A vaccination game based on public health actions and personal decisions

Susceptible-infective-removed (SIR) models are commonly used for representing the spread of contagious diseases. A SIR model can be described in terms of a probabilistic cellular automaton (PCA), where each individual (corresponding to a cell of the PCA lattice) is connected to others by a random network favoring local contacts. Here, this framework is employed for investigating the consequences of applying vaccine against the propagation of a contagious infection, by considering vaccination as a game, in the sense of game theory. In this game, the players are the government and the susceptible newborns. In order to maximize their own payoffs, the government attempts to reduce the costs for combating the epidemic, and the newborns may be vaccinated only when infective individuals are found in their neighborhoods and/or the government promotes an immunization program. As a consequence of these strategies supported by cost-benefit analysis and perceived risk, numerical simulations show that the disease is not fully eliminated and the government implements quasi-periodic vaccination campaigns. (C) 2011 Elsevier B.V. All rights reserved.

Who should wear mask against airborne infections? Altering the contact network for controlling the spread of contagious diseases

There are several ways of controlling the propagation of a contagious disease. For instance, to reduce the spreading of an airborne infection, individuals can be encouraged to remain in their homes and/or to wear face masks outside their domiciles. However, when a limited amount of masks is available, who should use them: the susceptible subjects, the infective persons or both populations? Here we employ susceptible-infective-recovered (SIR) models described in terms of ordinary differential equations and probabilistic cellular automata in order to investigate how the deletion of links in the random complex network representing the social contacts among individuals affects the dynamics of a contagious disease. The inspiration for this study comes from recent discussions about the impact of measures usually recommended by health public organizations for preventing the propagation of the swine influenza A (H1N1) virus. Our answer to this question can be valid for other eco-epidemiological systems. (C) 2010 Elsevier BM. All rights reserved.

On the basic reproduction number and the topological properties of the contact network: An epidemiological study in mainly locally connected cellular automata

We study the spreading of contagious diseases in a population of constant size using susceptible-infective-recovered (SIR) models described in terms of ordinary differential equations (ODEs) and probabilistic cellular automata (PCA). In the PCA model, each individual (represented by a cell in the lattice) is mainly locally connected to others. We investigate how the topological properties of the random network representing contacts among individuals influence the transient behavior and the permanent regime of the epidemiological system described by ODE and PCA. Our main conclusions are: (1) the basic reproduction number (commonly called R(0)) related to a disease propagation in a population cannot be uniquely determined from some features of transient behavior of the infective group; (2) R(0) cannot be associated to a unique combination of clustering coefficient and average shortest path length characterizing the contact network. We discuss how these results can embarrass the specification of control strategies for combating disease propagations. (C) 2009 Elsevier B.V. All rights reserved.

Economic design of an X chart for short-run production

The aim of this paper is to present an economical design of an X chart for a short-run production. The process mean starts equal to mu(0) (in-control, State I) and in a random time it shifts to mu(1) > mu(0) (out-of-control, State II). The monitoring procedure consists of inspecting a single item at every m produced ones. If the measurement of the quality characteristic does not meet the control limits, the process is stopped, adjusted, and additional (r - 1) items are inspected retrospectively. The probabilistic model was developed considering only shifts in the process mean. A direct search technique is applied to find the optimum parameters which minimizes the expected cost function. Numerical examples illustrate the proposed procedure. (C) 2009 Elsevier B.V. All rights reserved.

Expokit: A software package for computing matrix exponentials

Expokit provides a set of routines aimed at computing matrix exponentials. More precisely, it computes either a small matrix exponential in full, the action of a large sparse matrix exponential on an operand vector, or the solution of a system of linear ODEs with constant inhomogeneity. The backbone of the sparse routines consists of matrix-free Krylov subspace projection methods (Arnoldi and Lanczos processes), and that is why the toolkit is capable of coping with sparse matrices of large dimension. The software handles real and complex matrices and provides specific routines for symmetric and Hermitian matrices. The computation of matrix exponentials is a numerical issue of critical importance in the area of Markov chains and furthermore, the computed solution is subject to probabilistic constraints. In addition to addressing general matrix exponentials, a distinct attention is assigned to the computation of transient states of Markov chains.

