Search

This study investigated the dynamics of SARS-CoV-2 infection and diagnostics in household members of different ages and with different symptom severity after SARS-CoV-2 exposure during the early phase of the pandemic. Households with a SARS-CoV-2 confirmed positive case and at least one child in the Netherlands were followed for 6 weeks. Naso (NP)- and oropharyngeal (OP) swabs, oral fluid and feces specimens were analyzed for SARS-CoV-2 RNA and serum for SARS-CoV-2-specific antibodies. The dynamics of the presence of viral RNA and the serological response was modeled to determine the sampling time-frame and sample type with the highest sensitivity to confirm or reject a SARS-CoV-2 diagnosis. Transmission of SARS-CoV-2 between adults and children within a household was correlated with symptom severity of index cases. In children higher viral loads compared to adults were detected at symptom onset. Early in infection, higher viral loads were detected in NP and OP specimens, while RNA in especially feces were longer detectable. SARS-CoV-2-specific antibodies have a 90% probability of detection from 7 days (total Ig) and 18 days (IgG) since symptom onset. In conclusion this study has shown that on average, children carry higher loads of virus as compared to adults early after infection. For highest probability of detection in SARS-CoV-2 diagnostics early in infection, RT-PCR on NP and OP specimens are more sensitive than on oral fluid and feces. For SARS-CoV-2 diagnostics late after infection, RT-PCR on feces specimens and serology are more valuable.

Trichinella spiralis and Trichinella britovi are species of nematodes which are responsible for the majority of Trichinella infections in the world and the most prevalent in Poland. The most abundant species – T. spiralis, is considered to be more genetically homogeneous in Europe than T. britovi. The aim of the present study was to determine the genetic variability in T. spiralis and T. britovi populations based on nuclear 5S rDNA intergenic spacer region (5S rDNA) and cytochrome c oxidase 1 (COX1) gene sequences. For the study, 55 isolates of T. spiralis and 50 isolates of T. britovi isolated from wild boars, pigs, brown rat and a red fox were analyzed. Based on the analysis of both genes, the genetic variability within populations of T. spiralis and T. britovi differed. In T. spiralis, two single nucleotide polymorphisms (SNPs) were observed in the 612 bp 5S rDNA gene fragment, and one SNP was detected in the 700 bp COX1 gene fragment. In T. britovi, 17 single nucleotide variations (SNVs) were detected in the 5S rDNA gene fragment (among them 16 SNPs), while COX1 sequence analysis revealed the occurrence of 20 SNVs between the sequences tested (among them 19 SNPs). For the majority of T. spiralis isolates the investigated larvae presented uniform haplotypes. In contrast, most of the isolates of T. britovi consisted of larvae of different haplotypes. Geographical analysis showed that each region exhibited different haplotype composition and richness. Warmińsko-Mazurskie and Zachodniopomorskie regions were the richest in haplotypes (15 and 16 haplotypes, respectively). We used heatmaps showing a characteristic pattern for each region graphically. This may allow to differentiate regions based on the occurrence of particular haplotypes. Furthermore, a PCA analysis on the SNP level yielded biplots that show that certain haplotypes/genotypes are associated with (clusters of) regions., Graphical abstract Image 1, Highlights • The genetic variability within the Polish T. britovi population is high. • 5S rDNA and COX1 variability in T. spiralis is low compared to T. britovi. • T. britovi variability may correlate to geographical origin. • Heatmap and PCA analysis could be helpful analytical tool for epidemiological investigations.

This study investigated the dynamics of SARS-CoV-2 infection and diagnostics in 242 household members of different ages and with different symptom severity after SARS-CoV-2 exposure early in the pandemic (March-April 2020). Households with a SARS-CoV-2 confirmed positive case and at least one child in the Netherlands were followed for 6 weeks. Naso (NP)- and oropharyngeal (OP) swabs, oral fluid and feces specimens were analyzed for SARS-CoV-2 RNA and serum for SARS-CoV-2-specific antibodies. The dynamics of the presence of viral RNA and the serological response was modeled to determine the sampling time-frame and sample type with the highest sensitivity to confirm or reject a SARS-CoV-2 diagnosis. In children higher viral loads compared to adults were detected at symptom onset. Early in infection, higher viral loads were detected in NP and OP specimens, while RNA in especially feces were longer detectable. SARS-CoV-2-specific antibodies have 90% probability of detection from 7 days (total Ig) and 18 days (IgG) since symptom onset. For highest probability of detection in SARS-CoV-2 diagnostics early in infection, RT-PCR on NP and OP specimens are more sensitive than on oral fluid and feces. For SARS-CoV-2 diagnostics late after infection, RT-PCR on feces specimens and serology are more valuable.

