Guidance on the use of the benchmark dose approach in risk assessment.

The Scientific Committee (SC) reconfirms that the benchmark dose (BMD) approach is a scientifically more advanced method compared to the no-observed-adverse-effect-level (NOAEL) approach for deriving a Reference Point (RP). The major change compared to the previous Guidance (EFSA SC, 2017) concerns the Section 2.5, in which a change from the frequentist to the Bayesian paradigm is recommended. In the former, uncertainty about the unknown parameters is measured by confidence and significance levels, interpreted and calibrated under hypothetical repetition, while probability distributions are attached to the unknown parameters in the Bayesian approach, and the notion of probability is extended to reflect uncertainty of knowledge. In addition, the Bayesian approach can mimic a learning process and reflects the accumulation of knowledge over time. Model averaging is again recommended as the preferred method for estimating the BMD and calculating its credible interval. The set of default models to be used for BMD analysis has been reviewed and amended so that there is now a single set of models for quantal and continuous data. The flow chart guiding the reader step-by-step when performing a BMD analysis has also been updated, and a chapter comparing the frequentist to the Bayesian paradigm inserted. Also, when using Bayesian BMD modelling, the lower bound (BMDL) is to be considered as potential RP, and the upper bound (BMDU) is needed for establishing the BMDU/BMDL ratio reflecting the uncertainty in the BMD estimate. This updated guidance does not call for a general re-evaluation of previous assessments where the NOAEL approach or the BMD approach as described in the 2009 or 2017 Guidance was used, in particular when the exposure is clearly lower (e.g. more than one order of magnitude) than the health-based guidance value. Finally, the SC firmly reiterates to reconsider test guidelines given the wide application of the BMD approach.

Quantitative Microbial Risk Assessment Based on Whole Genome Sequencing Data: Case of Listeria monocytogenes.

The application of high-throughput DNA sequencing technologies (WGS) data remain an increasingly discussed but vastly unexplored resource in the public health domain of quantitative microbial risk assessment (QMRA). This is due to challenges including high dimensionality of WGS data and heterogeneity of microbial growth phenotype data. This study provides an innovative approach for modeling the impact of population heterogeneity in microbial phenotypic stress response and integrates this into predictive models inputting a high-dimensional WGS data for increased precision exposure assessment using an example of Listeria monocytogenes. Finite mixture models were used to distinguish the number of sub-populations for each of the stress phenotypes, acid, cold, salt and desiccation. Machine learning predictive models were selected from six algorithms by inputting WGS data to predict the sub-population membership of new strains with unknown stress response data. An example QMRA was conducted for cultured milk products using the strains of unknown stress phenotype to illustrate the significance of the findings of this study. Increased resistance to stress conditions leads to increased growth, the likelihood of higher exposure and probability of illness. Neglecting within-species genetic and phenotypic heterogeneity in microbial stress response may over or underestimate microbial exposure and eventual risk during QMRA.

Random effects models for estimation of the probability and time to progression of a continuous biomarker.

Biomarkers play a key role in the monitoring of disease progression. The time taken for an individual to reach a biomarker exceeding or lower than a meaningful threshold is often of interest. Due to the inherent variability of biomarkers, persistence criteria are sometimes included in the definitions of progression, such that only two consecutive measurements above or below the relevant threshold signal that "true" progression has occurred. In previous work, a novel approach was developed, which allowed estimation of the time to threshold using the parameters from a linear mixed model where the residual variance was assumed to be pure measurement error. In this paper, we extend this methodology so that serial correlation can be accommodated. Assuming that the Markov property holds and applying the chain rule of probabilities, we found that the probability of progression at each timepoint can be expressed simply as the product of conditional probabilities. The methodology is applied to a cohort of HIV positive individuals, where the time to reach a CD4 count threshold is estimated. The second application we present is based on a study on abdominal aortic aneurysms, where the time taken for an individual to reach a diameter exceeding 55 mm is studied. We observed that erroneously ignoring the residual correlation when it is strong may result in substantial overestimation of the time to threshold. The estimated probability of the biomarker reaching a threshold of interest, expected time to threshold, and confidence intervals are presented for selected patients in both applications.

An explorative study on systematic assessment of QOL and care needs with the CARES-SF in the early follow-up of patients with digestive cancer.