Risk premiums and benefit measures for generalized-expected-utility theories

Standard tools for the analysis of economic problems involving uncertainty, including risk premiums, certainty equivalents and the notions of absolute and relative risk aversion, are developed without making specific assumptions on functional form beyond the basic requirements of monotonicity, transitivity, continuity, and the presumption that individuals prefer certainty to risk. Individuals are not required to display probabilistic sophistication. The approach relies on the distance and benefit functions to characterize preferences relative to a given state-contingent vector of outcomes. The distance and benefit functions are used to derive absolute and relative risk premiums and to characterize preferences exhibiting constant absolute risk aversion (CARA) and constant relative risk aversion (CRRA). A generalization of the notion of Schur-concavity is presented. If preferences are generalized Schur concave, the absolute and relative risk premiums are generalized Schur convex, and the certainty equivalents are generalized Schur concave.

Minimum-order stable recursive filter design via the genetic algorithm approach

In this paper, the minimum-order stable recursive filter design problem is proposed and investigated. This problem is playing an important role in pipeline implementation sin signal processing. Here, the existence of a high-order stable recursive filter is proved theoretically, in which the upper bound for the highest order of stable filters is given. Then the minimum-order stable linear predictor is obtained via solving an optimization problem. In this paper, the popular genetic algorithm approach is adopted since it is a heuristic probabilistic optimization technique and has been widely used in engineering designs. Finally, an illustrative example is sued to show the effectiveness of the proposed algorithm.

Does management accounting play role in planning process?

This study examines the relationship between management accounting and planning profiles in Brazilian companies. The main goal is to understand the consequences of not including a fully structured management accounting scheme in the planning process. The authors conducted a field research among medium and large-sized companies, using a probabilistic sample from a population of 2281 companies. Using analytic hierarchy process (AHP) and statistical cluster analysis, the authors grouped the entities` strategic budget planning processes into five profiles, after which the authors applied statistical tests to assess the five clusters. The study concludes that poor or fully implemented strategic and budget-planning processes relate to the management accounting profiles of the Brazilian organizations studied. (C) 2009 Elsevier Inc. All rights reserved.

Assessing cost-effectiveness in mental health: family interventions for schizophrenia and related conditions

Objective: Existing evidence suggests that family interventions can be effective in reducing relapse rates in schizophrenia and related conditions. Despite this, such interventions are not routinely delivered in Australian mental health services. The objective of the current study is to investigate the incremental cost-effectiveness ratios (ICERs) of introducing three types of family interventions, namely: behavioural family management (BFM); behavioural intervention for families (BIF); and multiple family groups (MFG) into current mental health services in Australia. Method: The ICER of each of the family interventions is assessed from a health sector perspective, including the government, persons with schizophrenia and their families/carers using a standardized methodology. A two-stage approach is taken to the assessment of benefit. The first stage involves a quantitative analysis based on disability-adjusted life years (DALYs) averted. The second stage involves application of 'second filter' criteria (including equity, strength of evidence, feasibility and acceptability to stakeholders) to results. The robustness of results is tested using multivariate probabilistic sensitivity analysis. Results: The most cost-effective intervention, in order of magnitude, is BIF (A$8000 per DALY averted), followed by MFG (A$21 000 per DALY averted) and lastly BFM (A$28 000 per DALY averted). The inclusion of time costs makes BFM more cost-effective than MFG. Variation of discount rate has no effect on conclusions. Conclusions: All three interventions are considered 'value-for-money' within an Australian context. This conclusion needs to be tempered against the methodological challenge of converting clinical outcomes into a generic economic outcome measure (DALY). Issues surrounding the feasibility of routinely implementing such interventions need to be addressed.