Background Trichinellosis is caused by consumption of raw or undercooked meat containing infective Trichinella muscle larvae (ML). Only few studies on heat-inactivation of Trichinella ML are available in literature and more validated data concerning heat inactivation is needed to improve the risk estimation. Objective and methods The aim of the present study was to evaluate the two in vitro methods “staining” and “morphological examination” as proxies for Trichinella ML heat inactivation in comparison with the mouse bioassay method to get more insight in the relationship between heat, heating time and inactivation of Trichinella ML. The second aim was to evaluate whether these methods could replace the bioassay in the light of ongoing animal use reduction in lifescience research. Tubes containing quantified live Trichinella ML were exposed to heat profiles ranging from 40 to 80 °C. Subsequently, inactivation was evaluated using both methylene blue staining and morphological examination, which was validated by bioassay. Results were used to model Trichinella inactivation. Results Trichinella muscle larvae exposed to 60 °C or higher for 12–12.5 min were not infective to mice. We found that morphological examination was more consistent with the bioassay than methylene blue staining. Modelled inactivation fitted experimental data consistently. Moreover, this study shows that larval Trichinella morphology may be used in situations where bioassays are not possible or prohibited. Conclusions The relationship between heat and inactivation of larvae obtained from this study could be used in Trichinella QMRA models to improve quantification of the risk of Trichinella infection.

A model for pork chain production The pig processing model is developed in WP2 (primary production) and WP 3.2 (the slaughter process, consumption phase). It is developed to closely link to WP6, where an evidence synthesis approach for combining QMRA and epidemiology in the context of ESBL in the pork chain is developed. The model chain is parametrized for the Netherlands. With approval of the RaDAR project lead, the dissemination mode of the current deliverable has been changed from scientific report to scientific article, thereby increasing dissemination value. Hence, full coverage of the model development for the slaughter phase, consumer phase, and dose-response will be discussed in detail in a forthcoming publication (Swart et al., in preparation). The exposition below should be considered a brief summary, highlighting the most prominent features. The full QMRA model consists of a farm model, a slaughter model, a consumption model, and a dose-response model, all to be discussed below.

Introduction This deliverable focusses on the potential for deriving or creating generic methods for exposure assessments for different production types, different bacteria, different processing etc.. These generic methods may be more crude, but will allow for combining the risks in the different (sub-)categories and may thus help to create a more complete picture of the AMR problems throughout. In order to study how one could go about developing a generic modelling approach for assessing exposure while taking into account different exposure pathways the following was done. Four in this project independently developed models for three different food chains were compared in a synoptic way identifying conceptual communalities which were then considered central parts of a possible generic exposure modelling approach. The three different food chains were the chicken, pork and seafood chain. Within the seafood chain, there are two models: a comparative exposure assessment model for various types of seafood (fish) and an exposure model focussed on steamed mussels. The models for each food chain have of course their own idiosyncrasies given the different concrete question they try to answer. However, there are still many conceptual communalities, which are useful to highlight in order to identify the generic elements of current state of the art exposure assessment models. This document goes about its analysis in two steps. In the first step, there is a description of each model for the three food chains. The descriptions are kept at a more general level in order to facilitate the identification of common elements for a generic exposure assessment model approach. Thus, the second step consists in a synoptic analysis of the four models with the focus on the issue of generic modelling framework for exposure assessment might look like.

