Self-management interventions for people with intellectual disabillities: a systematic review

Health and self-regulatio

Challenges of quantitative microbial risk assessment at EU level.

Quantitative microbial risk assessment (QMRA) aims to model the fate of pathogenic micro-organisms along the food chain and the associated health risks. More importantly, it allows the a priori estimation of the impact on public health of interventions in the food chain. The European Food Safety Authority is increasingly asked to provide scientific advice to the European Commission based on QMRA. Its application at the European level poses some unique challenges, both of a scientific and of an organizational nature. On the other hand, collaboration at the European level will lead to more effective use of limited expertise and resources

A quantitative microbial risk assessment for meatborne Toxoplasma gondii infection in The Netherlands

Toxoplasma gondii is an important foodborne pathogen, and the cause of a high disease burden due to congenital toxoplasmosis in The Netherlands. The aim of this study was to quantify the relative contribution of sheep, beef and pork products to human T. gondii infections by Quantitative Microbial Risk Assessment (QMRA). Bradyzoite concentration and portion size data were used to estimate the bradyzoite number in infected unprocessed portions for human consumption. The reduction factors for salting, freezing and heating as estimated based on published experiments in mice, were subsequently used to estimate the bradyzoite number in processed portions. A dose–response relation for T. gondii infection in mice was used to estimate the human probability of infection due to consumption of these originally infected processed portions. By multiplying these probabilities with the prevalence of T. gondii per livestock species and the number of portions consumed per year, the number of infections per year was calculated for the susceptible Dutch population and the subpopulation of susceptible pregnant women. QMRA results predict high numbers of infections per year with beef as the most important source. Although many uncertainties were present in the data and the number of congenital infections predicted by the model was almost twenty times higher than the number estimated based on the incidence in newborns, the usefulness of the advice to thoroughly heat meat is confirmed by our results. Forty percent of all predicted infections is due to the consumption of unheated meat products, and sensitivity analysis indicates that heating temperature has the strongest influence on the predicted number of infections. The results also demonstrate that, even with a low prevalence of infection in cattle, consumption of beef remains an important source of infection. Developing this QMRA model has helped identify important gaps of knowledge and resulted in the following recommendations for future research: collect processing-effect data in line with consumer style processing and acquire product specific heating temperatures, investigate the presence and concentration of viable bradyzoites in cattle, determine the effect of mincing meat on bradyzoite concentrations using actual batch sizes, and obtain an estimate of the fraction of meat that has been frozen prior to purchase. With more accurate data this QMRA model will aid science-based decision-making on intervention strategies to reduce the disease burden from meatborne T. gondii infections in The Netherlands

Modeling of Salmonella Contamination in the Pig Slaughterhouse

In this article we present a model for Salmonella contamination of pig carcasses in the slaughterhouse. This model forms part of a larger QMRA (quantitative microbial risk assessment) on Salmonella in slaughter and breeder pigs, which uses a generic model framework that can be parameterized for European member states, to describe the entire chain from farm-to-consumption and the resultant human illness. We focus on model construction, giving mathematical formulae to describe Salmonella concentrations on individual pigs and slaughter equipment at different stages of the slaughter process. Variability among individual pigs and over slaughterhouses is incorporated using statistical distributions, and simulated by Monte Carlo iteration. We present the results over the various slaughter stages and show that such a framework is especially suitable to investigate the effect of various interventions. In this article we present the results of the slaughterhouse module for two case study member states. The model outcome represents an increase in average prevalence of Salmonella contamination and Salmonella numbers at dehairing and a decrease of Salmonella numbers at scalding. These results show good agreement when compared to several other QMRAs and microbiological studies

Detection probability of Campylobacter

A rapid presence/absence test for Campylobacter in chicken faeces is being evaluated to support the scheduling of highly contaminated broiler flocks as a measure to reduce public health risks [Nauta, M. J., & Havelaar, A. H. (2008). Risk-based standards for Campylobacter in the broiler meat chain. Food Control, 19, 372–381]. Although the presence/absence test is still under development, an example data set of test results is analysed to illustrate the benefit of the detection probability concept. The detection probability of Campylobacter increases with the logarithm of the Campylobacter concentration in faeces according to an S-shaped curve which stretches about 2–3 log units. The detection probability is 50% at a Campylobacter concentration of 7.4 × 106 cfu/g. The uncertainty in the detection probability is 32% at the most for a 90% confidence interval. This type of information allows for realistic calculations on the Campylobacter status of different food processing paths after splitting. Usable quantitative estimates on detection probability await a data set of test results from a test that is ready for use or has similar propertie

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

Campylobacter source attribution exposure assessment

A new application of exposure assessment aimed at improving insight into source attribution of human infectious diseases, i.e. estimation of the relative contribution of sources and transmission routes, is developed and explored. Human exposure, calculated as the mean number of Campylobacters ingested per person per day, is used as an indication of the relative importance of Campylobacter transmission routes in the Netherlands. Thirty-one routes were investigated, related to ingestion of food, direct contact with animals and water. Preliminary results suggest that raw food consumption and direct contact are significant transmission routes, but huge data gaps exist and no solid conclusions can be drawn. More data will have to be obtained to reduce uncertainty and thereby make this tool applicable for source attribution. Methodological improvements are necessary to take the step to numbers of cases as model output and thereby to risk assessment