Future challenges to microbial food safety

Despite significant efforts by all parties involved, there is still a considerable burden of foodborne illness, in which micro-organisms play a prominent role. Microbes can enter the food chain at different steps, are highly versatile and can adapt to the environment allowing survival, growth and production of toxic compounds. This sets them apart from chemical agents and thus their study from food toxicology. We summarize the discussions of a conference organized by the Dutch Food and Consumer Products Safety Authority and the European Food Safety Authority. The goal of the conference was to discuss new challenges to food safety that are caused by micro-organisms as well as strategies and methodologies to counter these. Management of food safety is based on generally accepted principles of Hazard Analysis Critical Control Points and of Good Manufacturing Practices. However, a more pro-active, science-based approach is required, starting with the ability to predict where problems might arise by applying the risk analysis framework. Developments that may influence food safety in the future occur on different scales (from global to molecular) and in different time frames (from decades to less than a minute). This necessitates development of new risk assessment approaches, taking the impact of different drivers of change into account. We provide an overview of drivers that may affect food safety and their potential impact on foodborne pathogens and human disease risks. We conclude that many drivers may result in increased food safety risks, requiring active governmental policy setting and anticipation by food industries whereas other drivers may decrease food safety risks. Monitoring of contamination in the food chain, combined with surveillance of human illness and epidemiological investigations of outbreaks and sporadic cases continue to be important sources of information. New approaches in human illness surveillance include the use of molecular markers for improved outbreak detection and source attribution, sero-epidemiology and disease burden estimation. Current developments in molecular techniques make it possible to rapidly assemble information on the genome of various isolates of microbial species of concern. Such information can be used to develop new tracking and tracing methods, and to investigate the behavior of micro-organisms under environmentally relevant stress conditions. These novel tools and insight need to be applied to objectives for food safety strategies, as well as to models that predict microbial behavior. In addition, the increasing complexity of the global food systems necessitates improved communication between all parties involved: scientists, risk assessors and risk managers, as well as consumer

Controlling Campylobacter in the chicken meat chain; Estimation of intervention costs

Campylobacter infections are a serious public health problem in the Netherlands. As a part of the CARMA project, this study focus on the estimation of the potential direct costs related to the implementation of various intervention measures to control campylobacters in the chicken meat chain. Costs were estimated using a second-order stochastic simulation model. Treating only positively tested flocks is far cheaper than treating all flocks. The implementation of equipment to reduce faecal leakage would be the cheapest, while irradiation would be costliness. However, indirect costs for the various interventions, if occurring, would be far higher than the estimated direct costs

Исследование семантических распределенных параметров информационных компонент системы защиты

A real time quantitative PCR combined with propidium monoazide (PMA) treatment of samples was implemented to quantify live C. jejuni, C. coli and C. lari on broiler chicken carcasses at selected processing steps in the slaughterhouse. The samples were enumerated by culture for comparison. The Campylobacter counts determined with the PMA-qPCR and the culture method were not concordant. We conclude that the qPCR combined with PMA treatment of the samples did not fully reduce the signal from dead cells

Systematic review of foodborne burden of disease studies: Quality assessment of data and methodology

Burden of disease (BoD) studies aim to identify the public health impact of different health problems and risk factors. To assess BoD, detailed knowledge is needed on epidemiology, disability and mortality in the population under study. This is particularly challenging for foodborne disease, because of the multitude of causative agents and their health effects. The purpose of this study is to systematically review the methodology of foodborne BoD studies. Three key questions were addressed: 1) which data sources and approaches were used to assess mortality, morbidity and disability?, 2) which methodological choices were made to calculate Disability Adjusted Life Years (DALY), and 3) were uncertainty analyses performed and if so, how? Studies (1990-June 2012) in international peer-reviewed journals and grey literature were identified with main inclusion criteria being that the study assessed disability adjusted life years related to foodborne disease. Twenty-four studies met our inclusion criteria. To assess incidence or prevalence of foodborne disease in the population, four approaches could be distinguished, each using a different data source as a starting point, namely 1) laboratory-confirmed cases, 2) cohort or cross-sectional data, 3) syndrome surveillance data and 4) exposure data. Considerable variation existed in BoD methodology (e.g. disability weights, discounting, age-weighting). Almost all studies analyzed the effect of uncertainty as a result of possible imprecision in the parameter values. Awareness of epidemiological and methodological rigor between foodborne BoD studies using the DALY approach is a critical priority for advancing burden of disease studies. Harmonization of methodology that is used and of modeling techniques and high quality data can enlarge the detection of real variation in DALY outcomes between pathogens, between populations or over time. This harmonization can be achieved by identifying substantial data gaps and uncertainty and establish which sequelae of foodborne disease agents should be included in BoD calculations

Practicalities of using non-local or non-recent multilocus sequence typing data for source attribution in space and time of human campylobacteriosis