Real-time reverse transcription-polymerase chain reaction (RT-PCR) on upper respiratory tract (URT) samples is the primary method to diagnose SARS-CoV-2 infections and guide public health measures, with a supportive role for serology. We reinforce previous findings on limited sensitivity of PCR testing, and solidify this fact by statistically utilizing a firm basis of multiple tests per individual. We integrate stratifications with respect to several patient characteristics such as severity of disease and time since onset of symptoms. Bayesian statistical modelling was used to retrospectively determine the sensitivity of RT-PCR using SARS-CoV-2 serology in 644 COVID-19-suspected patients with varying degrees of disease severity and duration. The sensitivity of RT-PCR ranged between 80% - 95%; increasing with disease severity, it decreased rapidly over time in mild COVID-19 cases. Negative URT RT-PCR results should be interpreted in the context of clinical characteristics, especially with regard to containment of viral transmission based on 'test, trace and isolate'. Keywords: SARS-CoV-2, RT-PCR, serology, sensitivity, public health.

Soil has been identified as an important source of exposure to a variety of chemical and biological contaminants. Toxoplasma gondii is one of those potential biological contaminants associated with serious health effects in pregnant women and immunocompromised patients. Gardening or consumption of homegrown vegetables may present an important route of T. gondii infection via accidental ingestion of soil. In the Netherlands, there is quantitative information on the risk of T. gondii infection via meat products, but not on the risk of infection through soil. The objective of this study was to develop a quantitative microbial risk assessment (QMRA) model for estimating the risk associated with T. gondii exposure via accidental soil ingestion in the Netherlands. In order to obtain the needed information, a magnetic capture method for detection of T. gondii oocysts in soil samples was developed, and T. gondii DNA was detected using qPCR targeting the 529 bp repeat element. The method was shown to provide 95% probability of detection (95% CI: 88–100%) when at least 34 oocysts are present in 25 g of soil. T. gondii DNA was detected in 5 of 148 soil samples with interpretable results (3%, 95% CI: 1.5–7.7%). Results for 18 samples were not interpretable due to PCR inhibition. The estimated amount of oocysts presented in qPCR positive samples was quantified by a linear model, and the amount varied from 8 to 478 in 25 g of soil. The estimated incidence rate of T. gondii infection from the QMRA model via soil varied from 0.3 to 1.8 per 1000 individuals per day. Several data gaps (e.g., soil contamination/ingestion and oocysts viability) have been identified in this study, the structure of the model can be applied to obtain more accurate estimates of the risk of T. gondii infection via soil when data become available.

We examined seroconversion rates by measuring IgG antibodies against Coxiella burnetii among two cohorts of veterinary students. During follow-up of 118 seronegative veterinary students, 23 students seroconverted. Although the clinical significance of the presence of antibodies is unknown, students should be informed about the potential risks of Q fever.

Real-time reverse transcription-polymerase chain reaction (RT-PCR) on upper respiratory tract (URT) samples is the primary method to diagnose SARS-CoV-2 infections and guide public health measures, with a supportive role for serology. However, the clinical sensitivity of RT-PCR remains uncertain. In the present study, Bayesian statistical modeling was used to retrospectively determine the sensitivity of RT-PCR using SARS-CoV-2 serology in 644 COVID-19-suspected patients with varying degrees of disease severity and duration. The sensitivity of RTPCR ranged between 79–95%; while increasing with disease severity, it decreased rapidly over time in mild COVID-19 cases. Negative URT RT-PCR results should therefore be interpreted in the context of clinical characteristics, especially with regard to containment of viral transmission based on the ‘test, trace and isolate’ principle.

BackgroundEvidence for indoor airborne transmission of SARS-CoV-2 is accumulating. If SARS-CoV-2 also spreads via aerosols, this has implications for measures taken to limit transmission.ObjectivesThe aim of this study is to assess exposure to airborne SARS-CoV-2 particles from breathing, speaking, coughing and sneezing in an indoor environment.MethodsAn exposure assessment model was developed to estimate numbers of SARS-CoV-2 particles in aerosol droplets, expelled during breathing, speaking, coughing and sneezing by an infected person in an unventilated indoor environment, and subsequent inhalation by one or more persons. Scenarios encompass a range of virus concentrations, room sizes and exposure times.ResultsThe calculated total volume of expelled aerosol droplets was highest for a sneeze, followed by a cough and speaking for 20 minutes, and lastly breathing for 20 minutes. A few to as much as tens of millions of virus particles were expelled. Exposure probability strongly depends on the viral concentration in mucus, as well as on the scenario. Exposure probabilities were generally below 1% at a virus concentration in mucus below 105 per mL for all scenarios, increasing steeply at different higher concentrations. According to nose / throat swab data collected from patients, 75%, 50% and 5% of infected individuals carry an estimated number of SARS-CoV-2 per mL mucus of at least 105, 106 and 108, respectively.DiscussionExposure to SARS-CoV-2 via aerosols generated during breathing, speaking, coughing and sneezing in an unventilated indoor environment is possible. This study forms a basis to estimate probabilities of exposure to SARS-Cov-2 by airborne transmission in indoor spaces. As long as it is uncertain what fraction of the airborne virus particles is infectious and as long as a dose response relation is lacking, it is recommended to be precautious.

