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Needs, Gaps, and Opportunities Assessment (NGOA) for Microbial Risk Assessment in Food and Water

MICROBIAL RISK ASSESSMENT AS A FOUNDATION FOR INFORMED DECISION

MAKING

APPENDIX

Aamir Fazil Health Canada Greg Paoli Decisionalysis Risk Consultants Mansel Griffiths University of Guelph Anna Lammerding Health Canada Valerie Davidson University of Guelph Steve Hrudey University of Alberta Judith Isaac-Renton University of British Columbia

1.0 Appendix: Literature Search ................................................................................... 3

1.1 Background ......................................................................................................... 3 1.2 FSRA Current Contents Searches ....................................................................... 3 1.3 NGOA Project Search Strategies ........................................................................ 4 1.4 Literature Review................................................................................................ 7

1.4.1 Dose-Response ............................................................................................ 7 1.4.2 Waterborne Risk Assessment...................................................................... 9 1.4.3 Food Risk Assessment .............................................................................. 18 1.4.4 Antimicrobial Resistance .......................................................................... 24 1.4.5 Geographical Information Systems........................................................... 28 1.4.6 Cost Benefit............................................................................................... 29 1.4.7 Exposure Information................................................................................ 32 1.4.8 Exposure modelling................................................................................... 36 1.4.9 Methods from Other Fields ....................................................................... 39 1.4.10 Reviews ..................................................................................................... 48 1.4.11 Predictive Microbiology............................................................................ 57 1.4.12 Methods for Risk Assessment ................................................................... 66

2.0 Appendix 2: Expert Consultation.......................................................................... 76 2.1 Consultation Correspondence ........................................................................... 77

2.1.1 Invitation ................................................................................................... 77 2.1.2 Attendee Travel Instructions ..................................................................... 78

2.2 Pre-consultation Update & Instruction.............................................................. 80 2.2.1 General Impressions.................................................................................. 80 2.2.2 Roundtable Preparation ............................................................................. 80 2.2.3 Breakout Session Questions ...................................................................... 80 2.2.4 Miscellaneous............................................................................................ 81

2.3 Agenda .............................................................................................................. 82 2.4 Introductory Presentation .................................................................................. 84 2.5 Framework Presentation.................................................................................... 87 2.6 Meeting Attendes .............................................................................................. 92

1.0 Appendix: Literature Search

1.1 Background A part of the day-to-day functions of the Food Safety Risk Assessment Unit (FSRA), at the Laboratory for Foodborne Zoonoses, is the maintenance and expansion of a library of published materials on risk assessment, microbial pathogens and food safety issues. The intent of this library is to have on hand, a database of readily accessible information and data, should the need or requests arise. This activity has been ongoing since approximately 1990, resulting in a substantial database of microbial risk related articles held in hard-copy and individually catalogued in a series of Procite© databases. These databases are populated by more than 142 500 citations, a majority of which were obtained through regular electronic searches of Current Contents database collections: Life Sciences (LS) and Agriculture, Biology & Environmental Sciences (ABES), which together include approximately 2300 journals. Search results are normally scanned for especially relevant articles, and these articles are then retrieved in hard copy. Citations of articles found in publications not tracked by the aforementioned Current Contents collections, but retrieved by the unit through other means, are entered manually into the FSRA databases.

1.2 FSRA Current Contents Searches The search profiles used to capture relevant citations have been modified and expanded over the years to reflect needs of the unit. The following searches are currently used to capture citations that populate the FSRA databases: Search #1 (Abstract):

(Bioterror or biowarfare or bioweapon* or biological warfare or biological weapon*) or (risk assessment or risk analysis or predictive model) or (zoono* or encephalitozoon or enterotox* or mycotox*) or ((safety and evaluation) or microbiolog* assay*) or (hyg*ene or (biofilm* and food*) or (haccp or (hazard analysis or critical control) and (food* or water*))) or (sous vide or sous-vide or (irradiation and food) or (food* and (safe* or bacteria*)) or ready to eat or ready-to-eat or carcass or (consumer and food))

Search #2 (Abstract):

(Diarrh* or outbreak* or foodborne or food-borne or food borne) or (case control or case-control or (fuzzy and (sets or logic or math or model*) and (food or health or biolog*))) or (bovine spongiform encephal* or bse or creutzfeld*) or (crohn* or mycobacterium paratuberculosis or mycobacterium avium*paratuberculosis or mycobacterium bovis or johne*) or (toxoplas* or neospor* or microsporid* or cryptosporid* or giardi*) or (Norwalk or enteric virus*) or (clostrid* not (acetobutylicum or thermocellum or thermoaceticum))

Search #3 (Abstract):

(Vtec or epec or eiec or ehec or o157* or o 157* or o-157* or verotoxi* or verocyto* or enteroh*em or enteroinvasive or shigell* or shiga-like or stec or (escherichi* and (adhe* or thrombocyt* or edema* or eae or enteropath* or attach*)) or (bacillus not (thuringiensis or stearothermophilus or megaterium or coagulans or licheniformis or subtilis)) or (staph* aureus or staph* epidermidis) or staphylococcal enterotoxin not methicillin*resistan*) or (aeromona* or plesiomona* or campylobacter* or arcobacter* or vibrio* or cholera* or enterobacter* or enterococc* or listeri* or salmonel* or streptococc*)

Excluding (in Journal Subject Categories):

Aquatic-sciences or biochemistry-and-biophysics or cardiovascular-and-haematology-research or cell-and-developmental-biology or chemistry-and-analysis or current-book-contents or entomology or pest-control or experimental-biology or medical-research-diagnosis-and-treatment or medical-research-organs-and-systems or neurosciences-and-behavior or oncogenesis-and-cancer-research or pharmacology-and-toxicology or plant-sciences

Excluding (in Journal Issues):

Endocrine-review* or chemosphere* or chemoecology* or rostlinna-vyroba* or american-journal-of-obstretics-and-gynecology* or biochemistry* or journal-of-the-institute-of-brewing* or endoscopy* or entomologia-generalis* or european-journal-of-immunology* or hypertension* or laboratory-animal-science* or journal-of-experimental-zoology* or ophthalmology* or thorax* or transfusion* or transfusion-medicine* or radiology* or soil-biology-biochemistry* or molecular-plant-microbe-interactions* or physiologia-plantarum* or plant-cell* or plant-cell-reports* or plant-pathology* or plant physiology* or plant-physiology-and-biochemistry* or plant-science*

1.3 NGOA Project Search Strategies Searches in Existing FSRA Databases The already-existing FSRA Procite© databases served as a starting point in the collection of citations relevant to the current NGOA project. The databases were searched for the following keywords in the database fields “Keywords” and/or “Abstract”: Food AND Risk Assessment Food AND Risk Analysis Food(-)borne AND Risk Food(-)borne Pathogen(s) AND Model Food(-)borne Pathogen(s) AND Modeling Food(-)borne Pathogen(s) AND Modelling Food(-)borne Pathogen(s) AND Predictive Food(-)borne Pathogen(s) AND Probabilistic

Food(-)borne Pathogen(s) AND Risk Food Microbiology AND Risk Food Safety AND Risk Assessment Food Safety-Microbiology AND Risk Microbial AND Modeling Microbial AND Modelling Microbial AND Predictive Microbial AND Probabilistic Microbial AND Risk Microbial AND Risk Analysis Microbial AND Risk Assessment Microbial Risk Assessment Microbiological AND Risk Assessment Microbiological Risk Assessment Risk Assessment-Microbial Water AND Risk Assessment Water AND Risk Analysis Water(-)borne AND Risk Water Safety AND Risk Assessment After eliminating any irrelevant citations and combining the hits from each database search, there were 1966 records in the database, including articles from the early 1990s through July 2003. Further Searches in Current Contents The search strategy was expanded to incorporate the Current Contents collections Physical, Chemical & Earth Sciences (PCET) and Engineering, Computing & Technology (ECT). The FSRA search profile was modified slightly for use in these searches to ensure inclusion of any relevant water- or food-related citations. Only citations dating from 01-01-99 were available to be searched using the current internet-based system. Combinations of the following search terms were used in this search: (assessment or analysis or model) (microb*) (risk and food) (risk and water) The PCET and ECT searches yielded 189 new records. In addition, an expanded search was conducted in Current Contents directly, of the LS and ABES collections but without the standard FSRA search profile parameters. The goal of this search was to eliminate the FSRA search limits and verify that the searches were as comprehensive and inclusive as possible of relevant citations. Again, only the most recent citations (01-01-99 to present) were available to be searched online. Combinations of the following search terms were used: (assessment or analysis or model) (microb*)

(risk and food) (risk and water) After pre-screening, 82 new hits were retrieved from this search. Finally, a Current Contents search was conducted that specifically targeted articles related to antimicrobial resistance risk assessment and food or water. Without excluding any journal subject categories or establishing search limits, all four collections (LS, ABES, ECT, PCET) were searched, using combinations of the following terms: (AMR) (antimicrobial) (antimicrobial resistance) (food or water) (risk) After pre-screening, there were 46 new records from this search. After combining all of the smaller databases and discarding the duplicates, the General Database contained 2042 records. Search strategies were designed to ensure that the collection of relevant records was as comprehensive as possible. An initial pre-screening eliminated any obviously irrelevant search hits. Each of the databases resulting from the searches was then scanned for citations that would be specifically relevant to the project. Relevant citations were assigned a preliminary code based on the area of focus for the article. Citations for articles that were not deemed to be immediately useful were not given any preliminary coding but were still retained in the database. All of the smaller databases were eventually amalgamated, duplicates were discarded and the coding system was refined and expanded, such that every citation in the database has a category-based code. The articles were grouped into the following categories: Dose-Response Waterborne Risk Assessment Food Risk Assessment Antimicrobial Resistance Geographical Information Systems Cost Benefit Exposure Information Exposure modelling Methods from Other Fields Reviews Predictive Microbiology Methods for Risk Assessment

1.4 Literature Review 1.4.1 Dose-Response Although the earliest work to quantify the relationships between infection/illness and numbers of microbes (or amount of toxin) ingested was published as early as the 1950s and 60’s (using human feeding trials) the work in this area is still relatively sparse. Of the thirty papers in the database on this topic since the work of (Haas, 1983) proposing a non-threshold model (versus earlier work establishing minimum infectious doses) only16 deal specifically with developing and testing mathematical models, and the majority have been published only since 2000 (although a small number of dose-response models have been developed within the context of food and water safety risk assessment publications and not included here). However, it is evident that dose-response modelling is becoming a focus for many researchers, and largely in the context of recognizing this information is becoming a foundation for regulatory decisions, and strategies, in both water and food safety. This is seen in particularly USA and the EU publications. The majority of work currently focuses on Listeria monocytogenes, Escherichia coli O157:H7, Salmonella enterica and Cryptosporidium. Challenges include lack of accurate dose data (human volunteer feeding trials can be used only for less virulent pathogens, and use healthy subjects); epidemiological outbreak investigators generally do not, or cannot, collect quantitative data; the need for models to extrapolate from high doses (which typically cause the detectable outbreaks) to low doses (which may cause illness in certain susceptible populations, or over a widespread geographical region); differences in virulence among phenotypically similar strains; incomplete follow-up on outbreak victims to assess infected state, overt illness, and severity of illness in various subpopulations; exposures in a population from multiple sources. Closer cooperation with epidemiologists and others in public health agencies is seen to be critical to acquiring data, and to validate dose-response models. Research is needed to gain a better understanding of differences among species and strains, in order to target highly virulent pathogens specifically. 1. Buchanan RL, Damert WG, Whiting RC, van Schothorst M. Use of epidemiologic and food survey

data to estimate a purposefully conservative dose-response relationship for Listeria monocytogenes levels and incidence of listeriosis. Journal of Food Protection 1997;60(8):918-22.

2. Chick SE, Koopman JS, Soorapanth S, Brown ME. Infection transmission system models for microbial risk assessment. Science of the Total Environment 2001;274(1-3):197-207.

3. Clifford CP, Crook DWM, Conlon CP, Fraise AP, Day DG, Peto TEA. Impact of waterborne outbreak of cryptosporidiosis on AIDS and renal transplant patients. Lancet 1990;335(8703):1455-6.

4. Coleman M, Marks H. Topics in dose-response modeling. Journal of Food Protection 1998;61(11):1550-9.

5. Coleman ME, Dreesen DW, Wiegert RG. A simulation of microbial competition in the human colonic ecosystem. Applied and Environmental Microbiology 1996;62(10):3632-9.

6. Crockett CS, Haas CN, Fazil A, Rose JB, Gerba CP. Prevalence of shigellosis in the US: Consistency with dose-response information. International Journal of Food Microbiology 1996;30(1-2):87-99.

7. Daniels JJD, Autenrieth IB, Goebel W. Interaction of Listeria monocytogenes with the intestinal epithelium. FEMS Microbiology Letters 2000;190(2):323-8.

8. Gerba CP, Rose JB, Haas CN. Sensitive populations: Who is at the greatest risk? International Journal of Food Microbiology 1996;30(1-2):113-23.

9. Haas CN. Estimation of Risk Due to Low Doses of Microoorganisms: A Comparison of Alternative Methodologies. American Journal of Epidemiology 1983;118(4):573-82.

10. Haas CN, Madabusi-Thayyar A. Development and Validation of Dose-Response Relationship for Listeria monocytogenes. Quantitative Microbiology 1999;1:89-102.

11. Haas CN, ThayyarMadabusi A, Rose JB, Gerba CP. Development of a dose-response relationship for Escherichia coli O157 : H7. International Journal of Food Microbiology 2000;56(2-3):153-9.

12. Holcomb DL, Smith MA, Ware GO, Hung Y, Brackett RE, Doyle MP. Comparison of Six Dose-Response Models for Use with Food-Borne Pathogens. Risk Analysis 1999;19(6):1091-100.

13. Jackson JK, Murphree RL, Tamplin ML. Evidence that mortality from Vibrio vulnificus infection results from single strains among heterogeneous populations in shellfish. Journal of Clinical Microbiology 1997;35(8):2098-101.

14. Kodell RL, Kang SH, Chen JJ. Statistical Models of Health Risk Due to Microbial Contamination of Foods. Environmental and Ecological Statistics 2002 Sep;9(3):259-71.

15. Kothary MH, Babu US. Infective dose of foodborne pathogens in volunteers: A review. Journal of Food Safety 2001;21(1):49-73.

16. Latimer HK, Jaykus L, Morales RA, Cowen P, Crawford-Brown D. A Weighted Composite Dose-Response Model For Human Salmonellosis. Risk Analysis 2001;21(2):295-305.

17. Lecuit M, Cossart P. Genetically-Modified-Animal Models for Human Infections: the Listeria Paradigm. Trends in Molecular Medicine 2002 Nov;8(11):537-42.

18. Maijala R, Lyytikainen O, Johansson T, Autio T, Aalto T, Haavisto L, et al. Exposure of Listeria Monocytogenes Within an Epidemic Caused by Butter in Finland. International Journal of Food Microbiology 2001 Oct;70(1-2):97-109.

19. Medema GJ, Teunis PFM, Havelaar AH, Haas CN. Assessment of the dose-response relationship of Campylobacter jejuni. International Journal of Food Microbiology 1996;30(1-2):101-11.

20. Nickerson CA, Goodwin TJ, Terlonge J, Ott CM, Buchanan KL, Uicker WCD, et al. Three-Dimensional Tissue Assemblies: Novel Models for the Study of Salmonella Enterica Serovar Typhimurium Pathogenesis. Infection and Immunity 2001 Nov;69(11):7106-20.

21. Ohl ME, Miller SI. Salmonella: A model for bacterial pathogenesis. Annual Review of Medicine 2001;52:259-74.

22. Powell MR, Ebel E, Schlosser W, Walderhaug M, Kause J. Dose-response envelope for Escherichia

coli O157:H7. Quantitative Microbiology 2000;2:141-63.

23. Raybourne RB. Virulence testing of Listeria mmocytogenes. JOURNAL-OF-AOAC-INTERNATIONAL 2002 Mar-2002 Apr;85(2):516-23.

24. Rivera ING, Chun J, Huq A, Sack RB, Colwell RR. Genotypes associated with virulence in environmental isolates of Vibrio cholerae. Applied and Environmental Microbiology 2001;67(6):2421-9.

25. Roche SM, Velge P, Bottreau E, Durier C, MarquetvanderMee N, Pardon P. Assessment of the virulence of Listeria monocytogenes: agreement between a plaque-forming assay with HT-29 cells and infection of immunocompetent mice. International Journal of Food Microbiology 2001;68(1-2):33-44.

26. Saklani Jusforgues H, Fontan E, Goossens PL. Effect of acid-adaptation on Listeria monocytogenes survival and translocation in a murine intragastric infection model. FEMS-MICROBIOLOGY-LETTERS 2000 Dec;193(1):155-9.

27. Strachan NJC, Fenlon DR, Ogden ID. Modelling the vector pathway and infection of humans in an environmental outbreak of Escherichia coli O157. FEMS Microbiology Letters 2001;203(1):69-73.

28. Teunis PF, Havelaar AH. The beta poisson dose-response model is not a single-hit model. Risk Anal 2000 Aug;20(4):513-20.

29. Teunis PFM, Chappel CL, Okhuysen PC. Cryptosporidium Dose-Response Studies: Variation Between Hosts. Risk Analysis 2002;22(3):475-85.

30. Teunis PFM, Chappell CL, Okhuysen PC. Cryptosporidium DOse Repsonse Studies: Variation Between Isolates. Risk Analysis 2002;22(1):175-83.

31. Teunis PFM, Nagelkerke NJD, Haas CN. Dose Response Models For Infectious Gastroenteritis. Risk Analysis 1999;19(6):1251-60.

32. WHO/FAO. Microbiological Risk Assessment Series, No. 1. Risk assessments for Salmonella in eggs and broiler chickens. Food and Agriculture Organization of the United Nations and World Health Organization., 2002.

33. WHO/FAO. Microbiological Risk Assessment Series, No. 2. Risk assessments for Salmonella in eggs and broiler chickens. Food and Agriculture Organization of the United Nations and World Health Organization. 2002.

34 WHO/FAO. Microbiological Risk Assessment Series, No. 3. Guidelines for Hazard Characterization for Pathogens in Food and Water. Food and Agriculture Organization of the United Nations. World Health Organization., 2003.

1.4.2 Waterborne Risk Assessment Of 119 papers compiled, that fit into the “waterborne risk assessment” through our search parameters for water risk assessments, approximately one-quarter were ecological risk assessments, modeling the likelihood of contamination of water sources with effluents and fecal microorganisms, nutrients, carcinogens, and other chemical contaminants. In effect, these assessments provide the exposure input for human health risks.

Eighteen papers integrated models for the likelihood of microbial contamination with dose-response data for specific pathogens to estimate human health impacts in a population. Most studies have focused on Cryptosporidium parvuum, followed by Giardia and enteroviruses; however risk assessment models have also included fecal bacteria (Campylobacter jejuni and Salmonella). Concerns around agricultural produce have prompted risk model developments: 5 papers address the use of wastewater irrigation and modeling, the risk of human illness from consumption of contaminated crops. Several pathogens have been looked at: hepatitis A, rotavirus, Salmonella enterica, Campylobacter jejuni, Giardia lamblia, and Cryptosporidium parvuum. Much of the work in the area of water risk assessment is within the context of regulatory guidelines for water quality and treatment facilities; some specifically present findings in the context of risk management decision-making ((Wong & Yeh, 2002); (Hauger et al., 2002)). (Havelaar et al., 2000) developed an integrated case study comparing risk of infection from microbial versus chemical risk (i.e. eliminating a bacterial hazard using a chemical disinfectant), and measuring predicted outcomes of both in terms of DALY’s (disability-adjusted life-years). (Dewettinck et al., 2001) refer to quantitative risk assessments as a basis for establishing CCPs (critical control points) in a drinking water production facility’s HACCP program. The balance of papers include epidemiological associations between drinking water quality indicators, such as turbidity, and human illness; general reviews of specific waterborne pathogens, data needs for risk assessments and risk management, uncertainty and variability in modeling exposures whether for chemical or microbial. 1. Albering HJ, Rila JP, Moonen EJ, Hoogewerff JA, Kleinjans JCS. Human health risk assessment in

relation to environmental pollution of two artificial freshwater lakes in the Netherlands. Environmental Health Perspectives 1999;107(1):27-35.

2. Andersen HV, Kjolholt J, Poll C, Dahl SO, StuerLauridsen F, Pedersen F, et al. Environmental risk assessment of surface water and sediments in Copenhagen harbour. Water Science and Technology 1998;37(6-7):263-72.

3. Beaudeau P, Payment P, Bourderont D, Mansotte F, Boudhabay O, Laubies B, et al. A time series study of anti-diarrheal drug sales and tap-water quality. International Journal of Environmental Health Research 1999;9(4):293-311.

4. Bixio D, Parmentier G, Rousseau D, Verdonck F, Meirlaen J, Vanrolleghem PA, et al. A Quantitative Risk Analysis Tool for Design/Simulation of Wastewater Treatment Plants. Water Science and Technology 2002;46(4-5):301-7.

5. Blumenthal UJ, Mara DD, Peasey A, RuizPalacios G, Stott R. Guidelines for the microbiological quality of treated wastewater used in agriculture: recommendations for revising WHO guidelines. Bulletin of the World Health Organization 2000;78(9):1104-16.

6. Boak RA, Packman MJ. A methodology for the assessment of risk of Cryptosporidium contamination of groundwater. QUARTERLY-JOURNAL-OF-ENGINEERING-GEOLOGY-AND-HYDROGEOLOGY 2001; MAY (34 Part 2 : 1):87-194.

7. Buck SP, Wolfe ML, Mostaghimi S, Woeste FE, Vietor DM. Application of probabilistic risk assessment to agricultural nonpoint source pollution. Journal of Soil and Water Conservation 2000;55(3):340-6.

8. Casman E, Fischhoff B, Small M, Dowlatabadi H, Rose J, Morgan MG. Climate change and cryptosporidiosis: A qualitative analysis. CLIMATIC-CHANGE 2001;2001; 50:: 219-49.

9. Casman EA, Fischhoff B, Palmgren C, Small MJ, Wu F. An integrated risk model of a drinking-water--borne cryptosporidiosis outbreak. Risk Anal 2000 Aug;20(4):495-511.

10. Charles K, Roser D, Ashbolt N, Deere D, McGuinness R. Buffer distances for on-site sewage systems in Sydney's drinking water catchments. WATER-SCIENCE-AND-TECHNOLOGY 183;2003; 47:7-8.

11. Chin DA, Qi X. Ground water under direct influence of surface water. JOURNAL-OF-ENVIRONMENTAL-ENGINEERING-ASCE 2000;JUN 2000; 126:: 501-8 .

12. Conboy MJ, Goss MJ. Natural protection of groundwater against bacteria of fecal origin. JOURNAL-OF-CONTAMINANT-HYDROLOGY 2000 Apr;43(1):1-24.

13. Cormier SM, Smith M, Norton S, Neiheisel T. Assessing ecological risk in watersheds: A case study of problem formulation in the Big Darby Creek watershed, Ohio, USA. Environmental Toxicology and Chemistry 2000;19(4):1082-96.

14. Crabtree KD, Gerba CP, Rose JB, Haas CN. Waterborne adenovirus: A risk assessment. Water Science and Technology 1997;35(11-12):1-6.

15. Craig DL, Fallowfield HJ, Cromar NJ. Effectiveness of guideline faecal indicator organism values in estimation of exposure risk at recreational coastal sites. WATER-SCIENCE-AND-TECHNOLOGY 2003;47(3):191-8.

16. Crowther J, Kay D, Wyer MD. Faecal-Indicator Concentrations in Waters Draining Lowland Pastoral Catchments in the Uk: Relationships With Land Use and Farming Practices. Water Research 2002 Apr;36(7):1725-34.

17. Dabrowski JM, Peall SKC, Van Niekerk A, Reinecke AJ, Day JA, Schulz R. Predicting Runoff-Induced Pesticide Input in Agricultural Sub-Catchment Surface Waters: Linking Catchment Variables and Contamination. Water Research 2002 Dec;36(20):4975-84.

18. Dai X, Boll J. Evaluation of attachment of Cryptosporidium parvum and Giardia lamblia to soil particles. JOURNAL-OF-ENVIRONMENTAL-QUALITY 296;JAN-FEB 2003; 32:1.

19. Dewettinck T, VanHoutte E, Geenens D, VanHege K, Verstraete W. HACCP (Hazard Analysis and Critical Control Points) to guarantee safe water reuse and drinking water production - a case study. Water Science and Technology 2001;43(12):31-8.

20. Diaper C, Dixon A, Butler D, Fewkes A, Parsons SA, Strathern M, et al. Small scale water recycling systems - risk assessment and modelling. Water Science and Technology 2001;43(10):83-90.

