Detection of hepatitis E RNA in pork products at point of retail in Ireland - Are consumers at risk?

Hepatitis E (HEV), a zoonotic virus, is the leading cause of acute viral hepatitis in Europe. The presence of HEV in domestic pigs can result in infections in humans through consumption of pork products which are undercooked or where processing methods are insufficient to inactivate the virus. In Ireland, pork accounts for 34 % of all meat consumption (CSO, 2022) and the prevalence of HEV in products at point of retail has not previously been characterised. A sampling strategy was designed in which high pork content sausages, fresh pork liver and raw fermented sausages were systematically purchased from three types of retailers between May 2018 and March 2019. In total, 200 pork products were tested using a lysing agent to release the HEV from the product for detection. RT-PCR for HEV was performed on samples with an extraction efficiency >1 % (n = 188/200) (94 %). Low level HEV RNA was detected in 9/188 (4.8 %) pork products tested. The highest incidence of HEV RNA was in pork liver where 6/25 (24 %) samples were positive. The concentration of HEV ranged from 0.02 - to 9.4 genome copies/g of pork. Based on these data an exposure assessment was performed which found that if consumers followed advice from the Food Safety Authority of Ireland to achieve core temperatures of 70 °C or higher when cooking, the risk was likely to be negligible.

Association between the Presence of Resistance Genes and Sanitiser Resistance of Listeria monocytogenes Isolates Recovered from Different Food-Processing Facilities.

Sanitisers are widely used in cleaning food-processing facilities, but their continued use may cause an increased resistance of pathogenic bacteria. Several genes have been attributed to the increased sanitiser resistance ability of L. monocytogenes. This study determined the presence of sanitiser resistance genes in Irish-sourced L. monocytogenes isolates and explored the association with phenotypic sanitiser resistance. The presence of three genes associated with sanitiser resistance and a three-gene cassette (mdrL, qacH, emrE, bcrABC) were determined in 150 L. monocytogenes isolates collected from Irish food-processing facilities. A total of 23 isolates contained bcrABC, 42 isolates contained qacH, one isolate contained emrE, and all isolates contained mdrL. Additionally, 47 isolates were selected and grouped according to the number and type of resistance genes, and the minimal inhibitory concentration (MIC) of these isolates for benzalkonium chloride (BAC) was determined experimentally using the broth microdilution method. The BAC resistance of the strain carrying the bcrABC gene cassette was significantly higher than that of strains lacking the gene cassette, and the BAC resistance of the strain carrying the qacH gene was significantly higher than that of strains lacking the qacH gene (p < 0.05). Isolates harbouring both the qacH and bcrABC genes did not show higher BAC resistance. With respect to environmental factors, there was no significant difference in MIC values for isolates recovered from different processing facilities. In summary, this investigation highlights the prevalence of specific sanitiser resistance genes in L. monocytogenes isolates from Irish food-processing settings. While certain genes correlated with increased resistance to benzalkonium chloride, the combination of multiple genes did not necessarily amplify this resistance.

Comprehensive Genomic Characterization of Cronobacter sakazakii Isolates from Infant Formula Processing Facilities Using Whole-Genome Sequencing.

Cronobacter sakazakii is an opportunistic pathogen linked to outbreaks in powdered infant formula (PIF), primarily causing meningitis and necrotizing enterocolitis. Whole-genome sequencing (WGS) was used to characterize 18 C. sakazakii strains isolated from PIF (powdered infant formula) manufacturing plants (2011-2015). Sequence Type (ST) 1 was identified as the dominant sequence type, and all isolates carried virulence genes for chemotaxis, flagellar motion, and heat shock proteins. Multiple antibiotic resistance genes were detected, with all isolates exhibiting resistance to Cephalosporins and Tetracycline. A significant correlation existed between genotypic and phenotypic antibiotic resistance. The plasmid Col(pHAD28) was identified in the isolates recovered from the same PIF environment. All isolates harbored at least one intact phage. All the study isolates were compared with a collection of 96 publicly available C. sakazakii genomes to place these isolates within a global context. This comprehensive study, integrating phylogenetic, genomic, and epidemiological data, contributes to a deeper understanding of Cronobacter outbreaks. It provides valuable insights to enhance surveillance, prevention, and control strategies in food processing and public health contexts.