Genome sequences provide information on the genetic elements present in an organism, and currently there are databases containing hundreds of thousands of bacterial genome sequences. These repositories allow for mining patterns concerning antibiotic resistance gene occurrence in both pathogenic and non-pathogenic bacteria in e.g. natural or animal environments, and link these to relevant metadata such as bacterial host species, country and year of isolation, and co-occurrence with other resistance genes. In addition, the advances in the prediction of mobile genetic elements, and discerning chromosomal from plasmid DNA, broadens our view on the mechanism mediating dissemination. In this study we utilize the vast amount of data in the public database PATRIC to investigate the dissemination of carbapenemase-encoding genes (CEGs), the emergence and spread of which is considered a grave public health concern. Based on publicly available genome sequences from PATRIC and manually curated CEG sequences from the beta lactam database, we found 7,964 bacterial genomes, belonging to at least 70 distinct species, that carry in total 9,892 CEGs, amongst which blaNDM, blaOXA, blaVIM, blaIMP and blaKPC. We were able to distinguish between chromosomally located resistance genes (4,137; 42%) and plasmid-located resistance genes (5,753; 58%). We found that a large proportion of the identified CEGs were identical, i.e. displayed 100% nucleotide similarity in multiple bacterial species (8,361 out of 9,892 genes; 85%). For example, the New Delhi metallo-beta-lactamase NDM-1 was found in 42 distinct bacterial species, and present in seven different environments. Our data show the extent of carbapenem-resistance far beyond the canonical species Acetinobacter baumannii, Klebsiella pneumoniae or Pseudomonas aeruginosa. These types of data complement previous systematic reviews, in which carbapenem-resistant Enterobacteriaceae were found in wildlife, livestock and companion animals. Considering the widespread distribution of CEGs, we see a need for comprehensive surveillance and transmission studies covering more host species and environments, akin to previous extensive surveys that focused on extended spectrum beta-lactamases. This may help to fully appreciate the spread of CEGs and improve the understanding of mechanisms underlying transmission, which could lead to interventions minimizing transmission to humans.

Between 2007 and 2010 a Q fever epidemic in Dutch dairy goat farms caused a large Q fever outbreak in human residents in the southern part of the Netherlands. Here we characterize the transmission of Coxiella burnetii, the aetiological agent of Q fever, between infected and susceptible dairy goat farms by estimating a spatial transmission kernel. In addition, we characterize the zoonotic transmission of C. burnetii by estimating the spatial kernel for transmission from infected farms to neighbouring residents. Whereas the range of between-farm transmission is comparable to the scale of the Netherlands, likely due to long-range between-farm contacts such as animal transport, the transmission risk from farms to humans is more localized, although still extending to 10 km and beyond. Within a range of about 10 km, the transmission risk from an infected goat farm to a single resident is of the same order of magnitude as the farm-to-farm transmission risk per animal in a receiving farm. We illustrate how, based on the estimated kernels, spatial patterns of transmission risks between farms and from farms to residents can be calculated and visualized by means of risk maps, offering further insight relevant to policy making in a one-health context.

