Posterior-based proposals for speeding up Markov chain Monte Carlo

Markov chain Monte Carlo (MCMC) is widely used for Bayesian inference in models of complex systems. Performance, however, is often unsatisfactory in models with many latent variables due to so-called poor mixing, necessitating development of application specific implementations. This paper introduces "posterior-based proposals" (PBPs), a new type of MCMC update applicable to a huge class of statistical models (whose conditional dependence structures are represented by directed acyclic graphs). PBPs generates large joint updates in parameter and latent variable space, whilst retaining good acceptance rates (typically 33%). Evaluation against other approaches (from standard Gibbs / random walk updates to state-of-the-art Hamiltonian and particle MCMC methods) was carried out for widely varying model types: an individual-based model for disease diagnostic test data, a financial stochastic volatility model, a mixed model used in statistical genetics and a population model used in ecology. Whilst different methods worked better or worse in different scenarios, PBPs were found to be either near to the fastest or significantly faster than the next best approach (by up to a factor of 10). PBPs therefore represent an additional general purpose technique that can be usefully applied in a wide variety of contexts.Comment: 54 pages, 11 figures, 2 table

Compatibility between the endoparasitoid Hyposoter didymator and the entomopathogenic fungus Metarhizium brunneum: A laboratory simulation for the simultaneous use to control Spodoptera littoralis

BACKGROUND The cotton leafworm, Spodoptera littoralis, is one of the most destructive pests in the Mediterranean basin, being predominantly controlled using synthetic chemical pesticides. Strain EAMa 01/58‐Su of the fungus Metarhizium brunneum and the parasitoid Hyposoter didymator are promising biological control agents for this pest. In this study, we assessed the compatibility between these two agents to control S. littoralis under joint attack scenarios. RESULTS Firstly, the direct and indirect effects of the fungus towards parasitoid adults were studied. The fungus significantly decreased life expectancy of the parasitoid (mortality=62.5%; mean lethal concentration=1.85×106 conidia ml‐1; average survival time=92.2h) when applied at high concentrations (108 conidia ml‐1), whereas it did not affect the reproductive potential of the parasitoid females during the three days after treatment. Secondly, the combinations between the two agents to control S. littoralis under different simultaneous use scenarios (inoculation of S. littoralis larvae with the fungus before being exposed to parasitoid females and vice versa) were investigated, with additive effect in all cases. A significant effect on fitness (preimaginal development time and reproductive potential) of the F1 parasitoid generation were detected. Moreover, parasitization significantly reduced the total haemocytes in S. littoralis haemolymph compared with the control, promoting fungal infection. Finally, parasitoids showed a significant preference for non‐inoculated S. littoralis larvae. CONCLUSIONS We demonstrated compatibility (additive effect) between fungus and parasitoid under different joint attack scenarios to control S. littoralis in laboratory conditions. However, this will be supported by our ongoing greenhouse and field studies

Revised estimates of influenza-associated excess mortality, United States, 1995 through 2005

<p>Abstract</p> <p>Background</p> <p>Excess mortality due to seasonal influenza is thought to be substantial. However, influenza may often not be recognized as cause of death. Imputation methods are therefore required to assess the public health impact of influenza. The purpose of this study was to obtain estimates of monthly excess mortality due to influenza that are based on an epidemiologically meaningful model.</p> <p>Methods and Results</p> <p>U.S. monthly all-cause mortality, 1995 through 2005, was hierarchically modeled as Poisson variable with a mean that linearly depends both on seasonal covariates and on influenza-certified mortality. It also allowed for overdispersion to account for extra variation that is not captured by the Poisson error. The coefficient associated with influenza-certified mortality was interpreted as ratio of total influenza mortality to influenza-certified mortality. Separate models were fitted for four age categories (<18, 18–49, 50–64, 65+). Bayesian parameter estimation was performed using Markov Chain Monte Carlo methods. For the eleven year study period, a total of 260,814 (95% CI: 201,011–290,556) deaths was attributed to influenza, corresponding to an annual average of 23,710, or 0.91% of all deaths.</p> <p>Conclusion</p> <p>Annual estimates for influenza mortality were highly variable from year to year, but they were systematically lower than previously published estimates. The excellent fit of our model with the data suggest validity of our estimates.</p