Detection of Hepatitis A RNA, Hepatitis E RNA, Human Adenovirus F DNA, and Norovirus RNA in Fresh and Frozen Berry Products at Point of Retail in Ireland.

Soft fruits are at particular risk of contamination with enteric viruses such as Hepatitis A virus (HAV), Hepatitis E Virus (HEV), Norovirus (NoV), Human Adenovirus (HAdV) and Sapovirus (SaV). The aim of this study was to investigate, for the first time, the presence of these biological agents in ready to eat (RTE) berries at point of retail in Ireland. A sampling strategy was designed in which RTE fresh and frozen strawberries and raspberries were purchased from five retailers between May and October 2018. Reverse Transcriptase Polymerase Chain Reaction (RT-qPCR) assays for HEV RNA, Nov RNA, SaV RNA, and human Adenovirus species F DNA (HAdV-F) were performed on 239 samples (25g portions). Viral nucleic acid was present in 6.7% (n = 16) of samples tested as follows: HAV RNA (n = 5), HAdV-F DNA (n = 5), HEV RNA (n = 3) and NoV GII RNA (n = 3). Sapovirus RNA was not detected in any product. No significant differences were found between berry type, fresh/frozen status, or supermarket source. This study suggests a risk that exists across all retail outlets however only low levels of nucleic acid ranging from 0 to 16 genome copies/g were present. Although these findings may reflect non-viable/non-infectious virus the continued provision of risk mitigation advice to consumers is warranted and further work is required to ensure control measures to reduce contamination are implemented and enforced.

Draft Genome Sequences of Bacillus licheniformis and Bacillus paralicheniformis Strains Isolated from Irish Skim Milk Powder.

Nineteen Bacillus licheniformis strains and four strains of the closely related species Bacillus paralicheniformis were isolated from a variety of Irish medium-heat skim milk powders. The draft genome sequences of these 23 isolates provide valuable genetic data for research work relevant to dairy products and process development. The isolates are available at Teagasc.

Cronobacter Species in the Built Food Production Environment: A Review on Persistence, Pathogenicity, Regulation and Detection Methods.

The powdered formula market is large and growing, with sales and manufacturing increasing by 120% between 2012 and 2021. With this growing market, there must come an increasing emphasis on maintaining a high standard of hygiene to ensure a safe product. In particular, Cronobacter species pose a risk to public health through their potential to cause severe illness in susceptible infants who consume contaminated powdered infant formula (PIF). Assessment of this risk is dependent on determining prevalence in PIF-producing factories, which can be challenging to measure with the heterogeneity observed in the design of built process facilities. There is also a potential risk of bacterial growth occurring during rehydration, given the observed persistence of Cronobacter in desiccated conditions. In addition, novel detection methods are emerging to effectively track and monitor Cronobacter species across the food chain. This review will explore the different vehicles that lead to Cronobacter species' environmental persistence in the food production environment, as well as their pathogenicity, detection methods and the regulatory framework surrounding PIF manufacturing that ensures a safe product for the global consumer.

Bayesian Networks modeling of diarrhetic shellfish poisoning in Mytilus edulis harvested in Bantry Bay, Ireland.

Diarrhetic Shellfish Poisoning (DSP) results from the human consumption of contaminated shellfish with marine biotoxins, which are produced by some species of marine dinoflagellates, mainly belonging to the genus Dinophysis. Shellfish contamination with marine biotoxins not only pose a threat to human health, but also lead to financial loss to aquaculture operations from the temporary closure of production areas when toxin concentrations exceed regulatory levels. In this study, we developed a Bayesian Network (BN) model for forecasting the short-term variations of DSP toxins in blue mussels (Mytilus edulis) from Bantry Bay, Southwest Ireland. Data inputs to a BN model from 10 production sites in Bantry Bay included plankton cell densities in sea water, DSP toxin concentration in mussels and sea surface temperature. The model was trained with data from 2014 to 2018, and validated with data of 2019. Validation consisted of predicting the DSP toxin concentration at one production site using the model parameters from the other locations as input values. Model validation showed that the prediction accuracy was higher than 86%. Sensitivity analysis indicated that in general, DSP toxin concentration was more relevant than plankton abundance. This initial work has demonstrated the usefulness of BN modeling as an approach to short term forecasting. Further work is ongoing to use the model for scenario testing and to increase the number of environmental parameters used as inputs to the model.