The protozoan parasite Toxoplasma gondii can infect all warm-blooded animals and it causes the disease toxoplasmosis. Meat containing viable T. gondii tissue cysts is considered one of the main sources of human infection. The relative importance of the different types of meat depends, not only on the prevalence of T. gondii infection in the different livestock species, but also on consumed volumes and preparation habits. To take these factors into account and to estimate the relative contribution of different meat products to human infection, a quantitative risk assessment model for meat-borne T. gondii infection was previously developed. However, at the time, the effect of salting on parasite viability was estimated based on a single experiment. In recent years, data using salting methods that are more in line with processing of meat products have come available. Literature data on the effect of salting on T. gondii viability were collected and used to fit a predictive model. In addition to the new salting model, a lower concentration of bradyzoites in cattle, more specific heating profiles, and more recent consumption data were implemented in the QMRA model for meat-borne T. gondii infection in the Netherlands. Results show that beef remains the most important source, as it contributed 84% of the total number of predicted infections in the Dutch population, followed by pork (12%), mutton (3.7%), lamb (0.2%) pork/beef mixed products (0.1%), and veal (0.01%). The predicted number of T. gondii infections is reasonably in line with epidemiological data. At the product level, filet americain (a raw beef spread) alone contributed 80% of the total predicted infections in the base model, but scenario analyses demonstrate that its contribution is highly dependent on the salting parameters. A clear identification of the most risky meat products is important, as interventions focussing on these products could have a great impact on reducing T. gondii disease burden in the Netherlands. For that reason, it is important that the effects of salting and other processing methods are evaluated in line with industrial processing and incorporated in quantitative risk assessment models for meat-borne toxoplasmosis.

The socio-economic and demographic changes occurred over the past 50 years have dramatically expanded urban areas around the globe, thus bringing urban settlers in closer contact with nature. Ticks have trespassed the limits of forests and grasslands to start inhabiting green spaces within metropolitan areas. Hence, the transmission of pathogens causing tick-borne diseases is an important threat to public health. Using volunteered tick bite reports collected by two Dutch initiatives, here we present a method to model tick bite risk using human exposure and tick hazard predictors. Our method represents a step forward in risk modelling, since we combine a well-known ensemble learning method, Random Forest, with four count data models of the (zero-inflated) Poisson family. This combination allows us to better model the disproportions inherent in the volunteered tick bite reports.Unlike canonical machine learning models, our method can capture the overdispersion or zero-inflation inherent in data, thus yielding tick bite risk predictions that resemble the original signal captured by volunteers. Mapping model predictions enables a visual inspection of the spatial patterns of tick bite risk in the Netherlands. The Veluwe national park and the Utrechtse Heuvelrug forest, which are large forest-urban interfaces with several cities, are areas with high tick bite risk. This is expected, since these are popular places for recreation and tick activity is high in forests. However, our model can also predict high risk in less-intensively visited recreational areas, such as the patchy forests in the northeast of the country, the natural areas along the coastline, or some of the Frisian Islands. Our model could help public health specialists to design mitigation strategies for tick-borne diseases, and to target risky areas with awareness and prevention campaigns.

Toxoplasma gondii, a protozoan zoonotic parasite, has a worldwide distribution. It can cause severe pathological damage to the fetus in primary infected pregnant women and life-threatening encephalitis in immunocompromised patients. One of the main transmission routes to humans is consumption of raw or undercooked meat containing viable T. gondii tissue cysts. In China, the lack of quantitative information on the risk and incidence of infection due to consumption of meat hampers the development of prevention strategies to reduce the burden of toxoplasmosis. The aim of this study was to set up a quantitative microbial risk assessment (QMRA) model to estimate the relative attribution of different types of meat (i.e., pork, beef, lamb and mutton, chicken and duck) to human T. gondii infections in China. The model was built based on the structure of the first meat-borne T. gondii infection QMRA model developed in the Netherlands and applied for seven regions of mainland China. Data on the prevalence of T. gondii in livestock and consumption were obtained from China, however information on preparation habits was lacking. Consumption data were available as average consumption amounts per day collected over three days. The results calculated from the QMRA model were at least thousand-fold higher compared to the incidence rate obtained from an epidemiological susceptible-infected (SI) type model. In general, pork and chicken meat contributed more to the estimated number of infections than beef, small ruminant and duck meat. Cooking temperature was identified as one of the parameters that most strongly affected the estimated incidence rate in the QMRA model. Sensitivity analysis showed that the estimated incidence rate from the QMRA model would be comparable to the results obtained from the SI model if final cooking temperatures are around 1.7 times higher than the temperatures based on a dataset for American consumers. Scenario analysis demonstrated that it is important to know portion size and frequency of consumption in addition to total consumed amounts to calculate incidence of infection. Due to uncertainties present in the input data and the at least thousand-fold overestimated incidence rates, the results merely give an indication of the relative importance of different types of meat. However, the QMRA model clearly identified the key knowledge gaps for future research and can subsequently support cost-effective decisions to reduce the disease burden of human toxoplasmosis.

