A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

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.     

The struggle for Via Bologna street market: crisis,racial denial and speaking back to power in Naples Italy

This paper is based on ethnographic research conducted with migrant and Italian street vendors in Naples, southern Italy, in 2012. It tells the story of Via Bologna market which was nearly closed down by the City Hall at the time. Naples is a city where issues of poverty and unemployment pre‐date and have been exacerbated by manifold narratives of crisis now unfolding across Europe regarding the economy, political legitimacy, security and migration. Street markets have always been an important and visible economic survival strategy for both Neapolitans and migrants there. This article shows how the Via Bologna street vendors appropriated and adapted discourses about crisis to form their own cosmopolitan social movement that halted the closure of the market. It argues that, in the age of globalized migration, the multilingual nature of such collective action is central to understanding social struggles that must be organized between marginalized groups of people divided by race, religion, politics and legal status. This, frequently ambiguous, transcultural solidarity speaks back against a mainstream post‐racial discourse – often articulated by the Neapolitan street vendors at the market – that would reduce the complexity of such collective action to questions of poverty and class struggle.     

Graduating Out of Poverty Across Generations: Unpacking Children’s Well‐being Trajectories in Burundi

Graduation model interventions represent a new wave of anti‐poverty programming that seeks to offer a sustainable pathway out of poverty. An expanding evidence base points towards positive economic outcomes at household level but little is known about impacts on child well‐being. This paper investigates children’s well‐being in Burundi during and after participation in a graduation model programme using a longitudinal mixed‐methods approach. The programme is found to improve child well‐being, particularly in relation to housing, food security and education. Covariate shocks undermine sustainability of effects but greater knowledge, experience and prioritisation of children’s needs contribute to harnessing improved outcomes.     

An Agent‐Based Model for Pathogen Persistence and Cross‐Contamination Dynamics in a Food Facility

We used an agent‐based modeling (ABM) framework and developed a mathematical model to explain the complex dynamics of microbial persistence and spread within a food facility and to aid risk managers in identifying effective mitigation options. The model explicitly considered personal hygiene practices by food handlers as well as their activities and simulated a spatially explicit dynamic system representing complex interaction patterns among food handlers, facility environment, and foods. To demonstrate the utility of the model in a decision‐making context, we created a hypothetical case study and used it to compare different risk mitigation strategies for reducing contamination and spread of Listeria monocytogenes in a food facility. Model results indicated that areas with no direct contact with foods (e.g., loading dock and restroom) can serve as contamination niches and recontaminate areas that have direct contact with food products. Furthermore, food handlers’ behaviors, including, for example, hygiene and sanitation practices, can impact the persistence of microbial contamination in the facility environment and the spread of contamination to prepared foods. Using this case study, we also demonstrated benefits of an ABM framework for addressing food safety in a complex system in which emergent system‐level responses are predicted using a bottom‐up approach that observes individual agents (e.g., food handlers) and their behaviors. Our model can be applied to a wide variety of pathogens, food commodities, and activity patterns to evaluate efficacy of food‐safety management practices and quantify contamination reductions associated with proposed mitigation strategies in food facilities.     

Agent‐Based Recovery Model for Seismic Resilience Evaluation of Electrified Communities

In this article, an agent‐based framework to quantify the seismic resilience of an electric power supply system (EPSS) and the community it serves is presented. Within the framework, the loss and restoration of the EPSS power generation and delivery capacity and of the power demand from the served community are used to assess the electric power deficit during the damage absorption and recovery processes. Damage to the components of the EPSS and of the community‐built environment is evaluated using the seismic fragility functions. The restoration of the community electric power demand is evaluated using the seismic recovery functions. However, the postearthquake EPSS recovery process is modeled using an agent‐based model with two agents, the EPSS Operator and the Community Administrator. The resilience of the EPSS–community system is quantified using direct, EPSS‐related, societal, and community‐related indicators. Parametric studies are carried out to quantify the influence of different seismic hazard scenarios, agent characteristics, and power dispatch strategies on the EPSS–community seismic resilience. The use of the agent‐based modeling framework enabled a rational formulation of the postearthquake recovery phase and highlighted the interaction between the EPSS and the community in the recovery process not quantified in resilience models developed to date. Furthermore, it shows that the resilience of different community sectors can be enhanced by different power dispatch strategies. The proposed agent‐based EPSS–community system resilience quantification framework can be used to develop better community and infrastructure system risk governance policies.     