Numbers of close contacts of individuals infected with SARS-CoV-2 and their association with government intervention strategies.

BACKGROUND: Contact tracing is conducted with the primary purpose of interrupting transmission from individuals who are likely to be infectious to others. Secondary analyses of data on the numbers of close contacts of confirmed cases could also: provide an early signal of increases in contact patterns that might precede larger than expected case numbers; evaluate the impact of government interventions on the number of contacts of confirmed cases; or provide data information on contact rates between age cohorts for the purpose of epidemiological modelling. We analysed data from 140,204 close contacts of 39,861 cases in Ireland from 1st May to 1st December 2020. RESULTS: Negative binomial regression models highlighted greater numbers of contacts within specific population demographics, after correcting for temporal associations. Separate segmented regression models of the number of cases over time and the average number of contacts per case indicated that a breakpoint indicating a rapid decrease in the number of contacts per case in October 2020 preceded a breakpoint indicating a reduction in the number of cases by 11 days. CONCLUSIONS: We found that the number of contacts per infected case was overdispersed, the mean varied considerable over time and was temporally associated with government interventions. Analysis of the reported number of contacts per individual in contact tracing data may be a useful early indicator of changes in behaviour in response to, or indeed despite, government restrictions. This study provides useful information for triangulating assumptions regarding the contact mixing rates between different age cohorts for epidemiological modelling.

Omnibus Modeling of Listeria monocytogenes Growth Rates at Low Temperatures.

Listeria monocytogenes is a pathogen of considerable public health importance with a high case fatality. L. monocytogenes can grow at refrigeration temperatures and is of particular concern for ready-to-eat foods that require refrigeration. There is substantial interest in conducting and modeling shelf-life studies on L. monocytogenes, especially relating to storage temperature. Growth model parameters are generally estimated from constant-temperature growth experiments. Traditionally, first-order and second-order modeling (or primary and secondary) of growth data has been done sequentially. However, omnibus modeling, using a mixed-effects nonlinear regression approach, can model a full dataset covering all experimental conditions in one step. This study compared omnibus modeling to conventional sequential first-order/second-order modeling of growth data for five strains of L. monocytogenes. The omnibus model coupled a Huang primary model for growth with secondary models for growth rate and lag phase duration. First-order modeling indicated there were small significant differences in growth rate depending on the strain at all temperatures. Omnibus modeling indicated smaller differences. Overall, there was broad agreement between the estimates of growth rate obtained by the first-order and omnibus modeling. Through an appropriate choice of fixed and random effects incorporated in the omnibus model, potential errors in a dataset from one environmental condition can be identified and explored.

Presymptomatic transmission of SARS-CoV-2 infection: a secondary analysis using published data.

OBJECTIVE: To estimate the proportion of presymptomatic transmission of SARS-CoV-2 infection that can occur, and the timing of transmission relative to symptom onset. SETTING/DESIGN: Secondary analysis of international published data. DATA SOURCES: Meta-analysis of COVID-19 incubation period and a rapid review of serial interval and generation time, which are published separately. PARTICIPANTS: Data from China, the Islamic Republic of Iran, Italy, Republic of Korea, Singapore and Vietnam from December 2019 to May 2020. METHODS: Simulations were generated of incubation period and of serial interval or generation time. From these, transmission times relative to symptom onset, and the proportion of presymptomatic transmission, were estimated. OUTCOME MEASURES: Transmission time of SARS-CoV-2 relative to symptom onset and proportion of presymptomatic transmission. RESULTS: Based on 18 serial interval/generation time estimates from 15 papers, mean transmission time relative to symptom onset ranged from -2.6 (95% CI -3.0 to -2.1) days before infector symptom onset to 1.4 (95% CI 1.0 to 1.8) days after symptom onset. The proportion of presymptomatic transmission ranged from 45.9% (95% CI 42.9% to 49.0%) to 69.1% (95% CI 66.2% to 71.9%). CONCLUSIONS: There is substantial potential for presymptomatic transmission of SARS-CoV-2 across a range of different contexts. This highlights the need for rapid case detection, contact tracing and quarantine. The transmission patterns that we report reflect the combination of biological infectiousness and transmission opportunities which vary according to context.