The most recent IPCC report presented further scientific evidence for global climate change in the twenty-first century. Important secondary effects of climate change include those on water resource availability, agricultural yields, urban healthy living, biodiversity, ecosystems, food security, and public health. The aim of this explorative study was to determine the range of expected airborne pathogen concentrations during a single outbreak or release in a future climate compared to a historical climatic period (1981-2010). We used five climate scenarios for the periods 2016-2045 and 2036-2065 defined by the Royal Netherlands Meteorological Institute and two conversion tools to create hourly future meteorological data sets. We modelled season-averaged airborne pathogen concentrations by means of an atmospheric dispersion model and compared these data to historical (1981-2010) modelled concentrations. Our results showed that modelled concentrations were modified several percentage points on average as a result of climate change. On average, concentrations were reduced in four out of five scenarios. Wind speed and global radiation were of critical importance, which determine horizontal and vertical dilution. Modelled concentrations decreased on average, but large positive and negative hourly averaged effects were calculated (from -67 to +639 %). This explorative study shows that further research should include pathogen inactivation and more detailed probability functions on precipitation, snow, and large-scale circulation.

A farm-to-consumption quantitative microbiological risk assessment (QMRA) for Salmonella in pigs in the European Union has been developed for the European Food Safety Authority. The primary aim of the QMRA was to assess the impact of hypothetical reductions of slaughter-pig prevalence and the impact of control measures on the risk of human Salmonella infection. A key consideration during the QMRA development was the characterization of variability between E.U. Member States (MSs), and therefore a generic MS model was developed that accounts for differences in pig production, slaughterhouse practices, and consumption patterns. To demonstrate the parameterization of the model, four case study MSs were selected that illustrate the variability in production of pork meat and products across MSs. For the case study MSs the average probability of illness was estimated to be between 1 in 100,000 and 1 in 10 million servings given consumption of one of the three product types considered (pork cuts, minced meat, and fermented ready-to-eat sausages). Further analyses of the farm-to-consumption QMRA suggest that the vast majority of human risk derives from infected pigs with a high concentration of Salmonella in their feces (≥10(4) CFU/g). Therefore, it is concluded that interventions should be focused on either decreasing the level of Salmonella in the feces of infected pigs, the introduction of a control step at the abattoir to reduce the transfer of feces to the exterior of the pig, or a control step to reduce the level of Salmonella on the carcass post-evisceration.

As part of the evidence base for the development of national control plans for Salmonella spp. in pigs for E.U. Member States, a quantitative microbiological risk assessment was funded to support the scientific opinion required by the EC from the European Food Safety Authority. The main aim of the risk assessment was to assess the effectiveness of interventions implemented on-farm and at the abattoir in reducing human cases of pig meat-borne salmonellosis, and how the effects of these interventions may vary across E.U. Member States. Two case study Member States have been chosen to assess the effect of the interventions investigated. Reducing both breeding herd and slaughter pig prevalence were effective in achieving reductions in the number of expected human illnesses in both case study Member States. However, there is scarce evidence to suggest which specific on-farm interventions could achieve consistent reductions in either breeding herd or slaughter pig prevalence. Hypothetical reductions in feed contamination rates were important in reducing slaughter pig prevalence for the case study Member State where prevalence of infection was already low, but not for the high-prevalence case study. The most significant reductions were achieved by a 1- or 2-log decrease of Salmonella contamination of the carcass post-evisceration; a 1-log decrease in average contamination produced a 90% reduction in human illness. The intervention analyses suggest that abattoir intervention may be the most effective way to reduce human exposure to Salmonella spp. However, a combined farm/abattoir approach would likely have cumulative benefits. On-farm intervention is probably most effective at the breeding-herd level for high-prevalence Member States; once infection in the breeding herd has been reduced to a low enough level, then feed and biosecurity measures would become increasingly more effective.

