Microbial Risk Analysis最新文献

This study aims to develop and evaluate a predictive model for Shiga toxin-producing Escherichia coli (STEC) growth on Minas Frescal cheese across varied temperature conditions. A pool of five STEC strains (3–4 log CFU/g) was inoculated onto 10 g Minas Frescal cheese portions (%moisture = 68.30 ± 0.47,%fat in dry basis = 26.55 ± 0.37, pH = 6.86 ± 0.02) stored at isothermal conditions (4, 8, 15, 25, 37, and 42 °C). STEC concentrations increased at 8 °C and above, persisting throughout the 504-hour study period at 4 °C, showing minimal cell loss. The growth curves were fitted with the primary model of Baranyi and Roberts using Combase DMFit, showcasing robust alignment between predicted and experimental data (R² ≥ 0.98). Further, the µ_max and λ values were fitted as a function of temperature to modified Ratkowsky equations, resulting in R² of 0.99 and 0.96, and RMSE of 0.03 and 0.08, respectively, for the secondary models. Model validation was performed under isothermal conditions at 20 and 30 °C. The Ratkowsky equations can reliably predict STEC growth rate and lag phase in Minas Frescal cheese at diverse temperatures (8 to 42 °C), evidenced by accuracy and bias factors of 1.06 and 1.06. These findings offer insights into cold chain management for STEC control during Minas Frescal cheese production, distribution, and storage, emphasizing the need for robust post-pasteurization manufacturing practices to prevent STEC survival even at lower temperatures.

Dairy farms are vulnerable to the impacts of climate change through the alteration of raw milk quality and pressure on animal health. Measures in dairy farms are necessary to reduce microbiological risks that may impact animal health and may be passed on to humans through the consumption of contaminated dairy products. However, these additional controls should incur lower environmental impact, have a low cost of implementation, minimal impact on milk property, and sufficient effectiveness to control risks. This study selected a dairy farm located under hot weather conditions to demonstrate how these challenges may be considered. Our objective was to present how a multi-criteria decision analysis (MCDA) could be used to select the appropriate mitigation strategy for this farm among fifteen potential food safety measures.

The MCDA framework brought together ten criteria classified into four supra criteria: stakeholder acceptance, food safety effectiveness, environmental impact, and impact on milk properties. The relative performances of various food safety measures scored against the ten criteria were expressed either in qualitative or quantitative values. Ultimately, the outranking MCDA technique, PROMETHEE II, was used to rank the measures.

This study ranked the selected four food safety measures, namely, sand bedding, chitosan supplementation, cooling mister operation, and phage spray, after a series of preselection filters. It was found that none of these dominated the others on the ten criteria. However, MCDA has allowed the determination of the best compromise among the selected measures. It was found that an increase in the frequency of changing the sand bedding ranked first, and an increase in the operation of cooling misters was ranked last.

The study demonstrated the benefit of MCDA in combining criteria of different nature (stakeholder acceptance, food safety effectiveness, environmental impact, milk properties), values, and scales to prioritize food safety measures. The approach can be applied to other dairy farms eager to limit the impacts of climate change while guaranteeing food safety.

Aujeszky's disease (AD) is a highly contagious disease of pigs that primarily transmits by respiratory and oral routes. Evidence from recent outbreaks suggests that some swine viruses can survive in contaminated animal feed, thus posing a risk of entry via imports from other countries. To this end, a qualitative risk assessment was undertaken to determine the risk of introduction of AD virus (ADV) and infection of pigs via this route to determine if contaminated animal feed is a viable pathway for the spread of ADV. The feed categories investigated were soya bean/meal/oilcake, pet food, choline/lysine and spray dried porcine plasma. These were chosen based on their use in animal feed and the available data on viral contamination. The overall probability of an animal becoming infected from the importation of feed contaminated with ADV was estimated as Negligible or Very Low for all feed categories. The uncertainty associated with the estimates was assessed as Medium, due to the lack of data around the mechanisms that ADV could contaminate feedstuffs and for infection of susceptible animals from ADV infected feed.