PURPOSE: Systematic assessment of QOL and care needs was applied in two gastroenterology departments to support "Cancer Care for the Whole Patient." METHODS: Patients with digestive cancer were asked to complete the Cancer Rehabilitation Evaluation System-Short Form (CARES-SF) at the start of treatment and 3 months later. Both times CARES data were processed, and summary reports on the retained insights were sent to the reference nurse for use in further follow-up of the patient. Patients' and reference nurse's experiences with the systematic CARES-assessment were explored with several survey questions and semi-structured interviews, respectively. RESULTS: The mean age of the 51 participants was 63 years (SD11.17), 52.9% was male. With the CARES-SF, a large variety of problems and care needs was detected. Problems most frequently experienced, and most burdensome for QOL are a mix of physical complaints, side effects from treatment, practical, relational, and psychosocial difficulties. Only for a limited number of experienced problems a desire for extra help was expressed. All patients positively evaluate the timing and frequency of the CARES-assessment. The majority believes that this assessment could contribute to the discussion of problems and needs with healthcare professionals, to get more tailored care. Reference nurses experienced the intervention as an opportunity to systematically explore patients' well-being in a comprehensive way, leading to detection and discussion of specific problems or needs in greater depth, and more efficient involvement of different disciplines in care. CONCLUSIONS: Systematic QOL and needs assessment with the CARES-SF in oncology can contribute to more patient-centeredness and efficiency of care.

The magnitude and factors related to facility-based maternal mortality in Mozambique.

Facility-based maternal mortality remains an important public health problem in Mozambique. A number of factors associated with health system functioning can be described behind the occurrence of these deaths. This paper aimed to evaluate the magnitude of the health facility-based maternal mortality, its geographical distribution and to assess the health facility factors implicated in the occurrence of these deaths. A secondary analysis was done on data from the survey on maternal health needs performed by the Ministry of Health of Mozambique in 2008. During the study period 2.198 maternal deaths occurred out of 312.537 deliveries. According to the applied model the availability of Maternal and Child Health (MCH) nurses performing Emergency Obstetric Care functions was related to the reduction of facility-based maternal mortality by 40%. No significant effects were observed for the availability of medical doctors, surgical technicians and critical delivery room equipment. Impact statement Is largely known that the availability of skilled attendants assisting every delivery and providing Emergency Obstetric Care services during the pregnancy, labor and Childbirth is key for maternal mortality reduction. This study add the differentiation on the impact of different cadres of health services providers working on maternal and child health services on the facility based maternal mortality. In this setting the study proven the high impact of the midlevel skilled maternal and child health nurses on the reduction of maternal mortality. Another important add from this study is the use of facility based maternal mortality data to inform the management process of maternal healthcare services. The findings from this study have potential to impact on the decision of staffing prioritization in setting like the study setting. The findings support the policy choice to improve the availability of maternal and child health nurses.

Microbial Performance of Food Safety Control and Assurance Activities in a Fresh Produce Processing Sector Measured Using a Microbial Assessment Scheme and Statistical Modeling.

Current approaches such as inspections, audits, and end product testing cannot detect the distribution and dynamics of microbial contamination. Despite the implementation of current food safety management systems, foodborne outbreaks linked to fresh produce continue to be reported. A microbial assessment scheme and statistical modeling were used to systematically assess the microbial performance of core control and assurance activities in five Kenyan fresh produce processing and export companies. Generalized linear mixed models and correlated random-effects joint models for multivariate clustered data followed by empirical Bayes estimates enabled the analysis of the probability of contamination across critical sampling locations (CSLs) and factories as a random effect. Salmonella spp. and Listeria monocytogenes were not detected in the final products. However, none of the processors attained the maximum safety level for environmental samples. Escherichia coli was detected in five of the six CSLs, including the final product. Among the processing-environment samples, the hand or glove swabs of personnel revealed a higher level of predicted contamination with E. coli , and 80% of the factories were E. coli positive at this CSL. End products showed higher predicted probabilities of having the lowest level of food safety compared with raw materials. The final products were E. coli positive despite the raw materials being E. coli negative for 60% of the processors. There was a higher probability of contamination with coliforms in water at the inlet than in the final rinse water. Four (80%) of the five assessed processors had poor to unacceptable counts of Enterobacteriaceae on processing surfaces. Personnel-, equipment-, and product-related hygiene measures to improve the performance of preventive and intervention measures are recommended.

Update: use of the benchmark dose approach in risk assessment.

