Risk programming analysis with imperfect information

A Monte Carlo procedure is used to demonstrate the dangers of basing (farm) risk programming on only a few states of nature and to study the impact of applying alternative risk programming methods. Two risk programming formulations are considered, namely mean-variance (E,V) programming and utility efficient (UE) programming. For the particular example of a Norwegian mixed livestock and crop farm, the programming solution is unstable with few states, although the cost of picking a sub-optimal plan declines with increases in number of states. Comparing the E,V results with the UE results shows that there were few discrepancies between the two and the differences which do occur are mainly trivial, thus both methods gave unreliable results in cases with small samples

Risk programming and sparse data: how to get more reliable results

Because relevant historical data for farms are inevitably sparse, most risk programming studies rely on few observations of uncertain crop and livestock returns. We show the instability of model solutions with few observations and discuss how to use available information to derive an appropriate multivariate distribution function that can be sampled for a more complete representation of the possible risks in risk-based models. For the particular example of a Norwegian mixed livestock and crop farm, the solution is shown to be unstable with few states of nature producing a risky solution that may be appreciably suboptimal. However, the risk of picking a sub-optimal plan declines with increases in number of states of nature generated by Latin hypercube sampling

Effectiveness and costs of interventions to reduce the within-farm Toxoplasma gondii seroprevalence on pig farms in the Netherlands.

BACKGROUND: The parasite Toxoplasma gondii (T. gondii) is recognized as one of the major foodborne pathogens with a high human disease burden. To control T. gondii infections in pigs, European Food Safety Agency (EFSA) advises serological testing of pigs and audits of pig farms to identify risk factors for T. gondii infection. In line with this approach, the aim of the current study was to assess the effectiveness and costs of intervention measures implemented to reduce the T. gondii seroprevalence on finishing pig farms in the Netherlands. A crossover clinical trial was conducted at five case farms were their own control and the cross-over moment was the implementation of interventions to reduce risk factors. Each of the case farms had a farm-specific intervention strategy with one principal intervention measure (neutering of cats, professional rodent control or covering food storage). RESULTS: All finishing pig farms (n = 5) showed a reduction in T. gondii seroprevalence within one year of implementing the intervention strategy. Cat neutering (n = 3) and feed coverage (n = 1) showed statistically significant reductions in seroprevalence. Rodent control (n = 1) did not show a statistically significant reduction. The estimated reduction in seroprevalence in response to the neutering of cats and feed coverage were 67 and 96 %, respectively. CONCLUSIONS: Our work demonstrates that it is possible to reduce the within-farm T. gondii seroprevalence within one year after interventions were implemented to reduce T. gondii risk factors. This information is essential and encouraging for policy makers, food business operators, and farmers to implement in their risk assessment and to apply to food safety control systems. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40813-021-00223-0

Potential risk factors for the presence of anti-Toxoplasma gondii antibodies in finishing pigs on conventional farms in the Netherlands.

Background: The parasite Toxoplasma gondii (T. gondii) causes a substantial human disease burden worldwide. Ingesting improperly cooked pork containing T. gondii is considered one of the major sources of human infection in Europe and North America. Consequently, control of T. gondii infections in pigs is warranted. The European Food Safety Authority advised to perform serological monitoring of pigs and to conduct farm audits for the presence of risk factors. Serological monitoring was implemented in several Dutch slaughterhouses, one to six blood samples (a total of 5134 samples) were taken from each delivery of finishing pigs and samples were tested for the presence of anti-T. gondii antibodies. Using these test results, a cross-sectional study was initiated to assess the association between the within-herd T. gondii seroprevalence and the presence of risk factors for T. gondii infections at 69 conventional finishing pig farms in the Netherlands.Results: A multivariable model showed significant (P ≤ 0.05) association with twelve potential risk factors: type of farm, presence of dogs, presence of ruminants, use of boots, use of shower and farm clothing, mode of rodent control, bedding accessibility for rodents, presence of cats, type of drinking water, heating of the feed, use of goat whey and shielding of birds.Conclusions: Serological monitoring of finishing pigs for T. gondii in slaughterhouses can be used to identify the presence of T. gondii risk factors on Dutch conventional finishing pig farms and seems a valuable tool to guide and monitor the control of T. gondii in pork production

Validation and update of a prediction model for risk of relapse after cessation of anti-TNF treatment in Crohn's disease

BACKGROUND: Anti-tumor necrosis factor (TNF) therapy is effective for the treatment of Crohn's disease. Cessation may be considered in patients with a low risk of relapse. We aimed to externally validate and update our previously developed prediction model to estimate the risk of relapse after cessation of anti-TNF therapy. METHODS: We performed a retrospective cohort study in 17 Dutch hospitals. Crohn's disease patients in clinical, biochemical or endoscopic remission were included after anti-TNF cessation. Primary outcome was a relapse necessitating treatment. Discrimination and calibration of the previously developed model were assessed. After external validation, the model was updated. The performance of the updated prediction model was assessed in internal-external validation and by using decision curve analysis. RESULTS: 486 patients were included with a median follow-up of 1.7 years. Relapse rates were 35 and 54% after 1 and 2 years. At external validation, the discriminative ability of the prediction model was equal to that found at the development of the model [c-statistic 0.58 (95% confidence interval (CI) 0.54-0.62)], though the model was not well-calibrated on our cohort [calibration slope: 0.52 (0.28-0.76)]. After an update, a c-statistic of 0.60 (0.58-0.63) and calibration slope of 0.89 (0.69-1.09) were reported in internal-external validation. CONCLUSION: Our previously developed and updated prediction model for the risk of relapse after cessation of anti-TNF in Crohn's disease shows reasonable performance. The use of the model may support clinical decision-making to optimize patient selection in whom anti-TNF can be withdrawn. Clinical validation is ongoing in a prospective randomized trial