Prediction of infectious disease epidemics via weighted density ensembles

Accurate and reliable predictions of infectious disease dynamics can be valuable to public health organizations that plan interventions to decrease or prevent disease transmission. A great variety of models have been developed for this task, using different model structures, covariates, and targets for prediction. Experience has shown that the performance of these models varies; some tend to do better or worse in different seasons or at different points within a season. Ensemble methods combine multiple models to obtain a single prediction that leverages the strengths of each model. We considered a range of ensemble methods that each form a predictive density for a target of interest as a weighted sum of the predictive densities from component models. In the simplest case, equal weight is assigned to each component model; in the most complex case, the weights vary with the region, prediction target, week of the season when the predictions are made, a measure of component model uncertainty, and recent observations of disease incidence. We applied these methods to predict measures of influenza season timing and severity in the United States, both at the national and regional levels, using three component models. We trained the models on retrospective predictions from 14 seasons (1997/1998 - 2010/2011) and evaluated each model's prospective, out-of-sample performance in the five subsequent influenza seasons. In this test phase, the ensemble methods showed overall performance that was similar to the best of the component models, but offered more consistent performance across seasons than the component models. Ensemble methods offer the potential to deliver more reliable predictions to public health decision makers.Comment: 20 pages, 6 figure

Narrative-based computational modelling of the Gp130/JAK/STAT signalling pathway.

BACKGROUND: Appropriately formulated quantitative computational models can support researchers in understanding the dynamic behaviour of biological pathways and support hypothesis formulation and selection by "in silico" experimentation. An obstacle to widespread adoption of this approach is the requirement to formulate a biological pathway as machine executable computer code. We have recently proposed a novel, biologically intuitive, narrative-style modelling language for biologists to formulate the pathway which is then automatically translated into an executable format and is, thus, usable for analysis via existing simulation techniques. RESULTS: Here we use a high-level narrative language in designing a computational model of the gp130/JAK/STAT signalling pathway and show that the model reproduces the dynamic behaviour of the pathway derived by biological observation. We then "experiment" on the model by simulation and sensitivity analysis to define those parameters which dominate the dynamic behaviour of the pathway. The model predicts that nuclear compartmentalisation and phosphorylation status of STAT are key determinants of the pathway and that alternative mechanisms of signal attenuation exert their influence on different timescales. CONCLUSION: The described narrative model of the gp130/JAK/STAT pathway represents an interesting case study showing how, by using this approach, researchers can model biological systems without explicitly dealing with formal notations and mathematical expressions (typically used for biochemical modelling), nevertheless being able to obtain simulation and analysis results. We present the model and the sensitivity analysis results we have obtained, that allow us to identify the parameters which are most sensitive to perturbations. The results, which are shown to be in agreement with existing mathematical models of the gp130/JAK/STAT pathway, serve us as a form of validation of the model and of the approach itself

The Effect of Cluster Size Variability on Statistical Power in Cluster-Randomized Trials

The frequency of cluster-randomized trials (CRTs) in peer-reviewed literature has increased exponentially over the past two decades. CRTs are a valuable tool for studying interventions that cannot be effectively implemented or randomized at the individual level. However, some aspects of the design and analysis of data from CRTs are more complex than those for individually randomized controlled trials. One of the key components to designing a successful CRT is calculating the proper sample size (i.e. number of clusters) needed to attain an acceptable level of statistical power. In order to do this, a researcher must make assumptions about the value of several variables, including a fixed mean cluster size. In practice, cluster size can often vary dramatically. Few studies account for the effect of cluster size variation when assessing the statistical power for a given trial. We conducted a simulation study to investigate how the statistical power of CRTs changes with variable cluster sizes. In general, we observed that increases in cluster size variability lead to a decrease in power

An exploration of how young people and parents use online support in the context of living with cystic fibrosis

Background: There is increasing recognition of the Internet's potential role in providing information and support for people living with long-term conditions. However, how young people and parents use online forms of self-care support in the context of living with childhood chronic illness has been under-researched. Objective: To explore how online peer support is used by young people and parents to support self-care in relation to cystic fibrosis (CF). Setting and participants: Online forum for young people and parents based on a CF charity website. A total of 279 individuals participated in the forum during the study. Design: An online ethnographical approach, involving observing, downloading and analysing discussion group postings. All postings made over a random 4-month period were included (151 discussion threads). Results: The online setting enabled a physically disconnected group to connect and create a safe space to collectively share experiences and receive support to manage and live with cystic fibrosis. Participants exchanged experientially derived advice and views on how to manage treatments, emotions, relationships, identity and support from services. While parents sought information and support on managing specific therapies/services and ways of maintaining their child's health, the information and support young people desired appeared to be more directed at how to 'fit' CF into their everyday lives. Discussion and conclusions: Online support groups appear to supplement professional support in relation to self-management. They enable young people and parents to share experiences, feelings and strategies for living with long-term conditions with peers and develop the expertise to empower them in interactions with health-care professionals

Temperature and leaf nitrogen affect performance of plant species at range overlap

Plant growth and survival near range limits are likely sensitive to small changes in environmental conditions. Warming temperatures are causing range shifts and thus changes in species composition within range-edge ecotones; however, it is often not clear how temperature alters performance. Through an observational field study, we assessed temperature and nitrogen effects on survival and growth of co-occurring temperate (Acer saccharum) and boreal (Abies balsamea) saplings across their overlapping range limits in the Great Lakes region, USA. Across sampled ranges of soil texture, soil pH, and precipitation, it appears that temperature affects leaf nitrogen for A. saccharum near its northern range limit (R2=0.64), whereas there was no significant leaf N ~ temperature relationship for A. balsamea. Higher A. saccharum leaf N at warm sites was associated with increased survival and growth. Abies balsamea survival and growth were best modeled with summer temperature (negative relationship); performance at warm sites depended upon light availability, suggesting the shade-tolerance of this species near its southern range limits may be mediated by temperature. The ranges of these two tree species overlap across millions of hectares, and temperature and temperature-mediated nitrogen likely play important roles in their relative performance