Survival extrapolation using the poly-Weibull model.

Recent studies of (cost-) effectiveness in cardiothoracic transplantation have required estimation of mean survival over the lifetime of the recipients. In order to calculate mean survival, the complete survivor curve is required but is often not fully observed, so that survival extrapolation is necessary. After transplantation, the hazard function is bathtub-shaped, reflecting latent competing risks which operate additively in overlapping time periods. The poly-Weibull distribution is a flexible parametric model that may be used to extrapolate survival and has a natural competing risks interpretation. In addition, treatment effects and subgroups can be modelled separately for each component of risk. We describe the model and develop inference procedures using freely available software. The methods are applied to two problems from cardiothoracic transplantation

Contemporary statistical inference for infectious disease models using Stan

This paper is concerned with the application of recent statistical advances to inference of infectious disease dynamics. We describe the fitting of a class of epidemic models using Hamiltonian Monte Carlo and variational inference as implemented in the freely available Stan software. We apply the two methods to real data from outbreaks as well as routinely collected observations. Our results suggest that both inference methods are computationally feasible in this context, and show a trade-off between statistical efficiency versus computational speed. The latter appears particularly relevant for real-time applications

Bayesian epidemic models for spatially aggregated count data

Epidemic data often possess certain characteristics, such as the presence of many zeros, the spatial nature of the disease spread mechanism, environmental noise, serial correlation and dependence on time varying factors. This paper addresses these issues via suitable Bayesian modelling. In doing so we utilise a general class of stochastic regression models appropriate for spatio-temporal count data with an excess number of zeros. The developed regression framework does incorporate serial correlation and time varying covariates through an Ornstein Uhlenbeck process formulation. In addition, we explore the effect of different priors, including default options and variations of mixtures of g-priors. The effect of different distance kernels for the epidemic model component is investigated. We proceed by developing branching process-based methods for testing scenarios for disease control, thus linking traditional epidemiological models with stochastic epidemic processes, useful in policy-focused decision making. The approach is illustrated with an application to a sheep pox dataset from the Evros region, Greece

Comparison of inference methods of genetic parameters with an application to body weight in broilers

REML (restricted maximum likelihood) has become the standard method of variance component estimation in animal breeding. Inference in Bayesian animal models is typically based upon Markov chain Monte Carlo (MCMC) methods, which are generally flexible but time-consuming. Recently, a new Bayesian computational method, integrated nested Laplace approximation (INLA), has been introduced for making fast non-sampling-based Bayesian inference for hierarchical latent Gaussian models. This paper is concerned with the comparison of estimates provided by three representative programs (ASReml, WinBUGS and the R package AnimalINLA) of the corresponding methods (REML, MCMC and INLA), with a view to their applicability for the typical animal breeder. Gaussian and binary as well as simulated data were used to assess the relative efficiency of the methods. Analysis of 2319 records of body weight at 35 days of age from a broiler line suggested a purely additive animal model, in which the heritability estimates ranged from 0.31 to 0.34 for the Gaussian trait and from 0.19 to 0.36 for the binary trait, depending on the estimation method. Although in need of further development, AnimalINLA seems a fast program for Bayesian modeling, particularly suitable for the inference of Gaussian traits, while WinBUGS appeared to successfully accommodate a complicated structure between the random effects. However, ASReml remains the best practical choice for the serious animal breeder

Extinction times in the subcritical stochastic SIS logistic epidemic

Many real epidemics of an infectious disease are not straightforwardly super- or sub-critical, and the understanding of epidemic models that exhibit such complexity has been identified as a priority for theoretical work. We provide insights into the near-critical regime by considering the stochastic SIS logistic epidemic, a well-known birth-and-death chain used to model the spread of an epidemic within a population of a given size $N$. We study the behaviour of the process as the population size $N$ tends to infinity. Our results cover the entire subcritical regime, including the "barely subcritical" regime, where the recovery rate exceeds the infection rate by an amount that tends to 0 as $N \to \infty$ but more slowly than $N^{-1/2}$. We derive precise asymptotics for the distribution of the extinction time and the total number of cases throughout the subcritical regime, give a detailed description of the course of the epidemic, and compare to numerical results for a range of parameter values. We hypothesise that features of the course of the epidemic will be seen in a wide class of other epidemic models, and we use real data to provide some tentative and preliminary support for this theory.Comment: Revised; 34 pages; 6 figure

The case for home based telehealth in pediatric palliative care: a systematic review

Background: Over the last decade technology has rapidly changed the ability to provide home telehealth services. At the same time, pediatric palliative care has developed as a small, but distinct speciality. Understanding the experiences of providing home telehealth services in pediatric palliative care is therefore important

Monitoring symptoms at home: What methods would cancer patients be comfortable using?