21. Dong WQ, Yu ZB, Weber D. Simulations on soil water variation in and regions. JOURNAL-OF-HYDROLOGY 162;MAY 1 2003; 275:3-4.

22. Dunn AJ, Frodsham DA, Kilroy RV. Predicting the risk to permit compliance of new sewage treatment works. Water Science and Technology 1998;38(3):7-14.

23. Duran AE, Muniesa M, Moce Llivina L, Campos C, Jofre J, Lucena F. Usefulness of different groups of bacteriophages as model micro-organisms for evaluating chlorination. JOURNAL-OF-APPLIED-MICROBIOLOGY 2003;95(1):29-37.

24. Eisenberg JNS, Seto EYW, Colford JM, Olivieri A, Spear RC. An analysis of the Milwaukee cryptosporidiosis outbreak based on a dynamic model of the infection process. Epidemiology 1998;9(3):255-63.

25. Elliott AH. Prediction of illness risk near ocean outfalls using frequency distributions of bacterial concentrations . Water Research 1998; 32(10):3182-7.

26. Fane SA, Ashbolt NJ, White SB. Decentralised Urban Water Reuse: the Implications of System Scale for Cost and Pathogen Risk. Water Science and Technology 2002;46(6-7):281-8.

27. Fewtrell L, Macgill SM, Kay D, Casemore D. Uncertainties in risk assessment for the determination of drinking water pollutant concentrations: Cryptosporidium case study. Water Research 2001;35(2):441-7.

28. Fewtrell L, Macgill SM, Kay D. Copper in drinking water supplies and gastrointestinal illness in England and Wales: a risk assessment. JOURNAL-OF-WATER-SUPPLY-RESEARCH-AND-TECHNOLOGY-AQUA 449;DEC 2002; 51:8.

29. Foran J, Brosnan T, Connor M, Delfino J, DePinto J, Dickson K, et al. A framework for comprehensive, integrated, watershed monitoring in New York City. Environmental Monitoring and Assessment 2000;62(2):147-67.

30. Gale P. Developments in microbiological risk assessment for drinking water. Journal of Applied Microbiology 2001;91(2):191-205.

31. Gale P. Developments in microbiological risk assessment models for drinking water - A short review. Journal of Applied Bacteriology 1996;81(4):403-10.

32. Gale P. Risk assessment model for a waterborne outbreak of cryptosporidiosis. Water Science and Technology 2000;41(7):1-7.

33. Gale P. Simulating Cryptosporidium exposures in drinking water during an outbreak. Water Science and Technology 1998;38(12):7-13.

34. Gale P, Stanfield G. Cryptosporidium during a simulated outbreak. JOURNAL-AMERICAN-WATER-WORKS-ASSOCIATION 2000;SEP 2000; 92:: 105-16 .

35. Gale P, Young C, Stanfield G, Oakes D. A Review: Development of a risk assessment for BSE in the aquatic environment. Journal of Applied Microbiology 1998;84(4):467-77.

36. Gale P, Young R, Stanfield G., Oakes D. Development of a risk assessment for BSE in the aquatic environment. Journal of Applied Microbiology 1998 May;84(4):467-677.

37. Gammie AJ, WynJones AP. Does hepatitis A pose a significant health risk to recreational water users? Water Science and Technology 1997;35(11-12):171-7.

38. Garber WF. Wastewater treatment and risk assessment in ocean outfall evaluations. Water Science and Technology 1998;38(10):309-16.

39. Gerba CP, Pepper IL, Whitehead LF. A Risk Assessment of Emerging Pathogens of Concern in the Land Application of Biosolids. Water Science and Technology 2002;46(10):225-30.

40. Gerba CP, Rose JB, Haas CN, Crabtree KD. Waterborne rotavirus: A risk assessment. Water Research 1996;30(12):2929-40.

41. Gibson CJ, Haas CN, Rose JB. Risk assessment of waterborne protozoa: current status and future trends. Parasitology 1998;117:S205-S212.

42. Gitis V, Haught RC, Clark RM, Rothenberg G. Assessing the Removal of Inorganic Colloids and Cryptosporidium Parvum From Drinking Water. Journal of Environmental Monitoring 2002 Apr;4(2):244-8.

43. Gofti Laroche L, Demanse D, Joret JC, Zmirou D. Health risks and parasitical quality of water. JOURNAL-AMERICAN-WATER-WORKS-ASSOCIATION 162;MAY 2003; 95:5.

44. Golet EM, Alder AC, Giger W. Environmental Exposure and Risk Assessment of Fluoroquinolone Antibacterial Agents in Wastewater and River Water of the Glatt Valley Watershed, Switzerland. Environmental Science & Technology 2002 Sep;36(17):3645-51.

45. Gordon SI, Majumder S. Empirical stressor-response relationships for prospective risk analysis. Environmental Toxicology and Chemistry 2000;19(4):1106-12.

46. Gurian PL, Small MJ, Lockwood JR, Schervish MJ. Benefit-cost estimation for alternative drinking water maximum contaminant levels. Water Resources Research 2001;37(8):2213-26.

47. Gyurek LL, Finch GR. Modeling water treatment chemical disinfection kinetics. Journal of Environmental Engineering ASCE 1998;124(9):783-93.

48. Haas CN. Epidemiology, microbiology, and risk assessment of waterborne pathogens including Cryptosporidium. Journal of Food Protection 2000;63(6):827-31.

49. Haas CN, Anotai J, Engelbrecht RS. Monte Carlo assessment of microbial risk associated with landfilling of fecal material. Water Environment Research 1996;68(7):1123-31.

50. Haas CN, Crockett CS, Rose JB, Gerba CP, Fazil AM. Assessing the risk posed by oocysts in drinking water. Journal of the American Water Works Association. 1996;88(9):131-6.

51. Haas CN, Rose JB, Gerba C, Regli S. Risk assessment of virus in drinking water. Risk Analysis 1993; 13(5):545-52.

52. Haas CN, Trussell RR. Frameworks for assessing reliability of multiple, independent barriers in potable water reuse. Water Science and Technology 1998;38(6):1-8.

53. Hardalo C, Edberg SC. Pseudomonas aeruginosa: Assessment of risk from drinking water. Critical Reviews in Microbiology 1997;23(1):47-75.

54. Hauger MB, Rauch W, Linde JJ, Mikkelsen PS. Cost Benefit Risk - a Concept for Management of Integrated Urban Wastewater Systems? Water Science and Technology 2002;45(3):185-93.

55. Havelaar AH, DeHollander AEM, Teunis PFM, Evers EG, VanKranen HJ, Versteegh JFM, et al. Balancing the risks and benefits of drinking water disinfection: Disability adjusted life-years on the scale. Environmental Health Perspectives 2000;108(4):315-21.

56. Havelaar AHaJMM. Yes/REPORT/water/CB . Quantifying public health risks in the WHO Guidelines for Drinking Water Quality A burden of disease approach. Bilthoven, the Netherlands.: National Institute for Public Health and the Environment, RIVM , 2003. Report No.: 734301022.

57. Hitzfeld BC, Hoger SJ, Dietrich DR. Cyanobacterial toxins: Removal during drinking water treatment, and human risk assessment. Environmental Health Perspectives 2000;108:113-22.

58. Hoglund C, Stenstrom TA, Ashbolt N. Microbial Risk Assessment of Source-Separated Urine Used in Agriculture. Waste Management & Research 2002 Apr;20(2):150-61.

59. Jin G, Englande AJ, Liu A. A preliminary study on coastal water quality monitoring and modeling. JOURNAL-OF-ENVIRONMENTAL-SCIENCE-AND-HEALTH-PART-A-TOXICHAZARDOUS-SUBSTANCES-AND-ENVIRONMENTAL-ENGINEERING 493;2003; 38:3.

60. Johnson WP, Blue KA, Logan BE, Arnold RG . Modeling bacterial detachment during transport through porous media as a residence-time-dependent process. Water Resources Research 1995 Nov;31(11):2649-58.

61. Kistemann T, Classen T, Koch C, Dangendorf F, Fischeder R, Gebel J, et al. Microbial Load of Drinking Water Reservoir Tributaries During Extreme Rainfall and Runoff. Applied and Environmental Microbiology 2002 May;68(5):2188-97.

62. Lloyd A, Drury D. Continuous Monitoring for Cryptosporidium - a Novel Approach to Public Health Protection. Water Science and Technology 2002;46(11-12):297-301.

63. Loge FN, Thompson DE, Call DR. PCR detection of specific pathogens in water: A risk-based analysis. ENVIRONMENTAL-SCIENCE-AND-TECHNOLOGY 2002;JUN 15 2002; 36::2754-9 .

64. LopezPila JM, Szewzyk R. Estimating the infection risk in recreational waters from the faecal indicator concentration and from the ratio between pathogens and indicators. Water Research 2000;34(17):4195-200.

65. MacGill SM, Fewtrell L, Kay D. Towards quality assurance of assessed waterborne risks. Water Research 2000;34(3):1050-6.

66. Macler BA, Regli S. Use of Microbial Risk Assessment in Setting United-States Drinking Water Standards. International Journal of Food Microbiology 1993 Jun;18(4):245-56.

67. Mallin MA, Williams KE, Esham EC, Lowe RP. Effect of human development on bacteriological water quality in coastal watersheds. ECOLOGICAL-APPLICATIONS 2000 Aug;10(4):1047-56.

68. Maxwell RM, Kastenberg WE, Rubin Y. A methodology to integrate site characterization information into groundwater-driven health risk assessment. Water Resources Research 1999;35(9):2841-55.

69. McAvoy DC, Masscheleyn P, Peng C, Morrall SW, Casilla AB, Lim JMU, et al. Risk assessment approach for untreated wastewater using the QUAL2E water quality model. CHEMOSPHERE- 1955;JUL 2003; 52:1.

70. McKay J, Moeller A. Is risk associated with drinking water in Australia of significant concern to justify mandatory regulation? Environmental Management 2001;28(4):469-81.

71. Medema GJ, Hoogenboezm W, van der Veer AJ, Ketelaars HAM, Hilnen WAM, Nobel PJ. Quantitative risk assessment of Cryptosporidium in surface water treatment. WATER-SCIENCE-AND-TECHNOLOGY 2003;47(3):241-7.

72. Mena KD, Gerba CP, Haas CN. Risk assessment of waterborne coxsackievirus. Journal of the American Water Works Association. 2003;95(7):122-31.

73. Morris BL, Foster SSD. Cryptosporidium contamination hazard assessment and risk management for British groundwater sources. Water Science and Technology 2000;41(7):67-77.

74. Mota P, Rauch C, Edberg SC. Microsporidia and Cyclospora: Epidemiology and assessment of risk from the environment. Critical Reviews in Microbiology 2000;26(2):69-90.

75. Mugglestone MA, Stutt ED, Rushton L. Setting microbiological water quality standards for sea bathing - a critical evaluation. Water Science and Technology 2001;43(12):9-18.

76. Mukhtasor, Husain T, Lye LM, Sharp JJ. Human health risk-based design of ocean outfalls. PROCEEDINGS-OF-THE-INSTITUTION-OF-CIVIL-ENGINEERS-WATER-AND-MARITIME-ENGINEERING 1929;MAR 2002; 154:1.

77. Muslu Y. Kinetics of biofilms in unsaturated granular media. Journal of Environmental Engineering - ASCE 1995 Jan;121(1):66-83.

78. Neumann DA, Foran JA. Assessing the risks associated with exposure to waterborne pathogens: An expert panel's report on risk assessment. Journal of Food Protection 1997;60(11):1426-31.

79. Njemanze PC, Anozie J, Ihenacho JO, Russell MJ, Uwaeziozi AB. Application of risk analysis and geographic information system technologies to the prevention of diarrheal diseases in Nigeria. AMERICAN-JOURNAL-OF-TROPICAL-MEDICINE-AND-HYGIENE 1999 Sep;61(3):356-60.

80. Nnadi FN, Fulkerson M. Assessment of groundwater under direct influence of surface water. JOURNAL-OF-ENVIRONMENTAL-SCIENCE-AND-HEALTH-PART-A-TOXICHAZARDOUS-SUBSTANCES-AND-ENVIRONMENTAL-ENGINEERING 2002;37(7):1209-22.

81. Odom R, Regli S, Messner M, Cromwell J, Javdan M. Benefit-cost analysis of the stage 1D/DBP rule. JOURNAL-AMERICAN-WATER-WORKS-ASSOCIATION 1999;91:137-47.

82. Ottoson J, Stenstrom TA. Faecal Contamination of Greywater and Associated Microbial Risks. Water Research 2003 Feb;37(3):645-55.

83. Parkin RT, Soller JA, Olivieri AW, INGA Study Grp. Incorporating susceptible subpopulations in microbial risk assessment: pediatric exposures to enteroviruses in river water. JOURNAL-OF-EXPOSURE-ANALYSIS-AND-ENVIRONMENTAL-EPIDEMIOLOGY 2003 Mar;13(2):161-8.

84. Payment P. Epidemiology of endemic gastrointestinal and respiratory diseases: Incidence, fraction attributable to tap water and costs to society. Water Science and Technology 1997;35(11-12):7-10.

85. Payment P, Berte A, PrTvost M, MTnard B , Barbeau B. Occurrence of pathogenic microorganisms in the Saint Lawrence River (Canada) and comparison of health risks for populations using it as their source of drinking water. Canadian Journal of Microbiology 2000;46(6):565-76.

86. Perz JF, Ennever FK, LeBlancq SM. Cryptosporidium in tap water: Comparison of predicted risks with observed levels of disease. American Journal of Epidemiology 1998;147(3):289-301.

87. Petterson SR, Ashbolt NJ. Viral risks associated with wastewater reuse: modeling virus persistence

on wastewater irrigated salad crop. Water Science and Technology 2001;43(12):23-6.

88. Petterson SR, Ashbolt NJ, Sharma A. Microbial Risks From Wastewater Irrigation of Salad Crops: a Screening-Level Risk Assessment. Water Environment Research 2001 Nov-2001 Dec;72(6):667-72.

89. Pinsky PF. Assessment of risk from long term exposure to waterborne pathogens. Environmental and Ecological Statistics 2000;7(2):155-75.

90. Pollard SJ, Harrop DO, Crowcroft P, Mallett SH, Jeffries SR, Young PJ. Risk assessment for environmental management: Approaches and applications. Journal of the Chartered Institution of Water and Environmental Management 1995 Dec;9(6):621-8.

91. Quevedo F, Arambulo P, Escalante JA, Estupinan J, Almeida C, Cuellar J. Risks of transmitting cholera through fishery products: the regional perspective of South America. Revue Scientifique Et Technique De L Office International Des Epizooties 1997;16(2):673-83.

92. Rai SN, Bartlett S, Krewski D, Paterson J. The Use of Probabilistic Risk Assessment in Establishing Drinking Water Quality Objectives. Human and Ecological Risk Assessment 2002 Apr;8(3):493-509.

93. Regli S, Odom R, Cromwell J, Lustic M, Blank V. Benefits and costs of the IESWTR. JOURNAL-AMERICAN-WATER-WORKS-ASSOCIATION 1999; 91:148-58 .

94. Regli S, Rose JB, Haas CN, Gerba CP. Modeling the risk from Giardia and viruses in drinking water. Journal of the American Water Works Association 1991;83(11):76-84.

95. Rose JB, Haas CN, Regli S. Risk assessment and control of waterborne giardiasis. American Journal of Public Health 1991;81(6):709-13.

96. Rose JB, Daeschner S, Easterling DR, Curriero FC, Lele S, Patz JA. Climate and waterborne disease outbreaks. JOURNAL-AMERICAN-WATER-WORKS-ASSOCIATION 2000;SEP 2000; 92:: 77-87 .

97. Rose JB, Gerba CP. Use of Risk Assessment for Development of Microbial Standards. Water Science and Technology 1991;24(2):29-34.

98. Sadiq R, Husain T, Al-Zahrani AM, Sheikh AK, Farooq S. Secondary Effluent Treatment by Slowsand Filters: Performance and Risk Analysis. Water Air and Soil Pollution 2003 Feb;143(1-4):41-63.

99. Sadiq R, Husain T, Kar S. Chloroform Associated Health Risk Assessment Using Bootstrapping: a Case Study for Limited Drinking Water Samples. Water Air and Soil Pollution 2002 Jul;138(1-4):123-40.

100. Sanders BF, Green CL, Chu AK, Grant SB. Case study: Modeling tidal transport of urban runoff in channels using the finite-volume method. JOURNAL-OF-HYDRAULIC-ENGINEERING-ASCE 2001;OCT 2001; 127:: 795-804 .

101. Schmidt W, Willmitzer H, Bornmann K, Pietsch J. Production of Drinking Water From Raw Water Containing Cyanobacteria - Pilot Plant Studies for Assessing the Risk of Microcystin Breakthrough. Environmental Toxicology 2002 Aug;17(4):375-85.

102. Schwartz J, Levin R, Goldstein R. Drinking water turbidity and gastrointestinal illness in the elderly of Philadelphia. Journal of Epidemiology and Community Health 2000;54(1):45-51.

103. Schwartz J, Levin R, Hodge K. Drinking water turbidity and pediatric hospital use for gastrointestinal illness in Philadelphia. Epidemiology 1997;8(6):615-20.

104. Seto E, Xu B, Liang S, Gong P, Wu WP, Davis G, et al. The use of remote sensing for predictive modeling of schistosomiasis in China. PHOTOGRAMMETRIC-ENGINEERING-AND-REMOTE-SENSING 2002;FEB 2002; 68:: 167-74 .

105. Shuval H, Lampert Y, Fattal B. Development of a risk assessment approach for evaluating wastewater reuse standards for agriculture. Water Science and Technology 1997;35(11-12):15-20.

106. Smith EP, Ye KY, Hughes C, Shabman L . Statistical assessment of violations of water quality standards under section 303(d) of the clean water act. ENVIRONMENTAL-SCIENCE-AND-TECHNOLOGY 606;FEB 1 2001; 35:3.

107. Soller JA, Olivieri AW, Crook J, Cooper RC, Tchobanoglous G, Parkin RT, et al. Risk-based approach to evaluate the public health benefit of additional wastewater treatment. ENVIRONMENTAL-SCIENCE-AND-TECHNOLOGY 1882;MAY 1 2003; 37:9.

108. Stewart MH, Yates MV, Anderson MA, Gerba CP, Rose JB, De Leon R, et al. Predicted public health consequences of body-contact recreation on a potable water reservoir. JOURNAL-AMERICAN-WATER-WORKS-ASSOCIATION 2002;MAY 2002; 94:: 84-97 .

109. Tanaka H, Asano T, Schroeder ED, Tchobanoglous G. Estimating the safety of wastewater reclamation and reuse using enteric virus monitoring data. Water Environment Research 1998;70(1):39-51.

110. Teunis PFM, Havelaar AH. Risk Assessment for Protozoan Parasites. International Biodeterioration & Biodegradation 2002;50(3-4):185-93.

111. Teunis PFM, Medema GJ, Kruidenier L, Havelaar AH. Assessment of the risk of infection by Cryptosporidium or Giardia in drinking water from a surface water source. Water Research 1997;31(6):1333-46.

112. Tian YQ, Gong P, Radke JD, Scarborough J. Spatial and Temporal Modeling of Microbial Contaminants on Grazing Farmlands. Journal of Environmental Quality 2002 May-2002 Jun;31(3):860-9.

113. vanGinneken M, Oron G. Risk assessment of consuming agricultural products irrigated with reclaimed wastewater: An exposure model. Water Resources Research 2000;36(9):2691-9.

114. Walker FR, Stedinger JR. Fate and transport model of Cryptosporidium. Journal of Environmental Engineering ASCE 1999;125(4):325-33.

115. Wang TA, Mcternan WF. The Development and Application of a Multilevel Decision Analysis Model for the Remediation of Contaminated Groundwater Under Uncertainty. Journal of Environmental Management 2002 Mar;64(3):221-35.

116. Westrell T, Bergstedt O, Stenstrom TA, Ashbolt NJ. A theoretical approach to assess microbial risks due to failures in drinking water systems. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2003 Jun;13:181-97.

117. Willems P, Berlamont J. Probabilistic Emission and Immission Modelling: Case-Study of the Combined Sewer - Wwtp - Receiving Water System at Dessel (Belgium). Water Science and Technology 2002;45(3):117-24.

118. Wong HS, Yeh WWG. Uncertainty Analysis in Contaminated Aquifer Management. Journal of Water Resources Planning and Management-Asce 2002 Jan-2002 Feb;128(1):33-45.

119. Woo DM, Vicente KJ. Sociotechnical systems, risk management, and public health: comparing the North Battleford and Walkerton outbreaks. RELIABILITY-ENGINEERING-AND-SYSTEM-SAFETY 253;JUN 2003; 80:3.

1.4.3 Food Risk Assessment Publications captured under the food risk assessment compilation demonstrate the increasing efforts in this field. Approximately one-third of 77 papers address both exposure models and dose-response relations to estimate human-health impacts associated with foods, dating from earlier semi-quantitative treatments of information ((Todd, 1996)) on risk of salmonellosis attributable to use of cracked eggs in Canada, ranking of microbial hazards associated with seafoods ((Huss et al., 2000)), quantitaive assessment of risk of campylocteriosis from shellfish ((Teunis et al., 1997)) through one of the first farm-to-fork probabilistic models ((Cassin et al., 1998)) for E. coli 0157:H7 in ground beef, when the term “Process Risk Model” was introduced, and to addressing current regulatory concerns for Salmonella entertidus in eggs ((Hope et al., 2002) and others) and Listeria monocytogenes in ready-to-eat foods ((Chen et al., 2003)). Health impacts due to accidental contamination of animal feeds with dioxins ((Stark et al., 2002)), and exposure to the BSE agent in foods or water sources ((Ferguson NM et al., 2002); (Gale, 1998a)) have also been quantified, under specific scenarios. In this general category, investigators also have applied systematic quantitative approaches to analysing potential exposures to pathogens, particularly in the context of improving meat inspection practices. Although a number of general reviews of data gaps and limitations for risk assessment in different commodity groups, of note are the very few publications examining some of the critical data gaps and assumptions used in available quantitative risk assessments; for example, (Barber et al., 2003) examine assumptions and practical applications of risk models of antimicrobial resistance and foodborne illness. These types of critiques are needed to advance QRA as a discipline, help strengthen future assessment work, and ideally provide more robust foundations for risk management decision-making, particularly in a regulatory context. However, a lack of such critiques also reflects the paucity of fully developed quantitative risk assessments in food safety. 1. Adams M, Mitchell R. Fermentation and Pathogen Control: a Risk Assessment Approach.

International Journal of Food Microbiology 2002 Nov;79(1-2):75-83.

2. Ahmed FE. Review - assessing and managing risk due to consumption of seafood contaminated with micro-organisms, parasites, and natural toxins in the united-states. Int J Food Sci Technol 1992;27(3):243-60.

3. Alban L, Olsen AM, Nielsen B, Sorensen R, Jessen B. Assessment of the human risk associated with use of pork with possible presence of Salmonella Typhimurium DT104 for dry-cured sausages. BERLINER-UND-MUNCHENER-TIERARZTLICHE-WOCHENSCHRIFT 2001 Sep-2001 Oct;114(9-10):366-9.

4. Alban L, Olsen AM, Nielsen B, Sorensen R, Jessen B. Qualitative and Quantitative Risk Assessment

for Human Salmonellosis Due to Multi-Resistant Salmonella Typhimurium Dt104 From Consumption of Danish Dry-Cured Pork Sausages. Preventive Veterinary Medicine 2002 Jan;52(3-4):251-65.

5. Anderson SA, Woo RWY, Crawford LM. Risk assessment of the impact on human health of resistant Campylobacter jejuni from fluoroquinolone use in beef cattle. Food Control 2001;12(1):13-25.

6. Barber DA, Miller GY, McNamara PE, ERRC Special Projects Team. Models of antimicrobial resistance and foodborne illness: Examining assumptions and practical applications. JOURNAL OF FOOD PROTECTION 2003 Apr;66(4):700-9.

7. Barker GC, Talbot NLC, Peck MW. Risk Assessment for Clostridium Botulinum: a Network Approach. International Biodeterioration & Biodegradation 2002;50(3-4):167-75.

8. Bemrah N, Bergis H, Colmin C, Beaufort A, Millemann Y, Dufour B, et al. Quantitative Risk Assessment of Human Salmonellosis From the Consumption of a Turkey Product in Collective Catering Establishments. International Journal of Food Microbiology 2003 Jan;80(1):17-30.

9. Berends BR, Van Knapen F, Mossel DAA, Burt SA, Snijders JMA. Impact on human health of Salmonella spp. on pork in The Netherlands and the anticipated effects of some currently proposed control strategies. International Journal of Food Microbiology 1998;44(3):219-29.

