularly through collaborative learning and the utilization of tools like forums and online learning platforms. Social capital emerges as a pivotal component in integrating diverse types of professional capital, fostering opportunities for knowledge creation and social networking. Conclusion/Significance: In conclusion, the study highlights the paramount significance of addressing teachers' professional capital development through collaborative approaches and leveraging technology, particularly in primary education. The article concludes by emphasizing the imperative for more research and knowledge dissemination in this field, aiming to ensure equity in learning and address the challenges posed by the COVID-19 pandemic.