Estimating the potential refolding yield of recombinant proteins expressed as inclusion bodies

Recombinant protein production in bacteria is efficient except that insoluble inclusion bodies form when some gene sequences are expressed. Such proteins must undergo renaturation, which is an inefficient process due to protein aggregation on dilution from concentrated denaturant. In this study, the protein-protein interactions of eight distinct inclusion-body proteins are quantified, in different solution conditions, by measurement of protein second virial coefficients (SVCs). Protein solubility is shown to decrease as the SVC is reduced (i.e., as protein interactions become more attractive). Plots of SVC versus denaturant concentration demonstrate two clear groupings of proteins: a more aggregative group and a group having higher SVC and better solubility. A correlation of the measured SVC with protein molecular weight and hydropathicity, that is able to predict which group each of the eight proteins falls into, is presented. The inclusion of additives known to inhibit aggregation during renaturation improves solubility and increases the SVC of both protein groups. Furthermore, an estimate of maximum refolding yield (or solubility) using high-performance liquid chromatography was obtained for each protein tested, under different environmental conditions, enabling a relationship between yield and SVC to be demonstrated. Combined, the results enable an approximate estimation of the maximum refolding yield that is attainable for each of the eight proteins examined, under a selected chemical environment. Although the correlations must be tested with a far larger set of protein sequences, this work represents a significant move beyond empirical approaches for optimizing renaturation conditions. The approach moves toward the ideal of predicting maximum refolding yield using simple bioinformatic metrics that can be estimated from the gene sequence. Such a capability could potentially screen, in silico, those sequences suitable for expression in bacteria from those that must be expressed in more complex hosts. (C) 2004 Wiley Periodicals, Inc.

Numerical simulation of dendrite growth during solidification

A comprehensive probabilistic model for simulating dendrite morphology and investigating dendritic growth kinetics during solidification has been developed, based on a modified Cellular Automaton (mCA) for microscopic modeling of nucleation, growth of crystals and solute diffusion. The mCA model numerically calculated solute redistribution both in the solid and liquid phases, the curvature of dendrite tips and the growth anisotropy. This modeling takes account of thermal, curvature and solute diffusion effects. Therefore, it can simulate microstructure formation both on the scale of the dendrite tip length. This model was then applied for simulating dendritic solidification of an Al-7%Si alloy. Both directional and equiaxed dendritic growth has been performed to investigate the growth anisotropy and cooling rate on dendrite morphology. Furthermore, the competitive growth and selection of dendritic crystals have also investigated.

Breast cancer five-year survival in New South Wales women, 1972 to 1991

This study of breast cancer survival is based on analysis of five-year relative survival of 38 362 cases of invasive breast cancer in New South Wales (NSW) women, incident between 1972 and 1991, with follow-up to 1992, using data from the population-based NSW Central Cancer Registry. Survival was ascertained by matching the registry file of breast cancers against NSW death certificates from 1972 to 1992, mainly by automated probabilistic linkage. Absolute survival of cases was compared with expected survival of age- and period-matched NSW women. Proportional hazard regression analysis was used for examination of the effects on excess mortality of age, period of diagnosis and degree of spread at diagnosis. Relative survival at five years increased from 70 per cent in 1972-1976 to 77 per cent in 1987-1991. Survival improved during the 1970s and in the late 1980s. Regression analysis suggested that part of the improved survival in the late 1980s was due to lesser degree of spread at diagnosis, whereas the improved survival during the 1970s may have been due to treatment. Survival was better for those aged 40-49 years (RR = 0.86) and worse for those aged greater than or equal to 70 years (RR = 1.22) compared with the referent group (60-69 years). Excess mortality was much less for those with invasive localised disease than those with regional spread (RR = 3.1) or metastatic cancer (RR = 15.5) at diagnosis. For the most recent period (1987-1991), relative five-year survival was 90, 70 and 18 per cent, respectively, for the three degree-of-spread categories.