10. Berends BR, vanKnapen F. An outline of a risk assessment-based system of meat safety assurance and its future prospects. Veterinary Quarterly 1999;21(4):128-34.

11. Bisaillon JR, Feltmate TE, Sheffield S, Julian R, Todd E, Poppe C, et al. Classification of Grossly Detectable Abnormalities and Conditions Seen at Postmortem in Canadian Poultry Abattoirs According to a Hazard Identification Decision Tree. Journal of Food Protection 2001 Dec;64(12):1973-80.

12. Brown MH. Quantitative Microbiological Risk Assessment: Principles Applied to Determining the Comparative Risk of Salmonellosis From Chicken Products. International Biodeterioration & Biodegradation 2002;50(3-4):155-60.

13. Brown MH, Davies KW, Billon CMP, Adair C, McClure PJ. Quantitative microbiological risk assessment: Principles applied to determining the comparative risk of salmonellosis from chicken products. Journal of Food Protection 1998;61(11):1446-53.

14. Buchanan RL. Comparison of the U.S. and FAO/WHO Listeria monocytogenes Risk Assessments. 2003 CSL/JIFSAN Joint Symposium - Food Safety and Nutrition: Risk Analysis 2003.

15. Buchholz U, Run G, Kool JL, Fielding J , Mascola L. A Risk-Based Restaurant Inspection System in Los Angeles County. Journal of Food Protection 2002 Feb;65(2):367-72.

16. Carlin F, Girardin H, Peck MW, Stringer SC, Barker GC, Martinez A, et al. Research on factors allowing a risk assessment of spore-forming pathogenic bacteria in cooked chilled foods containing vegetables: a FAIR collaborative project. International Journal of Food Microbiology 2000;60(2-3):117-35.

17. Cassin MH, Lammerding AM, Todd ECD, Ross W, McColl RS. Quantitative risk assessment for Escherichia coli O157:H7 in ground beef hamburgers. International Journal of Food Microbiology 1998;41(1):21-44.

18. Caya F, Fairbrother JM, Lessard L, Quessy S. Characterization of the risk to human health of pathogenic Escherichia coli isolates from chicken carcasses. Journal of Food Protection 1999;62(7):741-6.

19. Chen YH, Ross EH, Scott VN, Gombas DE . Listeria monocytogenes: Low levels equal low risk. JOURNAL OF FOOD PROTECTION 2003 Apr;66(4):570-7.

20. Den Aantrekker ED, Boom RM, Zwietering MH, Van Schothorst M. Quantifying Recontamination Through Factory Environments - a Review. International Journal of Food Microbiology 2003 Jan;80(2):117-30.

21. Dennis SB. Prioritizing Food Safety Risk Assessments: A New Approach. Food Safety Magazine 2003 Apr-2003 May;9(2):18-21.

22. Duffy S, Schaffner DW. Monte Carlo Simulation of the Risk of Contamination of Apples With Escherichia Coli O157 : H7. International Journal of Food Microbiology 2002 Oct;78(3):245-55.

23. Elliot EL, Kvenberg JE. Risk assessment used to evaluate the US position on Listeria monocytogenes in seafood. International Journal of Food Microbiology 2000;62(3):253-60.

24. Farber JM, Ross WH, Harwig J. Health risk assessment of Listeria monocytogenes in Canada. International Journal of Food Microbiology 1996;30(1-2):145-56.

25. Fazil AM, Lowman R, Stern N, Lammerding AM. A Quantitative Risk Assessment Model for C. jejuni in Fresh Poultry (Draft research project between Health Canada, Canadian Food Inspection Agency and United States Department of Agriculture). Yes/REPORT/foodRA: 1999.

26. Fazil AM, Ross T, Paoli G, Vanderlinde P, Desmarchelier P, Lammerding AM. A Probabilistic Analysis of Clostridium Perfringens Growth During Food Service Operations. International Journal of Food Microbiology 2002 Mar;73(2-3):315-29.

27. Ferguson NM, Ghani AC, Donnelly CA, Hagenaars TJ, Anderson RM. Estimating the human health risk from possible BSE infection of the British sheep flock. NATURE 2002;JAN 24 2002; 415:420-4.

28. Galbraith H. Hormones in International Meat Production: Biological, Sociological and Consumer Issues. Nutrition Research Reviews 2002 Dec;15(2):293-314.

29. Gale P. Quantitative BSE risk assessment: relating exposures to risk. Letters in Applied Microbiology 1998;27(5):239-42.

30. Gale P. Using Event Trees to Quantify Pathogen Levels on Root Crops From Land Application of Treated Sewage Sludge. Journal of Applied Microbiology 2003;94(1):35-47.

32. Goettsch W, Degener JE. Health council report 'Antimicrobial growth promoters'. Tijdschrift Voor Diergeneeskunde 1999;124(5):142-4.

33. Goga BTC, Clementi F. Safety Assurance of Foods: Risk Management Depends on Good Science but It Is Not a Scientific Activity. Journal of Agricultural & Environmental Ethics 2002 Fall;15(3):305-13.

34. Hamilton DR, Gallas P, Lyall L, Lester S, Mcorist S, Hathaway SC, et al. Risk-Based Evaluation of Postmortem Inspection Procedures for Pigs in Australia . Veterinary Record 2002 Jul;151(4):110-6.

35. Hartnett E, Kelly L, Newell D, Wooldridge M, Gettinby G. A Quantitative Risk Assessment for the Occurrence of Campylobacter in Chickens at the Point of Slaughter. Epidemiology and Infection 2001 Oct;127(2):195-206.

36. Hartnett E, Kelly LA, Gettinby G, Wooldridge M. A Quantitative Risk Assessment for Campylobacters in Broilers: Work in Progress. International Biodeterioration & Biodegradation 2002;50(3-4):161-5.

37. Health Canada. Risk assessment model for Salmonella Enteritidis (Paoli, G. Unpublished Report). Yes/REPORT/foodRA: 2000.

38. Henken AM, Havelaar AW, Van de Giessen AW, Teunis PFM, Nauta MJ. Risks of pathogens in meat and poultry causing human gasto-enteritis. National Institute for Public Health and the Environment 1997 Jun.

39. Hitchins AD, Whiting RC. Food-Borne Listeria Monocytogenes Risk Assessment . Food Additives and Contaminants 2001 Dec;18(12):1108-17.

40. Hoglund C, Stenstrom TA, Ashbolt N. Microbial Risk Assessment of Source-Separated Urine Used in Agriculture. Waste Management & Research 2002 Apr;20(2):150-61.

41. Hogue A, Akkina J, Angulo F, Johnson R, Petersen K, Saini P, et al. Situation Assessment: Salmonella typhimurium 1041997.

42. Hogue A, White P, Guard-Petter J, Schlosser W, Gast R, Ebel E, et al. Epidemiology and control of egg-associated Salmonella Enteritidis in the United States of America. Revue Scientifique Et Technique De L Office International Des Epizooties 1997;16(2):542-53.

43. Hope BK, Baker AR, Edel ED, Hogue AT, Schlosser WD, Whiting R, et al. An Overview of the Salmonella enteritis Risk Assessment for Shell Eggs and Egg Products. Risk Analysis 2002;22(2):203-18.

44. Huss HH, Reilly A, BenEmbarek PK. Prevention and control of hazards in seafood. Food Control 2000;11(2):149-56.

45. Jaykus LA. The application of quantitative risk assessment to microbial food safety risks. Critical Reviews in Microbiology 1996;22(4):279-93.

46. Kamphues J, Zentek J, Oberthur RC, Flachowsky G, Coenen M. Risk assessment for animal derived feedstuffs as vectors for bovine spongiform encephalopathy (BSE) in Germany. Part I: Comparative risk assessment for animal derived feedstuffs. Deutsche Tierarztliche Wochenschrift 2001;108(7):283-90.

47. Kuiper HA, Kleter GA, Noteborn HPJM, Kok EJ. Assessment of the food safety issues related to genetically modified foods. Plant Journal 2001;27(6):503-28.

48. Lee RJ, Younger AD. Developing Microbiological Risk Assessment for Shellfish Purification. International Biodeterioration & Biodegradation 2002;50(3-4):177-83.

49. Lindqvist R, Sylven S, Vagsholm I. Quantitative Microbial Risk Assessment Exemplified by Staphylococcus Aureus in Unripened Cheese Made From Raw Milk. International Journal

of Food Microbiology 2002 Sep;78(1-2):155-70.

50. Lindqvist R, Westoo A. Quantitative risk assessment for Listeria monocytogenes in smoked or gravad salmon and rainbow trout in Sweden. International Journal of Food Microbiology 2000;58(3):181-96.

51. Marie JR, Hass CN, Rose JB, Gerba CP. Quantitative Assessment of Benefits from Using Topical Antimicrobial Hand Products: Case Study on E. coli Risk from Handling Raw Beef. Society for Risk Analysis 2002 Annual Meeting 2002.

52. Marsden JL, Phebus RK, Thippareddi H, Kastner CJ, Gosch JB. Salmonella spp. and Listeria monocytogenes Risk Assessment for Production and Cooking of Blade Tenderized Beef Steaks2001 Jun.

53. McElroy DM, Jaykus LA, Foegeding PM. A quantitative risk assessment for Bacillus cereus emetic disease associated with the consumption of Chinese-style rice. Journal of Food Safety 1999;19(3):209-29.

54. McElroy DM, Jaykus LA, Foegeding PM. Validation and analysis of modeled predictions of growth of Bacillus cereus spores in boiled rice. Journal of Food Protection 2000;63(2):268-72.

55. Miller AJ, Whiting RC, Smith JL. Use of risk assessment to reduce listeriosis incidence. Food Technology 1997;51(4):100-3.

56. Nauta MJ, VandeGiessen AW, Henken AM. A model for evaluating intervention strategies to control salmonella in the poultry meat production chain. Epidemiology and Infection 2000;124(3):365-73.

57. Norrung B. Microbiological criteria for Listeria monocytogenes in foods under special consideration of risk assessment approaches. International Journal of Food Microbiology 2000;62(3):217-21.

58. Notermans S, Batt CA. A risk assessment approach for foodborne Bacillus cereus and its toxins. Journal of Applied Microbiology 1998;84:S51-S61.

59. Notermans S, Dufrenne J, Teunis P, Beumer R, te Giffel M, Peeters Weem P. A risk assessment study of Bacillus cereus present in pasteurized milk. Food Microbiology 1997;14(2):143-51.

60. Notermans S, Dufrenne J, Teunis P, Chackraborty T. Studies on the risk assessment of Listeria monocytogenes. Journal of Food Protection 1998;61(2):244-8.

61. Notermans S, Hoornstra E. Risk assessment of Listeria monocytogenes in fish products: some general principles, mechanism of infection and the use of performance standards to control human exposure. International Journal of Food Microbiology 2000;62(3):223-9.

62. Notermans S, Nauta MJ, Jansen J, Jouve JL, Mead GC. A risk assessment approach to evaluating food safety based on product surveillance. Food Control 1998;9(4):217-23.

63. Oscar TP. The development of a risk assessment model for use in the poultry industry. Journal of Food Safety 1998;18(4):371-81.

64. Petterson SR, Ashbolt NJ. Viral risks associated with wastewater reuse: modeling virus persistence on wastewater irrigated salad crop. Water Science and Technology 2001;43(12):23-6.

65. Petterson SR, Ashbolt NJ, Sharma A. Microbial Risks From Wastewater Irrigation of Salad Crops: a Screening-Level Risk Assessment. Water Environment Research 2001 Nov-2001 Dec;72(6):667-72.

66. Pointon AM, Hamilton D, Kolega V, Hathaway S. Risk assessment of organoleptic postmortem inspection procedures for pigs. Veterinary Record 2000;146(5):124-31.

68. Ranta J, Maijala R. A Probabilistic Transmission Model of Salmonella in the Primary Broiler Production Chain. Risk Analysis 2002;22(1):47-58.

69. Rosenquist H, Nielsen NL, Sommer HM, Norrung B, Christensen BB. Quantitative risk assessment of human campylobacteriosis associated with thermophilic Campylobacter species in chickens. INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY 2003;83:87-103.

70. Schlosser W, Ebel E. Use of a Markov-chain Monte Carlo model to evaluate the time value of historical testing information in animal populations. Preventive Veterinary Medicine 2001;48(3):167-75.

72. Sischo WM, Kiernan NE, Burns CM, Byler LI. Implementing a quality assurance program using a risk assessment tool on dairy operations. Journal of Dairy Science 1997;80(4):777-87.

73. Stark KDC, Boyd HB, Mousing J. Risk Assessment Following the Hypothetical Import of Dioxin-Contaminated Feed for Pigs - an Example of Quantitative Decision-Support Under Emergency Conditions. Food Control 2002 Jan;13(1):1-11.

74. TaljanskiZygmunt W, Grzesiuk E, Zabielski R, Pierzynowski SG. Is the use of antimicrobial drugs in agriculture risky for human health? Journal of Animal and Feed Sciences 1998;7:289-95.

76. Teunis P, Havelaar A, Vliegenthart J, Roessink C. Risk assessment of Campylobacter species in shellfish: Identifying the unknown. Water Science and Technology 1997;35(11-12):29-34.

77. Thippareddi H, Lambert D, Phebus RK, Marsden JL, Kastner CL, Boyle EAE, et al. Salmonella Risk Assessment for Blade Tenderized, Immersion Marinated, Needle Injected and Fibrinogen Processed Pork Cuts during Processin Storage and Cooking2000 Feb.

78. Todd ECD. Risk assessment of use of cracked eggs in Canada. International Journal of Food Microbiology 1996;30(1-2):125-43.

79. USDA. Draft Risk Assessment of the Public Health Impact of Escherichia coli: Hazard Identification2001.

80. USDA. Yes/REPORT/foodRA. Risk assessment of E.coli 0157:H7 in ground beef. Washington, DC.: USDA, 2001.

81. USDA. Yes/REPORT/foodRA. Salmonella Enteritidis risk assessment in shell eggs and egg products. Washington, DC. USDA, 1998.

82. vanderLogt PB, Hathaway SC, Vose DJ. Risk assessment model for human infection with the cestode Taenia saginata. Journal of Food Protection 1997;60(9):1110-9.

84. Vose DJ. The application of quantitative risk analysis to microbial food safety. Journal of Food Protection 1997;60(11):1416-.

85. Vose DJ. The application of quantitative risk assessment to microbial food safety. Journal of Food Protection 1998;61(5):640-8.

86. Whiting RC, Buchanan RL. Development of a quantitative risk assessment model for Salmonella enteritidis in pasteurized liquid eggs. International Journal of Food Microbiology 1997;36(2-3):111-25.

87. Whitting RC, Hogue A, Schlosser WD, Ebel ED, Morales RA, Baker A, et al. A quantitative process model for Salmonella enteritidis in shell eggs. Journal of Food Science 2000; 65(5):864-9.

88. WHO/FAO. Microbiological Risk Assessment Series, No. 1. Risk assessments for Salmonella in eggs and broiler chickens. Food and Agriculture Organization of the United Nations and World Health Organization., 2002.

89. WHO/FAO. Microbiological Risk Assessment Series, No. 2. Risk assessments for Salmonella in eggs and broiler chickens. Food and Agriculture Organization of the United Nations and World Health Organization. 2002.

90. Williams RA, Zorn DJ. Hazard analysis and critical control point systems applied to public health risks: the example of seafood. Revue Scientifique Et Technique De L Office International Des Epizooties 1997;16(2):349-58.

1.4.4 Antimicrobial Resistance An increasing concern globally, countries are taking a risk analysis approach to the impacts of antimicrobial resistant pathogens in primarily food sources. Few quantitative risk assessment models have been developed, with only 2 publications quantifying potential exposure with human health risk ((Alban et al., 2002), on Salmonella DT104 in pork sausages; (Anderson et al., 2001), on flouroquinolone-resistant Campylobacter jejuni in beef) (A note: 2 additional quantitative assessments have also been developed under the US regulatory system for fluoroquinolone use in poultry; these are available on the FDA website: www.fda.gov.). A number (7 papers) address current issues, and identify data needs for quantitative risk assessment; an additional 5 describe specific data gathering programs in various countries, surveillance and laboratory methods. One publication describes a risk framework to integrate risk assessments for the interrelated hazards: induction of resistance by an antimicrobial agent; the specific pathogen; and horizontal gene transfer of resistance between microbial populations, indicating the complexity of conducting risk assessments in this area. Three risk assessments for exposure to antimicrobial agents/residues in foods and water are also noted.

1. Acar J, Rostel B. Antimicrobial resistance: an overview. REVUE-SCIENTIFIQUE-ET-TECHNIQUE-DE-L-OFFICE-INTERNATIONAL-DES-EPIZOOTIES 2001 Dec;20(3):797-810.

2. Akwar T, Wilson J, Poppe C, Quessy S, McEwen S. Risk Assessment of Antimicrobial Resistance of Food Borne Enterobacteriaceae in Human and Pig Populations. OMAF Managing Antimicrobial Resistance Conference, Toronto, Oct 24-26, 1999 1999;[Poster].

3. Alban L, Olsen AM, Nielsen B, Sorensen R, Jessen B. Qualitative and Quantitative Risk Assessment for Human Salmonellosis Due to Multi-Resistant Salmonella Typhimurium Dt104 From Consumption of Danish Dry-Cured Pork Sausages. Preventive Veterinary Medicine 2002 Jan;52(3-4):251-65.

4. Anderson SA, Woo RWY, Crawford LM. Risk assessment of the impact on human health of resistant Campylobacter jejuni from fluoroquinolone use in beef cattle. Food Control 2001;12(1):13-25.

6. Bertolatti D, Munyard SJ, Grubb WB, Binns CW. Thermal inactivation of antimicrobial-resistant Gram-positive cocci in chicken meat: D and Z value determinations. INTERNATIONAL-JOURNAL-OF-ENVIRONMENTAL-HEALTH-RESEARCH 2001 Sep;11(3):257-66.

7. Burch DGS. Risk Assessment: Campylobacter infection transmission from pigs to man using erythromycin resistance as a marker. Paper Given at the International Conference on Antimicrobial Agents in Veterinary Medicine, Helsinki, Finland, August, 2002. 2002.

8. Charlett A, Cowden JM, Frost JA, Gillespie IA, Millward J, Neal KR, et al. Ciprofloxacin resistance in Campylobacter jejuni: case-case analysis as a tool for elucidating risks at home and abroad. JOURNAL-OF-ANTIMICROBIAL-CHEMOTHERAPY 2002 Oct;50(4):561-8.

9. Claycamp HG. Case Studies in Antimicrobial Resistance Risk Analysis. 2003 CSL/JIFSAN Joint Symposium - Food Safety and Nutrition: Risk Analysis 2003.

10. Davison J. Genetic exchange between bacteria in the environment. PLASMID 1999 Sep;42(2):73-91.

11. Dyke TM. Regulation of veterinary antibiotics in Australia. Communicable Diseases Intelligence 2003 May;27(Suppl):S6-S8.

12. EMEA. EMEA Discussion Paper on Antimicrobial Resistance1999 Mar;EMEA/9880/99, Rev. 1.

13. EMEA. EMEA Risk Assessment on Antimicrobial Resistance in Veterinary Medicine1999.

14. EMEA. Implementation of the Note for Guidance on Risk Analysis Approach for Residues of Veterinary Medicinal Products in Food of Animal Origin2002.

15. FAO. Discussion Paper: Risk Profile on the Antimicrobial Resistant Bacteria in Food (Agenda Item 11) .

16. FDA. The Human Health Impact of Fluoroquinolone Resistant Campylobacter Attributed to the Consumption of Chicken2000.

17. FDA. @Risk Model: Analysis of the human health effect of fluoroquinolone resistant Campylobacter in domestically reared and consumed broilers .

18. Ferenc S, McElvaine M, Miller M. Risk assessment and cost-benefit issues associated with antimicrobial use. The Role of Veterinary Therapeutics in Bacterial Resistance Development: Animal and Public Health Perspectives. The American Academy of Veterinary Pharmacology and Therapeutics. 1998 Jan.

19. Franklin A, Acar J, Anthony F, Gupta R, Nicholls T, Tamura Y, et al. Antimicrobial resistance: harmonisation of national antimicrobial resistance monitoring and surveillance programmes in animals and in animal-derived food. REVUE-SCIENTIFIQUE-ET-TECHNIQUE-DE-L-OFFICE-INTERNATIONAL-DES-EPIZOOTIES 2001 Dec;20(3):859-70.

20. Friedlander LG, Brynes SD, Fernandez AH. The human food safety evaluation of new animal drugs. VETERINARY-CLINICS-OF-NORTH-AMERICA-FOOD-ANIMAL-PRACTICE 1999 Mar;15(1):1-11,VII.

22. Gray JT, Fedorka CPJ. Antimicrobial resistance in commensal and pathogenic bacteria from swine and their implications for the swine industry. Journal of Animal Science / Journal of Dairy Science 2003;81 / 86(Suppl 1 / Suppl 1).

23. Guillemot D. Antibiotic use in humans and bacterial resistance. Current Opinion in Microbiology 1999;2(5):494-8.

24. Health Canada. Antimicrobial Resistance: A Deadly Burden No Country Can Afford to Ignore. Canada Communicable Disease Report 2003 Sep;29-18.

25. Health Canada. Uses of Antimicrobials in Food Animals in Canada: Impact on Resistance and Human Health. Report of the Advisory Committee on Animal Uses of Antimicrobials and Impact on Resistance and Human Health. Prepared for: Veterinary Drugs Directorate, Health Canada. 2002 Jun.

26. Hollinger K, Vose D, Miller M, Thompson S, Vugia D, Fiorentino T, et al. Fluoroquinolone resistance in Campylobacter from chickens and human health impact: a quantitative risk assessment using data from FoodNet and other sources. 2nd International Conference on Emerging Infectious Diseases. Atlanta, GA, July 2000 2000.

27. Humphry RW, Blake D, Fenlon D, Horgan G, Low JC, Gunn GJ. The Quantitative Measurement of Antimicrobial Resistance in Escherichia Coli at the Meta-Population Level (Meta-Population Analysis). Letters in Applied Microbiology 2002;35(4):326-30.

28. JETACAR. The use of antibiotics in food-producing animals: antibiotic-resistant bacteria in animals and humans. Report of the Joint Expert Advisory Committee on Antibiotic Resistance (JETACAR). Commonwealth Department of Health and Aged Care & Commonwealth Department of Agriculture, Fisheries & Forestry - Australia. 1999.

29. Lathers CM. Risk assessment in regulatory policy making for human and veterinary public health. JOURNAL-OF-CLINICAL-PHARMACOLOGY 2002 Aug; 42(8):846-66.

30. Lathers CM. Role of veterinary medicine in public health: Antibiotic use in food animals and humans and the effect on evolution of antibacterial resistance. JOURNAL-OF-CLINICAL-

PHARMACOLOGY 2001 Jun;41(6):595-9.

31. Lipsitch M. Measuring and interpreting associations between antibiotic use and penicillin resistance in Streptococcus pneumoniae. Clinical Infectious Diseases 2001;32(7):1044-54.

32. LopezLozano JM, Monnet DL, Yague A, Burgos A, Gonzalo N, Campillos P, et al. Modelling and forecasting antimicrobial resistance and its dynamic relationship to antimicrobial use: a time series analysis. International Journal of Antimicrobial Agents 2000;14(1):21-31.

33. Martel JL, Tardy F, Sanders P, Boisseau J. New trends in regulatory rules and surveillance of antimicrobial resistance in bacteria of animal origin. VETERINARY-RESEARCH 2001 May-2001 Aug;32(3-4):381-92.

34. McEwen S. Using Risk Assessment to Develop Antimicrobial Regulations. Proceedings From OMAF Conference 1999 1999.

35. McEwen SA. Human health risk assessment of antimicrobial use in food animals. FDA Center for Veterinary Medicine, Advisory Committee Meeting. Gaithersburg, Maryland. January 25-26, 1999. 1999.

36. Naimi T, Ringwald P, Besser R, Thompson S. Panel Summary from the 2000 Emerging Infectious Diseases Conference in Atlanta, Georgia: Antimicrobial Resistance Symposium at ICEID 20002000.

37. National Research Council. Human Health Risks with the Subtherapeutic Use of Penicillin and Tetracyclines in Animal Feed.1989.

38. Nicholls T, Acar J, Anthony F, Franklin A, Gupta R, Tamura Y, et al. Antimicrobial Resistance: Monitoring the Quantities of Antimicrobials Used in Animal Husbandry. Revue Scientifique Et Technique De L Office International Des Epizooties 2001 Dec;20(3):841-7.

39. Pouliquen H, Le Bris H. Residues of Antibacterial Drugs in Foodstuff of Fish Origin: Risk Assessment. Revue De Medecine Veterinaire 2002 Oct;153(10):675-8.