In this article we present a model for Salmonella contamination of pig carcasses in the slaughterhouse. This model forms part of a larger QMRA (quantitative microbial risk assessment) on Salmonella in slaughter and breeder pigs, which uses a generic model framework that can be parameterized for European member states, to describe the entire chain from farm-to-consumption and the resultant human illness. We focus on model construction, giving mathematical formulae to describe Salmonella concentrations on individual pigs and slaughter equipment at different stages of the slaughter process. Variability among individual pigs and over slaughterhouses is incorporated using statistical distributions, and simulated by Monte Carlo iteration. We present the results over the various slaughter stages and show that such a framework is especially suitable to investigate the effect of various interventions. In this article we present the results of the slaughterhouse module for two case study member states. The model outcome represents an increase in average prevalence of Salmonella contamination and Salmonella numbers at dehairing and a decrease of Salmonella numbers at scalding. These results show good agreement when compared to several other QMRAs and microbiological studies.

In response to the European Food Safety Authority's wish to assess the reduction of human cases of salmonellosis by implementing control measures at different points in the farm-to-consumption chain for pork products, a quantitative microbiological risk assessment (QMRA) was developed. The model simulated the occurrence of Salmonella from the farm to consumption of pork cuts, minced meat, and fermented ready-to-eat sausage, respectively, and a dose-response model was used to estimate the probability of illness at consumption. The QMRA has a generic structure with a defined set of variables, whose values are changed according to the E.U. member state (MS) of interest. In this article we demonstrate the use of the QMRA in four MSs, representing different types of countries. The predicted probability of illness from the QMRA was between 1 in 100,000 and 1 in 10 million per serving across all three product types. Fermented ready-to-eat sausage imposed the highest probability of illness per serving in all countries, whereas the risks per serving of minced meat and pork chops were similar within each MS. For each of the products, the risk varied by a factor of 100 between the four MSs. The influence of lack of information for different variables was assessed by rerunning the model with alternative, more extreme, values. Out of the large number of uncertain variables, only a few of them have a strong influence on the probability of illness, in particular those describing the preparation at home and consumption.

The performance of a 400-μm-mesh-size sieve (sieve400) has not previously been compared with that of a 180-μm-mesh-size sieve (sieve180). Using pork samples spiked with 0 to 10 Trichinella muscle larvae and an artificial digestion method, sieve performance was evaluated for control of Trichinella in meat-producing animals. The use of a sieve400 resulted in 12% lower larval counts, 147% more debris, and 28% longer counting times compared with the use of a sieve180. Although no false-negative results were obtained, prolonged counting times with the sieve400 may have an impact on performance in a high-throughput environment such as a slaughterhouse laboratory. Based on our results, the sieve180 remains the sieve of choice for Trichinella control in meat in slaughterhouse laboratories, according to the European Union reference method (European Commission regulation 2075/2005). Furthermore, the results of the present study contribute to the discussion of harmonization of meat inspection requirements among countries.

Highlights • We reviewed studies on atmospheric dispersion modelling of pathogenic bioaerosols with a special focus on risk assessment. • The type of model depends on the spatial scale, the complexity, and the preference for forward or backward analysis. • A major drawback of many studies was the lack of quantitative analyses. • We recommend including quantified emission and inactivation rates and a dosimetry and dose-response model in ADM studies., In this review we discuss studies that applied atmospheric dispersion models (ADM) to bioaerosols that are pathogenic to humans and livestock in the context of risk assessment studies. Traditionally, ADMs have been developed to describe the atmospheric transport of chemical pollutants, radioactive matter, dust, and particulate matter. However, they have also enabled researchers to simulate bioaerosol dispersion. To inform risk assessment, the aims of this review were fourfold, namely (1) to describe the most important physical processes related to ADMs and pathogen transport, (2) to discuss studies that focused on the application of ADMs to pathogenic bioaerosols, (3) to discuss emission and inactivation rate parameterisations, and (4) to discuss methods for conversion of concentrations to infection probabilities (concerning quantitative microbial risk assessment). The studies included human, livestock, and industrial sources. Important factors for dispersion included wind speed, atmospheric stability, topographic effects, and deposition. Inactivation was mainly governed by humidity, temperature, and ultraviolet radiation. A majority of the reviewed studies, however, lacked quantitative analyses and application of full quantitative microbial risk assessments (QMRA). Qualitative conclusions based on geographical dispersion maps and threshold doses were encountered frequently. Thus, to improve risk assessment for future outbreaks and releases, we recommended determining well-quantified emission and inactivation rates and applying dosimetry and dose–response models to estimate infection probabilities in the population at risk.