Assessment of factors that confound MRI and neuropathological correlation of human postmortem brain tissue

In spite of considerable technical advance in MRI techniques, the optical resolution of these methods are still limited. Consequently, the delineation of cytoarchitectonic fields based on probabilistic maps and brain volume changes, as well as small-scale changes seen in MRI scans need to be verified by neuronanatomical/neuropathological diagnostic tools. To attend the current interdisciplinary needs of the scientific community, brain banks have to broaden their scope in order to provide high quality tissue suitable for neuroimaging- neuropathology/anatomy correlation studies. The Brain Bank of the Brazilian Aging Brain Research Group (BBBABSG) of the University of Sao Paulo Medical School (USPMS) collaborates with researchers interested in neuroimaging-neuropathological correlation studies providing brains submitted to postmortem MRI in-situ. In this paper we describe and discuss the parameters established by the BBBABSG to select and to handle brains for fine-scale neuroimaging-neuropathological correlation studies, and to exclude inappropriate/unsuitable autopsy brains. We tried to assess the impact of the postmortem time and storage of the corpse on the quality of the MRI scans and to establish fixation protocols that are the most appropriate to these correlation studies. After investigation of a total of 36 brains, postmortem interval and low body temperature proved to be the main factors determining the quality of routine MRI protocols. Perfusion fixation of the brains after autopsy by mannitol 20% followed by formalin 20% was the best method for preserving the original brain shape and volume, and for allowing further routine and immunohistochemical staining. Taken to together, these parameters offer a methodological progress in screening and processing of human postmortem tissue in order to guarantee high quality material for unbiased correlation studies and to avoid expenditures by post-imaging analyses and histological processing of brain tissue.

Prevalence of cannabis use in Brazil: Data from the I Brazilian National Alcohol Survey (BNAS)

Aims: To estimate the prevalence of cannabis use in the last 12 months in the Brazilian population and to examine its association with individual and geographic characteristics. Design: Cross-sectional survey with a national probabilistic sample. Participants: 3006 individuals aged 14 to 65 years. Measurements: Questionnaire based on well established instruments, adapted to the Brazilian population. Findings: The 12-month prevalence of cannabis use was 2.1% (95%Cl 1.3-2.9). Male gender, better educational level, unemployment and living in the regions South and Southeast were independently associated with higher 12-month prevalence of cannabis use. Conclusion: While the prevalence of cannabis use in Brazil is lower than in many countries, the profile of those who are more likely to have used it is similar. Educational and prevention policies should be focused on specific population groups. (C) 2009 Elsevier Ltd. All rights reserved.

A practical approach to assess depression risk and to guide risk reduction strategies in later life

Background: Many factors have been associated with the onset and maintenance of depressive symptoms in later life, although this knowledge is yet to be translated into significant health gains for the population. This study gathered information about common modifiable and non-modifiable risk factors for depression with the aim of developing a practical probabilistic model of depression that can be used to guide risk reduction strategies. \Methods: A cross-sectional study was undertaken of 20,677 community-dwelling Australians aged 60 years or over in contact with their general practitioner during the preceding 12 months. Prevalent depression (minor or major) according to the Patient Health Questionnaire (PHQ-9) assessment was the main outcome of interest. Other measured exposures included self-reported age, gender, education, loss of mother or father before age 15 years, physical or sexual abuse before age 15 years, marital status, financial stress, social support, smoking and alcohol use, physical activity, obesity, diabetes, hypertension, and prevalent cardiovascular diseases, chronic respiratory diseases and cancer. Results: The mean age of participants was 71.7 +/- 7.6 years and 57.9% were women. Depression was present in 1665 (8.0%) of our subjects. Multivariate logistic regression showed depression was independently associated with age older than 75 years, childhood adverse experiences, adverse lifestyle practices (smoking, risk alcohol use, physical inactivity), intermediate health hazards (obesity, diabetes and hypertension), comorbid medical conditions (clinical history of coronary heart disease, stroke, asthma, chronic obstructive pulmonary disease, emphysema or cancers), and social or financial strain. We stratified the exposures to build a matrix that showed that the probability of depression increased progressively with the accumulation of risk factors, from less than 3% for those with no adverse factors to more than 80% for people reporting the maximum number of risk factors. Conclusions: Our probabilistic matrix can be used to estimate depression risk and to guide the introduction of risk reduction strategies. Future studies should now aim to clarify whether interventions designed to mitigate the impact of risk factors can change the prevalence and incidence of depression in later life.