40. Salisbury JG, Nicholls TJ, Lammerding AM, Turnidge J, Nunn MJ. A Risk Analysis Framework for the Long-Term Management of Antibiotic Resistance in Food-Producing Animals. International Journal of Antimicrobial Agents 2002 Sep;20(3):153-64.

41. Saylers AA. Transfer of antibiotic resistance genes from farm animals to man - how likely, how dangerous? Journal of Animal Science / Journal of Dairy Science 2003;81 / 86(Suppl 1 / Suppl 1).

42. Snary E, Kelly L, Wooldridge M, Clifton-Hadley F, Liebana E. Assessing the Risk of the Transfer of Antimicrobial Resistance Genes Between Bacteria in Stored and Spread Farm Wastes. Society for Risk Analysis 2002 Annual Meeting 2002.

43. Steinke D, Davey P. Association between antibiotic resistance and community prescribing: A critical review of bias and confounding in published studies. Clinical Infectious Diseases 2001;33:S193-S205.

44. Sundlof SF. Antimicrobial Resistance From Drug Use in Livestock: FDA's Approach to Risk Management. American College of Physicians Web Site .

45. Thomson JA. Horizontal transfer of DNA from GM crops to bacteria and to mammalian cells. JOURNAL-OF-FOOD-SCIENCE 2001 Mar;66(2):188-93.

46. Turnidge J, McCarthy LR, Master RN, Weslock J. TSN®Database Australia, a new tool to monitor antimicrobial resistance in Australia. Communicable Diseases Intelligence 2003 May;27(Suppl):S67-S69.

47. van den Bogaard AE, Stobberingh EE. Antibiotic usage in animals - Impact on bacterial resistance and public health. DRUGS 1999 Oct;58(4):589-607.

48. Vose D, Acar J, Anthony F, Franklin A, Gupta R, Nicholls T, et al. Antimicrobial resistance: risk analysis methodology for the potential impact on public health of antimicrobial resistant bacteria of animal origin. REVUE-SCIENTIFIQUE-ET-TECHNIQUE-DE-L-OFFICE-INTERNATIONAL-DES-EPIZOOTIES 2001 Dec;20(3):811-27.

49. Waltner-Toews D, McEwen SA. Residues of antibacterial and antiparasitic drugs in foods of animal origin: A risk assessment. Preventive Veterinary Medicine 1994 Aug;20(3):219-34.

50. Wegener HC, Aarestrup FM, Gerner Smidt P, Bager F. Transfer of antibiotic resistant bacteria from animals to man. ACTA-VETERINARIA-SCANDINAVICA 1999;Suppl. 92:51-7.

51. White DG, Acar J, Anthony F, Franklin A, Gupta B, Nicholls T, et al. Antimicrobial resistance: standardisation and harmonisation of laboratory methodologies for the detection and quantification of antimicrobial resistance. REVUE-SCIENTIFIQUE-ET-TECHNIQUE-DE-L-OFFICE-INTERNATIONAL-DES-EPIZOOTIES 2001 Dec;20(3):849-58.

1.4.5 Geographical Information Systems This literature was examined within the context of predictive modelling tools that can be applied to exposure assessments for microbial hazards. Most of the work relates to chemical contaminants in water. However, (Kistemann et al., 2000), applied the GIS spatial and temporal associations to identify a likely food in an salmonellosis outbreak; (Michel et al., 1999) used GIS to identify an association between E. coli O157:H7-illnesses and rural areas of high cattle density; (Tian et al., 2002) for assessing microbial contaminants on grazing lands; and (Njemanze et al., 1999) to evaluate the health impact (diarrheal incidence) of water sources in Nigeria. 1. Berka C, Schreier H, Hall K. Linking water quality with agricultural intensification in a rural

watershed. WATER-AIR-AND-SOIL-POLLUTION 2001 Apr;127(1-4):389-401.

4. Hendley P, Holmes C, Kay S, Maund SJ, Travis KZ, Zhang MH. Probabilistic risk assessment of cotton pyrethroids: III. A spatial analysis of the Mississippi, USA, cotton landscape. Environmental Toxicology and Chemistry 2001;20(3):669-78.

5. Hession WC, Storm DE, Haan CT, Burks SL, Matlock MD. A watershed-level ecological risk assessment methodology. Water Resources Bulletin 1996;32(5):1039-54.

6. Kistemann T, Dangendorf F, Exner M. A Geographical Information System (GIS) as a tool for microbial risk assessment in catchment areas of drinking water reservoirs. Internation

Journal of Hygiene and Environmental Health 2001;203:225-33.

7. Kistemann T, Dangendorf F, Krizek L, Sahl HG, Engelhart S, Exner M. GIS-supported investigation of a nosocomial Salmonella outbreak. International Journal of Hygiene and Environmental Health 2000;203(2):117-26.

8. Kistemann T, Herbst S, Dangendorf F, Exner M. GIS-based analysis of drinking-water supply structures: a module for microbial risk assessment. International Journal of Hygiene and Environmental Health 2001;203(4):301-10.

9. Kooistra L, Leuven RSEW, Nienhuis PH, Wehrens R, Buydens LMC. A procedure for incorporating spatial variability in ecological risk assessment of Dutch River floodplains. Environmental Management 2001;28(3):359-73.

10. Michel P, Wilson JB, Martin SW, Clarke RC, McEwen SA, Gyles CL. Temporal and geographical distributions of reported cases of Escherichia coli O157 : H7 infection in Ontario. Epidemiology and Infection 1999;122(2):193-200.

11. Njemanze PC, Anozie J, Ihenacho JO, Russell MJ, Uwaeziozi AB. Application of risk analysis and geographic information system technologies to the prevention of diarrheal diseases in Nigeria. AMERICAN-JOURNAL-OF-TROPICAL-MEDICINE-AND-HYGIENE 1999 Sep;61(3):356-60.

12. Schowanek D, Fox K, Holt M, Schroeder FR, Koch V, Cassani G, et al. GREAT-ER: a new tool for management and risk assessment of chemicals in river basins - Contribution to GREAT-ER #10. Water Science and Technology 2001;43(2):179-85.

13. Schulze C, Matthies M, Trapp S, Schroder FR. Georeferenced fate modelling of LAS in the Itter stream. Chemosphere 1999;39(11):1833-52.

16. Verro R, Calliera M, Maffioli G, Auteri D, Sala S, Finizio A, et al. GIS-Based system for surface water risk assessment of agricultural chemicals. 1. Methodological approach. ENVIRONMENTAL-SCIENCE-AND-TECHNOLOGY 2002;APR 1 2002; 36:: 1532-8 .

1.4.6 Cost Benefit A large ratio of references, approximately half, (18 papers) focus on risks vs. benefits in water systems. Factors considered include: the balance of risk vs. abatement costs ((Andersson C & Destouni G, 2001)); competing risks (e.g. microbial vs. disinfection by-products ((Havelaar et al., 2000)) and risks to drinking water quality caused by alternate uses (e.g. recreational uses ((Stewart MH et al., 2002))). Of particular interest, two of the references consider specific regulations ((Odom R et al., 1999);(Regli S et al., 1999)). Measures used include: disability adjusted life years ((Havelaar et al., 2000); (Havelaar, 2003)); general risk measures ((Jonkman SN et al., 2003)); benefits in regulatory processes and uncertainty in measures ((Montgomery, 1998)).

Thirteen references focus on food systems. Two are at the interface between food and water systems: microbial quality of irrigation water ((Shuval et al., 1997)); chemical levels in sewage sludge applied to agricultural soil ((Stenger, 2000)). Five papers are general discussions; one focuses on a specific risk, Salmonella in poultry products ((Brown, 2002)). One paper considers consumer willingness to pay in cost-benefit analysis ((Giamalva et al., 1998)). Most papers focus on costs of immediate health problems but one paper considers long-term sequelae to foodborne disease ((McDowell & McElvaine, 1997)). 1. Andersson C, Destouni G. Risk-cost analysis in ground water contaminant transport: the role of

random spatial variability and sorption kinetics. GROUND-WATER 2001;JAN-FEB 2001:35-48.

2. Brown MH. Quantitative Microbiological Risk Assessment: Principles Applied to Determining the Comparative Risk of Salmonellosis From Chicken Products. International Biodeterioration & Biodegradation 2002;50(3-4):155-60.

3. Fane SA, Ashbolt NJ, White SB. Decentralised Urban Water Reuse: the Implications of System Scale for Cost and Pathogen Risk. Water Science and Technology 2002;46(6-7):281-8.

5. Giamalva JN, Redfern M, Bailey WC. Dietitians employed by health care facilities preferred a HACCP system over irradiation or chemical rinses for reducing risk of foodborne disease. Journal of the American Dietetic Association 1998;98(8):885-8.

10. Havelaar AH, DeHollander AEM, Teunis PFM, Evers EG, VanKranen HJ, Versteegh JFM, et al. Balancing the risks and benefits of drinking water disinfection: Disability adjusted life-years on the scale. Environmental Health Perspectives 2000;108(4):315-21.

11. Havelaar AHaJMM. Yes/REPORT/water/CB . Quantifying public health risks in the WHO Guidelines for Drinking Water Quality A burden of disease approach. Bilthoven, the Netherlands.: National Institute for Public Health and the Environment, RIVM , 2003. Report No.: 734301022.

12. Hayes DJ, Shogren JF, Shin SY, Kliebenstein JB. Valuing Food Safety in Experimental Auction Markets. American Journal of Agricultural Economics 1995 Feb;77(1):40-53.

13. Health Canada. Yes/REPORT/CB. Economic Burden of Illness in Canada, 1998. Ottawa, Ontario: Health Canada, 1998. Report No.: Cat. N H21-136/1998E.

14. Johnson A, Thurow AP, Vietor D. Dairy manure management: An application of probabilistic risk assessment. Journal of Environmental Quality 1998;27(3):481-7.

15. Jonkman SN, van Gelder PHAJM, Vrijling JK. An overview of quantitative risk measures for loss of life and economic damage. JOURNAL-OF-HAZARDOUS-MATERIALS 2003;APR 4 2003; 99:1.

16. Lindsay JA. Chronic Sequelae of Foodborne Disease. Emerging and Infectious Disease. 1997 Oct-1997 Dec;3 (4 ).

18. McDowell RM, McElvaine MD. Long-term sequelae to foodborne disease. Revue Scientifique Et Technique De L Office International Des Epizooties 1997;16(2):337-41.

19. Montgomery WD. Cost-benefit analysis in a regulatory setting. Human and Ecological Risk Assessment 1998;4(4):971-89.

20. Morales RA. Microbial risk assessment, economics, and food safety. Journal of the American Veterinary Medical Association 1998;213(12):1746-9.

21. Morales RA, McDowell RM. Risk assessment and economic analysis for managing risks to human health from pathogenic microorganisms in the food supply. Journal of Food Protection 1998;61(11):1567-70.

22. Odom R, Regli S, Messner M, Cromwell J, Javdan M. Benefit-cost analysis of the stage 1D/DBP rule. JOURNAL-AMERICAN-WATER-WORKS-ASSOCIATION 1999;91:137-47.

24. Petersen KE, James WO, Thaler AM, Ragland RD, Hogue AT. Use of a Priority Rating Process to Sort Meatborne Zoonotic Agents in Beef. Journal of Agromedicine 1996;3(1):17-36.

25. Raschke AM, Burger AEC. Risk assessment as a management tool used to assess the effect of pesticide use in an irrigation system, situated in a semi-desert region. Archives of Environmental Contamination and Toxicology 1997;32(1):42-9.

28. Starbird SA. Designing food safety regulations: The effect of inspection policy and penalties for noncompliance on food processor behavior. Journal of Agricultural and Resource Economics 2000;25(2):616-35.

29. Stenger A. Experimental valuation of food safety - Application to sewage sludge. Food Policy 2000;25(2):211-8.

30. Stewart MH, Yates MV, Anderson MA, Gerba CP, Rose JB, De Leon R, et al. Predicted public health consequences of body-contact recreation on a potable water reservoir. JOURNAL-AMERICAN-WATER-WORKS-ASSOCIATION 2002;MAY 2002; 94:: 84-97 .

31. Tengs T AMPJSDSJWMGJ. Five-hundred life-saving interventions and their cost-effectiveness. Risk Analysis 1995;15(3):369-90.

34. Zepeda L, Buelow KL, Nordlund KV, Thomas CB, Collins MT, Goodger WJ. A linear programming assessment of the profit from strategies to reduce the prevalence of Staphylococcus aureus mastitis. Preventive Veterinary Medicine 1998;33(1-4):183-93.

1.4.7 Exposure Information The compilation of a list of research and data that could be used to describe exposure information one hazard at a time was not the primary focus of this project. Nevertheless, when relevant information of this nature was found it was included into the category titled “Exposure Information”. As a result, the information in this category should be looked upon as a general guide to the types of information that exist, as opposed to a comprehensive compilation of all information. There were an almost even number of waterborne (27) and foodborne (22) papers. A number of water papers considered watershed models and hydrological events ((Payment et al., 2000);(Conboy & Goss, 2000); (Walker & Stedinger, 1999); (Mallin et al., 2000)) and one paper considered swimming related risks ((Loge FN et al., 2002)). In addition, routes considered in food systems included: contamination through manufacturing systems ((Whiting & Golden, 2002);(Den Aantrekker et al., 2003)), home hygiene and consumer practices ((Scott et al., 1982);(Griffith et al., 1998); (Klontz et al., 1995)) and the derivation of individual consumption patterns ((Olendzki et al., 1999)). Specific hazards considered included: Campylobacter jejuni (3 records), Cryptosporidium (13 records), Salmonella (7 records), E. coli 0157:H7 (8 records), gene transfer from bacterial to mammalian cells (1 record). A few papers considered exposure for specific subpopulations. These included: children ((Parkin et al., 2003), (Schwartz et al., 1997)), elderly ((Schwartz et al., 2000)) and ethnic populations ((Williams & Hammitt, 2001)). 1. Beaudeau P, Payment P, Bourderont D, Mansotte F, Boudhabay O, Laubies B, et al. A time series

study of anti-diarrheal drug sales and tap-water quality. International Journal of Environmental Health Research 1999;9(4):293-311.

2. Brown P, Kidd D, Riordan T, Barrell RA. An outbreak of food-borne Campylobacter jejuni infection and the possible role of cross contamination. Journal of Infection 1988;17:171-6.

3. Casman EA, Fischhoff B, Palmgren C, Small MJ, Wu F. An integrated risk model of a drinking-water--borne cryptosporidiosis outbreak. Risk Anal 2000 Aug;20(4):495-511.

4. Charlett A, Cowden JM, Frost JA, Gillespie IA, Millward J, Neal KR, et al. Ciprofloxacin resistance in Campylobacter jejuni: case-case analysis as a tool for elucidating risks at home and abroad. JOURNAL-OF-ANTIMICROBIAL-CHEMOTHERAPY 2002 Oct;50(4):561-8.

5. Conboy MJ, Goss MJ. Natural protection of groundwater against bacteria of fecal origin. JOURNAL-OF-CONTAMINANT-HYDROLOGY 2000 Apr;43(1):1-24.

7. Crowther J, Kay D, Wyer MD. Faecal-Indicator Concentrations in Waters Draining Lowland Pastoral Catchments in the Uk: Relationships With Land Use and Farming Practices. Water Research 2002 Apr;36(7):1725-34.

8. Crump J, Griffin P, Angulo F. Bacterial Contamination of Animal Feed and Its Relationship to Human Foodborne Illness. Clinical Infectious Diseases 2002;35:859-65.

12. Duran AE, Muniesa M, Moce Llivina L, Campos C, Jofre J, Lucena F. Usefulness of different groups of bacteriophages as model micro-organisms for evaluating chlorination. JOURNAL-OF-APPLIED-MICROBIOLOGY 2003;95(1):29-37.

13. Fewtrell L, Macgill SM, Kay D, Casemore D. Uncertainties in risk assessment for the determination of drinking water pollutant concentrations: Cryptosporidium case study. Water Research 2001;35(2):441-7.

14. Flores RA, Tamplin ML. Distribution Patterns of Escherichia Coli O157 : H7 in Ground Beef Produced by a Laboratory-Scale Grinder. Journal of Food Protection 2002 Dec;65(12):1894-902.

15. Gibson LL, Rose JB, Haas CN, Gerba CP, Rusin PA. Quantitative Assessment of Risk Reduction From Hand Washing With Antibacterial Soaps. Journal of Applied Microbiology 2002;92:136S-43S.

17. Griffith C, Worsfold D, Mitchell R. Food preparation, risk communication and the consumer. Food Control 1998;9(4):225-32.

18. Hogue A, Akkina J, Angulo F, Johnson R, Petersen K, Saini P, et al. Situation Assessment:

Salmonella typhimurium 1041997.

20. Kistemann T, Classen T, Koch C, Dangendorf F, Fischeder R, Gebel J, et al. Microbial Load of Drinking Water Reservoir Tributaries During Extreme Rainfall and Runoff. Applied and Environmental Microbiology 2002 May;68(5):2188-97.

21. Klontz KC, Timbo B, Fein S, Levy A. Prevalence of selected food consumption and preparation behaviors associated with increased risks of food-borne disease. Journal of Food Protection 1995 Aug;58(8):927-30.

22. Lambe J, Kearney J, Leclercrq C, Berardi D, Zunft HFJ, Sulzer S, et al. Enhancing the capacity of food consumption surveys of short duration to estimate long term consumer-only intakes by combination with a qualitative food frequency questionnaire. Food Additives and Contaminants 2000;17(3):177-87.

23. Letrilliart L, Desenclos JC, Flahault A. Risk factors for winter outbreak of acute diarrhoea in France: case-control study. British Medical Journal 1997;315(7123):1645-9.

24. Lipsitch M. Measuring and interpreting associations between antibiotic use and penicillin resistance in Streptococcus pneumoniae. Clinical Infectious Diseases 2001;32(7):1044-54.

26. Mallin MA, Williams KE, Esham EC, Lowe RP. Effect of human development on bacteriological water quality in coastal watersheds. ECOLOGICAL-APPLICATIONS 2000 Aug;10(4):1047-56.

27. Martinez-Manzanares E, Morinigo MA, Castro D, Balebona MC, Munoz MA, Borrego JJ. Relationship Between Indicators of Fecal Pollution in Shellfish-growing Water and the Occurrence of Human Pathogenic Microorganisms in Shellfish. Journal of Food Protection 1992 Aug;55(8):609-14.

28. Meyer-Broseta S, Diot A, Bastian S, Riviere J, Cerf O. Estimation of Low Bacterial Concentration: Listeria Monocytogenes in Raw Milk. International Journal of Food Microbiology 2003 Jan;80(1):1-15.

30. Nicholls T, Acar J, Anthony F, Franklin A, Gupta R, Tamura Y, et al. Antimicrobial Resistance: Monitoring the Quantities of Antimicrobials Used in Animal Husbandry. Revue Scientifique Et Technique De L Office International Des Epizooties 2001 Dec;20(3):841-7.

31. Nissen H, Rosnes JT, Brendehaug J, Kleiberg GH. Safety Evaluation of Sous Vide-Processed Ready Meals. Letters in Applied Microbiology 2002;35(5):433-8.

32. Nnadi FN, Fulkerson M. Assessment of groundwater under direct influence of surface water. JOURNAL-OF-ENVIRONMENTAL-SCIENCE-AND-HEALTH-PART-A-

TOXICHAZARDOUS-SUBSTANCES-AND-ENVIRONMENTAL-ENGINEERING 2002;37(7):1209-22.

33. Nowell S, Coles B, Sinha R, Macleod S, Ratnasinghe DL, Stotts C, et al. Analysis of Total Meat Intake and Exposure to Individual Heterocyclic Amines in a Case-Control Study of Colorectal Cancer: Contribution of Metabolic Variation to Risk. Mutation Research-Fundamental and Molecular Mechanisms of Mutagenesis 2002 Sep;506:175-85.

34. Olendzki B, Hurley TG, Hebert JR, Ellis S, Merriam PA, Luippold R, et al. Comparing food intake using the Dietary Risk Assessment with multiple 24-hour dietary recalls and the 7-Day Dietary Recall. JOURNAL-OF-THE-AMERICAN-DIETETIC-ASSOCIATION 1999 Nov;99(11):1433-9.

35. Parkin RT, Soller JA, Olivieri AW, INGA Study Grp. Incorporating susceptible subpopulations in microbial risk assessment: pediatric exposures to enteroviruses in river water. JOURNAL-OF-EXPOSURE-ANALYSIS-AND-ENVIRONMENTAL-EPIDEMIOLOGY 2003 Mar;13(2):161-8.

36. Payment P, Berte A, PrTvost M, MTnard B , Barbeau B. Occurrence of pathogenic microorganisms in the Saint Lawrence River (Canada) and comparison of health risks for populations using it as their source of drinking water. Canadian Journal of Microbiology 2000;46(6):565-76.

37. Rose JB, Daeschner S, Easterling DR, Curriero FC, Lele S, Patz JA. Climate and waterborne disease outbreaks. JOURNAL-AMERICAN-WATER-WORKS-ASSOCIATION 2000;SEP 2000; 92:: 77-87 .

38. Schwartz J, Levin R, Goldstein R. Drinking water turbidity and gastrointestinal illness in the elderly of Philadelphia. Journal of Epidemiology and Community Health 2000;54(1):45-51.

39. Schwartz J, Levin R, Hodge K. Drinking water turbidity and pediatric hospital use for gastrointestinal illness in Philadelphia. Epidemiology 1997;8(6):615-20.

40. Scott E, Bloomfield SF. The Survival and Transfer of Microbial Contamination via Cloths, Hands and Utensils. Journal of Applied Bacteriology 1990;68:271-8.

41. Scott E, Bloomfield SF, Barlow CG. An investigation of microbial contamination in the home. Journal of Hygiene 1982;89:279-93.

42. Steinke D, Davey P. Association between antibiotic resistance and community prescribing: A critical review of bias and confounding in published studies. Clinical Infectious Diseases 2001;33:S193-S205.

43. Thomson JA. Horizontal transfer of DNA from GM crops to bacteria and to mammalian cells. JOURNAL-OF-FOOD-SCIENCE 2001 Mar;66(2):188-93.

44. Toh PS, Birchenough A, Smalley T. Risk assessment: foodhandling practices and food-contact surfaces of hawkers in Malaysia. International Journal of Environmental Health Research 2000;10(3):191-201.

46. Wegener HC, Aarestrup FM, Gerner Smidt P, Bager F. Transfer of antibiotic resistant bacteria from animals to man. ACTA-VETERINARIA-SCANDINAVICA 1999;Suppl. 92:51-7.

47. Whiting RC, Golden MH. Variation among Escherichia coli O157:H7 strains relative to their growth, survival, thermal inactivation, and toxin production in broth. International Journal of Food Microbiology 2002;75(1-2):127-33.

48. Williams BL, Florez Y, Pettygrove S. Inter- and Intra-Ethnic Variation in Water Intake, Contact, and Source Estimates Among Tucson Residents: Implications for Exposure Analysis. Journal of Exposure Analysis and Environmental Epidemiology 2001 Nov-2001 Dec;11(6):510-21.

49. Young PL, Komisar SJ. The variability introduced by partial sample analysis to numbers of Cryptosporidium oocysts and Giardia cysts reported under the information collection rule. Water Research 1999;33(11):2660-8.

1.4.8 Exposure modelling There appears to be, at least in the published literature, more papers dealing with food systems (30 records) than water systems (18 records). Typical examples for food systems: microbial risks in animal populations ((Jordan et al., 1999b); (Jordan et al., 1999a); (Turner et al., 2003)), growth/survivor variability for different processing operations ((Brul et al., 2002); (DelignetteMuller & Rosso, 2000); (Den Aantrekker et al., 2003), (Geeraerd et al., 2000); (Grijspeerdt & Herman, 2003); (Hoke et al., 2003); (Yang et al., 2002)), models of hygiene practises and food service handling ((Chen et al., 2001); (Montville et al., 2001); (Strachan et al., 2001); (Trick et al., 2003)), temporal variability of counts in food systems ((Corradini et al., 2002); (Gonzalez-Martinez et al., 2003); (Horowitz et al., 1999); (Nussinovitch & Peleg, 2000)) and consumption patterns ((Kynast-Wolf et al., 2002)). Exposure modelling in water systems included hazard transport by physical processes (e.g. detachment of biofilms, hydraulic, aerosols) ((Cane G & Clark ID, 1999); (Dowd et al., 2000); (Johnson et al., 1995); (Muslu, 1995); (Sanders BF et al., 2001); (Tian et al., 2002)), fate and transport models (combining growth and disinfection/degradation) ((Gale, 1998b); (Gyurek & Finch, 1998); (Jin G et al., 493-509); (McAvoy et al., 1998)) as well as sampling methods and bio-indicators ((Craig DL et al., 2003); (Young & Komisar, 1999)). 1. Brul S, Coote P, Oomes S, Mensonides F, Hellingwerf K, Klis F. Physiological Actions of

Preservative Agents: Prospective of Use of Modem Microbiological Techniques in Assessing Microbial Behaviour in Food Preservation. International Journal of Food Microbiology 2002 Nov;79(1-2):55-64.

