Mathematical modeling of growth of non-O157 Shiga toxin-producing Escherichia coli in raw ground beef

Validation of competition and dynamic models for Shiga toxin-producing Escherichia coli (STEC) growth in raw ground pork during temperature abuse

Epidemiological evidence suggests that pork products may be a vehicle for STEC transmission to humans. This study was conducted to validate competition and dynamic models for the growth of STEC during simulated temperature abuse of raw ground pork. Maximum specific growth rates μmax were modeled as a function of temperature using the Cardinal parameter equation, and a dynamic model was validated using sinusoidal temperature profiles. The Acceptable Prediction Zone (APZ) method was used to evaluate the model's performance. The competition model was well fitted to the experimental data having 93% (1849/1981) residual errors within the desired APZ. Growth rates were not different between STEC O157 and non-O157; however, serogroup O91 showed two to three times lower μmax than other STEC at 10, 25, and 30 °C. The theoretical minimum and optimum growth temperature for all STEC groups ranged from 3.4 to 7.8 °C and 33-35 °C, respectively. The dynamic model showed good prediction performance (pAPZ = 0.98) with the experimental data. These results can be used to inform risk assessment models and to support the implementation of risk mitigation strategies to improve the microbiological safety of raw pork products.

Quantitative microbial risk assessment of haemolytic uremic syndrome associated with Argentinean kosher beef consumption in Israel

The aim of this study was to perform a quantitative microbial risk assessment (QMRA) of Shiga toxin-producing Escherichia coli hemolytic uremic syndrome (STEC-HUS) linked to the consumption of Kosher beef produced in Argentina and consumed in Israel in children under 14 years. A probabilistic risk assessment model was developed to characterize STEC prevalence and contamination levels in the beef supply chain (cattle primary production, cattle transport, processing and storage in the abattoir, for export and at retail, and home preparation and consumption). The model was implemented in Microsoft Excel 2016 with the @Risk add-on package. Results of 302 surveys with data collected in Israel were as follows: 92.3% of people consumed beef, mostly at home, and 98.2% preferred levels of cooking that ensured STEC removal from the surface of beef cuts. The preferred degree of ground beef doneness was "well-done" (48.2%). Cooking preference ranged from red to "medium-well done" (51.8%). Median HUS probability from Argentinean beef cut and ground beef consumption in children under 14 years old was <10-15 and 8.57x10-10, respectively. The expected average annual number of HUS cases and deaths due to beef cut and ground beef consumption was zero. Risk of infection and HUS probability correlated with salting effect on E. coli count, processing raw beef before vegetables, ways of storage and refrigeration temperature at home, joint consumption of salad and beef cuts, degree of beef doneness and cutting board washing with detergent after each use with beef and vegetables. The STEC-HUS risk in Israel from consumption of bovine beef produced in Argentina was negligible. The current QMRA results were similar to those of previous beef cut consumption QMRA in Argentina and lower than any of the QMRA performed worldwide in other STEC-HUS linked to ground beef consumption. This study confirms the importance of QMRA to estimate and manage the risk of STEC-HUS from beef consumption. The impact variables identified in the sensitivity analysis allowed us to optimize resources and time management, to focus on accurate actions and to avoid taking measures that would not have an impact on the risk of STEC-HUS.

Establishment and Application of a Predictive Growth Kinetic Model of Salmonella with the Appearance of Two Other Dominant Background Bacteria in Fresh Pork

To better guide microbial risk management and control, growth kinetic models of Salmonella with the coexistence of two other dominant background bacteria in pork were constructed. Sterilized pork cutlets were inoculated with a cocktail of Salmonella Derby (S. Derby), Pseudomonas aeruginosa (P. aeruginosa), and Escherichia coli (E. coli), and incubated at various temperatures (4-37 °C). The predictive growth models were developed based on the observed growth data. By comparing R² of primary models, Baranyi models were preferred to fit the growth curves of S. Derby and P. aeruginosa, while the Huang model was preferred for E. coli (all R² ≥ 0.997). The secondary Ratkowsky square root model can well describe the relationship between temperature and μ_max (all R² ≥ 0.97) or Lag (all R² ≥ 0.98). Growth models were validated by the actual test values, with B_f and A_f close to 1, and MSE around 0.001. The time for S. Derby to reach a pathogenic dose (10⁵ CFU/g) at each temperature in pork was predicted accordingly and found to be earlier than the time when the pork began to be judged nearly fresh according to the sensory indicators. Therefore, the predictive microbiology model can be applied to more accurately predict the shelf life of pork to secure its quality and safety.

