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One of the important outcomes of the risk assessment work was the compilation and collation of a wealth of information on Salmonella in eggs and broiler chickens. The organization of these data in the structured risk assessment format allowed the identification of significant gaps that exist in the data. This can guide future research work and help ensure that it focuses on generating and collecting the most useful and relevant data. These data and research needs are outlined below.

3.1 Hazard characterization

In order to improve hazard characterization, additional outbreak and epidemiological data are needed. More specifically these data should indicate cell number in the implicated food, amount of food consumed, accurate estimates of the size of ill and exposed populations, and accurate characterization of the population, including age profiles, medical status, sex and other potential susceptibility factors.

The impact of the food matrix was not incorporated into the hazard characterization due to the limitations of available data. Hence, characterization and quantification are needed of the impact of food matrix effects and also host-pathogen interactions and virulence factors, and their effect on the probability of infection, with or without illness, so that these issues can be more completely addressed in future work. Quantitative information to facilitate estimating the probability of developing sequelae following illness is also required.

As this is a developing science, the optimal models have not yet been developed. Therefore, new dose-response models that improve our ability to estimate the probability of illness would be useful.

3.2 Data for exposure assessment in general

Quantitative modelling of the individual exposure steps requires quantitative information. Data can be collected from a number of sources including, but not limited to,

Often these data are publicly available, appearing, for example, in the published literature. However, other data, such as those collected through industry surveys, are often confidential and thus access becomes difficult. It is vital that confidence be built up between risk managers, assessors and those who can provide valuable data for risk assessment. Confidence building requires discussions and meetings (interactive risk communication) to discuss the type of data needed and for what the data are being used (the risk management activity). In addition, discussions provide insight into the data and how it has been generated, e.g. sampling strategy, testing methods, etc. Such insight can be important to ensure correct modelling and thus final results. Overall, good communications among all parties is essential.

In certain cases, adequate data may not be available. One way of dealing with this is to use expert opinion. Use of expert opinion introduces several considerations, such as how to choose experts, how to avoid biased judgement, how to elicit information and how to combine information from different experts. For further information of this area of study, see Kahneman, Slovic and Tversky (1982) and Vose (2000).

In risk assessment, and particularly in the development of generic models (i.e. for application in decision-making in general commodity production, processing, distribution and consumption management), data often come from many different sources. Two issues arise from this: first, what data to include within the model, and, second, how to combine such information. Determining what data to include involves considering applicability (e.g. Are the data relevant for a particular country? Are the data representative of the existing situation? Were scientifically and statistically sound sampling and testing methods used in the collection of the data?) Furthermore, regardless of the data selection criteria, the rationale and process for selection must be transparent. The importance of transparency is also emphasized for combining data. Various methodologies, including weighting of information, can be used, but the assessor must clearly set out the methodology to ensure clarity and reproducibility.

Overall, data collection is probably the most resource-intensive part of the modelling of exposure and involves many issues that influence the quality of the risk assessment outcome.

3.3 Exposure assessment of S. Enteriditis in eggs

Data relating to the biology of Salmonella in eggs is needed. This need is seemingly universal in its application to previous and future exposure assessments.

Additional studies on the numbers, and the factors that influence the survival and growth, of Salmonella in naturally (yolk-) contaminated intact shell eggs are needed, as information is currently available for only 63 intact shell eggs. Enumeration data of Salmonella in raw liquid egg are also required. Additional data concerning the numbers of Salmonella in raw liquid egg before pasteurization would assist in reliably predicting the effectiveness of any regulatory standard concerning egg products.

More data on the prevalence of Salmonella in breeder and pullet flocks and the environment, as well as in feedstuffs, is needed to adequately assess the benefit of pre-harvest interventions. In particular, associations between the occurrence of Salmonella in these pre-harvest steps and its occurrence in commercial layers should be quantified.

Better data on time and temperature, specifically in relation to egg storage and then preparation and cooking, would serve to build confidence in the modelling results. The importance of time and temperature distributions in predicting growth of Salmonella in eggs, combined with the lack of reliable data to describe these distributions, highlights the need for such data. Furthermore, new studies are needed on the relationship between cooking time, cooking method and cooking temperature and the death of S. Enteritidis.

More studies are needed on the survival and growth of Salmonella in eggs, particularly as a function of egg composition and the attributes of infecting strains (e.g. heat sensitivity).

3.4 Exposure assessment of Salmonella in broiler chickens

The lack of good quality data, prior to the end of processing in particular, limited the scope of this exposure assessment. In relation to primary production, the information available was mainly prevalence data, but for some regions of the world, including Africa, Asia and South America, even that was limited. In addition, information was lacking on study design, specificity or sensitivity of the analytical methodologies used. Very few quantitative data were available. A similar situation was observed for the processing stage. In addition, data tended to be old, and knowledge of processing practices was not readily available. In order to address these deficiencies, the areas where data collection and research efforts need to focus are identified below.

If an attempt were made to extend the risk assessment to more fully assess pre-slaughter interventions, then more data would also be required on the prevalence of Salmonella in feed and replacement stock, and fasting prior to slaughter. Data on the effect of scalding, de-feathering, evisceration, washing and chilling processes, as well as other decontamination treatments, are needed to effectively model the benefits of control interventions at the processing level.

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