The Socio‐Economic Determinants of HIV/AIDS Infection Rates in Lesotho,Malawi, Swaziland and Zimbabwe

Using data from the Demographic and Health Survey, this article analyses the relationship between HIV status and the socio‐economic and demographic characteristics of adults in Lesotho, Malawi, Swaziland and Zimbabwe. It constructs the risk profile of the average adult, computes the values of age, education and wealth where the estimated probability of infection assumes its highest value, and determines the percentage of adults for whom these three factors are positively correlated with that probability. It finds that in all four countries: (i) the probability of being HIV‐positive is higher for women than for men; (ii) the likelihood of infection is higher for urban than for rural residents; and (iii) there is an inverted‐U relationship between age and HIV status. Also that, unlike gender, rural/urban residence and age, the relationship between the probability of infection and wealth, education and marital status varies by country. The results provide support for country‐specific and more targeted HIV policies and programmes.     

Community Resilience and Decision Theory Challenges for Catastrophic Events

Extreme and catastrophic events pose challenges for normative models of risk management decision making. They invite development of new methods and principles to complement existing normative decision and risk analysis. Because such events are rare, it is difficult to learn about them from experience. They can prompt both too little concern before the fact, and too much after. Emotionally charged and vivid outcomes promote probability neglect and distort risk perceptions. Aversion to acting on uncertain probabilities saps precautionary action; moral hazard distorts incentives to take care; imperfect learning and social adaptation (e.g., herd‐following, group‐think) complicate forecasting and coordination of individual behaviors and undermine prediction, preparation, and insurance of catastrophic events. Such difficulties raise substantial challenges for normative decision theories prescribing how catastrophe risks should be managed. This article summarizes challenges for catastrophic hazards with uncertain or unpredictable frequencies and severities, hard‐to‐envision and incompletely described decision alternatives and consequences, and individual responses that influence each other. Conceptual models and examples clarify where and why new methods are needed to complement traditional normative decision theories for individuals and groups. For example, prospective and retrospective preferences for risk management alternatives may conflict; procedures for combining individual beliefs or preferences can produce collective decisions that no one favors; and individual choices or behaviors in preparing for possible disasters may have no equilibrium. Recent ideas for building “disaster‐resilient” communities can complement traditional normative decision theories, helping to meet the practical need for better ways to manage risks of extreme and catastrophic events.     

A Stochastic Model to Assess the Effect of Meat Inspection Practices on the Contamination of the Pig Carcasses

The objective of meat inspection is to promote animal and public health by preventing, detecting, and controlling hazards originating from animals. With the improvements of sanitary level in pig herds, the hazards profile has shifted and the inspection procedures no longer target major foodborne pathogens (i.e., not risk based). Additionally, carcass manipulations performed when searching for macroscopic lesions can lead to cross‐contamination. We therefore developed a stochastic model to quantitatively describe cross‐contamination when consecutive carcasses are submitted to classic inspection procedures. The microbial hazard used to illustrate the model was Salmonella, the data set was obtained from Brazilian slaughterhouses, and some simplifying assumptions were made. The model predicted that due to cross‐contamination during inspection, the prevalence of contaminated carcass surfaces increased from 1.2% to 95.7%, whereas the mean contamination on contaminated surfaces decreased from 1 logCFU/cm² to ?0.87 logCFU/cm², and the standard deviations decreased from 0.65 to 0.19. These results are explained by the fact that, due to carcass manipulations with hands, knives, and hooks, including the cutting of contaminated lymph nodes, Salmonella is transferred to previously uncontaminated carcasses, but in small quantities. These small quantities can easily go undetected during sampling. Sensitivity analyses gave insight into the model performance and showed that the touching and cutting of lymph nodes during inspection can be an important source of carcass contamination. The model can serve as a tool to support discussions on the modernization of pig carcass inspection.     

Incorporating Time‐Dose‐Response into Legionella Outbreak Models

A novel method was used to incorporate in vivo host–pathogen dynamics into a new robust outbreak model for legionellosis. Dose‐response and time‐dose‐response (TDR) models were generated for Legionella longbeachae exposure to mice via the intratracheal route using a maximum likelihood estimation approach. The best‐fit TDR model was then incorporated into two L. pneumophila outbreak models: an outbreak that occurred at a spa in Japan, and one that occurred in a Melbourne aquarium. The best‐fit TDR from the murine dosing study was the beta‐Poisson with exponential‐reciprocal dependency model, which had a minimized deviance of 32.9. This model was tested against other incubation distributions in the Japan outbreak, and performed consistently well, with reported deviances ranging from 32 to 35. In the case of the Melbourne outbreak, the exponential model with exponential dependency was tested against non‐time‐dependent distributions to explore the performance of the time‐dependent model with the lowest number of parameters. This model reported low minimized deviances around 8 for the Weibull, gamma, and lognormal exposure distribution cases. This work shows that the incorporation of a time factor into outbreak distributions provides models with acceptable fits that can provide insight into the in vivo dynamics of the host‐pathogen system.     

