Development and Consideration of Global Policies for Managing the Future Risks of Poliovirus Outbreaks: Insights and Lessons Learned Through Modeling

The success of the Global Polio Eradication Initiative promises to bring large benefits, including sustained improvements in quality of life (i.e., cases of paralytic disease and deaths avoided) and costs saved from cessation of vaccination. Obtaining and maintaining these benefits requires that policymakers manage the transition from the current massive use of oral poliovirus vaccine (OPV) to a world without OPV and free of the risks of potential future reintroductions of live polioviruses. This article describes the analytical journey that began in 2001 with a retrospective case study on polio risk management and led to development of dynamic integrated risk, economic, and decision analysis tools to inform global policies for managing the risks of polio. This analytical journey has provided several key insights and lessons learned that will be useful to future analysts involved in similar complex decision-making processes.     

The allocation of time to social and leisure activities as social indicators for the integration of aged ethnic minorities

One way in which a better understanding of social indicators to be employed in assessing the degree of social integration of aged ethnic minorities is to determine their time-use patterns for various daily activities. This paper reports on a research project undertaken in a planned community of La Villeneuve, France, which examines (a) the social context in which various activities took place, and (b) the duration and frequency of the activities. This was achieved through the combined techniques of time-budget analysis, social network mapping, and participant observations. Our data provides another dimension appropriate for social indicators research.     

Nonverbal behavior in families with adolescents

In fifty-three families, mothers, fathers and one adolescent were videotaped discussing two issues relevant to the adolescent's behavior: the aspects of their behavior they could change, and rules appropriate to life in the family. Family members later watched these videotapes and rated themselves and each other every 15 seconds on levels of perceived anxiety, involvement, strength and friend-liness. From these videotapes, each family member's behavior was also coded for the use of smiles, various face and head movements and gestures. Results revealed that adolescents looked frequently at both parents, but parents looked even more at each other and the adolescent. Adolescents smiled more than their parents, while mothers smiled and nodded their heads more than fathers. More nonverbal expresivity occurred in conversations between parents and daughters than between parents and sons, although these results were mainly due to the behavior of fathers with daughters. Ratings of involvement by parents were related to the adolescent's nonverbal behaviors, but other ratings were not. Mothers rated adolescents as more involved when they used more head up movements and nods. Fathers rated adolescents as more involved when they gazed and smiled more.     

Accounting for Both Random Errors and Systematic Errors in Uncertainty Propagation Analysis of Computer Models Involving Experimental Measurements with Monte Carlo Methods

A Monte Carlo method is presented to study the effect of systematic and random errors on computer models mainly dealing with experimental data. It is a common assumption in this type of models (linear and nonlinear regression, and nonregression computer models) involving experimental measurements that the error sources are mainly random and independent with no constant background errors (systematic errors). However, from comparisons of different experimental data sources evidence is often found of significant bias or calibration errors. The uncertainty analysis approach presented in this work is based on the analysis of cumulative probability distributions for output variables of the models involved taking into account the effect of both types of errors. The probability distributions are obtained by performing Monte Carlo simulation coupled with appropriate definitions for the random and systematic errors. The main objectives are to detect the error source with stochastic dominance on the uncertainty propagation and the combined effect on output variables of the models. The results from the case studies analyzed show that the approach is able to distinguish which error type has a more significant effect on the performance of the model. Also, it was found that systematic or calibration errors, if present, cannot be neglected in uncertainty analysis of models dependent on experimental measurements such as chemical and physical properties. The approach can be used to facilitate decision making in fields related to safety factors selection, modeling, experimental data measurement, and experimental design.     

Theoretical and research considerations of burnout

As in any new area of investigation, the study of the phenomenon of burnout contains much potential benefit, especially to workers in helping/service professions; and it contains sources of error which may delay or distort understandings that are sorely needed. This paper identifies and explains many pitfalls and sources of error in developing theory and research about burnout. After discussing the limitations of the current definitions of burnout, the authors explore the ramifications of the most well supported definition. Specific suggestions are made for further investigation, especially in the area of individual characteristics and their interaction with the burnout phenomenon. Finally, methodologies most likely to yield solid, usable information for practitioners are discussed.     

Interest rate policies and inflation in interdependent economies: Recent policy dilemmas

This paper examines Federal Reserve Board policies that are premised on a negative short-run association of interest rate movements and the rate of inflation. In particular, econometric evidence is provided, supporting the view that tighter monetary policy appears to raise inflation rates in the short run. Conversely, it is demonstrated that easier monetary policy does not necessarily raise inflation rates in the short run. In the case of uncoordinated monetary restrictiveness, interest rate competition among major countries can produce higher inflation and lower growth than was originally intended.