Scenario Tree Modeling to Analyze the Probability of Classical Swine Fever Virus Introduction into Member States of the European Union

The introduction of classical swine fever virus (CSFV) into a country free of disease without vaccination may have huge consequences in terms of both disease spread and economic losses. More quantitative insight into the main factors determining the probability of CSFV introduction (PCSFV) is needed to optimally use resources for the prevention of CSFV introduction. For this purpose a spreadsheet model was constructed that calculates the annual PCSFV into member states of the European Union (EU). The scenario pathway approach was used as most probabilities in the model are very small. Probability distributions were used to take into account inherent variability of input parameters. The model contained pathways of CSFV introduction including the import of pigs and pork products, returning livestock trucks, and contacts with wild boar. All EU member states were included as possible sources of CSFV. Default results for the Netherlands showed a mean overall annual PCSFV of approximately 0.06, indicating that the Netherlands can expect CSFV introduction on average once every 18 years from the pathways and countries included in the model. Almost 65% of this probability could be attributed to the pathway of returning livestock trucks. The most likely sources of CSFV introduction were Germany, Belgium, and the United Kingdom. Although the calculated probabilities were rather low when compared with expert estimates and recent history, the most likely causes of CSFV introduction indicated by the model were considered to be realistic. It was therefore concluded that the model is a useful tool to structure and analyze information for decision making concerning the prevention of CSFV introduction.     

Marital stability throughout the child-rearing years

Although there is evidence that the number and ages of children influence marital stability, studies have not systematically tracked the risk of marital disruption throughout the child-rearing years. This study uses marital and fertility histories from the June 1985 Current Population Survey to examine this issue. Continuous-time regression models with ages and numbers of children as time-varying covariates are estimated. Net of controls for age at marriage, year of marriage, education, and marital duration, stability increases with family size up to the third child but starts to decline as family size reaches five or more children. Aging of children is disruptive until the youngest child reaches adulthood, after which marriages become much more stable. Arrival and aging of children is an important dynamic with strong implications for marital stability.     

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.     

The Visibility of Feminist Thought in Family Studies

We assessed feminist visibility in family journals by tallying the feminist content of articles in Journal of Marriage and Family, Journal of Family Issues, and Family Relations. There was an increase in feminist visibility from 1972 to 1992, at which point the growth of visibility stalled. From 1992 to 2002, almost 1 out of 4 articles appeared to be influenced, at least minimally, by feminist scholarship when including in our tally a measure of articles' mentioning of gender in its abstract or title without a detectable feminist perspective in the article. Only about 6% of articles, however, involved an explicit feminist analysis. We offer explanations for this apparent glass ceiling for feminist visibility and make suggestions for future research.     

Quantitative Risk Assessment of FMD Virus Transmission via Water

Foot-and-mouth disease (FMD) is a viral disease of domesticated and wild cloven-hoofed animals. FMD virus is known to spread by direct contact between infected and susceptible animals, by animal products such as meat and milk, by the airborne route, and mechanical transfer on people, wild animals, birds, and by vehicles. During the outbreak of 2001 in the Netherlands, milk from dairy cattle was illegally discharged into the sewerage as a consequence of transport prohibition. This may lead to contaminated discharges of biologically treated and raw sewage in surface water that is given to cattle to drink. The objective of the present study was to assess the probability of infecting dairy cows that were drinking FMD virus contaminated surface water due to illegal discharges of contaminated milk. So, the following data were collected from literature: FMD virus inactivation in aqueous environments, FMD virus concentrations in milk, dilution in sewage water, virus removal by sewage treatment, dilution in surface water, water consumption of cows, size of a herd in a meadow, and dose-response data for ingested FMD virus by cattle. In the case of 1.6 x 10(2) FMD virus per milliliter in milk and discharge of treated sewage in surface water, the probability of infecting a herd of cows was estimated to be 3.3 x 10(-7) to 8.5 x 10(-5), dependent on dilution in the receiving surface water. In the case of discharge of raw sewage, all probabilities of infection were 100 times higher. In the case of little dilution in small rivers, the high level of 8.5 x 10(-3) is reached. For 10(4) times higher FMD virus concentrations in milk, the probabilities of infecting a herd of cows are high in the case of discharge of treated sewage (3.3 x 10(-3) to 5.7 x 10(-1)) and very high in the case of discharge of raw sewage (0.28-1.0). It can be concluded that illegal and uncontrolled discharges of contaminated milk into the sewerage system may lead to high risks to other cattle farms at 6-50 km distance of the location of discharge within one day. This clearly underlines current measures that prohibit such discharges, and also asks for strict control. This risk assessment clearly demonstrated the potential significance of FMD virus transmission via water, and the results will be useful on an international scale, and could also serve as a basis for other FMD risk-assessment models.     

The failure of meta-analytic asymptotics for the seemingly efficient estimator of the common risk difference

We consider the case of a multicenter trial in which the center specific sample sizes are potentially small. Under homogeneity, the conventional procedure is to pool information using a weighted estimator where the weights used are inverse estimated center-specific variances. Whereas this procedure is efficient for conventional asymptotics (e. g. center-specific sample sizes become large, number of center fixed), it is commonly believed that the efficiency of this estimator holds true also for meta-analytic asymptotics (e.g. center-specific sample size bounded, potentially small, and number of centers large). In this contribution we demonstrate that this estimator fails to be efficient. In fact, it shows a persistent bias with increasing number of centers showing that it isnot meta-consistent. In addition, we show that the Cochran and Mantel-Haenszel weighted estimators are meta-consistent and, in more generality, provide conditions on the weights such that the associated weighted estimator is meta-consistent.     

Clinical gait and stepping performance measures in older adults

Problems with ambulation and mobility are frequent problems in older adults. Each year, about one in 100 older adults develops new severe mobility disability. Assessment of abnormal gait constitutes a major component of clinical practice and may lead to fall reduction. Clinicians can benefit from simple gait and mobility assessment tools to be used in busy clinical settings. This review focuses on gait and stepping performance measures that can be used by the busy clinician to assess gait, mobility performance, balance, and falls risk in the older adult.