The use of residual streams from agricultural production and food consumption containing animal proteins entails the risk of disease transmission as illustrated by the epidemics of bovine spongiform encephalopathy (BSE) and African swine fever. To combat this risk, the use of animal proteins in livestock feed was banned in the European Union, resulting in a drain of valuable proteins from the agricultural system. With an increasing call for a circular food system, the use of residual streams as a feed ingredient needs to be reconsidered with the associated disease risks being assessed and mitigated where needed. In this study, we assessed the BSE risk of bovine spray-dried red blood cells (SDRBC) as an ingredient of aquafeed. Fish fed with bovine SDRBC could indirectly result in exposure of ruminants to BSE infectivity because one of the exemptions of the feed ban is the use of fishmeal as an ingredient in calf milk replacers. A quantitative risk model was built to evaluate the BSE infectivity present in blood sourced from a slaughtered BSE-infected cow and the reduction of infectivity due to processing steps along the production chain. The end point of the model was the BSE infectivity, expressed in cattle oral ID₅₀ (CoID₅₀), reaching calves fed calf milk replacer containing fishmeal, and the corresponding probability that this will result in at least one new BSE infection.

The expected BSE infectivity in blood from a BSE-infected cow at the clinical end state of infection is 0.75 CoID₅₀ (median value). Infectivity in blood mainly results from cross-contamination with brain tissue during stunning at the slaughterhouse. The initial infectivity is reduced along the pathway from slaughtered cow to calf milk replacer, with the highest reduction achieved by clearance of infectivity by fish fed bovine SDRBC as an ingredient of aquafeed, although this parameter has high uncertainty. The final infectivity reaching calves via inclusion of fishmeal in calf milk replacer is estimated to be very low (median value: 1.1 × 10⁻⁵ CoID₅₀). Assuming an exponential dose-response model, this corresponds with an expected probability that < 10 out of a million slaughtered BSE-infected cows will result in new BSE infections, which is far below the threshold value of 1 for the basic reproduction number (R0) to initiate a new epidemic. We thus conclude that it is very unlikely that the use of bovine SDRBC as ingredient of aquafeed will result in a new BSE epidemic in cattle. What-if analysis indicated that this conclusion is robust, despite high uncertainty for some input parameters.

This study assessed the influence of preparing iceberg lettuce salads at home on the risk of Escherichia coli O157:H7, Salmonella Typhimurium, Listeria monocytogenes, and Campylobacter jejuni by conducting quantitative microbial risk assessments (QMRAs¹) for distribution, retail, domestic storage, and cross-contamination. The QMRA simulated pathogen behaviors in lettuce and meat from-farm-to-fork environments. Order of food preparation, hand washing, and lettuce washing were assessed in domestic lettuce salad and raw meat processes. Scenario and sensitivity analyses were performed to compare the importance of the process factors. QMRA simulation revealed that factors related to initial contamination and at-home preparation of foods were more critical than those related to the time-temperature environment during distributions and storages. The risk of L. monocytogenes infection decreased only 1 % even in the absence of cross-contamination. Similarly, the risk of C. jejuni hardly decreased (0.91-fold) even in the absence of lettuce contamination. When the lettuce was not washed, the risk of L. monocytogenes was relatively higher (1.92-fold) than that of other pathogens (E. coli O157:H7,1.44-fold; S. Typhimurium, 1.38-fold; and C. jejuni, 1.36-fold). The risk of E. coli O157:H7 (2.60-fold), S. Typhimurium (2.18-fold), and C. jejuni (2.67-fold) increased when hands were not washed before lettuce preparation, whereas the risk of L. monocytogenes did not increase (1.07-fold). The importance of avoiding cross-contamination through appropriate order of food preparation and hand washing in lettuce salad preparation were quantitatively demonstrated in the present study, which provide essential information for food safety education at home.

Introduction

Brucellosis is rare in non-endemic countries where it mainly occurs as an imported or travel-related disease. In rare cases, Brucella species (spp.) are present in clinical specimens processed by clinical microbiology laboratories. These pathogens pose a risk to laboratory technicians, due to the high virulence, a low-infectious dose and ease of aerosol formation. Due to the low incidence in non-endemic countries, clinical samples are routinely processed on laboratory benches outside laminar flow cabinets. Recently, we have had three unexpected cases in which Brucella spp. were cultured at our clinical microbiology laboratory: one Brucella canis case and two Brucella melitenis cases. The B. canis and the first B. melitenis cases prompted the introduction of a biosafety software pop-up, which is presented in this paper.