The Scientific Committee (SC) reconfirms that the benchmark dose (BMD) approach is a scientifically more advanced method compared to the NOAEL approach for deriving a Reference Point (RP). Most of the modifications made to the SC guidance of 2009 concern the section providing guidance on how to apply the BMD approach. Model averaging is recommended as the preferred method for calculating the BMD confidence interval, while acknowledging that the respective tools are still under development and may not be easily accessible to all. Therefore, selecting or rejecting models is still considered as a suboptimal alternative. The set of default models to be used for BMD analysis has been reviewed, and the Akaike information criterion (AIC) has been introduced instead of the log-likelihood to characterise the goodness of fit of different mathematical models to a dose-response data set. A flowchart has also been inserted in this update to guide the reader step-by-step when performing a BMD analysis, as well as a chapter on the distributional part of dose-response models and a template for reporting a BMD analysis in a complete and transparent manner. Finally, it is recommended to always report the BMD confidence interval rather than the value of the BMD. The lower bound (BMDL) is needed as a potential RP, and the upper bound (BMDU) is needed for establishing the BMDU/BMDL per ratio reflecting the uncertainty in the BMD estimate. This updated guidance does not call for a general re-evaluation of previous assessments where the NOAEL approach or the BMD approach as described in the 2009 SC guidance was used, in particular when the exposure is clearly smaller (e.g. more than one order of magnitude) than the health-based guidance value. Finally, the SC firmly reiterates to reconsider test guidelines given the expected wide application of the BMD approach.

The Belgian policy of funding antimicrobial stewardship in hospitals and trends of selected quality indicators for antimicrobial use, 1999-2010: a longitudinal study.

OBJECTIVES: In order to improve antimicrobial (AM) use, a policy of providing technical and financial support to AM management teams (AMTs) was rolled out in all Belgian hospitals between 2002 and 2008. We aimed to analyse the association of this policy with AM use for the two indications accounting for the largest number of patients receiving AM: prophylaxis for major lower limb orthopaedic surgery and pneumonia. DESIGN, SETTING, PARTICIPANTS: We used patient-level data routinely collected in all Belgian acute care hospitals between 1999 and 2010. We modelled trends for selected quality indicators (QIs) using the year of AMT implementation in each hospital as the main 'change point', with fine-tuned case-mix adjustment. Of all admissions for lower limb orthopaedic surgery, and pneumonia between 1999 and 2010, 90% (325 094) and 95% (327 635), respectively, were found eligible for analyses. OUTCOMES: The surgery QI was defined as: cefazolin, dose in the expected range, and no use of other AM. For pneumonia, QIs were: ratio of oral/parenteral defined daily doses (DDD, O/P QI), and mean number of DDD minus penicillin, per 100 days of hospitalisation (DDD QI). RESULTS: Between 1999 and 2010, the surgery QI improved from 59% to 71%, the O/P QI from 0.72 to 0.97, and the DDD QI from 96 to 64. Heterogeneity between hospitals was high. Overall, no association was found with the year of implementation of the AMT. CONCLUSIONS: Improvements have been observed but could not be related at the national level to the policy under study. However, these results cannot be extrapolated to other QIs for AM use in hospitals. Our findings do not question the need for AMT, nor the need for continuation of AMT funding. Several recommendations can be made in order to make the best of Belgium's unique political and financial commitments in that field.

A mathematical model for HIV and hepatitis C co-infection and its assessment from a statistical perspective.

The hepatitis C virus (HCV) and the human immunodeficiency virus (HIV) are a clear threat for public health, with high prevalences especially in high risk groups such as injecting drug users. People with HIV infection who are also infected by HCV suffer from a more rapid progression to HCV-related liver disease and have an increased risk for cirrhosis and liver cancer. Quantifying the impact of HIV and HCV co-infection is therefore of great importance. We propose a new joint mathematical model accounting for co-infection with the two viruses in the context of injecting drug users (IDUs). Statistical concepts and methods are used to assess the model from a statistical perspective, in order to get further insights in: (i) the comparison and selection of optional model components, (ii) the unknown values of the numerous model parameters, (iii) the parameters to which the model is most 'sensitive' and (iv) the combinations or patterns of values in the high-dimensional parameter space which are most supported by the data. Data from a longitudinal study of heroin users in Italy are used to illustrate the application of the proposed joint model and its statistical assessment. The parameters associated with contact rates (sharing syringes) and the transmission rates per syringe-sharing event are shown to play a major role.

Expert judgement in a risk assessment model for Salmonella spp. in pork: the performance of different weighting schemes.

