The ultimate aim of the research is to give better support for science and risk based decisions that can improve food safety. A combination of experimental and modelling approaches are applied in order to improve our understanding of microbial ecology in the food chain and to develop predictive microbiology and risk assessment tools.
Main challenges include epidemiological and microbial data gaps as well as the ability to take variation and uncertainty into consideration. These factors are limiting for assessing risks associated with different human pathogens, foods, and production processes. For instance, data may exist on prevalence and levels of S. aureus in raw milk but in order to estimate the health risk due to staphylococcal enterotoxins via consumption of raw milk cheese it is necessary to have the ability to quantitatively describe bacterial growth, inactivation and enterotoxin formation during cheese production. This is an example within the domain of predictive microbiology.
Projects are often conducted in co-operation with researchers with complementary skills and recent, current and planned research efforts, cover four areas;
Knowledge gaps related to performing exposure assessments (e.g. storage temperatures) have been identified, and research has addressed factors and problems associated with several pathogens and foods. The common theme is the development and application of stochastic modelling techniques in order to include effects of variability and uncertainty in assessments of risk levels and risk management options.
Problems related to the ability to develop risk assessments (e.g. biological variability) and to understand safety aspects of food production processes (e.g. fermentation of sausages, on-farm cheese production, preparation of hamburgers) have been studied. For instance, the effect of water activity, pH, and lactic acid concentration on growth and inactivation of E. coli in fermented sausages have been investigated and described quantitatively. Further research address factors controlling inactivation of E. coli and S. aureus during lactic acid stress.
The lack of information on the incidence, causes and costs of foodborne illnesses are limiting our understanding of this problem and for setting priorities. We have summarised data on foodborne illnesses in Sweden collected via the voluntary reporting system used by the municipal public health authorities. The extent of underreporting and cost associated with foodborne illnesses as well as transmission routes of L. monocytogenes has also been estimated.
The objective is to develop decision support tools. First, a tool is planned that can integrate information on risk and benefits (DALY, cost of illness, risk assessment and source attribution data) as well as other legitimate factors (economy, risk perception, feasibility) relevant for food safety decisions. This project is being developed in co-operation with researchers from Stockholm University, and the Swedish Institute for Food and Agricultural Economics. Second, evaluation and potentially development of tools for risk ranking is pursued as part of an on-going task within the Biohazard panel of the European Food Safety Authority (EFSA).
1. Risk assessment
2. Predictive Microbiology
3. Epidemiology of foodborne illnesses
4. Tools for decision support and ranking