Methods

Here, we describe the two B. melitensis cases and the introduction of a biosafety pop-up. The software pop-up parameters are a time-to-positivity (TTP) of more than 48 h, in an aerobic blood culture bottle, and a Gram stain appearance as Gram-negative bacteria. The software pop-up warns the technician through the laboratory information system (LIS) to further process the specimen in the Class 2 biological safety cabinet. To assess the number of false-positive pop-ups we can expect and resulting additional workload, we retrospectively analyzed laboratory data from the last seven years.

Results

The biosafety pop-up prevented laboratory exposure in the second B. melitensis case. Based on the retrospective analysis of laboratory data, we estimated the resulting additional workload of implementation of the biosafety pop-up to be less than one blood culture bottle per week on average to be processed in a Class 2 biological safety cabinet.

Conclusion

Our experience demonstrates that implementation of the biosafety software pop-up can reduce the risk of laboratory exposure to Brucella spp. This intervention provides a feasible approach even in a setting where Brucella spp. are normally only encountered every few years.

Food safety has benefited from systematic approaches to assess and control risks. The paradigm of risk analysis calls for the components of risk assessment and risk management to be bridged and complemented with risk communication, yet still be separate activities. In practical terms, risk assessment and risk management are, in fact, heavily interdependent upon one another. Collectively, risk assessments, risk management and risk communications are tools or processes that deliver specific outputs. For food safety enhancement, these outputs must be translated into outcomes to yield the desired impacts—improved food safety, human health, and livelihoods. The purpose of this paper to illustrate, using the example of listeriosis, how steps in the risk analysis process used by the Codex Alimentarius Commission's, Codex Committee on Food Hygiene (CCFH), of the and the FAO/WHO Joint Expert Meeting on Microbiological Risk Assessment (JEMRA) align with the various components of the theory change, ultimately leading to impacts on food safety, enhanced health and livelihoods on the global scale.

In this study is presented a procedure for surveillance data-driven risk assessment, which can be used to inform inter-sectorial Campylobacter risk-based control, e.g. within National Action Plans and One Health (OH) systems. Campylobacter surveillance data (2019 to 2022) and a published quantitative microbial risk assessment (QMRA) model were used, to show the procedure. Moreover, an interface tool was developed in Excel for showing descriptive statistics on measured apparent flock prevalence (AP) and concentrations (colony forming units per gram, cfu/g) on the meat, together with their related QMRA outputs. Currently (mid-2024), Danish fresh broiler meat is produced by four slaughterhouse companies (A, B, C and D), where approximately 30 % of the annually slaughtered broiler flocks are randomly culture tested, on one leg skin (LS) sample per flock sampled from chilled carcasses. Data variables were: date of sampling, farm-ID, within farm house-ID, flock-ID, slaughterhouse name, sample-ID, and Campylobacter concentrations. Flocks were classified as carcass positive with a concentration ≥ 10 cfu/g. The data was fed into the QMRA model to assess: a) the average risk of human campylobacteriosis per serving (during a month or year), and b) the monthly/annual risk of 2022 relative (RR) to the baseline (average) risk from the previous three years. The descriptive statistics and the risk assessment (RA) were carried out at national level and for each slaughterhouse. In 2022, the national RR was 1.03, implying that the average annual risk increased by approximately 3 % compared to the baseline. Nevertheless, for slaughterhouses A, B and D, the annual risk decreased by ≈ 22 %, 21 % and 43 %, respectively; whereas for slaughterhouse C it increased by 48 %. Monthly risk estimates showed seasonal variations, according to the visualized changes of AP and meat contaminations. The national monthly RR was >1 in July and from September to December. During those months: slaughterhouse C had always RR > 1, slaughterhouse A had a relative increase of risk in July, slaughterhouse B in July and November, and slaughterhouse D in October and December. The procedure and the tools used in this study, allow identifying the impact of seasonality and food-chain stages (i.e. slaughterhouses and their broilers sourcing farms) on the risk per serving, so that Campylobacter risk-based control could be implemented accordingly, from farm to fork, across consecutive surveillance periods. The same principles could be applied in other countries, food chains, and/or for other foodborne pathogens, when similar data and QMRA models are available.