A structured expert judgement study was carried out in order to obtain input parameters for a quantitative microbial risk assessment (QMRA) model. This model aimed to estimate the risk of human Salmonella infections associated with the consumption of minced pork meat. Judgements of 11 experts were used to derive subjective probability density functions (PDFs) to quantify the uncertainty on the model input parameters. The performance of experts as probability assessors was measured by the experts' ability to correctly and precisely provide estimates for a set of seed variables (=variables from the experts' area of expertise for which the true values were known to the analyst). Subsequently different weighting schemes or "decision makers" (DMs) were applied using Cooke's classical model in order to obtain combined PDFs as a weighted linear combination of the expert's individual PDFs. The aim of this study was to compare the performance of four DMs namely the equal weight DM (each expert's opinion received equal weight), the user weight DM (weights are determined by the expert's self-perceived level of expertise) and two performance-based DMs: the global weight DM and the item weight DM. Weights in the performance-based DMs were calculated based on the expert's calibration and information performance as measured on the set of seed variables. The item weight DM obtained the highest performance with a calibration score of 0.62 and an information score of 0.52, as compared to the other DMs. The weights of the performance-based DMs outperformed those of the best expert in the panel. The correlation between the scores for self-rating of expertise and the weights based on the experts' performance on the calibration variables was low and not significant (r=0.37, p=0.13). The applied classical model provided a rational basis to use the combined distributions obtained by the item weight DM as input in the QMRA model since this DM yielded generally more informative distributions for the variables of interest than those obtained by the equal weight and user weight DM. Attention should be paid to find adequate and relevant seed variables, since this is important for the validation of the results of the weighting scheme.

Estimating the incidence of symptomatic rotavirus infections: a systematic review and meta-analysis.

BACKGROUND: We conducted for the first time a systematic review, including a meta-analysis, of the incidence of symptomatic rotavirus (RV) infections, because (1) it was shown to be an influential factor in estimating the cost-effectiveness of RV vaccination, (2) multiple community-based studies assessed it prospectively, (3) previous studies indicated, inconclusively, it might be similar around the world. METHODOLOGY: Pubmed (which includes Medline) was searched for surveys assessing prospectively symptomatic (diarrheal) episodes in a general population and situation, which also reported on the number of the episodes being tested RV+ and on the persons and the time period observed. A bias assessment tool was developed and used according to Cochrane guidelines by 4 researchers with different backgrounds. Heterogeneity was explored graphically and by comparing fits of study-homogenous 'fixed effects' and -heterogeneous 'random effects' models. Data were synthesized using these models. Sensitivity analysis for uncertainty regarding data abstraction, bias assessment and included studies was performed. PRINCIPAL FINDINGS: Variability between the incidences obtained from 20 studies is unlikely to be due to study groups living in different environments (tropical versus temperate climate, slums versus middle-class suburban populations), nor due to the year the study was conducted (from 1967 to 2003). A random effects model was used to incorporate unexplained heterogeneity and resulted in a global incidence estimate of 0.31 [0.19; 0.50] symptomatic RV infections per personyear of observation for children below 2 years of age, and of 0.24 [0.17; 0.34] when excluding the extreme high value of 0.84 reported for Mayan Indians in Guatemala. Apart from the inclusion/exclusion of the latter study, results were robust. CONCLUSIONS/SIGNIFICANCE: Rather than assumptions based on an ad-hoc selection of one or two studies, these pooled estimates (together with the measure for variability between populations) should be used as an input in future cost-effectiveness analyses of RV vaccination.

Development of a quantitative microbial risk assessment for human salmonellosis through household consumption of fresh minced pork meat in Belgium.

A quantitative microbial risk assessment (QMRA) according to the Codex Alimentarius Principles is conducted to evaluate the risk of human salmonellosis through household consumption of fresh minced pork meat in Belgium. The quantitative exposure assessment is carried out by building a modular risk model, called the METZOON-model, which covers the pork production from farm to fork. In the METZOON-model, the food production pathway is split up in six consecutive modules: (1) primary production, (2) transport and lairage, (3) slaughterhouse, (4) postprocessing, (5) distribution and storage, and (6) preparation and consumption. All the modules are developed to resemble as closely as possible the Belgian situation, making use of the available national data. Several statistical refinements and improved modeling techniques are proposed. The model produces highly realistic results. The baseline predicted number of annual salmonellosis cases is 20,513 (SD 9061.45). The risk is estimated higher for the susceptible population (estimate 4.713 x 10(-5); SD 1.466 x 10(-5)) compared to the normal population (estimate 7.704 x 10(-6); SD 5.414 x 10(-6)) and is mainly due to undercooking and to a smaller extent to cross-contamination in the kitchen via cook's hands.