Role of analytical testing for food fraud risk mitigation - A commentary on implementation of analytical fraud testing: Role of analytical testing for food fraud mitigation.

Food fraud is of high concern to the food industry. A multitude of analytical technologies exist to detect fraud. However, this testing is often expensive. Available databases detailing fraud occurrences were systematically examined to determine how frequently analytical testing triggered fraud detection. A conceptual framework was developed for deciding when to implement analytical testing programmes for fraud and a framework to consider the economic costs of fraud and the benefits of its early detection. Factors associated with statistical sampling for fraud detection were considered. Choice of sampling location on the overall food-chain may influence the likelihood of fraud detection.

Relative infectiousness of asymptomatic SARS-CoV-2 infected persons compared with symptomatic individuals: a rapid scoping review.

OBJECTIVES: The aim of this study was to determine the relative infectiousness of asymptomatic SARS-CoV-2 infected persons compared with symptomatic individuals based on a scoping review of available literature. DESIGN: Rapid scoping review of peer-reviewed literature from 1 January to 5 December 2020 using the LitCovid database and the Cochrane library. SETTING: International studies on the infectiousness of individuals infected with SARS-CoV-2. PARTICIPANTS: Studies were selected for inclusion if they defined asymptomatics as a separate cohort distinct from presymptomatics and if they provided a quantitative measure of the infectiousness of asymptomatics relative to symptomatics. PRIMARY OUTCOME MEASURES: PCR result (PCR studies), the rate of infection (mathematical modelling studies) and secondary attack rate (contact tracing studies) - in each case from asymptomatic in comparison with symptomatic individuals. RESULTS: There are only a limited number of published studies that report estimates of relative infectiousness of asymptomatic compared with symptomatic individuals. 12 studies were included after the screening process. Significant differences exist in the definition of infectiousness. PCR studies in general show no difference in shedding levels between symptomatic and asymptomatic individuals; however, the number of study subjects is generally limited. Two modelling studies estimate relative infectiousness to be 0.43 and 0.57, but both of these were more reflective of the infectiousness of undocumented rather than asymptomatic cases. The results from contact tracing studies include estimates of relative infectiousness of 0, but with insufficient evidence to conclude that it is significantly different from 1. CONCLUSIONS: There is considerable heterogeneity in estimates of relative infectiousness highlighting the need for further investigation of this important parameter. It is not possible to provide any conclusive estimate of relative infectiousness, as the estimates from the reviewed studies varied between 0 and 1.

Estimation of the serial interval and proportion of pre-symptomatic transmission events of COVID- 19 in Ireland using contact tracing data.

BACKGROUND: The serial interval is the period of time between the onset of symptoms in an infector and an infectee and is an important parameter which can impact on the estimation of the reproduction number. Whilst several parameters influencing infection transmission are expected to be consistent across populations, the serial interval can vary across and within populations over time. Therefore, local estimates are preferable for use in epidemiological models developed at a regional level. We used data collected as part of the national contact tracing process in Ireland to estimate the serial interval of SARS-CoV-2 infection in the Irish population, and to estimate the proportion of transmission events that occurred prior to the onset of symptoms. RESULTS: After data cleaning, the final dataset consisted of 471 infected close contacts from 471 primary cases. The median serial interval was 4 days, mean serial interval was 4.0 (95% confidence intervals 3.7, 4.3) days, whilst the 25th and 75th percentiles were 2 and 6 days respectively. We found that intervals were lower when the primary or secondary case were in the older age cohort (greater than 64 years). Simulating from an incubation period distribution from international literature, we estimated that 67% of transmission events had greater than 50% probability of occurring prior to the onset of symptoms in the infector. CONCLUSIONS: Whilst our analysis was based on a large sample size, data were collected for the primary purpose of interrupting transmission chains. Similar to other studies estimating the serial interval, our analysis is restricted to transmission pairs where the infector is known with some degree of certainty. Such pairs may represent more intense contacts with infected individuals than might occur in the overall population. It is therefore possible that our analysis is biased towards shorter serial intervals than the overall population.

