Perceptions of information gaps in farm-to-table studies☆

Abstract Foodborne disease is an increasing concern in the U.S. and has been linked to costs of millions of dollars annually. Among a large body of literature, the farm-to-table study has been recognized for its comprehensive and risk-based examination of pathogen contamination and social costs. Yet, what less examined is the issues pertaining to the lack of data and its substantial impact on simulation results. The objective of this study is to explore data gaps in current farm-to-table studies and assess their impact on the efficacy of the model. We identified some deficiencies of significant influence, including disconnects in data flows, disparities in input distributions, uncertainty in dose response relationships, and lack of knowledge in antibiotic resistance. Using an established model, we examined the impacts of the data gaps on risk assessments and outcomes. The findings indicate that data gaps along the current meat supply chain could significantly shape the farm-to-table model and its outcome estimates. The discussion has important implications for the on-going work of updating the regulations of the Food Safety Modernization Act in the United States.

[1]  M. Nauta,et al.  A comparison of risk assessments on Campylobacter in broiler meat. , 2009, International journal of food microbiology.

[2]  Wim Verbeke,et al.  Why consumers behave as they do with respect to food safety and risk information. , 2007, Analytica chimica acta.

[3]  M. Darr,et al.  Longitudinal study to evaluate the association between thermal environment and Salmonella shedding in a midwestern US swine farm. , 2013, Preventive veterinary medicine.

[4]  M. Rostagno,et al.  Variation of bacteriologic and serologic Salmonella enterica prevalence between cohorts within finishing swine production farms , 2012 .

[5]  K. Kubota,et al.  Variability among states in investigating foodborne disease outbreaks. , 2013, Foodborne pathogens and disease.

[6]  Bernd Appel,et al.  Combining analysis tools and mathematical modeling to enhance and harmonize food safety and food defense regulatory requirements. , 2010, International journal of food microbiology.

[7]  J. Garrett Morris,et al.  Annual cost of illness and quality-adjusted life year losses in the United States due to 14 foodborne pathogens. , 2012, Journal of food protection.

[8]  P. Luber Cross-contamination versus undercooking of poultry meat or eggs - which risks need to be managed first? , 2009, International journal of food microbiology.

[9]  L. McCaig,et al.  Food-related illness and death in the United States. , 1999, Emerging infectious diseases.

[10]  D. Baggesen,et al.  The serological response to Salmonella serovars typhimurium and infantis in experimentally infected pigs. The time course followed with an indirect anti-LPS ELISA and bacteriological examinations. , 1995, Veterinary microbiology.

[11]  B. Hope,et al.  An Overview of the Salmonella Enteritidis Risk Assessment for Shell Eggs and Egg Products , 2002, Risk analysis : an official publication of the Society for Risk Analysis.

[12]  B S Binkowitz,et al.  Disparity in Quantitative Risk Assessment: A Review of Input Distributions , 2001, Risk analysis : an official publication of the Society for Risk Analysis.

[13]  D. Vose Risk Analysis: A Quantitative Guide , 2000 .

[14]  J. Funk,et al.  Salmonella in commercial swine from weaning through slaughter , 1999 .

[15]  James M. MacDonald,et al.  Bacterial Foodborne Disease: Medical Costs and Productivity Losses , 2012 .

[16]  M H Cassin,et al.  Quantitative risk assessment for Escherichia coli O157:H7 in ground beef hamburgers. , 1998, International journal of food microbiology.

[17]  Maarten J Nauta,et al.  Modelling bacterial growth in quantitative microbiological risk assessment: is it possible? , 2002, International journal of food microbiology.

[18]  H. Tarabla,et al.  Quantitative risk assessment for verocytotoxigenic Escherichia coli in ground beef hamburgers in Argentina. , 2009, International journal of food microbiology.

[19]  Xuanli Liu,et al.  Influence of Salmonella in pigs preharvest and during pork processing on human health costs and risks from pork. , 2005, Journal of food protection.

[20]  M. Griffiths,et al.  Simultaneous separation and detection of hepatitis A virus and norovirus in produce. , 2010, International journal of food microbiology.

[21]  H. S. Hurd,et al.  The effect of lairage on Salmonella isolation from market swine. , 2001, Journal of food protection.

[22]  Jun Wang,et al.  Risk assessment for Listeria monocytogenes on lettuce from farm to table in Korea , 2013 .

[23]  Sarah Cahill,et al.  Risk assessments of Salmonella in eggs and broiler chickens , 2002 .

[24]  D J Parsons,et al.  A comparison of three modelling approaches for quantitative risk assessment using the case study of Salmonella spp. in poultry meat. , 2005, International journal of food microbiology.

[25]  M. Nauta,et al.  Quantitative Microbiological Risk Assessment on Salmonella in Slaughter and Breeder pigs: Final Report , 2010 .

[26]  B. Urlings,et al.  Effect of fermented feed on shedding of Enterobacteriaceae by fattening pigs. , 2002, Veterinary microbiology.

[27]  P. Warriss,et al.  Time in lairage needed by pigs to recover from the stress of transport , 1992, Veterinary Record.

[28]  M. Rostagno,et al.  Impact of commercial pre-harvest processes on the prevalence of Salmonella enterica in cull sows. , 2001, Berliner und Munchener tierarztliche Wochenschrift.

[29]  Paul E. McNamara,et al.  A farm-to-fork stochastic simulation model of pork-borne salmonellosis in humans: Lessons for risk ranking , 2007 .

[30]  T. Roberts,et al.  Risk assessment for foodborne microbial hazards , 1995 .

[31]  R. Mulder IMPACT OF TRANSPORT AND RELATED STRESSES ON THE INCIDENCE AND EXTENT OF HUMAN PATHOGENS IN PIGMEAT AND POULTRY , 1995 .

[32]  G C Barker,et al.  Strengths and weaknesses of Monte Carlo simulation models and Bayesian belief networks in microbial risk assessment. , 2010, International journal of food microbiology.

[33]  Shivaramu Keelara,et al.  Longitudinal Study of Distributions of Similar Antimicrobial-Resistant Salmonella Serovars in Pigs and Their Environment in Two Distinct Swine Production Systems , 2013, Applied and Environmental Microbiology.

[34]  Aamir Fazil,et al.  A risk assessment model for Escherichia coli O157:H7 in ground beef and beef cuts in Canada: Evaluating the effects of interventions , 2013 .

[35]  T. Hald,et al.  The occurrence and epidemiology of Salmonella in European pig slaughterhouses , 2003, Epidemiology and Infection.

[36]  Arie Havelaar,et al.  A Poultry‐Processing Model for Quantitative Microbiological Risk Assessment , 2005, Risk analysis : an official publication of the Society for Risk Analysis.

[37]  W. Messens,et al.  Quantitative microbiological risk assessment (QMRA) of food-borne zoonoses at the European level , 2013 .

[38]  J. Funk,et al.  Isolation of Salmonella serotypes from feces of pigs raised in a multiple-site production system. , 1998, Journal of the American Veterinary Medical Association.

[39]  M. Woodburn,et al.  Household Food Preparers' Food-Safety Knowledge and Practices Following Widely Publicized Outbreaks of Foodborne Illness. , 1997, Journal of food protection.