Combining QMRA and Epidemiology to Estimate Campylobacteriosis Incidence

The disease burden of pathogens as estimated by QMRA (quantitative microbial risk assessment) and EA (epidemiological analysis) often differs considerably. This is an unsatisfactory situation for policymakers and scientists. We explored methods to obtain a unified estimate using campylobacteriosis in the Netherlands as an example, where previous work resulted in estimates of 4.9 million (QMRA) and 90,600 (EA) cases per year. Using the maximum likelihood approach and considering EA the gold standard, the QMRA model could produce the original EA estimate by adjusting mainly the dose‐infection relationship. Considering QMRA the gold standard, the EA model could produce the original QMRA estimate by adjusting mainly the probability that a gastroenteritis case is caused by Campylobacter. A joint analysis of QMRA and EA data and models assuming identical outcomes, using a frequentist or Bayesian approach (using vague priors), resulted in estimates of 102,000 or 123,000 campylobacteriosis cases per year, respectively. These were close to the original EA estimate, and this will be related to the dissimilarity in data availability. The Bayesian approach further showed that attenuating the condition of equal outcomes immediately resulted in very different estimates of the number of campylobacteriosis cases per year and that using more informative priors had little effect on the results. In conclusion, EA was dominant in estimating the burden of campylobacteriosis in the Netherlands. However, it must be noted that only statistical uncertainties were taken into account here. Taking all, usually difficult to quantify, uncertainties into account might lead to a different conclusion.     

Effectiveness and Efficiency of Controlling Campylobacter on Broiler Chicken Meat

Campylobacter bacteria are an important cause of foodborne infections. We estimated the potential costs and benefits of a large number of possible interventions to decrease human exposure to Campylobacter by consumption of chicken meat, which accounts for 20-40% of all cases of human campylobacteriosis in the Netherlands. For this purpose, a farm-to-fork risk assessment model was combined with economic analysis and epidemiological data. Reduction of contamination at broiler farms could be efficient in theory. However, it is unclear which hygienic measures need to be taken and the costs can be very high. The experimental treatment of colonized broiler flocks with bacteriophages has proven to be effective and could also be cost efficient, if confirmed in practice. Since a major decrease of infections at the broiler farm is not expected in the short term, additional measures in the processing plant were also considered. At this moment, guaranteed Campylobacter-free chicken meat at the retail level is not realistic. The most promising interventions in the processing plant are limiting fecal leakage during processing and separation of contaminated and noncontaminated flocks (scheduling), followed by decontamination of the contaminated flock. New (faster and more sensitive) test methods to detect Campylobacter colonization in broilers flocks are a prerequisite for successful scheduling scenarios. Other methods to decrease the contamination of meat of colonized flocks such as freezing and heat treatment are more expensive and/or less effective than chemical decontamination.     

Uncertainty of Population Risk Estimates for Pathogens Based on QMRA or Epidemiology: A Case Study of Campylobacter in the Netherlands

Epidemiology and quantitative microbiological risk assessment are disciplines in which the same public health measures are estimated, but results differ frequently. If large, these differences can confuse public health policymakers. This article aims to identify uncertainty sources that explain apparent differences in estimates for Campylobacter spp. incidence and attribution in the Netherlands, based on four previous studies (two for each discipline). An uncertainty typology was used to identify uncertainty sources and the NUSAP method was applied to characterize the uncertainty and its influence on estimates. Model outcomes were subsequently calculated for alternative scenarios that simulated very different but realistic alternatives in parameter estimates, modeling, data handling, or analysis to obtain impressions of the total uncertainty. For the epidemiological assessment, 32 uncertainty sources were identified and for QMRA 67. Definitions (e.g., of a case) and study boundaries (e.g., of the studied pathogen) were identified as important drivers for the differences between the estimates of the original studies. The range in alternatively calculated estimates usually overlapped between disciplines, showing that proper appreciation of uncertainty can explain apparent differences between the initial estimates from both disciplines. Uncertainty was not estimated in the original QMRA studies and underestimated in the epidemiological studies. We advise to give appropriate attention to uncertainty in QMRA and epidemiological studies, even if only qualitatively, so that scientists and policymakers can interpret reported outcomes more correctly. Ideally, both disciplines are joined by merging their strong respective properties, leading to unified public health measures.     

Volunteering and Civic Action: Boundaries Blurring,Boundaries Redrawn

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - The aim of this introduction to the special issue is to call into question the presumed conceptual divide between...     

“We will Manage It” – Did Chancellor Merkel's Dictum Increase or Even Cause the Refugee Movement in 2015?

In public and scientific debates about the dynamics of the so-called refugee crisis of 2015, there are highly controversial positions concerning the statement on August 2015 by Chancellor Merkel: “We will manage it” Did this dictum actually increase or even unleash the refugee migration towards Europe in 2015? Was Germany's governmental policy against the legal European and national frame? Based on an analysis of legal documents and public statements, the article first reconstructs the development of refugee immigration into the EU, especially to Germany, in 2015 and reviews whether the German government violated law and opened one-sided borders. Based on survey data of 4,500 refugees in 2016, it then analyses whether the Merkel dictum significantly changed the volume and the reasons why refugees decided to flee to Germany. Finally, some conclusions are drawn.     

Book Review: Walter W. Powell and Elisabeth S. Clemens (eds.), Private Action and the Public Good,Yale University Press,New Haven and London, 1998

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations -     

Mending the Levee: How Supernaturally Anchored Conceptions of the Person Impact on Trauma Perception and Healing among Children (Cases from Madagascar and Nepal)

When dealing with children and youth who experience distressing events, psychosocial diagnostics and healing programmes principally resort to biomedical models. Children are often viewed as individualised ‘victims’ suffering from trauma and ‘in need’ of outside help. Highlighting case studies from Madagascar and Nepal, this article argues that the biomedical approach to trauma would be strengthened by a concomitant analysis of social networks, including the perceived relations with the supernatural. The various tandems of family and kin relationships, the living and the dead, constitute not only a social ‘levee’ breached by distressing events, but also the locus around which social relations are rebuilt.     

On the distributional transform, Sklar's theorem, and the empirical copula process

We review the distributional transform of a random variable, some of its applications, and some related multivariate distributional transformations. The distributional transform is a useful tool, which allows in many respects to deal with general distributions in the same way as with continuous distributions. In particular it allows to give a simple proof of Sklar's theorem in the general case. It has been used in the literature for stochastic ordering results. It is also useful for an adequate definition of the conditional value at risk measure and for many further purposes. We also discuss the multivariate quantile transform as well as the multivariate extension of the distributional transform and some of their applications. In the final section we consider an application to an extension of a limit theorem for the empirical copula process, also called empirical dependence function, to general not necessarily continuous distributions. This is useful for constructing and analyzing tests of dependence properties for general distributions.     

Two remarks on order statistics

Let X₍₁₎,…,X_(n) be the order statistics of n iid distributed random variables. We prove that (X_(i)) have a certain Markov property for general distributions and secondly that the order statistics have monotone conditional regression dependence. Both properties are well known in the case of continuous distributions.