Evaluation of Norovirus Reduction in Environmentally Contaminated Pacific Oysters During Laboratory Controlled and Commercial Depuration.

Norovirus contamination of oysters is the lead cause of non-bacterial gastroenteritis and a significant food safety concern for the oyster industry. Here, norovirus reduction from Pacific oysters (Crassostrea gigas), contaminated in the marine environment, was studied in laboratory depuration trials and in two commercial settings. Norovirus concentrations were measured in oyster digestive tissue before, during and post-depuration using the ISO 15216-1 quantitative real-time RT-PCR method. Results of the laboratory-based studies demonstrate that statistically significant reductions of up to 74% of the initial norovirus GII concentration was achieved after 3 days at 17-21 °C and after 4 days at 11-15 °C, compared to 44% reduction at 7-9 °C. In many trials norovirus GII concentrations were reduced to levels below 100 genome copies per gram (gcg-1; limit of quantitation; LOQ). Virus reduction was also assessed in commercial depuration systems, routinely used by two Irish oyster producers. Up to 68% reduction was recorded for norovirus GI and up to 90% for norovirus GII reducing the geometric mean virus concentration close to or below the LOQ. In both commercial settings there was a significant difference between the levels of reduction of norovirus GI compared to GII (p < 0.05). Additionally, the ability to reduce the norovirus concentration in oysters to < LOQ differed when contaminated with concentrations below and above 1000 gcg-1. These results indicate that depuration, carried out at elevated (> 11 °C) water temperatures for at least 3 days, can reduce the concentration of norovirus in oysters and therefore consumer exposure providing a practical risk management tool for the shellfish industry.

Incubation period of COVID-19: a rapid systematic review and meta-analysis of observational research.

OBJECTIVES: The aim of this study was to conduct a rapid systematic review and meta-analysis of estimates of the incubation period of COVID-19. DESIGN: Rapid systematic review and meta-analysis of observational research. SETTING: International studies on incubation period of COVID-19. PARTICIPANTS: Searches were carried out in PubMed, Google Scholar, Embase, Cochrane Library as well as the preprint servers MedRxiv and BioRxiv. Studies were selected for meta-analysis if they reported either the parameters and CIs of the distributions fit to the data, or sufficient information to facilitate calculation of those values. After initial eligibility screening, 24 studies were selected for initial review, nine of these were shortlisted for meta-analysis. Final estimates are from meta-analysis of eight studies. PRIMARY OUTCOME MEASURES: Parameters of a lognormal distribution of incubation periods. RESULTS: The incubation period distribution may be modelled with a lognormal distribution with pooled mu and sigma parameters (95% CIs) of 1.63 (95% CI 1.51 to 1.75) and 0.50 (95% CI 0.46 to 0.55), respectively. The corresponding mean (95% CIs) was 5.8 (95% CI 5.0 to 6.7) days. It should be noted that uncertainty increases towards the tail of the distribution: the pooled parameter estimates (95% CIs) resulted in a median incubation period of 5.1 (95% CI 4.5 to 5.8) days, whereas the 95th percentile was 11.7 (95% CI 9.7 to 14.2) days. CONCLUSIONS: The choice of which parameter values are adopted will depend on how the information is used, the associated risks and the perceived consequences of decisions to be taken. These recommendations will need to be revisited once further relevant information becomes available. Accordingly, we present an R Shiny app that facilitates updating these estimates as new data become available.

