RISK-BASED SURVEILLANCE FOR FOOD-BORNE PARASITES Advantages, requirements and limitations

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RISK-BASED SURVEILLANCE FOR FOOD-BORNE PARASITES Advantages, requirements and limitations Lis Alban DVM, PhD., DipECVPH Chief Scientist, Danish Agriculture & Food Council Adjunct Professor, University of Copenhagen Final Euro-FBP meeting, February 14, 2019, Oeiras, Portugal

Challenges regarding food safety are plenty - Risk-based surveillance offers a solution Lack of hygiene Toxoplasma gondii Salmonella Yersinia enterocolitica Food fraud Trichinella Inspection fraud Taenia solium

Risk-based surveillance systems Grown out of veterinary services world Applying risk analysis methods, when designing surveillance-and-control programmes To assure appropriate and cost-effective data collection Objective Identify surveillance needs to protect health of livestock and consumers Including trade Set priorities and allocate resources effectively and efficiently Focus on high benefit-cost ratio Risk communication Hazard identification Risk analysis Risk management Risk assessment

Risk-based surveillance systems First, strategic decision: Hazard identified and prioritized, e.g. based upon Burden of Disease Then, operational decisions: Intensification of sampling to specific subpopulations Often stratum with highest risk (Risk=probability*consequences) Using knowledge of life cycle of parasite Looking at number of human and animal cases Risk factors/commodities are identified Easiness and costs of sampling are evaluated together with a view on intended use of meat Similar for risk management options

Sampling in high-risk stratum Early warning/freedom If parasite is present, there will be minimum 1 per million (=Design prevalence) N = 18 million pigs 18 infected pigs Assuming RR 9 between the 2 compartments 16 infected pigs 2 infected pigs Pigs raised under low biosecurity N = 1 million Pigs raised under high biosecurity N = 17 million Probability of finding infection, when testing all low biosecurity pigs, and assuming test Se=0.4: P 1pos = 1-P 0pos = 1- (1-0.4) 16 = 0.99 Probability of overlooking all 16 positives

Similar approach to endemic infections Risk factor and scenarios No. of detected cases (95% CI) a Current 44 surveillance (15, 95) Gender 36 (12, 78) Grazing 31 (10, 67) Sensitivity of surveillance (95% CI) 0.15 (0.07, 0.22) 0.12 (0.06, 0.18) 0.10 (0.05, 0.16) No. of cattle visually inspected Net gain in million /year (95% CI) Costeffectiveness ratio In million /year (95% CI) 0 0-251,327 0.7 (0.6, 0.8) 299,374 0.8 (0.7, 0.9) 28.3 (17.1, 52.7) 20.3 (12.3, 37.9) Source: Calvo-Artavía et al., 2012

Meat inspection is surveillance All slaughter animals are subjected to inspection Consists of ante mortem and post mortem inspection As well as associated tests and treatments EFSA Opinions reg. relevant hazards to look for at meat inspection Pigs: Salmonella, Yersinia, Trichinella and Toxoplasma Cattle: Cysticercus bovis, bovine TB, Salmonella Dublin In the following, examples of risk-based surveillance will be given For Trichinella, C. bovis and Toxoplasma

Trichinella EU Trichinella Regulation 2015/1375 adopted risk-based surveillance Only testing of pigs raised in non-controlled compartment Negligible prevalence in pigs, raised under controlled housing Annex to Regulation specifies requirements for controlled housing on-farm Establishment and maintenance of negligible risk compartment Based upon biosecurity and/or test results Possibility to use third-party independent auditor As part of private standards run by the meat and livestock industry Private standard National legislation EU legislation

Prevalence of cysticercosis Cysticercus bovis in cattle Associated human infection not associated with severe disease Low sensitivity associated with lightly-infected cattle (<15%) Low prevalence of infection in many countries Suggestion: identify high-risk subpopulation and put focus there Young age and male gender have low risk Risk factor Risk group RR Proportion Gender Female 4.7 0.5 Male 1 0.5 Grazing Grazing 3.6 0.4 Zero-grazing 1 0.6 Figures for Denmark provided by Calvo-Artavía et al., 2012ab 0.050% 0.040% 0.030% 0.020% 0.010% 0.000% 0 1 2 3 4 5 6 7 8 9 Age

Belgian data indicate a different situation Jansen et al. (2018) estimated a prevalence of 43% One may wonder what causes this high prevalence Sewage system? Grazing patterns? With prevalences this high, all beef could be considered high-risk Unless farmer decides to document low-risk Role of using serological test? costly, if used on all slaughter cattle

EU Commission s proposal reg. meat inspection of cattle for C. bovis and bovine TB Cattle delivered to abattoir Young = Either <8 months, or <20 months and raised indoors in TB free country Adult TB: Palpation of tongue and its lymph nodes C. bovis: No incisions into masseter muscles Incision and palpation for TB and C. bovis

Toxoplasma gondii Data show that the apparent prevalence is: Low in indoor-raised finishing pigs Medium to high in sows and outdoor-raised finisher pigs Information may be used when considering design of surveillance-andcontrol Whether, where and how to put in place New requirements needed regarding prevention On-farm: Could consist of development of recommendations for biosecurity/hygiene Post-harvest: Freezing of raw meat intended for production of mildly cured ready-to-eat products Where raw meat originates from sows or outdoor-reared pigs

Advantages and requirements Higher benefit-cost, if planned well Risk factors need to be identified and documented At herd/group level or individual level They need to be feasible Ressource-demanding to collect data In particular in middle- and low-income countries Suggestion: share data among countries with similar agricultural practices Keep it simple Divide animal population into low-risk and high-risk Assume all animals/herds from high-risk compartment as potentially infected Use indicators to divide population E.g. through auditing of biosecurity

Limitations Changes in the EU Move towards higher demand for lean pork, based on local, animal welfare friendly, outdoor production Lower salt and less-thorough cooking Effect should be foreseen and handled Increase in exposure of humans to hazards Larger uncertainty No common agreement on what low-risk means Documentation of effect of risk factors needed If not, confidence among consumers and trade partners may be low

Trends outside the food supply system Climatic changes may result in expansion of habitat of insects or parasites May lead to increase in prevalence of infection in animals that form part of supply chain Likewise, requirement for increased feed production may lead to establishment of agriculture in areas previously free from human activities May lead to higher probability of introduction of pathogens into food supply system Emphasizes that food supply systems are nested in social-ecological context Unpredictable from production chain perspective and demands a broader approach Early warning surveillance may be needed

Structured prevention through collaboration Prevent unwanted events from happening In a structured way, in all parts of the supply chain In collaboration with Food Business Operator HACCP already in place in most supply chains Chain view with different kinds of measurement Hazard itself (direct) or indicators (indirect) Should be set up to allow fast and targeted implementation of risk mitigating activities, when needed Inputs Production Logistic Processing Distribution Consumption

Summing up Large need for surveillance, but few resources available in society Risk-based surveillance-and-control is based on risk analysis framework Helps to identify needs, set priorities, and allocate ressources Focus on high benefit-cost ratio in surveillance/control Think about biology, look at supply chain Use direct or indirect measurements Collaborate with Food Business Operator Find common interests, share data and act

Thank you for the attention RIBMINS Cost Action Network 2019-2024 Open workshop about risk-based meat inspection and integrated meat safety assurance on Monday 26 August 2019 Held in relation to the Safepork Conference Deadline for submission of abstract to Safepork: 28 February 2019