2. Cane G, Clark ID. Tracing ground water recharge in an agricultural watershed with isotopes. GROUND-WATER 1999;JAN-FEB 1999; 37:: 133-9 .

3. Chen YH, Jackson KM, Chea FP, Schaffner DW. Quantification and variability analysis of bacterial cross-contamination rates in common food service tasks. Journal of Food Protection 2001;64(1):72-80.

4. Corradini MG, Engel R, Normand MD, Peleg M. Estimating the Frequency of Future High Microbial Counts in Records With an Actual or Potential Trend or Periodicity. Journal of Food Science 2002 May;67(4):1278-85.

5. Corradini MG, Norman MD, Nussinovitch A, Horowitz J, Peleg M. Estimating the Frequency of High Microbial Counts in Commercial Food Products Using Various Distribution Functions. Journal of Food Protection 2001;64(5):674-81.

7. DelignetteMuller ML, Rosso L. Biological variability and exposure assessment. International Journal of Food Microbiology 2000;58(3):203-12.

9. Ebel E, Schlosser W. Estimating the annual fraction of eggs contaminated with Salmonella enteritidis in the United States. International Journal of Food Microbiology 2000;61(1):51-62.

10. Gale P. Simulating Cryptosporidium exposures in drinking water during an outbreak. Water Science and Technology 1998;38(12):7-13.

11. Gale P, Stanfield G. Cryptosporidium during a simulated outbreak. JOURNAL-AMERICAN-WATER-WORKS-ASSOCIATION 2000;SEP 2000; 92:: 105-16 .

12. Geeraerd AH, Herremans CH, VanImpe JF. Structural model requirements to describe microbial inactivation during a mild heat treatment. International Journal of Food Microbiology 2000;59(3):185-209.

15. Gonzalez-Martinez C, Corradini MG, Peleg M. Probabilistic Models of Food Microbial Safety and Nutritional Quality. Journal of Food Engineering 2003 Feb;56(2-3):135-42.

16. Grijspeerdt K, Herman L. Inactivation of Salmonella Enteritidis During Boiling of Eggs. International Journal of Food Microbiology 2003 Apr;82(1):13-24.

17. Gyurek LL, Finch GR. Modeling water treatment chemical disinfection kinetics. Journal of Environmental Engineering ASCE 1998;124(9):783-93.

18. Hald T, Vose D, Wegener HC, Koupeev T. A Bayesian Approach to Quantify the Contribution of Animal-Food Sources to Human Salmonellosis. Risk Analysis 2004;24(1):255-69.

19. Hoke K, Houska M, Kyhos K, Landfeld A , Pipek P. Modelling of Beef Surface Temperatures During Steam Decontamination. Journal of Food Engineering 2003 Jun;58(1):95-102.

20. Horowitz J, Normand M, Peleg M. On modeling the irregular fluctuations in microbial counts. Critical Reviews in Food Science and Nutrition 1999;39(6):503-17.

21. Humphry RW, Blake D, Fenlon D, Horgan G, Low JC, Gunn GJ. The Quantitative Measurement of Antimicrobial Resistance in Escherichia Coli at the Meta-Population Level (Meta-Population Analysis). Letters in Applied Microbiology 2002;35(4):326-30.

23. Johnson WP, Blue KA, Logan BE, Arnold RG . Modeling bacterial detachment during transport through porous media as a residence-time-dependent process. Water Resources Research 1995 Nov;31(11):2649-58.

24. Jordan D, McEwen SA. Herd-level test performance based on uncertain estimates of individual test performance, individual true prevalence and herd true prevalence. Preventive Veterinary Medicine 1998;36(3):187-209.

25. Jordan D, McEwen SA, Lammerding AM, McNab WB, Wilson JB. Pre-slaughter control of Escherichia coli O157 in beef cattle: a simulation study. Preventive Veterinary Medicine 1999;41(1):55-74.

26. Jordan D, McEwen SA, Lammerding AM, McNab WB, Wilson JB. A simulation model for studying the role of pre-slaughter factors on the exposure of beef carcasses to human microbial hazards. Preventive Veterinary Medicine 1999;41(1):37-54.

27. Kynast-Wolf G, Becker N, Kroke A, Brandstetter BR, Wahrendorf J, Boeing H. Linear Regression Calibration: Theoretical Framework and Empirical Results in Epic, Germany. Annals of Nutrition and Metabolism 2002 Jan-2002 Feb;46(1):2-8.

28. Lagido C, Wilson IJ, Glover LA, Prosser JI. A model for bacterial conjugal gene transfer on solid surfaces. FEMS-MICROBIOLOGY-ECOLOGY 2003;MAY 1 2003; 44:: 67-78 .

29. LopezLozano JM, Monnet DL, Yague A, Burgos A, Gonzalo N, Campillos P, et al. Modelling and forecasting antimicrobial resistance and its dynamic relationship to antimicrobial use: a time series analysis. International Journal of Antimicrobial Agents 2000;14(1):21-31.

30. McAvoy DC, Grady CPL, Blok J, Feijtel TCJ, Federle TW, Larson RJ. A simplified modeling approach using microbial growth kinetics for predicting exposure concentrations of organic chemicals in treated wastewater effluents. Chemosphere 1998;36(10):2291-304.

31. Meyer-Broseta S, Diot A, Bastian S, Riviere J, Cerf O. Estimation of Low Bacterial Concentration: Listeria Monocytogenes in Raw Milk. International Journal of Food Microbiology 2003 Jan;80(1):1-15.

32. Montville R, Chen YH, Schaffner DW. Glove barriers to bacterial cross-contamination between hands to food. Journal of Food Protection 2001;64(6):845-9.

33. Montville R, Chen YH, Schaffner DW. Risk Assessment of Hand Washing Efficacy Using Literature and Experimental Data. International Journal of Food Microbiology 2002 Mar;73(2-3):305-13.

34. Muslu Y. Kinetics of biofilms in unsaturated granular media. Journal of Environmental Engineering - ASCE 1995 Jan;121(1):66-83.

35. Nauta MJ, Litman S, Barker GC, Carlin F . A retail and consumer phase model for exposure assessment of Bacillus cereus. INTERNATIONAL JOURNAL OF FOOD MICROBIOLOGY 2003;83:205-18.

36. Nussinovitch A, Peleg M. Analysis of the fluctuating patterns of microbial counts in frozen

industrial food products. Food Research International 2000;33(1):53-62.

37. Peleg M. Microbial survival curves - the reality of flat ''shoulders'' and absolute thermal death times. Food Research International 2000;33(7):531-8.

38. Peleg M, Nussinovitch A, Horowitz J. Interpretation of and extraction of useful information from irregular fluctuating industrial microbial counts. Journal of Food Science 2000;65(5):740-7.

39. Petterson SR, Ashbolt NJ. Viral risks associated with wastewater reuse: modeling virus persistence on wastewater irrigated salad crop. Water Science and Technology 2001;43(12):23-6.

40. Reinders RD, De Jonge R, Evers EG. A statistical method to determine whether micro-organisms are randomly distributed in a food matrix, applied to coliforms and Escherichia coli O157 in minced beef. FOOD-MICROBIOLOGY 2003;JUN 2003; 20:: 297-303 .

41. Sanders BF, Green CL, Chu AK, Grant SB. Case study: Modeling tidal transport of urban runoff in channels using the finite-volume method. JOURNAL-OF-HYDRAULIC-ENGINEERING-ASCE 2001;OCT 2001; 127:: 795-804 .

42. Siebert KJ. Computer Simulation of Microbiological Sampling of Liquid Foods. Journal of Food Protection 1993 Jun;56(6):518-24.

45. Trick WE, Vernon MO, Hayes RA, Nathan C, Rice TW, Peterson BJ, et al. Impact of ring wearing on hand contamination and comparison of hand hygiene agents in a hospital. CLINICAL-INFECTIOUS-DISEASES 2003 Jun;36(11):1383-90.

46. Turner J, Begon M, Bowers RG, French NP. A Model Appropriate to the Transmission of a Human Food-Borne Pathogen in a Multigroup Managed Herd. Preventive Veterinary Medicine 2003 Apr;57(4):175-98.

48. Yang H, Wang S, Li Y, Johnson MG. Predictive Models for the Survival/Death of Campylobacter Jejuni and Salmonella Typhimurium in Poultry Scalding and Chilling. Journal of Food Science 2002 Jun-2002 Jul;67(5):1836-43.

49. Young PL, Komisar SJ. The variability introduced by partial sample analysis to numbers of Cryptosporidium oocysts and Giardia cysts reported under the information collection rule. Water Research 1999;33(11):2660-8.

1.4.9 Methods from Other Fields Almost one hundred of the references dealt with risks in water systems, particularly in groundwater. Many references were related to agricultural management practices (e.g. nitrogen, phosphorus, manure, pesticides). Non-agricultural hazards included a few

industrial (e.g. pulp mill effluents, heavy metals contamination soil and sediments, naval shipyard) and municipal (e.g. “down-the drain” chemicals, wastewater treatment plants, ocean outfalls) sources. Twenty-five of the papers considered non-microbial foodborne risks: hormone residues, mycotoxins, food additives, allergens, BSE and genetic modifications. Several references dealt with biofilms (models of growth, competition and antibiotic resistance). Additional topics included antibiotic resistant bacteria in hospitals, air quality and transportation of hazardous substances. Some mathematical methods were common to microbial risk assessment: use of GIS for spatially referenced data (14 papers); Monte Carlo methods to deal with stochastic elements (18 papers), Bayesian approaches (5). Methods that are less commonly used in microbial risk assessment included use of extreme value statistics in climate models, categorical regression to estimate minimum hazard levels for health impacts, smooth coloured noise to introduce stochastic elements in deterministic models, expectation functions to describe uncertain inputs, fault tree methods in risk assessment, relative risk ranking procedures, and multicriteria decision support tools. 1. Agarwal J, Blockley DI, Woodman NJ. Vulnerability of systems. CIVIL-ENGINEERING-AND-

ENVIRONMENTAL-SYSTEMS 141;2001; 18:2.

2. Albering HJ, Rila JP, Moonen EJ, Hoogewerff JA, Kleinjans JCS. Human health risk assessment in relation to environmental pollution of two artificial freshwater lakes in the Netherlands. Environmental Health Perspectives 1999;107(1):27-35.

3. Albering HJ, vanLeusen SM, Moonen EJC, Hoogewerff JA, Kleinjans JCS. Human health risk assessment: A case study involving heavy metal soil contamination after the flooding of the river Meuse during the winter of 1993-1994. Environmental Health Perspectives 1999;107(1):37-43.

5. Andersson C, Destouni G. Risk-cost analysis in ground water contaminant transport: the role of random spatial variability and sorption kinetics. GROUND-WATER 2001;JAN-FEB 2001:35-48.

6. Anklam E, Battaglia R. Food Analysis and Consumer Protection. Trends in Food Science & Technology 2001 May-2001 Jun;12(5-6):197-202.

7. Barling D, deVriend H, Cornelese JA, Ekstrand B, Hecker EFF, Howlett J, et al. The social aspects of food biotechnology: a European view. Environmental Toxicology and Pharmacology 1999;7(2):85-93.

8. Bender MJ, Simonovic SP. A fuzzy compromise approach to water resource systems planning under uncertainty. FUZZY-SETS-AND-SYSTEMS 1935;OCT 1 2000; 115:1.

9. Berka C, Schreier H, Hall K. Linking water quality with agricultural intensification in a rural watershed. WATER-AIR-AND-SOIL-POLLUTION 2001 Apr;127(1-4):389-401.

10. Besancon P. An evaluation of the safety of foods produced from genetically modified crops: what is certain and what isn't. OCL Oleagineux Corps Gras Lipides 2000;7(4):310-3.

11. Blackwood DJ, Ashley RM, Petrie M, Oltean Dumbrava C, Jones C. Making decisions for upgrading wastewater systems. PROCEEDINGS-OF-THE-INSTITUTION-OF-CIVIL-ENGINEERS-MUNICIPAL-ENGINEER 171;SEP 2000; 139:3.

12. Boeije G, Vanrolleghem P, Matthies M. A geo-referenced aquatic exposure prediction methodology for 'down-the-drain' chemicals. Water Science and Technology 1997;36(5):251-8.

13. Bottelberghs PH. Risk analysis and safety policy developments in the Netherlands. JOURNAL-OF-HAZARDOUS-MATERIALS 2000;71 (Special Iss.):59-84.

14. Brown CD, Hart A, Lewis KA, Dubus IG. P-Ema (I): Simulating the Environmental Fate of Pesticides for a Farm-Level Risk Assessment System. Agronomie 2003 Jan-2003 Feb;23(1):67-74.

15. Buche P, Dervin C, Brouillaud-Delattre A, Gnanou-Besse N. Combining Fuzzy Querying of Imprecise Data and Predictive Microbiology Using Category-Based Reasoning for Prediction of the Possible Microbial Spoilage in Foods: Application to Listeria Monocytogenes. International Journal of Food Microbiology 2002 Mar;73(2-3):171-85.

16. Buck SP, Wolfe ML, Mostaghimi S, Woeste FE, Vietor DM. Application of probabilistic risk assessment to agricultural nonpoint source pollution. Journal of Soil and Water Conservation 2000;55(3):340-6.

17. Burin GJ, Saunders DR. Addressing human variability in risk assessment - The robustness of the intraspecies uncertainty factor. Regulatory Toxicology and Pharmacology 1999;30(3):209-16.

18. Cane G, Clark ID. Tracing ground water recharge in an agricultural watershed with isotopes. GROUND-WATER 1999;JAN-FEB 1999; 37:: 133-9 .

19. Carbonell G, Ramos C, Pablos MV, Ortiz JA, Tarazona JV. A system dynamic model for the assessment of different exposure routes in aquatic ecosystems. SCIENCE-OF-THE-TOTAL-ENVIRONMENT 2000 Mar;247(2-3):107-18.

20. Chen Z, Huang GH, Chakma A. Hybrid Fuzzy-Stochastic Modeling Approach for Assessing Environmental Risks at Contaminated Groundwater Systems. Journal of Environmental Engineering-Asce 2003 Jan;129(1):79-88.

21. Coleman ME, Dreesen DW, Wiegert RG. A simulation of microbial competition in the human colonic ecosystem. Applied and Environmental Microbiology 1996;62(10):3632-9.

22. Collins G, Kremer JN, Valiela I. Assessing uncertainty in estimates of nitrogen loading to estuaries for research, planning, and risk assessment. Environmental Management 2000;25(6):635-45.

23. Cooper WE. Risk assessment and risk management: An essential integration. Human and Ecological Risk Assessment 1998;4(4):931-7.

24. Cormier SM, Smith M, Norton S, Neiheisel T. Assessing ecological risk in watersheds: A case study of problem formulation in the Big Darby Creek watershed, Ohio, USA. Environmental Toxicology and Chemistry 2000;19(4):1082-96.

25. Crevel RWR. Risk assessment for food allergy - the industry viewpoint. Allergy 2001;56:94-7.

26. Cullen AC. The sensitivity of probabilistic risk assessment results to alternative model structures: A case study of municipal waste incineration. Journal of the Air & Waste Management Association 1995 Jul;45(7):538-46.

27. Culp JM, Lowell RB, Cash KJ. Integrating mesocosm experiments with field and laboratory studies to generate weight-of-evidence risk assessments for large rivers. Environmental Toxicology and Chemistry 2000;19(4):1167-73.

29. Dodds MG, Grobe KJ, Stewart PS. Modeling biofilm antimicrobial resistance. Biotechnology and Bioengineering 2000;68(4):456-65.

30. Dong WQ, Yu ZB, Weber D. Simulations on soil water variation in and regions. JOURNAL-OF-HYDROLOGY 162;MAY 1 2003; 275:3-4.

31. Du Preez HH, Heath RGM, Sandham LA, Genthe B. Methodology for the Assessment of Human Health Risks Associated With the Consumption of Chemical Contaminated Freshwater Fish in South Africa. Water Sa 2003 Jan;29(1):69-90.

32. Dube MG, Culp JM, Cash KJ, Glozier NE , Maclatchy DL, Podemski CL, et al. Artificial Streams for Environmental Effects Monitoring (Eem): Development and Application in Canada Over the Past Decade. Water Quality Research Journal of Canada 2002;37(1):155-80.

33. Dunn AJ, Frodsham DA, Kilroy RV. Predicting the risk to permit compliance of new sewage treatment works. Water Science and Technology 1998;38(3):7-14.

34. Dust M, Baran N, Errera G, Hutson JL , Mouvet C, Schafer H, et al. Simulation of water and solute transport in field soils with the LEACHP model. Agricultural Water Management 2000;44(1-3):225-45.

35. Fewtrell L, Macgill SM, Kay D. Copper in drinking water supplies and gastrointestinal illness in England and Wales: a risk assessment. JOURNAL-OF-WATER-SUPPLY-RESEARCH-AND-TECHNOLOGY-AQUA 449;DEC 2002; 51:8.

36. Field MS. Risk assessment methodology for karst aquifers .2. Solute-transport modeling. Environmental Monitoring and Assessment 1997;47(1):23-37.

37. Field MS, Nash SG. Risk assessment methodology for karst aquifers .1. Estimating karst conduit-flow parameters. Environmental Monitoring and Assessment 1997;47(1):1-21.

38. Finley BL, Paustenbach DJ. Using applied research to reduce uncertainty in health risk assessment: Five case studies involving human exposure to chromium in soil and groundwater. Journal of Soil Contamination 1997;6(6):649-705.

39. Gaganis P, Smith L. A Bayesian approach to the quantification of the effect of model error on the predictions of groundwater models. WATER RESOURCES RESEARCH 2309;SEP 2001; 37:9.

40. Galassi S, Provini A, Halfon E. Risk assessment for pesticides and their metabolites in water. International Journal of Environmental Analytical Chemistry 1996;65(1-4):331-44.

42. Gheorghe AV, Vamanu DV. Decision-support software tools for integrated risk assessment of hazardous substances in complex terrain. International Journal of Environment and Pollution 1998;9(4):352-70.

43. Gibb HJ. Current Perspectives on Issues in Risk Assessment Methods. Human and Ecological Risk Assessment 2002 Oct;8(6):1249-51.

44. Gibson MC, deMonsabert SM, OrmeZavaleta J. Comparison of noncancer risk assessment approaches for use in deriving drinking water criteria. Regulatory Toxicology and Pharmacology 1997;26(3):243-56.

45. Gonzalez-Martinez C, Corradini MG, Peleg M. Probabilistic Models of Food Microbial Safety and Nutritional Quality. Journal of Food Engineering 2003 Feb;56(2-3):135-42.

48. Gyldenkaerne S, Jorgensen SE. Modelling the bioavailability of pesticides to soil-dwelling organisms. Ecological Modelling 2000;132(3):203-30.

49. Hajmeer MN, Basheer IA, Marsden JL, Fung DYC. New approach for modeling generalized microbial growth curves using artificial neural networks. Journal of Rapid Methods and Automation in Microbiology 2000;8:265-83.

50. Hendley P, Holmes C, Kay S, Maund SJ, Travis KZ, Zhang MH. Probabilistic risk assessment of cotton pyrethroids: III. A spatial analysis of the Mississippi, USA, cotton landscape. Environmental Toxicology and Chemistry 2001;20(3):669-78.

51. Hess AJ, Johnson PA. A systematic analysis of the constraints to urban stream enhancements. JOURNAL-OF-THE-AMERICAN-WATER-RESOURCES-ASSOCIATION 2001 Feb;37(1):213-21.

52. Hession WC, Storm DE. Watershed-level uncertainties: Implications for phosphorus management and eutrophication. Journal of Environmental Quality 2000;29(4):1172-9.

53. Hession WC, Storm DE, Haan CT, Burks SL, Matlock MD. A watershed-level ecological risk assessment methodology. Water Resources Bulletin 1996;32(5):1039-54.

54. Hoehn E, Johnson CA, Huggenberger P, Amirbahman A, Peter A, Zweifel HR. Investigative strategies and risk assessment of old unlined municipal solid waste landfills. Waste Management & Research 2000;18(6):577-89.

55. Huggett A, Petersen BJ, Walker R, Fisher CE, Notermans SHW, Rombouts FM, et al. Towards internationally acceptable standards for food additives and contaminants based on the use of risk analysis. Environmental Toxicology and Pharmacology 1998;5(4):227-36.

56. Illing HPA. Are societal judgments being incorporated into the uncertainty factors used in toxicological risk assessment? Regulatory Toxicology and Pharmacology 1999;29(3):300-8.

58. Johnston RK, Munns WR, Tyler PL, Marajh-Whittemore PR, Finkelstein K, Munney K, et al. Weighing the Evidence of Ecological Risk From Chemical Contamination in the Estuarine Environment Adjacent to the Portsmouth Naval Shipyard, Kittery, Maine, Usa. Environmental Toxicology and Chemistry 2002 Jan;21(1):182-94.

59. Jonkman SN, van Gelder PHAJM, Vrijling JK. An overview of quantitative risk measures for loss of life and economic damage. JOURNAL-OF-HAZARDOUS-MATERIALS 2003;APR 4 2003; 99:1.

60. Keating BA, Carberry PS, Hammer GL, Probert ME, Robertson MJ, Holzworth D, et al. An overview of APSIM, a model designed for farming systems simulation. EUROPEAN-JOURNAL-OF-AGRONOMY 2003 Jan;18(3-4):267-88.

61. Khadam I, Kaluarachchi JJ. Applicability of risk-based management and the need for risk-based economic decision analysis at hazardous waste contaminated sites. ENVIRONMENT-INTERNATIONAL 503;JUL 2003; 29:4.

62. Kickert RN, Tonella G, Simonov A, Krupa SV. Predictive modeling of effects under global change. Environmental Pollution 1999;100(1-3):87-132.

63. Kimmel CA. US EPA reference dose/reference concentration methodology: Update on a review of the process. Human and Ecological Risk Assessment 2001;7(1):117-23.

64. Kooistra L, Leuven RSEW, Nienhuis PH, Wehrens R, Buydens LMC. A procedure for incorporating spatial variability in ecological risk assessment of Dutch River floodplains. Environmental Management 2001;28(3):359-73.

65. Kreft JU, Picioreanu C, Wimpenny JWT, Van Loosdrecht MCM. Individual-Based Modelling of Biofilms. Microbiology-Sgm 2001 Nov;147:2897-912.

66. Krishnan K, Paterson J, Williams DT. Health risk assessment of drinking water contaminants in Canada: The applicability of mixture risk assessment methods. Regulatory Toxicology and Pharmacology 1997;26(2):179-87.

67. Kunkel HO, Thompson PB, Miller BA, Skaggs CL. Use of competing conceptions of risk in animal agriculture. Journal of Animal Science 1998;76(3):706-13.

68. Lahkim MB, Garcia LA. Stochastic modeling of exposure and risk in a contaminated heterogeneous aquifer. 1. Monte Carlo uncertainty analysis. Environmental Engineering Science 1999;16(5):315-28.

69. Lahkim MB, Garcia LA, Nuckols JR. Stochastic modeling of exposure and risk in a contaminated heterogeneous aquifer. 2: Application of Latin Hypercube Sampling. Environmental Engineering Science 1999;16(5):329-43.

70. Lambe J, Kearney J, Leclercrq C, Berardi D, Zunft HFJ, Sulzer S, et al. Enhancing the capacity of food consumption surveys of short duration to estimate long term consumer-only intakes by combination with a qualitative food frequency questionnaire. Food Additives and Contaminants 2000;17(3):177-87.

71. Lansigan FP, Pandey S, Bouman BAM. Combining crop modelling with economic risk-analysis for the evaluation of crop management strategies. Field Crops Research 1997;51(1-2):133-45.

72. Larsen JC, Farland W, Winters D. Current risk assessment approaches in different countries. Food Additives and Contaminants 2000;17(4):359-69.

73. Li JB, Huang GH, Zeng GM. An integrated decision support system for the management of petroleum-contaminated sites. Journal of Environmental Science and Health Part A Toxic/Hazardous Substances & Environmental Engineering 2001;36(7):1163-86.

74. Lowell RB, Culp JM, Dube MG. A weight-of-evidence approach for Northern River risk assessment: Integrating the effects of multiple stressors. Environmental Toxicology and Chemistry 2000;19(4):1182-90.

