Human Salmonellosis: Estimation of Dose-Illness from Outbreak Data

The quantification of the relationship between the amount of microbial organisms ingested and a specific outcome such as infection, illness, or mortality is a key aspect of quantitative risk assessment. A main problem in determining such dose-response models is the availability of appropriate data. Human feeding trials have been criticized because only young healthy volunteers are selected to participate and low doses, as often occurring in real life, are typically not considered. Epidemiological outbreak data are considered to be more valuable, but are more subject to data uncertainty. In this article, we model the dose-illness relationship based on data of 20 Salmonella outbreaks, as discussed by the World Health Organization. In particular, we model the dose-illness relationship using generalized linear mixed models and fractional polynomials of dose. The fractional polynomial models are modified to satisfy the properties of different types of dose-illness models as proposed by Teunis et al . Within these models, differences in host susceptibility (susceptible versus normal population) are modeled as fixed effects whereas differences in serovar type and food matrix are modeled as random effects. In addition, two bootstrap procedures are presented. A first procedure accounts for stochastic variability whereas a second procedure accounts for both stochastic variability and data uncertainty. The analyses indicate that the susceptible population has a higher probability of illness at low dose levels when the combination pathogen-food matrix is extremely virulent and at high dose levels when the combination is less virulent. Furthermore, the analyses suggest that immunity exists in the normal population but not in the susceptible population.     

Bilateral Donors' Efforts to Assess and Manage UN Agencies' Effectiveness: Seeking a Balance between Paris Principles and Domestic Accountability

Since the turn of the century, results orientation and performance measurement have become buzzwords in development aid. Bilateral donors are increasingly concerned about the effectiveness of core‐funded UN specialised agencies, funds and programmes, through which they channel a substantial part of their funds. While the logic for increased monitoring is clear, it is less evident how to assess this information for purposes of accountability, performance‐based funding and governance. This article describes the general evolution in this area and discusses two major initiatives to harmonise and align bilateral assessments, using case‐study material from three bilateral donors (Belgium, the Netherlands and the UK) with clearly diverging performance‐management cultures, and exploring the extent to which they rely upon joint and aligned initiatives.     

Trust in American Government: Longitudinal Measurement Equivalence in the ANES, 1964–2008

For over 50 years (1958–2012) the American National Election Studies (ANES) survey has been measuring citizens’ evaluations of the trustworthiness of the “government in Washington”—an indicator that has been widely used to monitor the dynamics of political trust in the US over time. However, a critical assumption in using attitudinal constructs for longitudinal research is that the meaning-and-interpretation of such items should be comparable across groups of respondents at any one point in time and across samples over time. Using multigroup confirmatory factor analysis for ordered-categorical data, we test the measurement equivalence assumption with data collected by the ANES from 1964 to 2008. The results confirm that the ANES’ political trust scale has the same basic factorial structure over time. But for two key items, several threshold parameters were found to be different across time points, indicating that the meaning-and-interpretation of these questions, and especially the question about whether the government in Washington wastes money that people pay in taxes, varies significantly over time.

     

Parents' Family Time and Work Schedules: The Split‐Shift Schedule in Spain

This study used data on couples from the 2003 Spanish Time Use Survey (N = 1,416) to analyze how work schedules are associated with family, couple, parent–child, and non‐family leisure activities. Spain is clearly an interesting case for the institutionalized split‐shift schedule, a long lunch break rooted in the traditional siesta that splits the workday between morning and evening. Results showed strong negative associations between the split shift and both family and parent–child activities. The evening shift was negatively associated with couple and family time, but not with parent–child time. Women spent much more time than men in parent–child activities for all work categories, and they were more responsive to the spouse's work hours. Men were substantially more active than women in non‐family leisure, considering both individuals' and their spouses' work schedules. Altogether, this study has important implications for scientific and public policy debates.     

Development of a Quantitative Microbial Risk Assessment for Human Salmonellosis Through Household Consumption of Fresh Minced Pork Meat in Belgium

A quantitative microbial risk assessment (QMRA) according to the Codex Alimentarius Principles is conducted to evaluate the risk of human salmonellosis through household consumption of fresh minced pork meat in Belgium. The quantitative exposure assessment is carried out by building a modular risk model, called the METZOON-model, which covers the pork production from farm to fork. In the METZOON-model, the food production pathway is split up in six consecutive modules: (1) primary production, (2) transport and lairage, (3) slaughterhouse, (4) postprocessing, (5) distribution and storage, and (6) preparation and consumption. All the modules are developed to resemble as closely as possible the Belgian situation, making use of the available national data. Several statistical refinements and improved modeling techniques are proposed. The model produces highly realistic results. The baseline predicted number of annual salmonellosis cases is 20,513 ( SD 9061.45). The risk is estimated higher for the susceptible population (estimate  4.713 × 10⁻⁵; SD 1.466 × 10⁻⁵  ) compared to the normal population  (estimate 7.704 × 10⁻⁶; SD 5.414 × 10⁻⁶)  and is mainly due to undercooking and to a smaller extent to cross-contamination in the kitchen via cook's hands.     

Semiparametric Analysis of Network Formation

ABSTRACT

We consider a statistical model for directed network formation that features both node-specific parameters that capture degree heterogeneity and common parameters that reflect homophily among nodes. The goal is to perform statistical inference on the homophily parameters while treating the node-specific parameters as fixed effects. Jointly estimating all parameters leads to incidental-parameter bias and incorrect inference. As an alternative, we develop an approach based on a sufficient statistic that separates inference on the homophily parameters from estimation of the fixed effects. The estimator is easy to compute and can be applied to both dense and sparse networks, and is shown to have desirable asymptotic properties under sequences of growing networks. We illustrate the improvements of this estimator over maximum likelihood and bias-corrected estimation in a series of numerical experiments. The technique is applied to explain the import and export patterns in a dense network of countries and to estimate a more sparse advice network among attorneys in a corporate law firm.