The Use of Twitter to Track Levels of Disease Activity and Public Concern in the U.S. during the Influenza A H1N1 Pandemic

Twitter is a free social networking and micro-blogging service that enables its millions of users to send and read each other's “tweets,” or short, 140-character messages. The service has more than 190 million registered users and processes about 55 million tweets per day. Useful information about news and geopolitical events lies embedded in the Twitter stream, which embodies, in the aggregate, Twitter users' perspectives and reactions to current events. By virtue of sheer volume, content embedded in the Twitter stream may be useful for tracking or even forecasting behavior if it can be extracted in an efficient manner. In this study, we examine the use of information embedded in the Twitter stream to (1) track rapidly-evolving public sentiment with respect to H1N1 or swine flu, and (2) track and measure actual disease activity. We also show that Twitter can be used as a measure of public interest or concern about health-related events. Our results show that estimates of influenza-like illness derived from Twitter chatter accurately track reported disease levels

Predictors of switching antipsychotic medications in the treatment of schizophrenia

<p>Abstract</p> <p>Background</p> <p>To identify patient characteristics and early changes in patients' clinical status that best predict subsequent switching of antipsychotic agents in the long-term treatment of schizophrenia.</p> <p>Methods</p> <p>This post-hoc analysis used data from a one-year randomized, open-label, multisite study of antipsychotics in the treatment of schizophrenia. The study protocol permitted switching of antipsychotics when clinically warranted after the first eight weeks. Baseline patient characteristics were assessed using standard psychiatric measures and reviews of medical records. The prediction model included baseline sociodemographics, comorbid psychiatric and non-psychiatric conditions, body weight, clinical and functional variables, as well as change scores on standard efficacy and tolerability measures during the first two weeks of treatment. Cox proportional hazards modeling was used to identify the best predictors of switching from the initially assigned antipsychotic medication.</p> <p>Results</p> <p>About one-third of patients (29.5%, 191/648) switched antipsychotics before the end of the one-year study. There were six variables identified as the best predictors of switching: lack of antipsychotic use in the prior year, pre-existing depression, female gender, lack of substance use disorder, worsening of akathisia (as measured by the Barnes Akathisia Scale), and worsening of symptoms of depression/anxiety (subscale score on the Positive and Negative Syndrome Scale) during the first two weeks of antipsychotic therapy.</p> <p>Conclusions</p> <p>Switching antipsychotics appears to be prevalent in the naturalistic treatment of schizophrenia and can be predicted by a small and distinct set of variables. Interestingly, worsening of anxiety and depressive symptoms and of akathisia following two weeks of treatment were among the more robust predictors of subsequent switching of antipsychotics.</p

Survey on schizophrenia treatment in Mexico: perception and antipsychotic prescription patterns

BACKGROUND: Since the introduction of antipsychotics, especially the so called atypicals, the treatment of schizophrenia has shown important improvements. At the present time, it is preferred to label clozapine and other antipsychotics sharing similar profiles as second-generation antipsychotics (SGAs). These medications have been proposed by some experts as a first line treatment for schizophrenia. It is critical to have reliable data about antipsychotic prescription in Mexico and to create management guidelines based on expert meetings and not only on studies carried out by the pharmaceutical industry. Only this approach will help to make the right decisions for the treatment of schizophrenia. METHODS: A translated version of Rabinowitz's survey was used to evaluate antipsychotic prescription preferences and patterns in Mexican psychiatrists. The survey questionnaire was sent by mail to 200 psychiatrists from public institutions and private practice in Mexico City and Guadalajara, Mexico. RESULTS: Recommendations for antipsychotics daily doses at different stages of the treatment of schizophrenia varied widely. Haloperidol was considered as the first choice for the treatment of positive symptoms. On the contrary, risperidone was the first option for negative symptoms. For a patient with a high susceptibility for developing extrapyramidal symptoms (EPS), risperidone was the first choice. It was also considered that SGAs had advantages over typical antipsychotics in the management of negative symptoms, cognitive impairment and fewer EPS. Besides, there was a clear tendency for prescribing typical antipsychotics at higher doses than recommended and inadequate doses for the atypical ones. CONCLUSIONS: Some of the obstacles for the prescription of SGAs include their high cost, deficient knowledge about their indications and dosage, the perception of their being less efficient for the treatment of positive symptoms and the resistance of some Mexican physicians to change their prescription pattern. It is necessary to reach a consensus, in order to establish and standardize the treatment of schizophrenia, based on the information reported in clinical trials and prevailing economic conditions in Mexico