Inferred duration of infectious period of SARS-CoV-2: rapid scoping review and analysis of available evidence for asymptomatic and symptomatic COVID-19 cases.

OBJECTIVES: Our objective was to review the literature on the inferred duration of the infectious period of COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, and provide an overview of the variation depending on the methodological approach. DESIGN: Rapid scoping review. Literature review with fixed search terms, up to 1 April 2020. Central tendency and variation of the parameter estimates for infectious period in (A) asymptomatic and (B) symptomatic cases from (1) virological studies (repeated testing), (2) tracing studies and (3) modelling studies were gathered. Narrative review of viral dynamics. INFORMATION SOURCES: Search strategies developed and the following searched: PubMed, Google Scholar, MedRxiv and BioRxiv. Additionally, the Health Information Quality Authority (Ireland) viral load synthesis was used, which screened literature from PubMed, Embase, ScienceDirect, NHS evidence, Cochrane, medRxiv and bioRxiv, and HRB open databases. RESULTS: There was substantial variation in the estimates, and how infectious period was inferred. One study provided approximate median infectious period for asymptomatic cases of 6.5-9.5 days. Median presymptomatic infectious period across studies varied over <1-4 days. Estimated mean time from symptom onset to two negative RT-PCR tests was 13.4 days (95% CI 10.9 to 15.8) but was shorter when studies included children or less severe cases. Estimated mean duration from symptom onset to hospital discharge or death (potential maximal infectious period) was 18.1 days (95% CI 15.1 to 21.0); time to discharge was on average 4 days shorter than time to death. Viral dynamic data and model infectious parameters were often shorter than repeated diagnostic data. CONCLUSIONS: There are limitations of inferring infectiousness from repeated diagnosis, viral loads and viral replication data alone and also potential patient recall bias relevant to estimating exposure and symptom onset times. Despite this, available data provide a preliminary evidence base to inform models of central tendency for key parameters and variation for exploring parameter space and sensitivity analysis.

Estimating the distribution of norovirus in individual oysters.

Norovirus in oysters is a significant food safety risk. A recent ISO detection method allows for reliable and repeatable estimates of norovirus concentrations in pooled samples, but there is insufficient data to estimate a distribution of copies per animal from this. The spread of norovirus accumulated across individual oysters is useful for risk assessment models. Six sets of thirty individual Crassostrea gigas oysters were tested for norovirus concentration levels by reverse-transcription quantitative PCR (RT-qPCR): three from a commercial harvest site, and three post-depuration. Five sets had norovirus GII means above the limit of quantification (LOQ), and one below the LOQ, but above the limit of detection. No norovirus GI was detected in pooled tests, and individual oysters were not tested for norovirus GI. Depuration was shown to reduce the mean concentration of GII copies, but not to affect the shape of the distribution around the mean. Deconvoluting the uncertainty of the method, the coefficient of variation was stationary (0.45 ±â€¯0.2). The best fit distribution was either a lognormal distribution or a gamma. Multiplying these distributions by the weight of oyster digestive tissues gave an estimate for the count mean. This was used as the parameter λ in three compound Poisson distributions: Poisson-lognormal, Poisson-gamma, and Poisson-K. No model was found to fit better than the others, with advantages for each. All three could be used in future risk assessments. Preliminary validation of sampling uncertainty using repeated testing data from a previous study suggests that these results have predictive power.

The Impact of Winter Relocation and Depuration on Norovirus Concentrations in Pacific Oysters Harvested from a Commercial Production Site.