Common attitudes about concomitant vaccine injections for infants and adolescents in Flanders, Belgium.

Quantitative information on parents' preferences regarding multiple vaccine injections and on work-loss due to vaccination is important to guide decision making on the use of combination vaccines for universal vaccination. Our survey in families of 1347 toddlers (18 -- 24 months) and 1315 adolescents residing in Flanders, Belgium, revealed common attitudes in both age groups. The majority of parents would allow maximum two injections in one visit. 39% were not willing to pay anything to avoid a concomitant injection, whereas the remainder mentioned amounts around a median of c.20. The responses were hardly influenced by the socioeconomic determinants studied and the concordance between the number of concomitant injections parents would allow and their willingness-to-pay assessed by an open-ended question was limited, which suggests that more sensitive quantification using other methods would be useful. Work-loss due to vaccination was assessed for infants only and was rare (4.5%).

NUSAP method for evaluating the data quality in a quantitative microbial risk assessment model for Salmonella in the pork production chain.

The numeral unit spread assessment pedigree (NUSAP) system was implemented to evaluate the quality of input parameters in a quantitative microbial risk assessment (QMRA) model for Salmonella spp. in minced pork meat. The input parameters were grouped according to four successive exposure pathways: (1) primary production (2) transport, holding, and slaughterhouse, (3) postprocessing, distribution, and storage, and (4) preparation and consumption. An inventory of 101 potential input parameters was used for building the QMRA model. The characteristics of each parameter were defined using a standardized procedure to assess (1) the source of information, (2) the sampling methodology and sample size, and (3) the distributional properties of the estimate. Each parameter was scored by a panel of experts using a pedigree matrix containing four criteria (proxy, empirical basis, method, and validation) to assess the quality, and this was graphically represented by means of kite diagrams. The parameters obtained significantly lower scores for the validation criterion as compared with the other criteria. Overall strengths of parameters related to the primary production module were significantly stronger compared to the other modules (the transport, holding, and slaughterhouse module, the processing, distribution, and storage module, and the preparation and consumption module). The pedigree assessment contributed to select 20 parameters, which were subsequently introduced in the QMRA model. The NUSAP methodology and kite diagrams are objective tools to discuss and visualize the quality of the parameters in a structured way. These two tools can be used in the selection procedure of input parameters for a QMRA, and can lead to a more transparent quality assurance in the QMRA.

Caregivers' willingness to pay to reduce the number of vaccine injections in infants.

As part of a larger face-to-face immunization coverage survey, 1347 families of infants (18-24 months) were questioned on their willingness to pay for a reduction in the number of concomitant vaccine injections. The median willingness to pay for a reduction by 1 injection was 5 EUR. The responses fell into 3 broad categories (willing to pay nothing at all, or anything, or a finite amount) and were hardly influenced by socioeconomic determinants. These results suggest that more sophisticated methods are required, and similar analyses should exert a similar level of caution when presenting their results.

Model averaging in microbial risk assessment using fractional polynomials.

The alleviation of food-borne diseases caused by microbial pathogen remains a great concern in order to ensure the well-being of the general public. The relation between the ingested dose of organisms and the associated infection risk can be studied using dose-response models. Traditionally, a model selected according to a goodness-of-fit criterion has been used for making inferences. In this article, we propose a modified set of fractional polynomials as competitive dose-response models in risk assessment. The article not only shows instances where it is not obvious to single out one best model but also illustrates that model averaging can best circumvent this dilemma. The set of candidate models is chosen based on biological plausibility and rationale and the risk at a dose common to all these models estimated using the selected models and by averaging over all models using Akaike's weights. In addition to including parameter estimation inaccuracy, like in the case of a single selected model, model averaging accounts for the uncertainty arising from other competitive models. This leads to a better and more honest estimation of standard errors and construction of confidence intervals for risk estimates. The approach is illustrated for risk estimation at low dose levels based on Salmonella typhi and Campylobacter jejuni data sets in humans. Simulation studies indicate that model averaging has reduced bias, better precision, and also attains coverage probabilities that are closer to the 95% nominal level compared to best-fitting models according to Akaike information criterion.