Quantitative Microbiological Risk Assessment and Source Attribution for Salmonella: Taking it Further

Risk Analysis: Celebrating the Accomplishments and Embracing Ongoing Challenges

As part of the celebration of the 40th anniversary of the Society for Risk Analysis and Risk Analysis: An International Journal, this essay reviews the 10 most important accomplishments of risk analysis from 1980 to 2010, outlines major accomplishments in three major categories from 2011 to 2019, discusses how editors circulate authors' accomplishments, and proposes 10 major risk-related challenges for 2020-2030. Authors conclude that the next decade will severely test the field of risk analysis.

Source Attribution and Risk Assessment of Antimicrobial Resistance

Source attribution and microbial risk assessment methods have been widely applied for the control of several foodborne pathogens worldwide by identifying (i) the most important pathogen sources and (ii) the risk represented by specific foods and the critical points in these foods' production chains for microbial control. Such evidence has proved crucial for risk managers to identify and prioritize effective food safety and public health strategies. In the context of antimicrobial resistance (AMR) from livestock and pets, the utility of these methods is recognized, but a number of challenges have largely prevented their application and routine use. One key challenge has been to define the hazard in question: Is it the antimicrobial drug use in animals, the antimicrobial-resistant bacteria in animals and foods, or the antimicrobial resistance genes that can be transferred between commensal and pathogenic bacteria in the animal or human gut or in the environment? Other important limitations include the lack of occurrence and transmission data and the lack of evidence to inform dose-response relationships. We present the main principles, available methods, strengths, and weaknesses of source attribution and risk assessment methods, discuss their utility to identify sources and estimate risks of AMR from livestock and pets, and provide an overview of conducted studies. In addition, we discuss remaining challenges and current and future opportunities to improve methods and knowledge of the sources and transmission routes of AMR from animals through food, direct contact, or the environment, including improvements in surveillance and developments in genotypic typing methods.

Livestock Health and Food Chain Risk Assessment

The EUFORA fellowship programme ‘Livestock Health and Food Chain Risk Assessment’ was proposed by the Animal and Plant Health Agency (APHA), a British governmental institution responsible for safeguarding animal and plant health in the UK. The working programme, which was organised into four different modules, covered a wide range of aspects related to risk assessment including identification of emerging risks, risk prioritisation methods, scanning surveillance, food production exposure assessment and import risk assessment of animal and human infectious diseases. Over the course of the year, the Fellow had the opportunity to work for international projects with experts in these disciplines. This allowed for significant opportunities to ‘learn‐by‐doing’ the methods and the techniques that are employed to assess animal health and food safety risks. Moreover, he consolidated his knowledge by attending several training courses and academic lessons, submitting scientific papers to peer‐reviewed journals and conferences, giving presentations and using modelling software.

Looking for new approaches for the use of serology in the context of control programmes against pig salmonellosis

Most swine Salmonella national control programmes in Europe have been based on the categorization of herds according to risk levels based on serological results. However, none of the non-Scandinavian countries have reported of any significant success on Salmonella infection reduction in fattening pigs or the number of human cases attributable to pigs or pork. The limited accuracy of the tests used, the small number of animals sampled and the likely lack of herd representativeness of the samples used could be major factors affecting the suitability of these programmes. Focusing on minimizing Salmonella shedding at slaughter appears more important to prevent human infections than focusing on detection of seropositive pigs/herds at this stage. This study assessed whether performing on-farm serology may help to predict shedding at slaughter. Between 2010 and 2016, pigs from six cohorts from a Salmonella-positive herd were bled at 30, 60 and 90 days on fattening and before slaughter, and faecal samples collected at slaughter. Serology on days 60, 90 and before slaughter predicted somewhat shedding at slaughter with no significant differences among them. Pigs with higher OD% values at these point times would have higher risk of shedding when arriving to slaughter. The probability of shedding for a pig sampled on day 90 and showing an OD% value of 10 was 43%, and the risk increased up to 65% if the OD% was 40. Concluding, on-farm serology may help to determine to some extent the risk of Salmonella shedding at slaughter from seropositive fattening units, which would allow for prompt on-farm and slaughter interventions to reduce the likelihood of slaughter contamination with Salmonella.

Correlation between slaughter practices and the distribution of Salmonella and hygiene indicator bacteria on pig carcasses during slaughter

This study investigated the distribution of hygiene indicator bacteria and Salmonella on pig carcasses. Moreover, the relation between hygiene indicator counts and Salmonella presence as well as associations between specific slaughter practices and carcass contamination were determined for each carcass area. Seven Belgian pig slaughterhouses were visited three times to swab five randomly selected carcasses at nine different areas, after evisceration and trimming. Information about slaughter practices was collected using a questionaire. In all samples, the E. coli and Salmonella presence was analyzed and Enterobacteriaceae and total aerobic bacteria were quantified. Average total aerobic counts ranged from 3.1 (loin, pelvic duct, ham) to 4.4 log₁₀ CFU/cm² (foreleg). Median Enterobacteriaceae numbers varied between 0.4 (ham) an 1.8 log₁₀ CFU/cm² (foreleg). E. coli and Salmonella presence ranged from 15% (elbow) to 89% (foreleg) and 5% (elbow) to 38% (foreleg), respectively. Positive relations were found between hygiene indicator counts and Salmonella presence at the head, sternum, loin and throat. Several slaughter practices, such as splitting the head and incising tonsils, were associated with higher levels of hygiene indicator bacteria and Salmonella. These findings can be used to educate slaughterhouse personnel and estimate the public health risk involved in consumption of different pork cuts.

Towards an integrated food safety surveillance system: a simulation study to explore the potential of combining genomic and epidemiological metadata

Foodborne infection is a result of exposure to complex, dynamic food systems. The efficiency of foodborne infection is driven by ongoing shifts in genetic machinery. Next-generation sequencing technologies can provide high-fidelity data about the genetics of a pathogen. However, food safety surveillance systems do not currently provide similar high-fidelity epidemiological metadata to associate with genetic data. As a consequence, it is rarely possible to transform genetic data into actionable knowledge that can be used to genuinely inform risk assessment or prevent outbreaks. Big data approaches are touted as a revolution in decision support, and pose a potentially attractive method for closing the gap between the fidelity of genetic and epidemiological metadata for food safety surveillance. We therefore developed a simple food chain model to investigate the potential benefits of combining 'big' data sources, including both genetic and high-fidelity epidemiological metadata. Our results suggest that, as for any surveillance system, the collected data must be relevant and characterize the important dynamics of a system if we are to properly understand risk: this suggests the need to carefully consider data curation, rather than the more ambitious claims of big data proponents that unstructured and unrelated data sources can be combined to generate consistent insight. Of interest is that the biggest influencers of foodborne infection risk were contamination load and processing temperature, not genotype. This suggests that understanding food chain dynamics would probably more effectively generate insight into foodborne risk than prescribing the hazard in ever more detail in terms of genotype.