Data from a set of different studies on the infectivity and pathogenicity of Campylobacter jejuni were analyzed with a multilevel model, allowing for effects of host species (nonhuman primates and humans) and different strains of the pathogen.All challenge studies involved high doses of the pathogen, resulting in all exposed subjects to become infected. In only one study a dose response effect (increasing trend with dose) for infection was observed. High susceptibility to infection with C. jejuni was found in a joint analysis of outbreaks and challenge studies. For that reason four outbreaks, associated with raw milk consumption, were also included in the present study.The high doses used for inoculation did not cause all infected subjects to develop acute enteric symptoms. The observed outcomes are consistent with a dose response effect for acute symptoms among infected subjects: a conditional illness dose response relation. Nonhuman primates and human volunteers did not appear to have different susceptibilities for developing enteric symptoms, but exposure in outbreaks (raw milk) did lead to a higher probability of symptomatic campylobacteriosis. Keywords: Campylobacter jejuni, Hierarchical dose response, Natural experiments, Challenge studies, Infectivity

Background: Brown rats (Rattus norvegicus) may carry pathogens that can be a risk for public health. Brown rats in the Netherlands were tested for the zoonotic pathogens Leptospira spp. and Seoul hantavirus (SEOV), in order to obtain insight in their prevalence. Methods and results: Cross-sectional studies were performed at four locations from 2011 to 2015. The rats were tested for Leptospira spp. using real-time PCR and/or culture resulting in a prevalence ranging between 33–57%. Testing for SEOV was done through an adapted human Seoul hantavirus ELISA and real-time RT-PCR. Although at several locations the ELISA indicated presence of SEOV antibodies, none could be confirmed by focus reduction neutralization testing. Conclusion: The results indicate a widespread presence of Leptospira spp. in brown rats in the Netherlands, including areas with a low leptospirosis incidence in humans. No evidence for circulation of SEOV was found in this study.

Background: Brown rats (Rattus norvegicus) may carry pathogens that can be a risk for public health. Brown rats in the Netherlands were tested for the zoonotic pathogens Leptospira spp. and Seoul hantavirus (SEOV), in order to obtain insight in their prevalence. Methods and results: Cross-sectional studies were performed at four locations from 2011 to 2015. The rats were tested for Leptospira spp. using real-time PCR and/or culture resulting in a prevalence ranging between 33–57%. Testing for SEOV was done through an adapted human Seoul hantavirus ELISA and real-time RT-PCR. Although at several locations the ELISA indicated presence of SEOV antibodies, none could be confirmed by focus reduction neutralization testing. Conclusion: The results indicate a widespread presence of Leptospira spp. in brown rats in the Netherlands, including areas with a low leptospirosis incidence in humans. No evidence for circulation of SEOV was found in this study.

To estimate the exposure of local residents to substances emitted by livestock farms, we applied a dispersion model to calculate the air concentrations in the surroundings following from these emissions. At several livestock farms, indoor air measurements were performed to determine emission strengths, while ambient measurements were carried out to compare with model results. Measured substances were particulate matter (PM), endotoxins and micro-organisms. The dispersion model only simulated PM concentrations, which were used as a proxy to determine the dispersion concentrations of endotoxins and micro-organisms. For the living micro-organisms, the process of inactivation has to be taken into account. Here we describe the followed methodology and preliminary results.

In dit artikel beschrijven we een eerste aanzet gegeven tot een kwantitatief microbieel ­verspreidingsmodel. Dit moet een onderdeel gaan vormen van een modelketen die leidt tot een risicobeoordelingsmodel voor de volksgezondheidseffecten van endotoxinen uit de landbouw.