A core outcome set for evaluating self-management interventions in people with comorbid diabetes and severe mental illness : study protocol for a modified Delphi study and systematic review

BACKGROUND: People with diabetes and comorbid severe mental illness (SMI) form a growing population at risk of increased mortality and morbidity compared to those with diabetes or SMI alone. There is increasing interest in interventions that target diabetes in SMI in order to help to improve physical health and reduce the associated health inequalities. However, there is a lack of consensus about which outcomes are important for this comorbid population, with trials differing in their focus on physical and mental health. A core outcome set, which includes outcomes across both conditions that are relevant to patients and other key stakeholders, is needed. METHODS: This study protocol describes methods to develop a core outcome set for use in effectiveness trials of self-management interventions for adults with comorbid type-2 diabetes and SMI. We will use a modified Delphi method to identify, rank, and agree core outcomes. This will comprise a two-round online survey and multistakeholder workshops involving patients and carers, health and social care professionals, health care commissioners, and other experts (e.g. academic researchers and third sector organisations). We will also select appropriate measurement tools for each outcome in the proposed core set and identify gaps in measures, where these exist. DISCUSSION: The proposed core outcome set will provide clear guidance about what outcomes should be measured, as a minimum, in trials of interventions for people with coexisting type-2 diabetes and SMI, and improve future synthesis of trial evidence in this area. We will also explore the challenges of using online Delphi methods for this hard-to-reach population, and examine differences in opinion about which outcomes matter to diverse stakeholder groups. TRIAL REGISTRATION: COMET registration: http://www.comet-initiative.org/studies/details/911 . Registered on 1 July 2016

A systematic review of the incidence of schizophrenia: the distribution of rates and the influence of sex, urbanicity, migrant status and methodology

BACKGROUND: Understanding variations in the incidence of schizophrenia is a crucial step in unravelling the aetiology of this group of disorders. The aims of this review are to systematically identify studies related to the incidence of schizophrenia, to describe the key features of these studies, and to explore the distribution of rates derived from these studies. METHODS: Studies with original data related to the incidence of schizophrenia (published 1965–2001) were identified via searching electronic databases, reviewing citations and writing to authors. These studies were divided into core studies, migrant studies, cohort studies and studies based on Other Special Groups. Between- and within-study filters were applied in order to identify discrete rates. Cumulative plots of these rates were made and these distributions were compared when the underlying rates were sorted according to sex, urbanicity, migrant status and various methodological features. RESULTS: We identified 100 core studies, 24 migrant studies, 23 cohort studies and 14 studies based on Other Special Groups. These studies, which were drawn from 33 countries, generated a total of 1,458 rates. Based on discrete core data for persons (55 studies and 170 rates), the distribution of rates was asymmetric and had a median value (10%–90% quantile) of 15.2 (7.7–43.0) per 100,000. The distribution of rates was significantly higher in males compared to females; the male/female rate ratio median (10%–90% quantile) was 1.40 (0.9–2.4). Those studies conducted in urban versus mixed urban-rural catchment areas generated significantly higher rate distributions. The distribution of rates in migrants was significantly higher compared to native-born; the migrant/native-born rate ratio median (10%–90% quantile) was 4.6 (1.0–12.8). Apart from the finding that older studies reported higher rates, other study features were not associated with significantly different rate distributions (e.g. overall quality, methods related to case finding, diagnostic confirmation and criteria, the use of age-standardization and age range). CONCLUSIONS: There is a wealth of data available on the incidence of schizophrenia. The width and skew of the rate distribution, and the significant impact of sex, urbanicity and migrant status on these distributions, indicate substantial variations in the incidence of schizophrenia