Containment of Polioviruses After Eradication and OPV Cessation: Characterizing Risks to Improve Management

The goal of the World Health Organization is to stop routine use of oral poliovirus vaccine shortly after interruption of wild poliovirus transmission. A key component of this goal is to minimize the risk of reintroduction by destruction of polioviruses except in an absolute minimum number of facilities that serve essential functions and implement effective containment. Effective containment begins with a complete facility risk assessment. This article focuses on characterizing the risks of exposure to polioviruses from the essential vaccine production, quality control, and international reference and research facilities that remain. We consider the potential exposure pathways that might lead to a poliovirus reintroduction, including para-occupational exposures and releases to the environment, and review the literature to provide available estimates and a qualitative assessment of containment risks. Minimizing the risk of poliovirus transmission from a poliovirus facility to increasingly susceptible communities is a crucial and ongoing effort requiring understanding and actively managing the potential exposure pathways.     

Multi-profile welfarism: A generalization

This paper characterizes welfarist social evaluation in a multi-profile setting where, in addition to multiple utility profiles, there may be more than one profile of non-welfare information. We prove a new version of the welfarism theorem in this alternative framework, and we demonstrate that adding a plausible and weak anonymity property to the welfarism axioms generates welfarist social-evaluation orderings that are anonymous.This is a revised version of our earlier paper “Welfarism with multiple non-welfare profiles.” We thank François Maniquet, Kotaro Suzumura, John Weymark, an editor and two referees for comments and discussions. The paper was presented at the International Symposium on Intergenerational Equity in Tokyo, December 2001 and at the Meeting of the Society for Social Choice and Welfare in Pasadena, July 2002. Financial support through a grant from the Social Sciences and Humanities Research Council of Canada is gratefully acknowledged.     

Dealing with selective dropout in clinical trials

Clinical trials in severely diseased populations often suffer from a high dropout rate that is related to the investigated target morbidity. These dropouts can bias estimates and treatment comparisons, particularly in the event of an imbalance. Methods to describe such selective dropout are presented that use the time in study distribution to generate so‐called population evolution charts. These charts show the development of a distribution of a covariate or the target morbidity measure as it changes as a result of the dropout process during the follow‐up time. The selectiveness of the dropout process with respect to a variable can be inferred from the change in its distribution. Different types of selective dropout are described with real data from several studies in metastatic bone disease, where marked effects can be seen. A general strategy to cope with selective dropout seems to be the inclusion of dropout events into the endpoint. Within a time‐to‐event analysis framework this simple approach can lead to valid conclusions and still retains conservative elements. Morbidity measures that are based on (recurrent) event counts react differently in the presence of selective dropout. They differ mainly in the way dropout is included. One simple measure achieves good performance under selective dropout by introducing a non‐specific penalty for premature study termination. The use of a prespecified scoring system to assign a weight for each works well. This simple and transparent approach performs well even in the presence of unbalanced selective dropout. Copyright © 2002 John Wiley & Sons, Ltd.     

Variable-population extensions of social aggregation theorems

This paper examines principles for social evaluation under uncertainty in environments with a variable population. In contrast to most of the literature, we employ a model that is formulated in terms of prospects rather than lotteries. Starting from a fixed-population result, a multi-profile variant of Harsanyi’s social aggregation theorem is extended to a variable-population environment. Two nested classes of population principles under uncertainty are characterized. Each is a variable-population extension of ex-ante utilitarianism. The results continue to apply if the probability distribution may vary, as long as probabilities are objectively known or agreed upon by all individuals and society.     

Optimal adaptive sequential designs for crossover bioequivalence studies

In prior works, this group demonstrated the feasibility of valid adaptive sequential designs for crossover bioequivalence studies. In this paper, we extend the prior work to optimize adaptive sequential designs over a range of geometric mean test/reference ratios (GMRs) of 70–143% within each of two ranges of intra‐subject coefficient of variation (10–30% and 30–55%). These designs also introduce a futility decision for stopping the study after the first stage if there is sufficiently low likelihood of meeting bioequivalence criteria if the second stage were completed, as well as an upper limit on total study size. The optimized designs exhibited substantially improved performance characteristics over our previous adaptive sequential designs. Even though the optimized designs avoided undue inflation of type I error and maintained power at 80%, their average sample sizes were similar to or less than those of conventional single stage designs. Copyright © 2015 John Wiley & Sons, Ltd.     

Measuring societal effects of transdisciplinary research projects: design and application of an evaluation method

Most Transdisciplinary Research (TdR) projects combine scientific research with the building of decision making capacity for the involved stakeholders. These projects usually deal with complex, societally relevant, real-world problems. This paper focuses on TdR projects, which integrate the knowledge of researchers and stakeholders in a collaborative transdisciplinary process through structured methods of mutual learning. Previous research on the evaluation of TdR has insufficiently explored the intended effects of transdisciplinary processes on the real world (societal effects). We developed an evaluation framework for assessing the societal effects of transdisciplinary processes. Outputs (measured as procedural and product-related involvement of the stakeholders), impacts (intermediate effects connecting outputs and outcomes) and outcomes (enhanced decision making capacity) are distinguished as three types of societal effects. Our model links outputs and outcomes of transdisciplinary processes via the impacts using a mediating variables approach. We applied this model in an ex post evaluation of a transdisciplinary process. 84 out of 188 agents participated in a survey. The results show significant mediation effects of the two impacts "network building" and "transformation knowledge". These results indicate an influence of a transdisciplinary process on the decision making capacity of stakeholders, especially through social network building and the generation of knowledge relevant for action.