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Solving this conflict requires open communication; Uncertainty is often large. \3 P"  3cPcc  FOur survey Internet based, voluntary participation, 39 valid responsesGG +Completion times of some farm-to-fork QRAs,,+cb"'  g$USDA-FSIS-FDA Salmonella EnteritidisP%c c c b $  Although the goal was to make the model comprehensive, it has some important limitations. It is a static model and does not incorporate possible changes in SE over time as either host, environment or agent factor change. For many variables, data were limited or nonexistent. Some obvious sources of contamination, such as food handlers, restaurant environment, or other possible sites of contamination on or in the egg (such as the yolk), were not included. And, as complex as the model is, it still represents a simplistic view of the entire farm-to-table continuum. Finally, the model does not yet separate our uncertainty from the inherent variability of the system. Much more work is needed to address this, and all other, limitations. V Zc4gcc  FDA Listeria risk assessment,c b .    +Complete modelling of antimicrobial system?,,b Very little data available, system being modelled is hugely complex! Exposure pathways generally unknown Hazard = resistance determinant Exposure pathways generally unknown Difficult because microbial population is mix of resistant and susceptible Risk analysis needs to incorporate entire picture. RM action and probable total change in human health outcome World issue  travel and food imports can contribute enormously Multi-resistance F2F considers only pathogen on the food source E.g. not E.coli produced during life of animal, appearing in water, vegetables, farmers exposure EZsZ/ZbZZEq/b  :i N9  T /Complete modelling of antimicrobial system? (2)00b Predictive microbiology still unreliable Lab data doesn t translate well to actual food Models crude Attenuation may not be death D-R models inadequate Feeding trial data don t match epidemiological data  can hugely underestimate the risk Epidemiological data not available for sporadic cases (eg Campylobacter) Little cost-benefit analysis effort made Including actions affecting several risk issues Requires enormous resources  impractical for many countries)PZPPP)P0P=P)Z  )0=2 7 jConflict between microbiology and risk assessment focus (Adapted from presentation by Maarten Nauta, 2002)k83@V     fMicrobiology About the detectable Micro-world Selected strains Against variability Qualitative Science. Z 3Z g  sRisk Assessment What is there (prevalence, load) Macro-world All strains Pro variability Quantitative Decision tool.d3d t $The complicated nature of resistance%% $  Co-selection (genes encoding resistance often linked together so use of one drug can select for resistance to unrelated drug) Resistance can enhance spread of infection or duration of fecal shedding in animal populations therefore increasing availability to humans Nosocomial infections Resistant commensals Human and animal use of the same antimicrobials Conclusion: Far more complicated than usual bacterial food safety type risk issues0fPPSP  L       / T Human use of antimicrobials One of the indicator organisms in EARSS is Streptococcus pneumoniae. It is of major clinical importance for pneumonia, bacterial meningitis; and S. pneumoniae is representative of organisms that are transmitted in the community. 2 ,U Q HAttribution of resistance, b Is it necessary to prove a causal relationship between antimicrobial use and resistance? We can t prove with statistics, despite some claims Because of complex pathways, we do need to use more sophisticated methods for risk attribution Eg DAGs, Bayesian model averaging, classification trees But we need to do so fairly Very easy to misdirect arguments Eg Cox (2002) attribute campylobacteriosis to gender, and surrogate measures of wealth (have health insurance), visiting a restaurant, etc instead of sources of Campylobacter vYZ4Z_ZTZZY4_T  Jn Regulators v industry, bnOpponents of restriction of use of antimicrobials more focused than for food safety Few, very large pharmaceutical companies Large intensive farmers for whom antimicrobials essential Financial agenda in potential conflict with reduction of resistance Tend to be conservative, lag behind in risk analysis expertise Limits debate and cooperation Tend to use tactics in fighting off restrictions, not reasoned debate Major potential source of information, but withhold it Have produced some nonsense analyses and arguments Have not accepted that animal drug use is a risk factor for antimicrobial resistance in human diseaseTPdPPPFPjPfPTcdcc c Fcjcfcn APHA press release June 2001, b Visby, Sweden, 13 June 2001: The use of antibiotics in farm animals has little connection with the emergence of so-called  super-bugs, according to the Animal and Plant Health Association (APHA). This statement is based on a new study by the European Federation of Animal Health (FEDESA). The study & estimates that farm animals consumed only 35% of all the antibiotics administered in the EU during 1999 while humans consumed 65%.  By showing that farm animals account for only one-third of the antibiotics used in the European Union  even though their combined liveweight is three times greater than the human patient population  this study suggests that treating sick animals with modern medicine can only be a very small contributing factor to the problem of antimicrobial resistance, if it s a factor at all, & The study should make government officials across the EU pause before jumping to the erroneous conclusion that they can stop the emergence of new bacteria by over-regulating the use of antibiotics and restricting the proper treatment of farm animals. Although there is no evidence that the use of antibiotics in farm animals represents a risk to human health, some government officials have suggested that the EU limit the medications that can be administered to treat sick cows, pigs, horses, sheep, goats, chickens and rabbits as a way to stop the spread of these new bacteria. The new study undermines those arguments because it illustrates that farm animals consume far less antibiotics than people. & zP}H4 4    Remedies: focusing on decisions>   b Consider what is known about the risk problem, and data available immediately or within acceptable time frame Use epi data as much as possible Collect more epi data (e.g. Japan, Denmark) Consider what analysis could be done with this knowledge i.e. a risk-based reasoned argument for evaluating particular actions Estimate the possible magnitude of benefit for a risk action Note that it may not be possible to evaluate all actions Perform a cost-benefit analysis on these actions Get into proportion: eg FQ-Res Salmonella v total salmonella Legacy issue needs addressing in valuing risk Once present, resistant bacterial population has effect until antimicrobial use over Perform a Value of Information analysis Determines whether it is worth collecting more data before making a decision Consider strategy to validate whether predicted improvement occurs Train data producers to supply maximally useful data E.g. microbiologists taken more than one cfu from a plate nPMP9PFP=P:PPUP(PNPxP;PnM9F  =:U(  N$$x((;,,r  '  C    >Danish Vet Service Salmonella QRA  A Bayesian Approach to Quantify the Contribution of Animal-food Sources to Human Salmonellosis - Hald, Vose, Koupeev (2002)L!ccccHW +   z7Fluoroquinolone-resistant Campylobacter risk assessment*8   7 xRisk Assessment of Campylobacter infection transmission from pigs to man using erythromycin resistance as a marker by David Burch Paper at Intl Conf on Antimicrobial Agents in Vet Med, Helsinki, 2002FDErythromicin resistance high in Campylobacter coli (57%) in pigs, but low in humans and chickens (both 15%) Erythromicin resistance high in Campylobacter jejuni (35%) in pigs, but low in humans (2%) and chickens (4%) C.jejuni most common in humans (92%), chickens (90%) and cattle (99%), but C.coli most common in pigs (96%) Conclusion: patterns between humans and pigs don t match, so pig production not a major human threat. 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