Quantitative risk assessment of haemolytic uremic syndrome associated with beef consumption in Argentina

We developed a quantitative microbiological risk assessment (QMRA) of haemolytic uremic syndrome (HUS) associated with Shiga toxin-producing Escherichia coli (STEC)-contaminated beef (intact beef cuts, ground beef and commercial hamburgers) in children under 15 years of age from Argentina. The QMRA was used to characterize STEC prevalence and concentration levels in each product through the Argentinean beef supply chain, including cattle primary production, cattle transport, processing and storage in the abattoir, retail and home preparation, and consumption. Median HUS probability from beef cut, ground beef and commercial hamburger consumption was <10-15, 5.4x10-8 and 3.5x10-8, respectively. The expected average annual number of HUS cases was 0, 28 and 4, respectively. Risk of infection and HUS probability were sensitive to the type of abattoir, the application or not of Hazard Analysis and Critical Control Points (HACCP) for STEC (HACCP-STEC), stx prevalence in carcasses and trimmings, storage conditions from the abattoir to retailers and home, the joint consumption of salads and beef products, and cooking preference. The QMRA results showed that the probability of HUS was higher if beef cuts (1.7x) and ground beef (1.2x) were from carcasses provided by abattoirs not applying HACCP-STEC. Thus, the use of a single sanitary standard that included the application of HACCP-STEC in all Argentinean abattoirs would greatly reduce HUS incidence. The average number of annual HUS cases estimated by the QMRA (n = 32) would explain about 10.0% of cases in children under 15 years per year in Argentina. Since other routes of contamination can be involved, including those not related to food, further research on the beef production chain, other food chains, person-to-person transmission and outbreak studies should be conducted to reduce the impact of HUS on the child population of Argentina.

A Systematic Review of Beef Meat Quantitative Microbial Risk Assessment Models

Each year in Europe, meat is associated with 2.3 million foodborne illnesses, with a high contribution from beef meat. Many of these illnesses are attributed to pathogenic bacterial contamination and inadequate operations leading to growth and/or insufficient inactivation occurring along the whole farm-to-fork chain. To ensure consumer health, decision-making processes in food safety rely on Quantitative Microbiological Risk Assessment (QMRA) with many applications in recent decades. The present study aims to conduct a critical analysis of beef QMRAs and to identify future challenges. A systematic approach, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, was used to collate beef QMRA models, identify steps of the farm-to-fork chain considered, and analyze inputs and outputs included as well as modelling methods. A total of 2343 articles were collected and 67 were selected. These studies focused mainly on western countries and considered Escherichia coli (EHEC) and Salmonella spp. pathogens. Future challenges were identified and included the need of whole-chain assessments, centralization of data collection processes, and improvement of model interoperability through harmonization. The present analysis can serve as a source of data and information to inform QMRA framework for beef meat and will help the scientific community and food safety authorities to identify specific monitoring and research needs.

Exposure to antimicrobial-resistant Escherichia coli through the consumption of ground beef in Western Canada

Emergence and dissemination of antimicrobial resistance (AMR) in food-borne bacteria is a public health issue. Retail meat is considered an important carrier for antimicrobial-resistant Escherichia coli. Currently, resistance of E. coli strains to third generation cephalosporins are of particular concern, with significant potential animal and public health consequences. Resistance to tetracyclines is also a concern, due to high prevalence of this resistance and important co-resistance patterns. However, the actual likelihood of exposure to antimicrobial-resistant bacteria via the consumption of retail meats, beyond the simple frequencies of resistance found in samples of meat at the grocery store, in Canada remains to be investigated. This study was conducted to estimate the potential human exposure to ceftriaxone- and tetracycline-resistant E.coli (CREC and TREC; the hazards of interest) through the consumption of ground beef in Western Canada. Our exposure assessment simulation model included five modules: 1) estimation of prevalence and concentration of the hazards of interest in retail ground beef samples collected by the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS), 2011-2014; 2) potential growth of the hazards during transportation from retail to home; 3) potential growth or reduction of the hazards during home storage; 4) thermal inactivation of the hazards due to cooking; and 5) consumption. The outputs of the model were presented as the probability of consumers' exposure to various threshold levels of the hazards [10 to 10⁶ colony forming units (CFU)] in one serving of cooked ground beef. Overall, the probabilities of exposure to high threshold levels of the hazards (>4 log₁₀ CFU/serving) were estimated to be lower than 0.12% in the study population (2011-2014). The mean probabilities of exposure to at least 1 log₁₀ CFU CREC and TREC in a single meal containing cooked ground beef were 0.067% (SD: 0.001%) and 1.20% (SD: 0.02%), respectively. This probability substantially decreased as the threshold level of exposure increased to ≥6 log₁₀ CFU. The probability of exposure to TREC was consistently greater than that for CREC. Cooking led to a prominent drop in the mean concentration of the hazards (4.7 log₁₀ CFU/g). The findings from this research could inform the policy-making process and provide suggestions for adjustments in future retail surveillance plans. In addition, important knowledge gaps in this area have been highlighted.