Oysters contaminated with norovirus present a significant public health risk when consumed raw. In this study, norovirus genome copy concentrations were determined in Pacific oysters (Magallana gigas) harvested from a sewage-impacted production site and then subjected to site-specific management procedures. These procedures consisted of relocation of oysters to an alternative production area during the norovirus high-risk winter periods (November to March) followed by an extended depuration (self-purification) under controlled temperature conditions. Significant differences in norovirus RNA concentrations were demonstrated at each point in the management process. Thirty-one percent of oyster samples from the main harvest area (Site 1) contained norovirus concentrations > 500 genome copies/g and 29% contained norovirus concentrations < 100 genome copies/g. By contrast, no oyster sample from the alternative harvest area (Site 2) or following depuration contained norovirus concentrations > 500 genome copies/g. In addition, 60 and 88% of oysters samples contained norovirus concentrations < 100 genome copies/g in oysters sampled from Site 2 and following depuration, respectively. These data demonstrate that site-specific management processes, supported by norovirus monitoring, can be an effective strategy to reduce, but not eliminate, consumer exposure to norovirus genome copies.

Risk-based approach to developing a national residue sampling plan for testing under European Union regulation for veterinary medicinal products and coccidiostat feed additives in domestic animal production.

A ranking system for veterinary medicinal products and coccidiostat feed additives has been developed as a tool to be applied in a risk-based approach to the residue testing programme for foods of animal origin in the Irish National Residue Control Plan (NRCP). Three characteristics of substances that may occur as residues in food are included in the developed risk ranking system: Potency, as measured by the acceptable daily intake assigned by the European Medicines Agency Committee for Medicinal Products for Veterinary Use, to each substance; Usage, as measured by the three factors of Number of Doses, use on Individual animals or for Group treatment, and Withdrawal Period; and Residue Occurrence, as measured by the number of Non-Compliant Samples in the NRCP. For both Number of Doses and Non-Compliant Samples, data for the 5-year period 2008-12 have been used. The risk ranking system for substances was developed for beef cattle, sheep and goats, pigs, chickens and dairy cattle using a scoring system applied to the various parameters described above to give an overall score based on the following equation: Potency × Usage (Number of Doses + Individual/Group Use + Withdrawal Period) × Residue Occurrence. Applying this risk ranking system, the following substances are ranked very highly: antimicrobials such as amoxicillin (for all species except pigs), marbofloxacillin (for beef cattle), oxytetracycline (for all species except chickens), sulfadiazine with trimethoprim (for pigs and chickens) and tilmicosin (for chickens); antiparasitic drugs, such as the benzimidazoles triclabendazole (for beef and dairy cattle), fenbendazole/oxfendazole (for sheep/goats and dairy cattle) and albendazole (for dairy cattle), the avermectin ivermectin (for beef cattle), and anti-fluke drugs closantel and rafoxanide (for sheep/goats); the anticoccidials monensin, narasin, nicarbazin and toltrazuril (for chickens). The risk ranking system described is a relatively simple system designed to provide a reliable basis for selecting the veterinary medicinal products and coccidiostat feed additives that might be prioritised for residue testing.

Modeling the growth of Listeria monocytogenes on the surface of smear- or mold-ripened cheese.

Surface-ripened cheeses are matured by means of manual or mechanical technologies posing a risk of cross-contamination, if any cheeses are contaminated with Listeria monocytogenes. In predictive microbiology, primary models are used to describe microbial responses, such as growth rate over time and secondary models explain how those responses change with environmental factors. In this way, primary models were used to assess the growth rate of L. monocytogenes during ripening of the cheeses and the secondary models to test how much the growth rate was affected by either the pH and/or the water activity (aw) of the cheeses. The two models combined can be used to predict outcomes. The purpose of these experiments was to test three primary (the modified Gompertz equation, the Baranyi and Roberts model, and the Logistic model) and three secondary (the Cardinal model, the Ratowski model, and the Presser model) mathematical models in order to define which combination of models would best predict the growth of L. monocytogenes on the surface of artificially contaminated surface-ripened cheeses. Growth on the surface of the cheese was assessed and modeled. The primary models were firstly fitted to the data and the effects of pH and aw on the growth rate (µmax) were incorporated and assessed one by one with the secondary models. The Logistic primary model by itself did not show a better fit of the data among the other primary models tested, but the inclusion of the Cardinal secondary model improved the final fit. The aw was not related to the growth of Listeria. This study suggests that surface-ripened cheese should be separately regulated within EU microbiological food legislation and results expressed as counts per surface area rather than per gram.