76. Maxwell RM, Pelmulder SD, Tompson AFB, Kastenberg WE. On the development of a new methodology for groundwater-driven health risk assessment. Water Resources Research 1998;34(4):833-47.

77. McAvoy DC, Grady CPL, Blok J, Feijtel TCJ, Federle TW, Larson RJ. A simplified modeling approach using microbial growth kinetics for predicting exposure concentrations of organic chemicals in treated wastewater effluents. Chemosphere 1998;36(10):2291-304.

78. McAvoy DC, Masscheleyn P, Peng C, Morrall SW, Casilla AB, Lim JMU, et al. Risk assessment approach for untreated wastewater using the QUAL2E water quality model. CHEMOSPHERE- 1955;JUL 2003; 52:1.

79. McKay J, Moeller A. Is risk associated with drinking water in Australia of significant concern to justify mandatory regulation? Environmental Management 2001;28(4):469-81.

80. Montgomery WD. Cost-benefit analysis in a regulatory setting. Human and Ecological Risk Assessment 1998;4(4):971-89.

81. Moutou F, Dufour B, Ivanov Y. A Qualitative Assessment of the Risk of Introducing Foot and Mouth Disease Into Russia and Europe From Georgia, Armenia and Azerbaijan. Revue Scientifique Et Technique De L Office International Des Epizooties 2001 Dec;20(3):723-30.

82. Mujumdar PP, Sasikumar K. A fuzzy risk approach for seasonal water quality management of a river system. WATER-RESOURCES-RESEARCH 2002; 38:1.

83. Murado MA, Gonzalez MP, Vazquez JA. Dose-Response Relationships: an Overview, a Generative Model and Its Application to the Verification of Descriptive Models. Enzyme and Microbial Technology 2002 Sep;31(4):439-55.

84. Myhr AI, Traavik T. Genetically modified (GM) crops: Precautionary science and conflicts of interests. JOURNAL OF AGRICULTURAL AND ENVIRONMENTAL ETHICS 2003;16:227-47.

85. Naito W, Miyamoto K, Nakanishi J, Masunaga S, Bartell SM. Application of an Ecosystem Model for Aquatic Ecological Risk Assessment of Chemicals for a Japanese Lake. Water Research 2002 Jan;36 (1):1-14.

86. Nickelsen L, Jakobsen M. Quantitative risk analysis of aflatoxin toxicity for the consumers of 'kenkey' - A fermented maize product. Food Control 1997;8(3):149-59.

87. Obery AM, Landis WG. A Regional Multiple Stressor Risk Assessment of the Codorus Creek Watershed Applying the Relative Risk Model. Human and Ecological Risk Assessment 2002 Feb;8(2):405-28.

88. Parkin RT, Balbus JM. Variations in concepts of "susceptibility" in risk assessment. Risk Anal 2000 Oct;20(5):603-11.

89. Patz JA, McGeehin MA, Bernard SM, Ebi KL, Epstein PR, Grambsch A, et al. The potential health impacts of climate variability and change for the United States: Executive summary of the report of the health sector of the US National Assessment. Environmental Health Perspectives 2000;108(4):367-76.

90. Paustenbach DJ. The practice of exposure assessment: A state-of-the-art review (Reprinted from Principles and Methods of Toxicology, 4th edition, 2001). Journal of Toxicology and Environmental Health Part B Critical Reviews 2000;3(3):179-291.

92. Portielje R, HvitvedJacobsen T, SchaarupJensen K. Risk analysis using stochastic reliability methods applied to two cases of deterministic water quality models. Water Research 2000;34(1):153-70.

93. Pouillot R, Albert I, Cornu M, Denis JB. Estimation of Uncertainty and Variability in Bacterial Growth Using Bayesian Inference. Application to Listeria Monocytogenes. International Journal of Food Microbiology 2003 Mar;81(2):87-104.

94. Pouteau S. Beyond substantial equivalence: Ethical equivalence. Journal of Agricultural & Environmental Ethics 2000;13(3-4):273-91.

95. Prodanovic P, Simonovic SP. Comparison of fuzzy set ranking methods for implementation in water resources decision-making. CANADIAN-JOURNAL-OF-CIVIL-ENGINEERING 2002;OCT 2002; 29:: 692-701 .

96. Ragas AMJ, Etienne RS, Willemsen FH, vandeMeent D. Assessing model uncertainty for environmental decision making: A case study of the coherence of independently derived environmental quality objectives for air and water. Environmental Toxicology and Chemistry 1999;18(8):1856-67.

98. Raschke AM, Burger AEC. Risk assessment as a management tool used to assess the effect of pesticide use in an irrigation system, situated in a semi-desert region. Archives of Environmental Contamination and Toxicology 1997;32(1):42-9.

99. Regan HM, Hope BY, Ferson S. Analysis and Portrayal of Uncertainty in a Food-Web Exposure Model. Human and Ecological Risk Assessment 2002 Dec;8(7):1757-77.

100. Rowlands JC. Determining the Safety of Bioengineered Microorganisms. Food Technology 2002 Oct;56(10):28-31.

101. Sadiq R, Husain T, Kar S. Chloroform Associated Health Risk Assessment Using Bootstrapping: a

Case Study for Limited Drinking Water Samples. Water Air and Soil Pollution 2002 Jul;138(1-4):123-40.

102. Sasikumar K, Mujumdar PP. Application of fuzzy probability in water quality management of a river system. INTERNATIONAL-JOURNAL-OF-SYSTEMS-SCIENCE 575;MAY 2000; 31:5.

103. Scavizzi MR, Labia R, Petitjean OJ, Elbhar A. Antimicrobial Susceptibility Test: From Bacterial Population Analysis to Therapy. International Journal of Antimicrobial Agents 2002 Jan;19(1):9-20.

104. Schowanek D, Fox K, Holt M, Schroeder FR, Koch V, Cassani G, et al. GREAT-ER: a new tool for management and risk assessment of chemicals in river basins - Contribution to GREAT-ER #10. Water Science and Technology 2001;43(2):179-85.

105. Schulze C, Matthies M, Trapp S, Schroder FR. Georeferenced fate modelling of LAS in the Itter stream. Chemosphere 1999;39(11):1833-52.

106. Scott PK, Rabbe DE, Liebig EW, Finley BL. Evaluation of three measures of exposure concentration: A case study of surface sediment concentrations in the Passaic River. Human and Ecological Risk Assessment 2000;6(3):511-28.

107. Sebille V, Valleron AJ. A computer simulation model for the spread of nosocomial infections caused by multidrug-resistant pathogens. Computers and Biomedical Research 1997;30(4):307-22.

108. Sekizawa J, Suter G, Birnbaum L. Integrated Human and Ecological Risk Assessment: a Case Study of Tributyltin and Triphenyltin Compounds. Human and Ecological Risk Assessment 2003 Feb;9(1):325-42.

111. Solomon K, Giesy J, Jones P. Probabilistic risk assessment of agrochemicals in the environment. Crop Protection 2000;19(8-10):649-55.

112. Stijnen JW, Heemink AW, Ponnambalam K. Numerical treatment of stochastic river quality models driven by colored noise - art. no. 1053. WATER-RESOURCES-RESEARCH 2003;39:3.

113. Toll JE, Pavlou SP. Risk assessment modeling: Beyond exposure and effects. Human and Ecological Risk Assessment 1998;4(4):939-49.

114. Tomerlin JR. The US Food Quality Protection Act - policy implications of variability and consumer risk. Food Additives and Contaminants 2000;17(7):641-8.

115. Tyagi A, Haan CT. Reliability, risk and uncertainty analysis using generic expectation functions. JOURNAL-OF-ENVIRONMENTAL-ENGINEERING-ASCE 938;OCT 2001; 127:10.

116. Varis O, Kuikka S. Learning Bayesian decision analysis by doing: lessons from environmental and natural resources management. Ecological Modelling 1999;119(2-3):177-95.

117. Verro R, Calliera M, Maffioli G, Auteri D, Sala S, Finizio A, et al. GIS-Based system for surface

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118. Vorhees DJ, Driscoll SBK, Von Stackelberg K, Cura JJ, Bridges TS. An Evaluation of Sources of Uncertainty in a Dredged Material Assessment. Human and Ecological Risk Assessment 2002 Feb;8(2):369-89.

119. Walter MT, Walter MF, Brooks ES, Steenhuis TS, Boll J, Weiler K. Hydrologically sensitive areas: Variable source area hydrology implications for water quality risk assessment. Journal of Soil and Water Conservation 2000;55(3):277-84.

120. Waltner-Toews D, McEwen SA. Residues of hormonal substances in foods of animal origin: A risk assessment. Preventive Veterinary Medicine 1994 Aug;20(3):235-47.

122. Washburn ST, Kleiman CF, Arsnow DE. Applying USEPA risk assessment guidance in the 90s. Human and Ecological Risk Assessment 1998;4(3):763-74.

123. Wolt J, Singh P, Cryer S, Lin J. Sensitivity Analysis for Validating Expert Opinion as to Ideal Data Set Criteria for Transport Modeling. Environmental Toxicology and Chemistry 2002 Aug;21(8):1558-65.

124. Zepeda L, Buelow KL, Nordlund KV, Thomas CB, Collins MT, Goodger WJ. A linear programming assessment of the profit from strategies to reduce the prevalence of Staphylococcus aureus mastitis. Preventive Veterinary Medicine 1998;33(1-4):183-93.

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2. Anklam E, Battaglia R. Food Analysis and Consumer Protection. Trends in Food Science & Technology 2001 May-2001 Jun;12(5-6):197-202.

3. Anonymous. Canadian researchers develop computerized microbiological hazard assessment system. World Food Chemical News 1996 May;21-2.

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5. Ashley RM, Souter N, Butler D, Davies J, Dunkerley J, Hendry S. Assessment of the sustainability of alternatives for the disposal of domestic sanitary waste. WATER-SCIENCE-AND-TECHNOLOGY 1999;39(5):251-8.

6. Bailar JC, Travers K. Review of Assessments of the Human Health Risk Associated With the Use of Antimicrobial Agents in Agriculture. Clinical Infectious Diseases 2002 Jun;34:S135-S143.

7. Balbus J, Parkin R, Embrey M. Susceptibility in Microbial Risk Assessment: Definitions and Research Needs. Environmental Health Perspectives 2000 Sep;108(9):901-5.

8. Banati D, Lakner Z. The Food Safety Issue and the Consumer Behaviour in a Transition Economy: a Case Study of Hungary. Acta Alimentaria 2002 Mar;31(1):21-36.

9. Bernard DT, Scott VN. Risk assessment and food-borne micro-organisms: The difficulties of biological diversity. Food Control 1995 Dec;6(6):329-33.

10. Besancon P. An evaluation of the safety of foods produced from genetically modified crops: what is certain and what isn't. OCL Oleagineux Corps Gras Lipides 2000;7(4):310-3.

12. Bockstael NE. Valuing the benefits of microbial food safety risk reduction: Discussion. American Journal of Agricultural Economics 1999;81(5):1200-4.

13. Boenke A. Contribution of European Research to Risk Analysis. Food Additives and Contaminants 2001 Dec;18(12):1135-40.

15. Bruce D. Finding a Balance Over Precaution. Journal of Agricultural & Environmental Ethics 2002;15(1):7-16.

16. Buchanan RL, Lammerding AM, Clarke IR, vanSchothorst M, Roberts TA. Potential application of risk assessment techniques to microbiological issues related to international trade in food and food products. Journal of Food Protection 1998;61(8):1075-86.

17. Buchanan RL, Smith JL, Long W. Microbial risk assessment: dose-response relations and risk characterization. International Journal of Food Microbiology 2000;58(3):159-72.

18. Buchanan RL, Whiting RC. Risk assessment and predictive microbiology. Journal of Food

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19. Buchanan RL, Whiting RC, Damert WC. When is simple good enough: A comparison of the Gompertz, Baranyi, and three-phase linear models for fitting bacterial growth curves. Food Microbiology 1997;14(4):313-26.

20. Busch L. The Homiletics of Risk. Journal of Agricultural & Environmental Ethics 2002;15(1):17-29.

21. Butcher JB. Practical decision methods for watershed management. Human and Ecological Risk Assessment 1999;5(2):263-74.

22. Canet C. Importance of International Cooperation in Food Safety. Food Additives and Contaminants 1993 Jan-1993 Feb;10(1):97-104.

23. Carrington CD, Bolger PM. Uncertainty and risk assessment. Human and Ecological Risk Assessment 1998;4(2):253-7.

24. Christophe B. The 1999 Belgian food crisis. Development and management. BIOMEDICAL-RESEARCH-TOKYO 2000 Dec;21(6):345-52.

25. Cooper WE. Risk assessment and risk management: An essential integration. Human and Ecological Risk Assessment 1998;4(4):931-7.

26. Craun GF, Frost FJ. Possible information bias in a waterborne outbreak investigation. INTERNATIONAL-JOURNAL-OF-ENVIRONMENTAL-HEALTH-RESEARCH 2002 Mar;12(1):5-15.

27. Craun GE, Calderon RL. Waterborne disease outbreaks caused by distribution system deficiencies. JOURNAL-AMERICAN-WATER-WORKS-ASSOCIATION 1964;SEP 2001; 93:9.

28. Crerar SK. Ensuring food safety throughout the food supply chain. Asian Australasian Journal of Animal Sciences 2000;13:376.

29. Crerar SK. Key information underpinning an effective national food safety strategy. Food Australia 1999;51(11):556-9.

31. Dayan AD. Future problems requiring scientific consideration. Food and Chemical Toxicology 2000;38:S101-S106.

33. Driscoll SBK, Wickwire WT, Cura JJ, Vorhees DJ, Butler CL, Moore DW, et al. A Comparative Screening-Level Ecological and Human Health Risk Assessment for Dredged Material Management Alternatives in New York/New Jersey Harbor. Human and Ecological Risk Assessment 2002 Apr;8(3):603-26.

34. FAO/WHO Expert Consultation. Application of Risk Analysis to Food Standards Issues.

35. Farber JM, Harwig J. The Canadian position on Listeria monocytogenes in ready-to-eat foods. Food Control 1996;7(4-5):253-8.

36. Feldman J. Risk assessment, a community perspective. Environmental Health Perspectives 1995 Sep;103( Suppl. 6):153-8.

37. Foegeding PM. Driving predictive modelling on a risk assessment path for enhanced food safety. International Journal of Food Microbiology 1997;36(2-3):87-95.

38. Foegeding PM, Roberts T. Assessment of risks associated with foodborne pathogens: An overview of a council for agricultural science and technology report. Journal of Food Protection 1996;( Suppl.):19-23.

39. Foegeding PM, Roberts T. Interpretive Summary. Foodborne Pathogens: Risks and Consequences. Foodborne Pathogens: Risks and Consequences 1994 Sep.

40. Food and Agriculture Organization. Risk Management and Food Safety65.

42. Forsythe RH. Risk - Reality Versus Perception. Poultry Science 1993 Jun;72(6):1152-6.

43. Fowle JR. Accounting for susceptibility in risk assessment: The need for full disclosure. Environmental Toxicology and Pharmacology 1997; 4(3-4):247-50.

44. Franklin A, Acar J, Anthony F, Gupta R, Nicholls T, Tamura Y, et al. Antimicrobial resistance: harmonisation of national antimicrobial resistance monitoring and surveillance programmes in animals and in animal-derived food. REVUE-SCIENTIFIQUE-ET-TECHNIQUE-DE-L-OFFICE-INTERNATIONAL-DES-EPIZOOTIES 2001 Dec;20(3):859-70.

45. Friedlander LG, Brynes SD, Fernandez AH. The human food safety evaluation of new animal drugs. VETERINARY-CLINICS-OF-NORTH-AMERICA-FOOD-ANIMAL-PRACTICE 1999 Mar;15(1):1-11,VII.

46. Gale P. Developments in microbiological risk assessment for drinking water. Journal of Applied Microbiology 2001;91(2):191-205.

47. Gale P. Developments in microbiological risk assessment models for drinking water - A short review. Journal of Applied Bacteriology 1996;81(4):403-10.

48. Garrett ES, Jahncke ML, Tennyson JM. Microbiological hazards and emerging food-safety issues associated with seafoods. Journal of Food Protection 1997;60(11):1409-15.

49. Gaylor DW, Axelrad JA, Brown RP, Cavagnaro JA, Cyr WH, Hulebak KL, et al. Health risk assessment practices in the US Food and Drug Administration. Regulatory Toxicology and Pharmacology 1997;26(3):307-21.

50. Gibb HJ. Current Perspectives on Issues in Risk Assessment Methods. Human and Ecological Risk Assessment 2002 Oct;8(6):1249-51.

51. Gibson CJ, Haas CN, Rose JB. Risk assessment of waterborne protozoa: current status and future trends. Parasitology 1998;117:S205-S212.

52. Goldstein BD. The precautionary principle also applies to public health actions. AMERICAN-JOURNAL-OF-PUBLIC-HEALTH 2001 Sep;91(9):1358-61.

53. Guillemot D. Antibiotic use in humans and bacterial resistance. Current Opinion in Microbiology 1999;2(5):494-8.

54. Guzewich JJ, Bryan FL, Todd ECD. Surveillance of foodborne disease .1. Purposes and types of surveillance systems and networks. Journal of Food Protection 1997;60(5):555-66.

55. Haas CN. Progress and Data Gaps in Quantitative Microbial Risk Assessment. Water Science and Technology 2002;46(11-12):277-84.

56. Haas CN, Rose JB, Gerba CP, Crockett CS. What predictive food microbiology can learn from water microbiology. Food Technology 1997;51(4):91-4.

57. Harremoes P. Advanced water treatment as a tool in water scarcity management. WATER-SCIENCE-AND-TECHNOLOGY 2000;42(12):73-92.

58. Hathaway S. Management of food safety in international trade. Food Control 1999;10(4-5):247-53.

59. Hathaway S. The principle of equivalence. FOOD-CONTROL 1999 Aug-1999 Oct;10(4-5):261-5.

60. Hathaway SC. Development of food safety risk assessment guidelines for foods of animal origin in international trade . Journal of Food Protection 1997;60(11):1432-8.

61. Hathaway SC. Risk assesment procedures used by the Codex Alimentarius Commission and its subsidiary and advisory bodies. Food Control 1993;4(4):189-201.

62. Hathaway SC, Cook RL. A regulatory perspective on the potential uses of microbial risk assessment in international trade. International Journal of Food Microbiology 1997;36(2-3):127-33.

63. Herikstad H, Yang S, Van Gilder TJ, Vugia D, Hadler J, Blake P, et al. A Population-Based Estimate of the Burden of Diarrhoeal Illness in the United States: Foodnet, 1996-7. Epidemiology and Infection 2002 Aug;129(1):9-17.

64. Hildebrandt T. Some aspects of the white paper and the longitudinal integration of safety assurance. Fleischwirtschaft 2001;81(1):69-75.

65. Hitzfeld BC, Hoger SJ, Dietrich DR. Cyanobacterial toxins: Removal during drinking water treatment, and human risk assessment. Environmental Health Perspectives 2000;108:113-22.

66. Horton LR. Risk Analysis and the Law: International Law, the World Trade Organization, Codex Alimentarius and National Legislation. Food Additives and Contaminants 2001 Dec;18(12):1057-67.

67. Hubert P. A comparative approach to some developments in risk management in France through the organisation of agencies. OCL Oleagineux Corps Gras Lipides 2000;7(5):416-23.

68. Huggett A, Petersen BJ, Walker R, Fisher CE, Notermans SHW, Rombouts FM, et al. Towards internationally acceptable standards for food additives and contaminants based on the use of risk analysis. Environmental Toxicology and Pharmacology 1998;5(4):227-36.

69. Hunter PR, ESEN Project. Modelling the impact of prior immunity, case misclassification and bias on case-control studies in the investigation of outbreaks of cryptosporidiosis. EPIDEMIOLOGY-AND-INFECTION 2000 Dec;125(3):713-8.

70. Huss HH, Reilly A, BenEmbarek PK. Prevention and control of hazards in seafood. Food Control

2000;11(2):149-56.

71. Jaykus LA. The application of quantitative risk assessment to microbial food safety risks. Critical Reviews in Microbiology 1996;22(4):279-93.

72. Jouve JL. Principles of food safety legislation. Food Control 1998;9(2-3):75-81.

73. Kastner JJ, Pawsey RK. Harmonising Sanitary Measures and Resolving Trade Disputes Through the Wto-Sps Framework. Part I: a Case Study of the Us-Eu Hormone-Treated Beef Dispute. Food Control 2002 Jan;13(1):49-55.

74. Kilsby DC, Davies KW, McClure PJ, Adair C, Anderson WA. Bacterial thermal death kinetics based on probability distributions: The heat destruction of Clostridium botulinum and Salmonella Bedford . Journal of Food Protection 2000;63(9):1197-203.

75. Kindred TP. Risk analysis and its application in FSIS. Journal of Food Protection 1996;( Suppl.):24-30.

76. Klapwijk PM, Jouve JL, Stringer MF. Microbiological risk assessment in Europe: the next decade. International Journal of Food Microbiology 2000;58(3):223-30.

77. Kleer J, Hildebrandt G. Importance of Predictive Microbiology for risk minimization in food production processes - 2. Shortcomings and benefits. FLEISCHWIRTSCHAFT 2001;81(7):91-5.

78. Knox B. Consumer perception and understanding of risk from food. BRITISH-MEDICAL-BULLETIN 2000;56(1):97-109.

79. Kotloff KL, Winickoff JP, Ivanoff B, Clemens JD, Swerdlow DL, Sansonetti PJ, et al. Global burden of Shigella infections: implications for vaccine development and implementation of control strategies. Bulletin of the World Health Organization 1999;77(8):651-66.

80. Kruse H. Globalization of the food supply-food safety implications Special regional requirements: future concerns. Food Control 1999;10(4-5):315-20.

81. Kynast-Wolf G, Becker N, Kroke A, Brandstetter BR, Wahrendorf J, Boeing H. Linear Regression Calibration: Theoretical Framework and Empirical Results in Epic, Germany. Annals of Nutrition and Metabolism 2002 Jan-2002 Feb;46(1):2-8.

82. Lammerding AM. An overview of microbial food safety risk assessment. Journal of Food Protection 1997;60(11):1420-5.

83. Lammerding AM, Fazil A. Hazard identification and exposure assessment for microbial food safety risk assessment. International Journal of Food Microbiology 2000;58(3):147-57.

84. Lammerding AM, Paoli GM. Quantitative risk assessment: an emerging tool for emerging foodborne pathogens. Emerging Infectious Diseases 1997;3(4):483-7.

85. Lathers CM. Risk assessment in regulatory policy making for human and veterinary public health. JOURNAL-OF-CLINICAL-PHARMACOLOGY 2002 Aug; 42(8):846-66.

86. Lathers CM. Role of veterinary medicine in public health: Antibiotic use in food animals and humans and the effect on evolution of antibacterial resistance. JOURNAL-OF-CLINICAL-PHARMACOLOGY 2001 Jun;41(6):595-9.

87. Lawrence E. Advisory Committee on Dangerous Pathogens (ACDP) seminar on microbiological risk assessment, 28 January 1997. Journal of Applied Microbiology 1997;83(5):659-64.

88. Lindqvist R, Sylven S, Vagsholm I. Quantitative Microbial Risk Assessment Exemplified by Staphylococcus Aureus in Unripened Cheese Made From Raw Milk. International Journal of Food Microbiology 2002 Sep;78(1-2):155-70.

89. Lloyd A, Drury D. Continuous Monitoring for Cryptosporidium - a Novel Approach to Public Health Protection. Water Science and Technology 2002;46(11-12):297-301.

91. Macler BA, Regli S. Use of Microbial Risk Assessment in Setting United-States Drinking Water Standards. International Journal of Food Microbiology 1993 Jun;18(4):245-56.

92. Mara DD, Horan NJ. Sludge to Land: Microbiological Double Standards. Journal of the Chartered Institution of Water and Environmental Management 2002 Nov;16(4):249-52.

93. Martel JL, Tardy F, Sanders P, Boisseau J. New trends in regulatory rules and surveillance of antimicrobial resistance in bacteria of animal origin. VETERINARY-RESEARCH 2001 May-2001 Aug;32(3-4):381-92.

94. Mayer S, Stirling A. Finding a Precautionary Approach to Technological Developments - Lessons for the Evaluation of Gm Crops. Journal of Agricultural & Environmental Ethics 2002;15(1):57-71.

95. McCarthy JF. The 1996 Food Quality Protection Act - An evolution or a revolution for toxicology and risk assessment? Toxicologic Pathology 1998;26(6):828-9.

96. Mcintosh WA, Christensen LB, Acuff GR. Perceptions of Risks of Eating Undercooked Meat and Willingness to Change Cooking Practices. Appetite 1994 Feb;22(1):83-96.