PURPOSE: This study aimed to determine which methods of remote symptom assessment cancer outpatients would be comfortable using, including those involving information technology, and whether this varied with age and gender. METHODS: A questionnaire survey of 477 outpatients attending the Edinburgh Cancer Centre in Edinburgh, UK. RESULTS: Most patients reported that they would not feel comfortable using methods involving technology such as a secure website, email, mobile phone text message, or a computer voice on the telephone but that they would be more comfortable using more traditional methods such as a paper questionnaire, speaking to a nurse on the telephone, or giving information in person. CONCLUSIONS: The uptake of new, potentially cost-effective technology-based methods of monitoring patients' symptoms at home might be limited by patients' initial discomfort with the idea of using them. It will be important to develop methods of addressing this potential barrier (such as detailed explanation and supervised practice) if these methods are to be successfully implemented

Development and testing of an online community care platform for frail older adults in the Netherlands: a user-centred design

Background Recent transitions in long-term care in the Netherlands have major consequences for community-dwelling older adults. A new paradigm expects them to manage and arrange their own care and support as much as possible. Technology can support this shift. A study has been conducted to explore the needs of community-dwelling frail older adults with regard to an online platform. An existing platform was subsequently modified, based upon these needs, resulting in an online community care platform (OCC-platform) comprising of care, health, and communication functions. The purpose of this platform was to support frail older adults in their independence and functioning, by stimulating self-care and providing reliable information, products and services. Methods The study used a User-Centred Design. The development processes involved the following steps: Step 1) Identification of the User Requirements. To assess the user requirements, direct observations (N = 3) and interviews (N = 14) were performed. Step 2) Modification of an Existing Online Platform. Based upon Step 1, available online platforms were explored to determine whether an existing useful product was available. Two companies collaborated in modifying such a platform; Step 3) Testing the Modified Platform. A total of 73 older adults were invited to test a prototype of the OCC-platform during 6 months, which comprised of two phases: (1) a training phase; and (2) a testing phase. Results An iterative process of modifications resulted in an interactive software concept on a Standard PC, containing 11 Functions. The Functions of ‘contacts’, ‘services’ and ‘messaging’, were by far, the most frequently used. The use was at its highest during the first 2 weeks of the testing and then its use steadily declined. The vast majority of the subjects (94%) were positive about the usability of the platform. Only a minority of the subjects (27%) indicated that the platform had added value for them. Conclusion The overall prospect was that an OCC-platform can contribute to the social participation and the self-management competencies of frail older adults, together with their social cohesion in the community. In order to validate these prospects, further research is needed on the characteristics and the impact of online platforms

Point of Care Nucleic Acid Testing for SARS-CoV-2 in Hospitalized Patients: A Clinical Validation Trial and Implementation Study

There is an urgent need for rapid SARS-CoV-2 testing in hospitals to limit nosocomial spread. We report an evaluation of point of care (POC) nucleic acid amplification testing (NAAT) in 149 participants with parallel combined nasal and throat swabbing for POC versus standard lab RT-PCR testing. Median time to result is 2.6 (IQR 2.3–4.8) versus 26.4 h (IQR 21.4–31.4, p < 0.001), with 32 (21.5%) positive and 117 (78.5%) negative. Cohen’s κ correlation between tests is 0.96 (95% CI 0.91–1.00). When comparing nearly 1,000 tests pre- and post-implementation, the median time to definitive bed placement from admission is 23.4 (8.6-41.9) versus 17.1 h (9.0–28.8), p = 0.02. Mean length of stay on COVID-19 “holding” wards is 58.5 versus 29.9 h (p < 0.001). POC testing increases isolation room availability, avoids bed closures, allows discharge to care homes, and expedites access to hospital procedures. POC testing could mitigate the impact of COVID-19 on hospital systems