In this study, 1208 Campylobacter jejuni and C. coli isolates from humans and 400 isolates from chicken, collected in two separate periods over 12 years in The Netherlands, were typed using multilocus sequence typing (MLST). Statistical evidence was found for a shift of ST frequencies in human isolates over time. The human MLST data were also compared to published data from other countries to determine geographical variation. Because only MLST typed data from chicken, taken from the same time point and spatial location, were available in addition to the human data, MLST datasets for other Campylobacter reservoirs from selected countries were used. The selection was based on the degree of similarity of the human isolates between countries. The main aim of this study was to better understand the consequences of using non-local or non-recent MLST data for attributing domestically acquired human Campylobacter infections to specific sources of origin when applying the asymmetric island model for source attribution. In addition, a power-analysis was done to find the minimum number of source isolates needed to perform source attribution using an asymmetric island model. This study showed that using source data from other countries can have a significant biasing effect on the attribution results so it is important to carefully select data if the available local data lack in quality and/or quantity. Methods aimed at reducing this bias were proposed

Risk Factors for Campylobacteriosis of Chicken, Ruminant, and Environmental Origin: A Combined Case-Control and Source Attribution Analysis

Background: Campylobacteriosis contributes strongly to the disease burden of food-borne pathogens. Case-control studies are limited in attributing human infections to the different reservoirs because they can only trace back to the points of exposure, which may not point to the original reservoirs because of cross-contamination. Human Campylobacter infections can be attributed to specific reservoirs by estimating the extent of subtype sharing between strains from humans and reservoirs using multilocus sequence typing (MLST). Methodology/Principal Findings: We investigated risk factors for human campylobacteriosis caused by Campylobacter strains attributed to different reservoirs. Sequence types (STs) were determined for 696 C. jejuni and 41 C. coli strains from endemic human cases included in a case-control study. The asymmetric island model, a population genetics approach for modeling Campylobacter evolution and transmission, attributed these cases to four putative animal reservoirs (chicken, cattle, sheep, pig) and to the environment (water, sand, wild birds) considered as a proxy for other unidentified reservoirs. Most cases were attributed to chicken (66%) and cattle (21%), identified as the main reservoirs in The Netherlands. Consuming chicken was a risk factor for campylobacteriosis caused by chicken-associated STs, whereas consuming beef and pork were protective. Risk factors for campylobacteriosis caused by ruminant-associated STs were contact with animals, barbecuing in non-urban areas, consumption of tripe, and never/seldom chicken consumption. Consuming game and swimming in a domestic swimming pool during springtime were risk factors for campylobacteriosis caused by environment-associated STs. Infections with chicken-and ruminant-associated STs were only partially explained by food-borne transmission; direct contact and environmental pathways were also important. Conclusion/Significance: This is the first case-control study in which risk factors for campylobacteriosis are investigated in relation to the attributed reservoirs based on MLST profiles. Combining epidemiological and source attribution data improved campylobacteriosis risk factor identification and characterization, generated hypotheses, and showed that genotype-based source attribution is epidemiologically sensible

Methodological framework for World Health Organization estimates of the global burden of foodborne disease

Background: The Foodborne Disease Burden Epidemiology Reference Group (FERG) was established in 2007 by the World Health Organization to estimate the global burden of foodborne diseases (FBDs). This paper describes the methodological framework developed by FERG's Computational Task Force to transform epidemiological information into FBD burden estimates. Methods and Findings: The global and regional burden of 31 FBDs was quantified, along with limited estimates for 5 other FBDs, using Disability-Adjusted Life Years in a hazard- and incidence-based approach. To accomplish this task, the following workflow was defined: outline of disease models and collection of epidemiological data; design and completion of a database template; development of an imputation model; identification of disability weights; probabilistic burden assessment; and estimating the proportion of the disease burden by each hazard that is attributable to exposure by food (i.e., source attribution). All computations were performed in R and the different functions were compiled in the R package 'FERG'. Traceability and transparency were ensured by sharing results and methods in an interactive way with all FERG members throughout the process. Conclusions: We developed a comprehensive framework for estimating the global burden of FBDs, in which methodological simplicity and transparency were key elements. All the tools developed have been made available and can be translated into a user-friendly national toolkit for studying and monitoring food safety at the local level

Impact of infectious diseases on population health using incidence-based disability-adjusted life years (DALYs)

Background and aims: The Burden of Communicable Diseases in Europe (BCoDE) study aimed to calculate disability-adjusted life years (DALYs) for 31 selected diseases in the European Union (EU) and European Economic Area (EEA). Methods: DALYs were estimated using an incidence-based and pathogen-based approach. Incidence was estimated through assessment of data availability and quality, and a correction was applied for under-estimation. Calculation of DALYs was performed with the BCoDE software toolkit without applying time discounting and age-weighting. Results: W