97. McNab WB. A Literature Review Linking Microbial Risk Assessment, Predictive Microbiology, and Dose-Response Modeling. Dairy, Food and Environmental Sanitation 1997 Jul;17(7):405-16.

98. Miles DW, Ross T. Identifying and quantifying risks in the food production chain. Food Australia 1999;51(7):298-303.

99. Miller SA. Science, law and society: The pursuit of food safety. Journal of Nutrition 1993 Feb;123(2 Suppl.):279-84.

100. Morales RA. Microbial risk assessment, economics, and food safety. Journal of the American Veterinary Medical Association 1998;213(12):1746-9.

101. Morales RA, McDowell RM. Risk assessment and economic analysis for managing risks to human health from pathogenic microorganisms in the food supply. Journal of Food Protection 1998;61(11):1567-70.

102. Morris J. The relationship between risk analysis and the precautionary principle. Toxicology 2002 Dec;181-182:127-30.

103. Mossel DAA, Weenk GH, Morris GP, Struijk CB. Identification, assessment and management of food-related microbiological hazards: historical, fundamental and psycho-social essentials.

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105. Mugglestone MA, Stutt ED, Rushton L. Setting microbiological water quality standards for sea bathing - a critical evaluation. Water Science and Technology 2001;43(12):9-18.

107. Norrung B. Microbiological criteria for Listeria monocytogenes in foods under special consideration of risk assessment approaches. International Journal of Food Microbiology 2000;62(3):217-21.

108. Notermans S, Hoornstra E. Risk assessment of Listeria monocytogenes in fish products: some general principles, mechanism of infection and the use of performance standards to control human exposure. International Journal of Food Microbiology 2000;62(3):223-9.

109. Ohl ME, Miller SI. Salmonella: A model for bacterial pathogenesis. Annual Review of Medicine 2001;52:259-74.

111. Paustenbach DJ. The practice of exposure assessment: A state-of-the-art review (Reprinted from Principles and Methods of Toxicology, 4th edition, 2001). Journal of Toxicology and Environmental Health Part B Critical Reviews 2000;3(3):179-291.

112. Periago PM, Palop A, Martinez A, Fernandez PS. Exploring New Mathematical Approaches to Microbiological Food Safety Evaluation: An Approach to More Efficeint Risk Assessment Implementation. Dairy, Food and Environmental Sanitation 2002 Jan;22(1):18-23.

113. Potter ME, Brudney JL. Risk Assessment for Infectious Foodborne Diseases: A Priority with Problems. Journal of Agromedicine 1994;1(3):11-22.

114. Pouteau S. The Food Debate: Ethical Versus Substantial Equivalence. Journal of Agricultural & Environmental Ethics 2002 Fall;15(3):291-303.

116. Randell AW, Whitehead AJ. Codex Alimentarius: food quality and safety standards for international trade. Revue Scientifique Et Technique De L Office International Des Epizooties 1997;16(2):313-21.

117. Reckhow KH. Lessons from risk assessment. Human and Ecological Risk Assessment 1999;5(2):245-53.

119. Reij MW, vanSchothorst M. Critical notes on microbiological risk assessment of food. Brazilian Journal of Microbiology 2000;31(1):1-8.

120. Rizak S, Cunliffe D, Sinclair M, Vulcano R, Howard J, Hrudey S, et al. Drinking water quality management: a holistic approach. WATER-SCIENCE-AND-TECHNOLOGY 2003;47(9):31-6.

121. Sas B. About the phylosophy and international considerations related to the risk analysis and assessment of microbiological contamination in foods. Magyar Allatorvosok Lapja 2000;122(5):303-9.

122. Saunders RD. Reducing the Risk of Foodborne Illness: A State Perspective. Journal of the Association of Food and Drug Officials 2001 Mar; 65(1):9-13.

123. Schaffner DW. Use of microbial risk assessment to improve food safety. Dairy, Food and Environmental Sanitation 1999 Jun;19(6):404-5.

124. Schilter B, Holzhauser D, Cavin C, Huggett AC. An integrated in vivo and in vitro strategy to improve food safety evaluation. Trends in Food Science & Technology 1996;7(10):327-32.

125. Schlundt J. Comparison of microbiological risk assessment studies published. International Journal of Food Microbiology 2000;58(3):197-202.

126. Schlundt J. New Directions in Foodborne Disease Prevention. International Journal of Food Microbiology 2002 Sep;78(1-2):3-17.

127. Schlundt J. Principles of food safety Risk management. Food Control 1999;10(4-5):299-302.

128. Shank FR, Elliot EL, Wachsmuth IK, Losikoff ME. US position on Listeria monocytogenes in foods. Food Control 1996;7(4-5 ):229-34.

129. Somogyi A. Food Safety in the Light of Consumer Health Protection. Magyar Allatorvosok Lapja 2001 Nov;123(11):666-9.

130. Sperber WH. The role of microbiological criteria and risk assessment in HACCP - Response. Food Microbiology 1995 Oct;12 (5):431.

131. Starbird SA. Designing food safety regulations: The effect of inspection policy and penalties for noncompliance on food processor behavior. Journal of Agricultural and Resource Economics 2000;25(2):616-35.

133. Szewzyk U, Szewzyk R, Manz W, Schleifer KH. Microbiological safety of drinking water. Annual Review of Microbiology 2000;54:81-127.

134. Teufel P. Foodsafety objectives - Is there a zero-risk? KIELER-MILCHWIRTSCHAFTLICHE-FORSCHUNGSBERICHTE 1999;51(1):5-14.

135. Thompson PB. Risk, Consent and Public Debate: Some Preliminary Considerations for the Ethics of Food Safety. International Journal of Food Science and Technology 2001 Dec;36(8):833-43.

136. Todd ECD, Harwig J. Microbial risk analysis of food in Canada. Journal of Food Protection 1996;Suppl.( Suppl.):10-8.

137. Tomerlin JR. The US Food Quality Protection Act - policy implications of variability and consumer

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138. Trautman TD. Risk Communication - the Perceptions and Realities. Food Additives and Contaminants 2001 Dec;18(12):1130-4.

139. Untermann F. Risk assessment of microorganisms in food. Zentralblatt Fur Hygiene Und Umweltmedizin 1995 Apr;197(1-3):222-31.

140. van den Bogaard AE, Stobberingh EE. Antibiotic usage in animals - Impact on bacterial resistance and public health. DRUGS 1999 Oct;58(4):589-607.

141. van Gerwen SJC, Zwietering MH. Growth and inactivation models to be used in quantitative risk assessments. Journal of Food Protection 1998;61(11):1541-9.

142. van Schothorst M. Microbiological Risk Assessment of foods in international trade. SAFETY-SCIENCE 359;FEB-JUN 2002; 40:1-4.

143. van Schothorst M. Practical approaches to risk assessment. Journal of Food Protection 1997;60(11):1439-43.

144. van Schothorst M. Principles for the establishment of microbiological food safety objectives and related control measures. Food Control 1998;9(6):379-84.

145. Vanderlinde P. Quantitative microbial risk assessment - An Australian perspective. Food Australia 1998;50(12):626-8.

146. vanGerwen SJC, teGiffel MC, vantRiet K, Beumer RR, Zwietering MH. Stepwise quantitative risk assessment as a tool for characterization of microbiological food safety. Journal of Applied Microbiology 2000;88(6):938-51.

147. Varis O, Kuikka S. Learning Bayesian decision analysis by doing: lessons from environmental and natural resources management. Ecological Modelling 1999;119(2-3):177-95.

148. Voysey PA, Brown M. Microbiological risk assessment: a new approach to food safety control. International Journal of Food Microbiology 2000;58(3):173-9.

149. Wadhwa SG, Khaled GH, Edberg SC. Comparative Microbial Character of Consumed Food and Drinking Water. Critical Reviews in Microbiology 2002;28(3):249-79.

150. Walls I, Scott VN. Use of predictive microbiology in microbial food safety risk assessment. International Journal of Food Microbiology 1997;36(2-3):97-102.

151. White DG, Acar J, Anthony F, Franklin A, Gupta B, Nicholls T, et al. Antimicrobial resistance: standardisation and harmonisation of laboratory methodologies for the detection and quantification of antimicrobial resistance. REVUE-SCIENTIFIQUE-ET-TECHNIQUE-DE-L-OFFICE-INTERNATIONAL-DES-EPIZOOTIES 2001 Dec;20(3):849-58.

152. Woo DM, Vicente KJ. Sociotechnical systems, risk management, and public health: comparing the North Battleford and Walkerton outbreaks. RELIABILITY-ENGINEERING-AND-SYSTEM-SAFETY 253;JUN 2003; 80:3.

1.4.11 Predictive Microbiology The goal of predictive microbiology is to develop mathematical equations that describe

the behaviour of microorganisms under different environmental factors (physical, chemical, competitive). All of the references focused on predictive microbiology in food systems. Only one paper considered common elements between food and water systems. Growth, survival and thermal inactivation (death) models have been developed for the most important foodborne pathogens (Listeria spp. (58 papers), E.coli O157:H7 (34 papers), Salmonella spp. (21 papers), Yersinia spp. (16 papers), Staphylococcus spp. (16 papers), Clostridium botulinum (5 papers)). Many food systems have been studied: beef, poultry, fish, seafood, dairy, vegetables and processed foods. Although all of the papers included quantitative mathematical descriptions of microbial growth and inactivation, a relatively small number focused on the use of these models in quantitative risk assessment. The effect of temperature on microbial growth or lethality was the most commonly studied environmental factor (100 papers). Other important factors were pH (90 papers), water activity (28 papers), salts (53 papers), fat (4 papers). Curve fitting techniques include statistical methods and neural networks. Some models described different growth phases (lag, exponential, stationary) while others classified boundaries between growth and no-growth, death and survival. User-friendly application software has been developed (e.g. Food MicroModel and Pathogen Modelling Program). Most studies were based on one species but a few considered mixed cultures and competition effects. There are strong predictive microbiology research groups in the USA (USDA, National Food Processors Association), Europe (Food Research Institute, Katholieke Univ Leuven, RIVM Netherlands) and Australia (University of Tasmania). Agriculture and Agri-Food Canada researchers (McKellar and Piyasena) are conducting predictive microbiology studies in Canada. 1. Akterian SG, Fernandez PS, Hendrickx ME, Tobback PP, Periago PM, Martinez A. Risk analysis of

the thermal sterilization process. Analysis of factors affecting the thermal resistance of microorganisms. International Journal of Food Microbiology 1999;47(1-2):51-7.

2. Aran N. The effect of calcium and sodium lactates on growth from spores of Bacillus cereus and Clostridium perfringens in a 'sous-vide' beef goulash under temperature abuse. International Journal of Food Microbiology 2001;63(1-2):117-23.

3. Baker DA. Probability Models to Assess the Safety of Foods with Respect to Clostridium botulinum. Journal of Industrial Microbiology 1993 Fall;12(3-5):156-61.

4. Baranyi J, Mcclure PJ, Sutherland JP, Roberts TA. Modeling Bacterial Growth Responses. Journal of Industrial Microbiology 1993 Fall;12(3-5):190-4.

5. Baranyi J, Roberts TA. A Dynamic Approach to Predicting Bacterial Growth in Food. International Journal of Food Microbiology 1994 Nov;23(3-4):277-94.

6. Baranyi J, Robinson TP, Kaloti A, Mackey BM. Predicting growth of Brochothrix thermosphacta at changing temperature. International Journal of Food Microbiology 1995 Sep;27(1):61-75.

7. Bello J, Sanchez-Fuertes MA. Application of a mathematical model to describe the behaviour of the Lactobacillus spp. during the ripening of a Spanish dry fermented sausage (Chorizo). International Journal of Food Microbiology 1995 Oct;27(2-3):215-27.

8. Bertolatti D, Munyard SJ, Grubb WB, Binns CW. Thermal inactivation of antimicrobial-resistant Gram-positive cocci in chicken meat: D and Z value determinations. INTERNATIONAL-JOURNAL-OF-ENVIRONMENTAL-HEALTH-RESEARCH 2001 Sep;11(3):257-66.

9. Bhaduri S, Turner-Jones CO, Buchanan RL, Phillips JG. Response Surface Model of the Effect of pH, Sodium Chloride and Sodium Nitrite on Growth of Yersinia enterocolitica at Low Temperatures. International Journal of Food Microbiology 1994 Nov;23(3-4):333-43.

10. Bharathi S, Ramesh MN, Varadaraj MC. Predicting the behavioural pattern of Escherichia coli in minimally processed vegetables. Food Control 2001;12(5):275-84.

11. Borch E, Wallentin C. Conductance Measurements for Data Generation in Predictive Modeling. Journal of Industrial Microbiology 1993 Fall;12(3-5):286-90.

12. Breidt F, Fleming HP. Modeling of the competitive growth of Listeria manocytogenes and Lactococcus lactis in vegetable broth. Applied and Environmental Microbiology 1998;64(9):3159-65.

13. Buchanan RL, Whiting RC, Damert WC. When is simple good enough: A comparison of the Gompertz, Baranyi, and three-phase linear models for fitting bacterial growth curves. Food Microbiology 1997;14(4):313-26.

14. Buche P, Dervin C, Brouillaud-Delattre A, Gnanou-Besse N. Combining Fuzzy Querying of Imprecise Data and Predictive Microbiology Using Category-Based Reasoning for Prediction of the Possible Microbial Spoilage in Foods: Application to Listeria Monocytogenes. International Journal of Food Microbiology 2002 Mar;73(2-3):171-85.

15. Campanella OH, Peleg M. Theoretical comparison of a new and the traditional method to calculate Clostridium botulinum survival during thermal inactivation. Journal of the Science of Food and Agriculture 2001;81(11):1069-76.

16. Castillejo-Rodriguez AM, Gimeno RM, Cosano GZ, Alcala EB, Perez MR. Assessment of mathematical models for predicting Staphylococcus aureus growth in cooked meat products. Journal of Food Protection 2002;65(4):659-65.

17. Chhabra AT, Carter WH, Linton RH, Cousin MA. A Predictive Model That Evaluates the Effect of Growth Conditions on the Thermal Resistance of Listeria Monocytogenes. International Journal of Food Microbiology 2002 Oct;78(3):235-43.

18. Chhabra AT, Carter WH, Linton RH, Cousin MA. A predictive model to determine the effects of pH, milkfat, and temperature on thermal inactivation of Listeria monocytogenes. Journal of Food Protection 1999;62(10):1143-9.

19. Coleman ME. Guest editorial: Interactions of predictive microbiology and risk assessment. Risk Analysis 2003 Feb;23(1):175-8.

20. Cornu M, DelignetteMuller ML, Flandrois JP. Characterization of unexpected growth of Escherichia coli O157 : H7 by modeling. Applied and Environmental Microbiology 1999;65(12):5322-7.

21. Dalgaard P, Koutsoumanis K. Comparison of maximum specific growth rates and lag times estimated from absorbance and viable count data by different mathematical models. Journal of Microbiological Methods 2001;43(3):183-96.

22. Daughtry GJ, Davey KR, King KD. Temperature dependence of growth kinetics of food bacteria.

Food Microbiology 1997;14(1):21-30.

23. Davey KR. Linear-Arrhenius Models for Bacterial Growth and Death and Vitamin Denaturations. Journal of Industrial Microbiology 1993 Fall; 12(3-5):172-9.

24. Davey KR. Modelling the Combined Effect of Temperature and pH on the Rate Coefficient for Bacterial Growth. International Journal of Food Microbiology 1994 Nov;23(3-4):295-303.

25. Davey KR, Amos SA. Untitled. Journal of Applied Microbiology 2002;92(3):583-5.

26. Davey KR, Daughtry BJ. Validation of a model for predicting the combined effect of three environmental factors on both exponential and lag phases of bacterial growth: Temperature, salt concentration and pH. Food Research International 1995;28(3):233-7.

27. Delignette-Muller ML. Relation between the generation time and the lag time of bacterial growth kinetics. International Journal of Food Microbiology 1998;43(1-2):97-104.

28. DelignetteMuller ML, Rosso L. Biological variability and exposure assessment. International Journal of Food Microbiology 2000;58(3):203-12.

29. Dengremont E, Membre JM. Statistical approach for comparison of the growth rates of five strains of Staphylococcus aureus. Applied and Environmental Microbiology 1995 Dec;61(12):4389-95.

30. Dens EJ, VanImpe JF. On the need for another type of predictive model in structured foods. International Journal of Food Microbiology 2001;64(3):247-60.

31. Duffy S, Schaffner DW. Modeling the survival of Escherichia coli 0157 : H7 in apple cider using probability distribution functions for quantitative risk assessment. Journal of Food Protection 2001;64(5):599-605.

32. Eifert JD, Gennings C, Carter WH, Duncan SE, Hackney CR. Predictive model with improved statistical analysis of interactive factors affecting the growth of Staphylococcus aureus 196E. Journal of Food Protection 1996 Jun;59(6):608-14.

33. Erkmen O. Mathematical modeling of Escherichia coli inactivation under high-pressure carbon dioxide. Journal of Bioscience and Bioengineering 2001;92(1):39-43.

34. Fernandez A, Ocio MJ, Fernandez PS, Rodrigo M, Martinez A. Application of nonlinear regression analysis to the estimation of kinetic parameters for two enterotoxigenic strains of Bacillus cereus spores. Food Microbiology 1999;16(6):607-13.

35. Gaillard S, Leguerinel I, Mafart P. Model for combined effects of temperature, pH and water activity on thermal inactivation of Bacillus cereus spores. Journal of Food Science 1998;63(5):887-9.

36. Geeraerd AH, Herremans CH, Cenens C, VanImpe JF. Application of artificial neural networks as a non-linear modular modeling technique to describe bacterial growth in chilled food products. International Journal of Food Microbiology 1998;44(1-2):49-68.

38. Giannuzzi L, Pinotti A, Zaritzky N. Mathematical Modelling of Microbial Growth in Packaged

Refrigerated Beef Stored at Different Temperatures. International Journal of Food Microbiology 1998;39:101-10.

39. Grijspeerdt K, Herman L. Inactivation of Salmonella Enteritidis During Boiling of Eggs. International Journal of Food Microbiology 2003 Apr;82(1):13-24.

40. Haas CN, Rose JB, Gerba CP, Crockett CS. What predictive food microbiology can learn from water microbiology. Food Technology 1997;51(4):91-4.

41. Hajmeer M, Basheer I. A Probabilistic Neural Network Approach for Modeling and Classification of Bacterial Growth/No-Growth Data. Journal of Microbiological Methods 2002 Oct;51(2):217-26.

42. Hajmeer MN, Basheer IA, Marsden JL, Fung DYC. New approach for modeling generalized microbial growth curves using artificial neural networks. Journal of Rapid Methods and Automation in Microbiology 2000;8:265-83.

43. Hajmeer MN, Basheer IA, Najjar YM. Computational neural networks for predictive microbiology .1. Methodology - .2. Application to microbial growth. International Journal of Food Microbiology 1997;34(1):51-66.

44. Han Y, Floros JD, Linton RH, Nielsen SS, Nelson PE. Response surface modeling for the inactivation of Escherichia coli O157 : H7 on green peppers (Capsicum annuum L.) by chlorine dioxide gas treatments. Journal of Food Protection 2001;64(8):1128-33.

45. Han Y, Floros JD, Linton RH, Nielsen SS, Nelson PE. Response Surface Modeling for the Inactivation of Escherichia Coli O157 : H7 on Green Peppers (Capsicum Annuum) by Ozone Gas Treatment. Journal of Food Science 2002 Apr;67(3):1188-93.

46. Hervas C, Zurera G, Garcia RM, Martinez JA. Optimization of Computational Neural Network for Its Application in the Prediction of Microbial Growth in Foods. Food Science and Technology International 2001 Apr;7(2):159-63.

47. Houtsma PC, Kusters BJM, Dewit JC, Rombouts FM, Zwietering MH. Modelling growth rates of Listeria innocua as a function of lactate concentration. International Journal of Food Microbiology 1994 Dec;24(1-2):113-23.

48. Hsiao CP, Siebert KJ. Modeling the inhibitory effects of organic acids on bacteria. International Journal of Food Microbiology 1999;47(3):189-201.

49. Hyytia E, Hielm S, Mokkila M, Kinnunen A, Korkeala H. Predicted and observed growth and toxigenesis by Clostridium botulinum type E in vacuum-packaged fishery product challenge tests. International Journal of Food Microbiology 1999;47(3):161-9.

50. Jaczynski J, Park JW. Predictive models for microbial inactivation and texture degradation in surimi seafood during thermal processing. JOURNAL-OF-FOOD-SCIENCE 1025;APR 2003; 68:3.

51. Jagannath A, Ramesh A, Ramesh MN, Chandrashekar A, Varadaraj MC. Predictive model for the behavior of Listeria monocytogenes Scott A in Shrikhand, prepared with a biopreservative, pediocin K7. Food Microbiology 2001; 18(3):335-43.

52. Jagannath A, Ramesh MN, Varadaraj MC. Predicting the behavior of Escherichia coli introduced as a postprocessing contaminant in Shrikhand, a traditional sweetened lactic fermented milk product. Journal of Food Protection 2001;64(4):462-9.

53. Jeneja VK, Marks HM, Huang L. Growth and heat resistance kinetic variation among various isolates of Salmonella and it application to risk assessment. Risk Analysis 2003 Feb;23(1):199-213.

54. Jeyamkondan S, Jayas DS, Holley RA. Microbial growth modelling with artificial neural networks. International Journal of Food Microbiology 2001;64(3):343-54.

55. Juneja VK, Marmer BS, Call JE. Influence of modified atmosphere packaging on growth of Clostridium perfringens in cooked turkey. Journal of Food Safety 1996;16(2):141-50.

56. Kleer J, Hildebrandt G. Importance of predictive microbiology for risk minimization in food production processes - 1. Model development, application software, model validation. Fleischwirtschaft 2001;81(6):99-103.

57. Kleer J, Hildebrandt G. Importance of Predictive Microbiology for risk minimization in food production processes - 2. Shortcomings and benefits. FLEISCHWIRTSCHAFT 2001;81(7):91-5.

58. Labuza TP, Fu B. Growth Kinetics for Shelf-Life Prediction: Theory and Practice. Journal of Industrial Microbiology 1993 Fall;12(3-5):309-23.

59. Le Marc Y, Huchet V, Bourgeois CM, Guyonnet JP, Mafart P, Thuault D. Modelling the Growth Kinetics of Listeria as a Function of Temperature, Ph and Organic Acid Concentration. International Journal of Food Microbiology 2002 Mar;73(2-3):219-37.

60. Lebert I, Begot C, Lebert A. Development of two Listeria monocytogenes growth models in a meat broth and their application to beef meal. Food Microbiology 1998;15(5 ):499-509.

61. Lebert I, RoblesOlvera V, Lebert A. Application of polynomial models to predict growth of mixed cultures of Pseudomonas spp. and Listeria in meat. International Journal of Food Microbiology 2000;61(1):27-39.

62. Lindberg CW, Borch E. Predicting the Aerobic Growth of Y. enterocolitica O:3 at Different pH-Values, Temperatures and L-Lactate Concentrations Using Conductance Measurements. International Journal of Food Microbiology 1994 May;22(2-3):141-53.

63. Little CL, Adams MR, Anderson WA, Cole MB. Application of a Log-Logistic Model to Describe the Survival of Yersinia enterocolitica at Sub-Optimal pH and Temperature. International Journal of Food Microbiology 1994 Apr;22(1):63-71.

64. Martens DE, Beal C, Malakar P, Zwietering MH, vantRiet K. Modelling the inter-actions between Lactobacillus curvatus and Enterobacter cloacae I. Individual growth kinetics. International Journal of Food Microbiology 1999;51(1):53-65.

65. Masana NO, Baranyi J. Adding new factors to predictive models: the effect on the risk of extrapolation. Food Microbiology 2000;17(4):367-74.

66. Masson Y, Ainsworth P, Fuller D, Bozkurt H, Ibanoglu S. Growth of Pseudomonas Fluorescens and Candida Sake in Homogenized Mushrooms Under Modified Atmosphere. Journal of Food Engineering 2002 Sep;54(2):125-31.

67. Mattick KL, Jorgensen F, Wang P, Pound J, Vandeven MH, Ward LR, et al. Effect of challenge temperature and solute type on heat tolerance of Salmonella serovars at low water activity. Applied and Environmental Microbiology 2001;67(9):4128-36.

68. Mccann TL, Eifert JD, Gennings C, Schilling MW, Carter WH. A Predictive Model With Repeated Measures Analysis of Staphylococcus Aureus Growth Data. Food Microbiology 2003 Apr;20(2):139-47.