Changes in the Factors Influencing Public Acceptance of Nuclear Power Generation in Japan Since the 2011 Fukushima Daiichi Nuclear Disaster

Public support for nuclear power generation has decreased in Japan since the Fukushima Daiichi nuclear accident in March 2011. This study examines how the factors influencing public acceptance of nuclear power changed after this event. The influence factors examined are perceived benefit, perceived risk, trust in the managing bodies, and pro‐environmental orientation (i.e., new ecological paradigm). This study is based on cross‐sectional data collected from two online nationwide surveys: one conducted in November 2009, before the nuclear accident, and the other in October 2011, after the accident. This study's target respondents were residents of Aomori, Miyagi, and Fukushima prefectures in the Tohoku region of Japan, as these areas were the epicenters of the Great East Japan Earthquake and the locations of nuclear power stations. After the accident, trust in the managing bodies was found to have a stronger influence on perceived risk, and pro‐environmental orientation was found to have a stronger influence on trust in the managing bodies; however, perceived benefit had a weaker positive influence on public acceptance. We also discuss the theoretical and practical implications of these findings.     

Reputation spillover effects from grant‐providing institutions

There is a broad academic discussion about the impact of funding grants from a foundation or a government department on individual support intentions toward the nonprofit organization receiving the grant. However, the role of the grant provider's reputation has frequently been overlooked. In this study, we experimentally tested whether there is a reputation spillover effect of a grant‐providing organization. Based on a real‐life example, we asked citizens to rate their willingness to donate to a nonprofit organization, and we experimentally manipulated the available information on funding sources. We test this for both a government department and a foundation as a grant provider. Our results suggest that not the act of receiving a grant, but the citizens' awareness about the funding organization—at least in the case of a foundation—has an impact on support intentions. In contrast, for a prominent government department as a grant provider, we did not find support for a reputation spillover effect.     

Transnational connections and anti‐colonial radicalism in the Royal Indian Navy mutiny, 1946

In this article, I explore the spatial politics of the Royal Indian Navy mutiny of 1946 and call for a more maritime sense of ‘the political’. The RIN only existed from 1934 to 1950; it became the Indian Navy after independence. Its mutiny in 1946, which was caused by a number of grievances from anticolonial nationalism to more mundane challenges about the standard of food, continues to be the dominant event in this history. Leela Gandhi (2014) used the RIN mutiny to challenge the binary distinction between elite and subaltern in much Indian historiography by depicting it as an ‘anti‐colonial counterpublic’, or space in which discourses other than the dominant nationalist framings of independence were mobilized. She also regards the mutiny as a potential example of inconsequential ethics in which, instead of worrying about its causes, the mutiny can be read as an experimental space in which democratic politics occurred, rather than one in which people were striving for a ‘successful’ outcome. I argue that, while there is much to be admired in Gandhi's reading of these events, she discounts the maritime nature of the RIN mutiny. In other words, she fails to acknowledge that travelling to different international locations allowed the sailors to learn about democracy and other ideas, which in turn influenced their beliefs about what the future of India, and the RIN, should look like. As a result, I argue for the need to explore in greater depth the important connections that exist between anti‐colonialism, democratic politics and the naval/maritime experience.     

Joint Modelling of Survival and Longitudinal Data with Informative Observation Times

In this paper, we consider the joint modelling of survival and longitudinal data with informative observation time points. The survival model and the longitudinal model are linked via random effects, for which no distribution assumption is required under our estimation approach. The estimator is shown to be consistent and asymptotically normal. The proposed estimator and its estimated covariance matrix can be easily calculated. Simulation studies and an application to a primary biliary cirrhosis study are also provided.