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The project will develop new methods for performing microbial risk assessments and interpreting the results.
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The models would be created from data including disease outbreak investigations, and animal and in-vitro studies and then adjusted to reflect the effects on humans in general or on sub-populations, for instance the young, elderly or immuno-compromised individuals.</p>
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The models would then make up a vital part of risk assessments which would give policy makers,regulators, educators, the food industry and others a scientifically based prediction of the risk associated with the microbial hazards and the probable effects of various mitigation, control, strategies.</p>
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This research will provide well tested models of what happens when we are exposed to different levels of microbial hazards from our food supply. For many hazards, this is information that we currently do not have.
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We know that certain bacteria contaminating our food can cause sickness and even death. Although science has found out a lot about some of these pathogenic (disease causing) bacteria, there are still gaps in our knowledge, such as: How many of the bacteria (dose) have to be in the food to cause a range of effects or responses from mild upset to death? What are the monetary costs associated with illnesses from different microbial hazards and doses. What are the effects on humans of microbial endotoxins (the poisons released during infection). Since direct testing of pathogens on human test subjects can be dangerous and ethically questionable, how can we relate animal or in vitro (human or animal cells grown in a laboratory) studies to humans? Do different groups of people (such as the very young or elderly, immuno-compromised or ethnic groups) react differently to different bacteria, or even to the same level of contamination, and how can any differences in response be measured?
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Risk assessments are scientifically based evaluations of the data we know, filling in the gaps in a variety of ways, so that an estimate or probability is derived of the likelihood of an illness or other adverse event. A common limitation of risk assessments is that a single endpoint, such as hospitalization, is identified as the adverse event. </P>
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One of the ways that the gaps in our knowledge can be accounted for is by using statistical models to simulate the different scenarios we do not know. Statistical models can be created that would take into account the range of endpoints, from mild discomfort to acute pain, permanent disability and death, and incorporate these into a single risk assessment.
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