Validation and Application of Models to Predict Facemask Influenza Contamination in Healthcare Settings

Facemasks are part of the hierarchy of interventions used to reduce the transmission of respiratory pathogens by providing a barrier. Two types of facemasks used by healthcare workers are N95 filtering facepiece respirators (FFRs) and surgical masks (SMs). These can become contaminated with respiratory pathogens during use, thus serving as potential sources for transmission. However, because of the lack of field studies, the hazard associated with pathogen‐exposed facemasks is unknown. A mathematical model was used to calculate the potential influenza contamination of facemasks from aerosol sources in various exposure scenarios. The aerosol model was validated with data from previous laboratory studies using facemasks mounted on headforms in a simulated healthcare room. The model was then used to estimate facemask contamination levels in three scenarios generated with input parameters from the literature. A second model estimated facemask contamination from a cough. It was determined that contamination levels from a single cough (≈19 viruses) were much less than likely levels from aerosols (4,473 viruses on FFRs and 3,476 viruses on SMs). For aerosol contamination, a range of input values from the literature resulted in wide variation in estimated facemask contamination levels (13–202,549 viruses), depending on the values selected. Overall, these models and estimates for facemask contamination levels can be used to inform infection control practice and research related to the development of better facemasks, to characterize airborne contamination levels, and to assist in assessment of risk from reaerosolization and fomite transfer because of handling and reuse of contaminated facemasks.     

Improving predictive accuracy of logistic regression model using ranked set samples

Logistic regression is often confronted with separation of likelihood problem, especially with unbalanced success–failure distribution. We propose to address this issue by drawing a ranked set sample (RSS). Simulation studies illustrated the advantages of logistic regression models fitted with RSS samples with small sample size regardless of the distribution of the binary response. As sample size increases, RSS eventually becomes comparable to SRS, but still has the advantage over SRS in mitigating the problem of separation of likelihood. Even in the presence of ranking errors, models from RSS samples yield higher predictive ability than its SRS counterpart.     

The Organization of Corrective Demonstrations Using Embodied Action in Sports Coaching Feedback

Focusing on video recordings of coaching sessions in the context of basketball and powerlifting, this paper investigates how the sports coaching process unfolds as situated interactions. The work of sports coaching is pervasively oriented toward teaching athletes the correct forms of motion and play. Correction then is one of the central constitutive practices of sports training sessions. In this paper, we draw on a collection of instances of correction demonstrations from powerlifting and basketball to describe their order. We demonstrate the three phases of these demonstrations: arranging bodies and gaze for visual access, presenting the error visually, and proposing a correction with an embodied demonstration. Findings underscore the management of shared visual access in multi‐party correction demonstrations. In demonstrating how multiple bodies may be involved in embodied reenactments of a correctable problem, and demonstrating that it is seeing an error, more than reenactment per se, that is necessary for correction activities, the study extends existing understandings both of sports coaching processes and of instructional correction in embodied activities.     

Modeling the welfare impacts of agricultural policies in developing countries

This paper presents a new model incorporating features of developing country agriculture likely to shape the welfare outcomes of alternative agricultural policies. The model features heterogeneous households linked through markets in a rural economy-wide structure, with endogenous market participation for farmers facing transactions costs. We use it to simulate the impacts on rural welfare of market price supports, production subsidies, input subsidies, and the removal of transaction costs. Applications to six countries demonstrate the diversity of potential impacts, exhibit some systemic differences compared with impacts in developed countries, and identify specific circumstances under which market interventions may be only slightly less efficient than direct payments at transferring incomes to rural households.     

Marginal Structural Models: An Application to Incarceration and Marriage During Young Adulthood

Advanced methods for panel data analysis are commonly used in research on family life and relationships, but the fundamental issue of simultaneous time‐dependent confounding and mediation has received little attention. In this article the authors introduce inverse‐probability‐weighted estimation of marginal structural models, an approach to causal analysis that (unlike conventional regression modeling) appropriately adjusts for confounding variables on the causal pathway linking the treatment with the outcome. They discuss the need for marginal structural models in social science research and describe their estimation in detail. Substantively, the authors contribute to the ongoing debate on the effects of incarceration on marriage by applying a marginal structural model approach to panel data from the National Longitudinal Survey of Youth 1997 (N = 4,781). In line with the increasing evidence on the collateral consequences of contact with the criminal justice system, the authors find that incarceration is associated with reduced chances of entering marriage.     

A New Markov Binomial Distribution

In this article, we introduce a two-state homogeneous Markov chain and define a geometric distribution related to this Markov chain. We define also the negative binomial distribution similar to the classical case and call it NB related to interrupted Markov chain. The new binomial distribution is related to the interrupted Markov chain. Some characterization properties of the geometric distributions are given. Recursion formulas and probability mass functions for the NB distribution and the new binomial distribution are derived.     

Supply Chain Vulnerability Analysis Using Scenario‐Based Input‐Output Modeling: Application to Port Operations

Disruptive events such as natural disasters, loss or reduction of resources, work stoppages, and emergent conditions have potential to propagate economic losses across trade networks. In particular, disruptions to the operation of container port activity can be detrimental for international trade and commerce. Risk assessment should anticipate the impact of port operation disruptions with consideration of how priorities change due to uncertain scenarios and guide investments that are effective and feasible for implementation. Priorities for protective measures and continuity of operations planning must consider the economic impact of such disruptions across a variety of scenarios. This article introduces new performance metrics to characterize resiliency in interdependency modeling and also integrates scenario‐based methods to measure economic sensitivity to sudden‐onset disruptions. The methods will be demonstrated on a U.S. port responsible for handling $36.1 billion of cargo annually. The methods will be useful to port management, private industry supply chain planning, and transportation infrastructure management.     

Inference of Seasonal Long‐memory Time Series with Measurement Error

We consider the Whittle likelihood estimation of seasonal autoregressive fractionally integrated moving‐average models in the presence of an additional measurement error and show that the spectral maximum Whittle likelihood estimator is asymptotically normal. We illustrate by simulation that ignoring measurement errors may result in incorrect inference. Hence, it is pertinent to test for the presence of measurement errors, which we do by developing a likelihood ratio (LR) test within the framework of Whittle likelihood. We derive the non‐standard asymptotic null distribution of this LR test and the limiting distribution of LR test under a sequence of local alternatives. Because in practice, we do not know the order of the seasonal autoregressive fractionally integrated moving‐average model, we consider three modifications of the LR test that takes model uncertainty into account. We study the finite sample properties of the size and the power of the LR test and its modifications. The efficacy of the proposed approach is illustrated by a real‐life example.     

Use of jump process to model mobility in massive multiplayer on-line games

This paper proposes a methodology to model the mobility of characters in Massively Multiplayer On-line (MMO) Games. We propose to model the mobility of characters in the map of an MMO game as a jump process using two approaches to model the times spent in the states of the process: parametric and non-parametric. Furthermore, a simulator for the mobility is presented. We analyze geographic position data of the characters in the map of the game World of Warcraft and compare the observed and simulated data. The proposed methodology and the simulator can be used to optimize computing load allocation of servers, which is extremely important for game performance, service quality and cost.