An EWMA chart for monitoring process mean

In the statistical process control literature, there exists several improved quality control charts based on cost-effective sampling schemes, including the ranked set sampling (RSS) and median RSS (MRSS). A generalized cost-effective RSS scheme has been recently introduced for efficiently estimating the population mean, namely varied L RSS (VLRSS). In this article, we propose a new exponentially weighted moving average (EWMA) control chart for monitoring the process mean using VLRSS, named the EWMA-VLRSS chart, under both perfect and imperfect rankings. The EWMA-VLRSS chart encompasses the existing EWMA charts based on RSS and MRSS (named the EWMA-RSS and EWMA-MRSS charts). We use extensive Monte Carlo simulations to compute the run length characteristics of the EWMA-VLRSS chart. The proposed chart is then compared with the existing EWMA charts. It is found that, with either perfect or imperfect rankings, the EWMA-VLRSS chart is more sensitive than the EWMA-RSS and EWMA-MRSS charts in detecting small to large shifts in the process mean. A real dataset is also used to explain the working of the EWMA-VLRSS chart.     

A new estimator of proportion with a linear function using data from two-decks randomized response model

A new estimator for estimating the proportion of a potentially sensitive attribute in survey sampling has been introduced by solving a linear equation. The proposed estimator has been compared with the estimator proposed by Odumade and Singh (2009) with equal protection to all of the respondents. The asymptotic properties of the proposed estimator are investigated through exact numerical illustrations for different choices of parameters. A non randomized response approach has been suggested. A scope for further research has also been pointed out.     

Response‐adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?

Response‐adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. In this paper, we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial. The most common cause of this phenomenon is changes in the characteristics of recruited patients—referred to as patient drift. This is a realistic concern for clinical trials in rare diseases due to their lengthly accrual rate. We compute the type I error inflation as a function of the time trend magnitude to determine in which contexts the problem is most exacerbated. We then assess the ability of different correction methods to preserve type I error in these contexts and their performance in terms of other operating characteristics, including patient benefit and power. We make recommendations as to which correction methods are most suitable in the rare disease context for several RAR rules, differentiating between the 2‐armed and the multi‐armed case. We further propose a RAR design for multi‐armed clinical trials, which is computationally efficient and robust to several time trends considered.     

Meningococcal serogroup B outbreak response University of Wisconsin-Madison

A meningococcal serogroup B (MenB) outbreak at a large public university prompted an emergency response to immunize undergraduates. Objective: To report on a successful meningococcal serogroup B (MenB) vaccine clinic response at a large public university. Methods: We assembled the team leaders to write this case report. Results: Activation of the emergency plan and points of dispensing required cooperation of many units on campus under the leadership of university health officials with support from Centers for Disease Control and Prevention, state division of public health and the city-county health department. Significant efforts to provide consistent messages to students and parents regarding the outbreak and the availability of the MenB vaccines were made. Volunteers were recruited to staff the clinics alongside university healthcare providers. Over 22,000 doses of vaccine were administered. Conclusion: We report our experience and lessons learned which may be helpful to universities in preventing and responding to disease outbreaks.     

考虑异质性行为的灾后应急物资动态调度优化

在以人道主义为本的应急救援活动中，不可忽视被救灾民和施救决策者们异质性行为的影响。一方面，将各灾民因救援物资需求未被及时满足而呈现的差异化心理痛苦度量成经济损失，并纳入应急救援调度的社会成本这一决策目标中；另一方面，在灾后物资调度决策中，关注具有异质性偏好的各应急决策者所展现出的不同救援态度。结合面向联合机会约束规划的动态供需平衡限制，最终构建一个考虑灾民和决策者们异质性行为的多阶段灾后救援物资分配和应急路径优化模型。采用2008年汶川地震为案例背景，应用遗传算法对模型求解和参数分析，将仿真结果与不考虑异质性行为的传统救援调度方案进行比较，得出一些结论为构建高效的应急救援体系提供有益参考。     

Building a Human Health Risk Assessment Ontology (RsO): A Proposed Framework

Over the last decade the health and environmental research communities have made significant progress in collecting and improving access to genomic, toxicology, exposure, health, and disease data useful to health risk assessment. One of the barriers to applying these growing volumes of information in fields such as risk assessment is the lack of informatics tools to organize, curate, and evaluate thousands of journal publications and hundreds of databases to provide new insights on relationships among exposure, hazard, and disease burden. Many fields are developing ontologies as a way of organizing and analyzing large amounts of complex information from multiple scientific disciplines. Ontologies include a vocabulary of terms and concepts with defined logical relationships to each other. Building from the recently published exposure ontology and other relevant health and environmental ontologies, this article proposes an ontology for health risk assessment (RsO) that provides a structural framework for organizing risk assessment information and methods. The RsO is anchored by eight major concepts that were either identified by exploratory curations of the risk literature or the exposure‐ontology working group as key for describing the risk assessment domain. These concepts are: (1) stressor, (2) receptor, (3) outcome, (4) exposure event, (5) dose‐response approach, (6) dose‐response metric, (7) uncertainty, and (8) measure of risk. We illustrate the utility of these concepts for the RsO with example curations of published risk assessments for ionizing radiation, arsenic in drinking water, and persistent pollutants in salmon.     

Overcoming the ‘tyranny of the urgent’: integrating gender into disease outbreak preparedness and response

ABSTRACT

This article contributes to discussions on the gender dimensions of disease outbreaks, and preparedness policies and responses, by providing a multi-level analysis of gender-related gaps, particularly illustrating how the failure to challenge gender assumptions and incorporate gender as a priority at the global level has national and local impacts. The implications of neglecting gender dynamics, as well as the potential of equity-based approaches to disease outbreak responses, is illustrated through a case study of the Social Enterprise Network for Development (SEND) Sierra Leone, a non-government organisation (NGO) based in Kailahun, during the Ebola outbreak.     

Socioeconomic status and the dynamics of preferences for income inequality in the United States, 1978–2016

Although considerable evidence indicates that public preferences for income inequality and redistribution vary across socioeconomic groups (i.e., occupation and income), much less is known about the temporal dynamics of these preferences. The purpose of this study is (a) to examine whether the attitudinal distance between managerial/professional workers and unskilled manual workers has changed (converged or diverged) over time and to (b) explore the reasons for and implications of the dynamics of preferences in the past several decades. Using data from the General Social Survey 1978–2016 (23 time‐points; N = 27,211), this study finds that the influence of occupational class has lost some of its significance in shaping public preferences for income inequality and that the declining effect of occupation can be explained in part by the attitudinal convergence between better‐ and less‐educated citizens. Findings suggest that proequality coalitions across educational boundaries play a remedial role in bridging the occupational divide over government redistribution in the United States.