Daily Inhalation Rate and Time‐Activity/Location Pattern in Japanese Preschool Children

Lack of data on daily inhalation rate and activity of children has been an issue in health risk assessment of air pollutants. This study aimed to obtain the daily inhalation rate and intensity and frequency of physical activity in relation to the environment in Japanese preschool children. Children aged four–six years (n= 138) in the suburbs of Tokyo participated in this study, which involved three days' continuous monitoring of physical activity using a tri‐axial accelerometer and parent's completion of a time/location diary during daily life. The estimated three‐day mean daily inhalation rate (body temperature, pressure, saturated with water vapor) was 9.9 ± 1.6 m³/day (0.52 ± 0.09 m³/kg/day). The current daily inhalation rate value of 0.580 m³/kg/day proposed for use in health risk assessment in Japan is confirmed to be valid to calculate central value of inhaled dose of air pollutants in five‐ to six‐year‐old children. However, the 95th percentile daily inhalation rate of 0.83 m³/kg/day based on measurement for five‐year‐old children is recommended to be used to provide an upper bound estimate of exposure that ensure the protection of all five‐ to six‐year‐old children from the health risk of air pollutants. Children spent the majority of their time in sedentary and light level of physical activity (LPA) when indoors, while 85% of their time when outdoors was spent in LPA and moderate‐to‐vigorous physical activity. The results suggest the need to consider variability of minute respiratory ventilation rate according to the environment for more refined short‐term health risk assessment.     

The Box–Cox Transformation and Non‐Iterative Estimation Methods for Ordinal Log‐Linear Models

Recently Beh and Farver investigated and evaluated three non‐iterative procedures for estimating the linear‐by‐linear parameter of an ordinal log‐linear model. The study demonstrated that these non‐iterative techniques provide estimates that are, for most types of contingency tables, statistically indistinguishable from estimates from Newton's unidimensional algorithm. Here we show how two of these techniques are related using the Box–Cox transformation. We also show that by using this transformation, accurate non‐iterative estimates are achievable even when a contingency table contains sampling zeros.     

Child‐caregiver Attachment Representations in a Non‐Western Context: The Feasibility and Cultural Equivalence of Story Stems in Urban Ghana

Story stem measures are an increasingly popular method for assessing the attachment representations of young children, but little is known of their cross‐cultural applicability. This study aimed to characterise the attachment representations in 73 five‐ to eight‐year‐old children in urban Ghana, West Africa, using the Manchester Child Attachment Story Task (MCAST) to test its feasibility, psychometric characteristics and concurrent associations with caregiver‐ and teacher‐rated child behaviour, and to conduct a qualitative thematic analysis of methodological observations. Among the classifiable cases (92 percent), all attachment classifications were observed, yielding a higher rate of secure attachment than in European samples. Inter‐rater reliability, internal consistency, and internal structure were reasonable and largely similar to European studies, although one structural difference was the separation of ‘child assuagement of distress’ from other secure‐related items. MCAST narratives were associated with teacher‐ and caregiver‐rated hyperactivity, but internal consistency was low in most Strengths and Difficulties Questionnaire scales. Possible culturally‐sensitive explanations for our psychometric and qualitative findings are discussed. Overall, story stems are a promising tool for accessing attachment representations in non‐Western samples, although modifications are likely to improve cross‐cultural equivalence when applied to non‐Western cultures. Further investigation is needed to link MCAST outcomes to parenting and socio‐emotional development.     

Using In Vitro High‐Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high‐throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline‐based meta‐regression can be used to integrate data across multiple assay replicates to generate a concentration–response curve. We used this analysis to calculate an in vitro point of departure of 0.751 μM and risk‐specific in vitro concentrations of 0.29 μM and 0.28 μM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta‐regression, may allow risk assessors to identify points of departure and risk‐specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods.     

Women's participation in self‐help groups as a pathway to women's empowerment: A case of Nepal

Non‐governmental organizations (NGOs) and the government of Nepal have made some effort to reduce poverty in Nepal by creating women's affiliation groups, some of which are micro‐credit organizations. Using capabilities as defined by Amartya Sen (Development as freedom, Oxford University Press, New Delhi, 2000), which includes employment opportunities, women's ownership in productive resources such as land and/or homes, educational opportunities, and women's participation in decision‐making in the family, this study evaluated the extent to which women's ethnic group or caste affiliation affected a woman's likelihood of being empowered by participation in these groups. We analyzed a sample of 8,973 women which was taken from the 2011 Nepal Demographic and Health Survey. Previous research has demonstrated that participation in gender‐based groups is correlated with higher economic status. This study adds to the literature on women's affiliation groups by investigating the impact of structural factors, such as caste and ethnicity, on women's self‐help group participation (women's groups and credit groups).     

Global Governance,neoliberalism and national responses: The case of Bangladesh’s ready‐made garment (RMG) sector

This article on the ready‐made garment (RMG) sector of Bangladesh shows how over‐reliance on foreign capital for development financing and deregulated investment—a hallmark of neoliberal economic arrangements—undermines the incorporation of SDGs’ and INGOs’ equity principles, contributing to biased policy responses yielding unequal outcomes. The article cautions that while countries prioritize economic growth over social and environmental nourishment and continue to adopt neoliberal economic policies to promote economic growth, inequity is unavoidable, if not inevitable. Thus, the way forward may be to shift the focus of ‘development’ from the economy to society, to building ‘good societies’ where institutions and strategies, including those that contribute to economic growth, are organized such that these complement not compromise the evolution of such societies.