69. McClure PJ, Beaumont AL, Sutherland JP, Roberts TA. Predictive modelling of growth of Listeria monocytogenes - The effects on growth of NaCl, pH, storage temperature and NaNO2. International Journal of Food Microbiology 1997;34(3):221-32.

70. McClure PJ, Cole MB, Davies KW, Anderson WA. The Use of Automated Tubidimetric Data for the Construction of Kinetic Models. Journal of Industrial Microbiology 1993 Fall;12(3-5):277-85.

71. McKellar RC. A heterogeneous population model for the analysis of bacterial growth kinetics. International Journal of Food Microbiology 1997;36(2-3):179-86.

72. McKellar RC, Butler G, Stanich K. Modelling the influence of temperature on the recovery of Listeria monocytogenes from heat injury. Food Microbiology 1997;14(6 ):617-25.

73. McKellar RC, Knight K. A combined discrete-continuous model describing the lag phase of Listeria monocytogenes. International Journal of Food Microbiology 2000;54(3):171-80.

74. Mckellar RC, Lu X, Knight KP. Growth Ph Does Not Affect the Initial Physiological State Parameter (P(0)) of Listeria Monocytogenes. International Journal of Food Microbiology 2002 Mar;73(2-3):137-44.

75. McKellar RC, Piyasena P. Predictive modelling of inactivation of bovine milk alpha-L-fucosidase in a high-temperature short-time pasteurizer. International Dairy Journal 2000;10(1-2):1-6.

76. McMeekin TA, Presser K, Ratkowsky D, Ross T, Salter M, Tienungoon S. Quantifying the hurdle concept by modelling the bacterial growth/no growth interface. International Journal of Food Microbiology 2000;55(1-3):93-8.

77. Membre J-M, Majchrzak V, Jolly I. Effects of temperature, pH, glucose, and citric acid on the inactivation of Salmonella typhimurium in reduced calorie mayonnaise. Journal of Food Protection 1997;60(12):1497-501.

78. Membre JM, Thurette J, Catteau M. Modelling the growth, survival and death of Listeria monocytogenes. Journal of Applied Microbiology 1997;82(3):345-50.

79. Miller AJ. Data Collection and Capture Systems for Microbial Modeling. Journal of Industrial Microbiology 1993 Fall;12(3-5):291-4.

80. Nauta MJ. Modelling Bacterial Growth in Quantitative Microbiological Risk Assessment: Is It Possible? International Journal of Food Microbiology 2002 Mar;73(2-3):297-304.

81. Ng TM, Schaffner DW. Mathematical models for the effects of pH, temperature, and sodium chloride on the growth of Bacillus stearothermophilus in salty carrots . Applied and Environmental Microbiology 1997;63(4):1237-43.

82. Ng TM, Viard E, Caipo ML, Duffy S, Schaffner DW. Expansion and Validation of a Predictive Model for the Growth of Bacillus Stearothermophilus in Military Rations. Journal of Food Science 2002 Jun-2002 Jul;67(5):1872-8.

83. Nissen H, Rosnes JT, Brendehaug J, Kleiberg GH. Safety Evaluation of Sous Vide-Processed Ready Meals. Letters in Applied Microbiology 2002;35(5):433-8.

84. Oscar TP. Development and Validation of a Tertiary Simulation Model for Predicting the Potential Growth of Salmonella Typhimurium on Cooked Chicken. International Journal of Food Microbiology 2002 Jun;76(3):177-90.

85. Oscar TP. Response surface models for effects of temperature and previous growth sodium chloride on growth kinetics of Salmonella typhimurium on cooked chicken breast. Journal of Food Protection 1999;62(12):1470-4.

86. Panagou EZ, Skandamis PN, Nychas GJE. Modelling the Combined Effect of Temperature, Ph and a(W) on the Growth Rate of Monascus Ruber, a Heat-Resistant Fungus Isolated From Green Table Olives. Journal of Applied Microbiology 2003;94(1):146-56.

87. Peleg M. Microbial survival curves - the reality of flat ''shoulders'' and absolute thermal death times. Food Research International 2000;33(7):531-8.

88. Peleg M, Cole MB. Reinterpretation of microbial survival curves. Critical Reviews in Food Science and Nutrition 1998;38(5):353-80.

89. Peleg M, Penchina CM, Cole MB. Estimation of the survival curve of Listeria monocytogenes during non-isothermal heat treatments. Food Research International 2001;34(5):383-8.

90. Pirovani ME, Guemes DR, Piagnetini AM. Predictive models for available chlorine depletion and total microbial count reduction during washing of fresh-cut spinach. Journal of Food Science 2001;66(6):860-4.

91. Piyasena P, Mckellar RC, Bartlett FM. Thermal Inactivation of Pediococcus Sp in Simulated Apple Cider During High-Temperature Short-Time Pasteurization. International Journal of Food Microbiology 2003 Apr;82(1):25-31.

92. Pleasants AB, Soboleva TK, Dykes GA, Jones RJ, Filippov AE. Modelling of the Growth of Populations of Listeria Monocytogenes and a Bacteriocin-Producing Strain of Lactobacillus in Pure and Mixed Cultures. Food Microbiology 2001 Dec;18(6):605-15.

93. Poschet F, Geeraerd AH, Scheerlinck N, Nicolai BM, Van Impe JF. Monte Carlo analysis as a tool to incorporate variation on experimental data in predictive microbiology. FOOD-MICROBIOLOGY 285;JUN 2003; 20:3.

95. Ross T. Indices for performance evaluation of predictive models in food microbiology. Journal of Applied Bacteriology 1996;81(5):501-8.

96. Ross T, Dalgaard P, Tienungoon S. Predictive modelling of the growth and survival of Listeria in fishery products. International Journal of Food Microbiology 2000;62(3):231-45.

97. Ross T, McMeekin TA. Modeling microbial growth within food safety risk assessments. Risk Analysis 2003 Feb;23(1):179-97.

98. Schaffner DW. The application of the WLF equation to predict lag time as a function of temperature for three psychrotrophic bacteria. International Journal of Food Microbiology 1995 Oct;27(2-3):107-15.

99. Shimoni E, Anderson EM, Labuza TP. Reliability of Time Temperature Indicators Under

Temperature Abuse. Journal of Food Science 2001 Nov-2001 Dec;66(9):1337-40.

100. Skinner GE, Larkin JW. Conservative prediction of time to Clostridium botulinum toxin formation for use with time-temperature indicators to ensure the safety of foods. Journal of Food Protection 1998;61(9):1154-60.

101. Stewart CM, Cole MB, Legan JD, Slade L, Vandeven MH, Schaffner DW. Modeling the growth boundary of Staphylococcus aureus for risk assessment purposes. Journal of Food Protection 2001;64(1):51-7.

102. Stewart CM, Cole MB, Legan JD, Slade L, Vandeven MH, Schaffner DW. Staphylococcus aureus growth boundaries: Moving towards mechanistic predictive models based on solute-specific effects. APPLIED-AND-ENVIRONMENTAL-MICROBIOLOGY 2002 Apr;68(4):1864-71.

103. Sutherland JP, Bayliss AJ. Predictive Modelling of Growth of Yersinia enterocolitica - The Effects of Temperature, pH and Sodium Chloride. International Journal of Food Microbiology 1994 Feb;21(3):197-215.

104. Sutherland JP, Bayliss AJ, Braxton DS, Beaumont AL. Predictive modelling of Escherichia coli O157:H7: Inclusion of carbon dioxide as a fourth factor in a pre-existing model. International Journal of Food Microbiology 1997;37(2-3):113-20.

105. Sutherland JP, Bayliss AJ, Roberts TA. Predictive Modelling of Growth of Staphylococcus aureus - The Effects of Temperature, pH and Sodium Chloride. International Journal of Food Microbiology 1994 Feb;21(3):217-36.

106. Van Boekel Majs. On the Use of the Weibull Model to Describe Thermal Inactivation of Microbial Vegetative Cells. International Journal of Food Microbiology 2002 Mar;74(1-2):139-59.

107. van Gerwen SJC, Zwietering MH. Growth and inactivation models to be used in quantitative risk assessments. Journal of Food Protection 1998;61(11):1541-9.

108. Van Impe JF, Nicolaď BM, Schellekens M, Martens T, De Baerdemaeker J. Predictive microbiology in a dynamic environment: A system theory approach. International Journal of Food Microbiology 1995 May;25(3):227-49.

109. Vereecken KM, Van Impe JF. Analysis and Practical Implementation of a Model for Combined Growth and Metabolite Production of Lactic Acid Bacteria. International Journal of Food Microbiology 2002 Mar;73(2-3):239-50.

110. Vialette M, Pinon A, Chasseignaux E, Lange M. Growths kinetics comparison of clinical and seafood Listeria monocytogenes isolates in acid and osmotic environment. INTERNATIONAL-JOURNAL-OF-FOOD-MICROBIOLOGY 121;APR 25 2003; 82:2.

111. Walls I, Scott VN. Use of predictive microbiology in microbial food safety risk assessment. International Journal of Food Microbiology 1997;36(2-3):97-102.

112. Walls I, Scott VN. Validation of predictive mathematical models describing the growth of Listeria monocytogenes. Journal of Food Protection 1997;60(9):1142-5.

113. Werner BG, Hotchkiss JH. Effect of Carbon Dioxide on the Growth of Bacillus Cereus Spores in Milk During Storage. Journal of Dairy Science 2002 Jan;85(1):15-8.

114. Whiting RC, Golden MH. Variation among Escherichia coli O157:H7 strains relative to their

growth, survival, thermal inactivation, and toxin production in broth. International Journal of Food Microbiology 2002;75(1-2):127-33.

115. Wilson PDG, Brocklehurst TF, Arino S, Thuault D, Jakobsen M, Lange M, et al. Modelling Microbial Growth in Structured Foods: Towards a Unified Approach. International Journal of Food Microbiology 2002 Mar;73(2-3):275-89.

116. Yang H, Wang S, Li Y, Johnson MG. Predictive Models for the Survival/Death of Campylobacter Jejuni and Salmonella Typhimurium in Poultry Scalding and Chilling. Journal of Food Science 2002 Jun-2002 Jul;67(5):1836-43.

117. Zaika LL, Phillips JG, Fanelli JS, Scullen OJ. Revised model for aerobic growth of Shigella flexneri to extend the validity of predictions at temperatures between 10 and 19 degrees C. International Journal of Food Microbiology 1998;41(1):9-19.

118. Zwietering MH, deWit JC, Notermans S. Application of predictive microbiology to estimate the number of Bacillus cereus in pasteurised milk at the point of consumption. International Journal of Food Microbiology 1996;30(1-2):55-70.

1.4.12 Methods for Risk Assessment This subset of the literature, much of which is captured under other search topics, nevertheless provides a relatively comprehensive collection of current specific methodologies, plus broader issues relevant to the application of risk assessment, and risk management practices (for example, use of food safety objectives to satisfy the intent of food safety law, (Baker, 2002); mathematical models as tools for evaluating the effectiveness of interventions, (Kristinsson, 2001); microbiological double standards for enhanced treated sludge versus food requirements, (Mara & Horan, 2002). Methodologies to improve inputs for microbial risk assessment are addressed, for example adding new factors to predictive models ((Masana & Baranyi, 2000)), evaluating time value of historical testing information in animal populations, (Schlosser & Ebel, 2001)) plus risk assessment tools designed to simplify the process ((Ross & Sumner, 2002)). 1. Albering HJ, Rila JP, Moonen EJ, Hoogewerff JA, Kleinjans JCS. Human health risk assessment in

relation to environmental pollution of two artificial freshwater lakes in the Netherlands. Environmental Health Perspectives 1999;107(1):27-35.

3. Ashley RM, Souter N, Butler D, Davies J, Dunkerley J, Hendry S. Assessment of the sustainability of alternatives for the disposal of domestic sanitary waste. WATER-SCIENCE-AND-TECHNOLOGY 1999;39(5):251-8.

4. Atherton KT. Safety assessment of genetically modified crops. Toxicology 2002 Dec;181-182:421-6.

5. Baker DA. Use of Food Safety Objectives to Satisfy the Intent of Food Safety Law. Food Control 2002 Sep-2002 Oct;13(6-7):371-6.

7. Barling D, deVriend H, Cornelese JA, Ekstrand B, Hecker EFF, Howlett J, et al. The social aspects of food biotechnology: a European view. Environmental Toxicology and Pharmacology 1999;7(2):85-93.

8. Beaudeau P, Payment P, Bourderont D, Mansotte F, Boudhabay O, Laubies B, et al. A time series study of anti-diarrheal drug sales and tap-water quality. International Journal of Environmental Health Research 1999;9(4):293-311.

9. Bedford T, Cooke R. Yes/REPORT/methodsRA. Probabilistic Risk Analysis : Foundations and Methods.Cambridge University Press, 2001.

10. Berends BR, Van Knapen F, Mossel DAA, Burt SA, Snijders JMA. Impact on human health of Salmonella spp. on pork in The Netherlands and the anticipated effects of some currently proposed control strategies. International Journal of Food Microbiology 1998;44(3):219-29.

11. Berends BR, vanKnapen F. An outline of a risk assessment-based system of meat safety assurance and its future prospects. Veterinary Quarterly 1999;21(4):128-34.

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2.0 Appendix 2: Expert Consultation The expert consulation was held at the Westin Edmonton, 10135 - 100 Street, Edmonton, AB, T5J 0N7 on November 5th and 6th, 2003. The consultation drew upon the experience of a substantial roster of both Canadian and international expertise in risk assessment. The primary focus of the consultation was to tap into the experience and insight of the experts so as to ensure that the outputs from this product were in tune with a good cross-section of the risk assessment community, as well as to get feedback on the completeness of the environmental scan to that point and to critically evaluate the advancement directions proposed. This section of the appendix provides some of the background information related to the consultation including invition and attendee lists.

2.1 Consultation Correspondence 2.1.1 Invitation Laboratory for Foodborne Zoonoses Microbial Risk Assessment Unit 110 Stone Road West Guelph, Ontario N1G-3W4 Dear The Canadian Institutes of Health Research (CIHR) Institute of Infection and Immunity, the Canadian Water Network, and the Natural Sciences and Engineering Research Council have funded a project entitled “Microbial Risk Assessment as a Foundation for Informed Decision Making” under the Strategic Initiative “Needs, Gaps and Opportunities Assessment in the area of microbial contamination of food and water. The focus of the work is to identify needs and current barriers to the development of microbial risk assessment, what activities are being undertaken to meet needs and overcome barriers, and what opportunities exist to improve its application in decision-making. One component of this project is to convene an expert consultation to gain insights into future directions, both short-term and long-term, and to identify opportunities to advance the development of microbial risk assessment with consideration for the tools available, synthesis methods, quality of information as well as its implementation as an information base for decision-making and policy development. We invite you to participate in this consultation, November 5 and 6th, 2003, in Edmonton, Alberta. In appreciation of your expertise and your time, all travel and accommodation expenses will be provided. The format of the consultation will lead to a draft report, which once finalized, will be distributed to all participants. We would appreciate it if you would advise us at your earliest convenience if you will be available to participate in the consultation. Once confirmed, you will receive further background information that will provide a basis for the agenda and discussions of the consultation With sincere regards Aamir Fazil Health Canada

2.1.2 Attendee Travel Instructions Laboratory for Foodborne Zoonoses Microbial Risk Assessment Unit 110 Stone Road West Guelph, Ontario N1G-3W4 Dear We are pleased that you accepted our earlier invitation to attend the two-day expert consultation to look at the needs, gaps and opportunities for microbial risk assessment in food and water to be held November 5th and 6th, 2003 in Edmonton, Alberta. Since the date is quickly approaching and so that you can secure reasonably priced air tickets, we would appreciate it if you could proceed with flight bookings as soon as possible. To assist you with the arrangements we are including some relevant information. The start and stop times for the meeting are: Day 1 – Wednesday November 5th 2003 – 8:00 a.m. to 5:00 p.m. Day 2 – Thursday November 6th 2003 – 8:00 a.m. to 5:00 p.m. We would suggest that your arrival date be Tuesday November 4th, to accommodate the early start on the Wednesday. Departure can be anytime after we adjourn on Thursday November 6th at 5pm As you are aware all travel and accommodation expenses will be provided within certain guidelines:

Due to budgetary considerations we would ask that you make bookings on the basis of lowest economy flight fares. Accommodation and meetings will be at the Westin Edmonton Hotel located at

10135 - 100 Street, Edmonton, AB, T5J 0N7. To confirm your room, please contact Jennifer Robertson as soon as possible (contact information listed below) and at the latest before October 12th, specifying preferences (smoking etc.). Although accommodation expenses are covered, you will be responsible for

incidental charges (phone, bar etc) billed to your room, which you will have to settle upon checkout Meals will be catered on both days including Breakfast, Lunch and Dinner (5th

only). If you would like assistance with booking your travel arrangements as well as to confirm your hotel booking, please contact:

Jennifer Robertson 519-822-3300 ext. 252, or Jennifer_Robertson@hc-sc.gc.ca , as soon as possible. Thank you for your interest in this project and we look forward to your contributions at the consultation. With sincere regards Aamir Fazil Health Canada

2.2 Pre-consultation Update & Instruction This memo / document is a follow up to the discussion document sent out last week (2003-10-23), that is intended to serve as the starting point for the consultation scheduled for Nov 5th and 6th, 2003. The purpose of this memo is to give you some additional information and direction on things you may want to think about and how the two-day Edmonton consultation will progress. 2.2.1 General Impressions First of all, when reading the document over the next week or so, consider if you agree/disagree with the identified goals of risk based decision-making, or the objectives for microbial risk assessment for food and water (are they legitimatee in your opinion, is anything missing, etc). The same sort of consideration should be given to the pathways, both major and the sub-pathways. Major pathways are things like "Methodology Development" and "Coordination", and sub-pathways are things like "Risk assessment tools for emerging pathogens are available" and “Prioritization and Co-ordination of Research and Information Gathering” 2.2.2 Roundtable Preparation On the first day of the meeting, during the morning session, we would like to get all of you involved directly. So, there will be a roundtable introduction, but in addition to introducing yourselves we would like each of you to bring to the table a few key issues of importance to you in relation to the needs for microbial risk assessment in food or water. Keep in mind this is intended to be a quick roundtable, so 2-3 minutes a person is all that is allotted. The purpose of the roundtable is to try to ensure that everyone gets a chance to be heard initially and to present ideas of importance to them. Keep in mind there will be ample opportunity if warranted to revisit and expand on issues as the meeting progresses. 2.2.3 Breakout Session Questions On the afternoon of the 5th we will be breaking up the larger group into a few breakout groups in which the intention is to tackle in more detail the "sub-pathways" identified in the document, as well as any other potential pathways that might have been introduced and consensus arrived at as to their applicability. In order to facilitate the groups and so as to maximize efficiency, there will be 4 questions that should be addressed as they relate to these sub-pathways. Each of you will be part of a breakout group that will be assigned a few of these "sub-pathways" to deal with, in reading the document prior to arrival, it may help to consider these questions and start formulating your thoughts and ideas. If you have thoughts about a sub-pathway that you are not subsequently assigned, you can of course still contribute those ideas either to the group dealing with them or

during plenary sessions when groups report back. The questions the groups will be asked to work on as they apply to the sub-pathways are as follows: 1) Description of current pathway status

• •

Is the characterization of the current status fair ?, Is there some critique from your position and as a group that you/we can level against the description of the current status of the pathway?

2) Advancement along pathway

What steps or action items need to be addressed in order to advance along this pathway ? Can these steps be categorized into short-term and more medium-term action items ? (e.g what needs to be done, and can be done now, and what needs to be done, but requires additional groundwork to be covered before they can be done)

3) Limitations

• What are potential limitations to progress along this pathway? (even though an action item is achieved or steps are taken what are the potential limits to its contribution)

4) Contribution

• If progress is made along this pathway, which objectives (listed in Figure 1, and in the text) will it contribute towards.?

2.2.4 Miscellaneous If any of you have reference material or, other supporting information to help make a point or to raise an issue, or to highlight a development, please bring it along with you so that it can be incorporated in our records if necessary as quickly as possible In order to enhance the breadth of expertise to which these ideas are exposed, we hope to send the report to a group of reviewers. If you know of an individual that you think should be asked to review the report, please bring along the contact information for them.

2.3 Agenda Wednesday, November 5th, 2003

Start End 8:00 AM 8:30 AM Continental Breakfast

8:30 AM 9:00 AM Introduction Welcome and Housekeeping Project Background Objectives

9:00 AM 10:15 AM Roundtable Participant Introductions Statement on key issues of importance

10:15 AM 10:45 AM Coffee

10:45 AM 12:00 PM Presentation of Framework Presentation of "Goals", "Objectives" & "Pathways" Discussion on draft report content

12:00 PM 12:30 PM Pathway prioritization

12:30 PM 1:30 PM Lunch

1:30 PM 1:45 PM Prioritization results and Group assignment

1:45 PM 3:00 PM Breakout Group Session Address questions for each pathway

3:00 PM 3:15 PM Coffee

3:15 PM 4:15 PM Breakout Group Session Address questions for each pathway

4:15 PM 5:00 PM Plenary Session Presentation of breakout activities / results

6:30 PM Group Dinner

Thursday, November 6th, 2003

Start End 8:00 AM 8:30 AM Continental Breakfast

8:30 AM 9:00 AM Plenary Session Regroup and review of charge

9:00 AM 10:15 AM Breakout Group Session Incorporate feedback Address questions for remaining pathways

10:15 AM 10:45 AM Coffee

10:45 AM 11:30 AM Plenary Session Presentation of remaining breakout activities / results

11:30 AM 12:30 PM Plenary Session Discussion and consideration of international issues

12:30 PM 1:30 PM Lunch

1:30 PM 3:00 PM Roundtable What has been learned Most important issue to advance the field

3:00 PM 3:15 PM Coffee

3:15 PM 4:30 PM Wrap Up Conclusions, Key Findings Strategy to progress

2.4 Introductory Presentation

2.5 Framework Presentation

2.6 Meeting Attendes NAME

AFFILIATION

Aamir Fazil Health Canada, Guelph, Ontario

Greg Paoli Decisionalysis Risk Consultants, Ottawa, Ontario

Valerie Davidson University of Guelph, Guelph, Ontario

Anna Lammerding Health Canada, Guelph, Ontario

Steve Hrudey University of Alberta Edmonton, Alberta

Judy Isaac-Renton University of British Columbia / BCCDC Vancouver, British Columbia

Mansel Griffiths University of Guelph, Guelph, Ontario

Bruce McNab Epidemiology and Risk Assessment

Ontario Ministry of Agriculture and Food, Guelph, Ontario

Sandra Honour Head, Agri-Food Systems Branch Agriculture Food and Rural Development, Edmonton, Alberta

Andrijana Rajic

Agriculture Food and Rural Development, Edmonton, Alberta

Ray Copes Clinical Associate Professor Dept. of Health Care and Epiemiology University of British Columbia / BCCDC, Vancouver, British Columbia

Norman Neumann Program Director, Environmental Microbiology Provincial Laboratory of Public Health Calgary, Alberta

AFFILIATION

William Ross Director Health Products and Food Branch Health Canada, Ottawa, Ontario

Tom Feltmate Chief, Food Safety Risk Analysis Unit Canadian Food Inspection Agency, Ottawa, Ontario

Pierre Payment Professeur INRS-Institut Armand-Frappier, University of Quebec Laval, Quebec

Kevin Brand Assistant Professor McLaughlin Centre for Population Health RA University of Ottawa, Ottawa, Ontario

Robert de Valk Further Poultry Processors Association, Ottawa, Ontario

Will Robertson Head, Microbiology Section Health Environments and Consumer Safety Health Canada, Ottawa, Ontario

Diane Medeiros Health Environments and Consumer Safety Health Canada, Ottawa, Ontario

Mark Servos University of Waterloo / Canadian Water Network Waterloo, Canada

Peter M Huck Civil Engineering, University of Waterloo / NSERC Chair in Water Treatment Waterloo, Canada

Joan Rose Homer Nowlin Chair in Water Research Michigan State University E. Lansing, Michigan

Charles Haas Betz Professor of Environmental Engineering Drexel University, Philadelphia, Pennsylvania

AFFILIATION

Mark Powell US Department of Agriculture, ORACBA Washington, DC

Arie Havelaar National Institute of Public Health and the Environment of the Netherlands (RIVM) Bilthoven, Netherlands

Leon Gorris Unilever, SEAC Sharnbrook, UK

Nick Ashbolt Deputy Director, Centre for Water and Waste Technology University of New South Wales, Sydney, Australia

Mike Cassidy Coordinator, Food Safety Science Unit Ontario Ministry of Agriculture and Food, Guelph, Ontario

Frances Natress Lacombe Research Centre Agriculture Canada, Lacombe, Alberta

Shari Orders Decisionalysis Risk Consultants, Ottawa, Ontario

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