MILK Symposium review: Foodborne diseases from milk and milk products in developing countries-Review of causes and health and economic implications.

Dairy production is rapidly increasing in developing countries and making significant contributions to health, nutrition, environments, and livelihoods, with the potential for still greater contributions. However, dairy products can also contribute to human disease in many ways, with dairyborne disease likely being the most important. Health risks may be from biological, chemical, physical, or allergenic hazards present in milk and other dairy products. Lacking rigorous evidence on the full burden of foodborne and dairyborne disease in developing countries, we compiled information from different sources to improve our estimates. The most credible evidence on dairyborne disease comes from the World Health Organization initiative on the Global Burden of Foodborne Disease. This suggests that dairy products may has been responsible for 20 disability-adjusted life years per 100,000 people in 2010. This corresponds to around 4% of the global foodborne disease burden and 12% of the animal source food disease burden. Most of this burden falls on low- and middle-income countries (LMIC). However, the estimate is conservative. Weaker evidence from historical burden in high-income countries, outbreak reports from LMIC and high-income countries, and quantitative microbial risk assessment suggest that the real burden may be higher. The economic burden in terms of lost human capital is at least US$4 billion/yr in LMIC. Among the most important hazards are Mycobacterium bovis, Campylobacter spp., and non-typhoidal Salmonella enterica. The known burden of chemical hazards is lower but also more uncertain. Important chemical hazards are mycotoxins, dioxins, and heavy metals. Some interventions have been shown to have unintended and unwanted consequences, so formative research and rigorous evaluation should accompany interventions. For example, there are many documented cases in which women's control over livestock is diminished with increasing commercialization. Dairy co-operatives have had mixed success, often incurring governance and institutional challenges. More recently, there has been interest in working with the informal sector. New technologies offer new opportunities for sustainable dairy development.

Climate change effects on airborne pathogenic bioaerosol concentrations: a scenario analysis.

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.

Comorbidities and factors associated with central nervous system infections and death in non-perinatal listeriosis: a clinical case series.

BACKGROUND: Listeriosis is a rare disease caused by the bacterium Listeria monocytogenes and mainly affects at risk people. Listeriosis can lead to sepsis, central nervous system (CNS) infections and death. The objectives of this study were to describe and quantify comorbidities and neurological sequelae underlying non-perinatal listeriosis cases and to describe the factors associated with death and CNS infections in non-perinatal listeriosis. METHODS: We retrospectively collected clinical data through computerized, paper or microfilmed medical records in two Belgian university hospitals. Logistic regression models and likelihood ratio tests allowed identifying factors associated with death and CNS infections. RESULTS: Sixty-four cases of non-perinatal listeriosis were included in the clinical case series and 84 % were affected by at least one comorbid condition. The main comorbidities were cancer, renal and severe cardio-vascular diseases. Twenty-nine patients (45 %) suffered from a CNS infection and 14 patients (22 %) died during hospitalization, among whom six (43 %) had a CNS involvement. Among surviving patients, eleven suffered from neurological sequelae (22 %) at hospital discharge; all had CNS infection. Five of these patients (45 %) still suffered of their neurological sequelae after a median follow-up of one year (range: 0.08-19). The factor associated with death during the hospitalization was the presence of a severe cardiovascular disease (OR = 4.72, p = 0.015). Two factors inversely related with CNS infections were antibiotic monotherapy (OR = 0.28, p = 0.04) and the presence of renal disease (OR = 0.18, p = 0.02). CONCLUSIONS: In a public health context these results could be a starting point for future burden of listeriosis studies taking into account comorbidity.

Evaluation of a Performance-Based Expert Elicitation: WHO Global Attribution of Foodborne Diseases.

For many societally important science-based decisions, data are inadequate, unreliable or non-existent, and expert advice is sought. In such cases, procedures for eliciting structured expert judgments (SEJ) are increasingly used. This raises questions regarding validity and reproducibility. This paper presents new findings from a large-scale international SEJ study intended to estimate the global burden of foodborne disease on behalf of WHO. The study involved 72 experts distributed over 134 expert panels, with panels comprising thirteen experts on average. Elicitations were conducted in five languages. Performance-based weighted solutions for target questions of interest were formed for each panel. These weights were based on individual expert's statistical accuracy and informativeness, determined using between ten and fifteen calibration variables from the experts' field with known values. Equal weights combinations were also calculated. The main conclusions on expert performance are: (1) SEJ does provide a science-based method for attribution of the global burden of foodborne diseases; (2) equal weighting of experts per panel increased statistical accuracy to acceptable levels, but at the cost of informativeness; (3) performance-based weighting increased informativeness, while retaining accuracy; (4) due to study constraints individual experts' accuracies were generally lower than in other SEJ studies, and (5) there was a negative correlation between experts' informativeness and statistical accuracy which attenuated as accuracy improved, revealing that the least accurate experts drive the negative correlation. It is shown, however, that performance-based weighting has the ability to yield statistically accurate and informative combinations of experts' judgments, thereby offsetting this contrary influence. The present findings suggest that application of SEJ on a large scale is feasible, and motivate the development of enhanced training and tools for remote elicitation of multiple, internationally-dispersed panels.

Human Q fever incidence is associated to spatiotemporal environmental conditions.

Airborne pathogenic transmission from sources to humans is characterised by atmospheric dispersion and influence of environmental conditions on deposition and reaerosolisation. We applied a One Health approach using human, veterinary and environmental data regarding the 2009 epidemic in The Netherlands, and investigated whether observed human Q fever incidence rates were correlated to environmental risk factors. We identified 158 putative sources (dairy goat and sheep farms) and included 2339 human cases. We performed a high-resolution (1 × 1 km) zero-inflated regression analysis to predict incidence rates by Coxiella burnetii concentration (using an atmospheric dispersion model and meteorological data), and environmental factors - including vegetation density, soil moisture, soil erosion sensitivity, and land use data - at a yearly and monthly time-resolution. With respect to the annual data, airborne concentration was the most important predictor variable (positively correlated to incidence rate), followed by vegetation density (negatively). The other variables were also important, but to a less extent. High erosion sensitive soils and the land-use fractions "city" and "forest" were positively correlated. Soil moisture and land-use "open nature" were negatively associated. The geographical prediction map identified the largest Q fever outbreak areas. The hazard map identified highest hazards in a livestock dense area. We conclude that environmental conditions are correlated to human Q fever incidence rate. Similar research with data from other outbreaks would be needed to more firmly establish our findings. This could lead to better estimations of the public health risk of a C. burnetii outbreak, and to more detailed and accurate hazard maps that could be used for spatial planning of livestock operations.

Atmospheric dispersion modelling of bioaerosols that are pathogenic to humans and livestock - A review to inform risk assessment 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.

Potential association between the recent increase in campylobacteriosis incidence in the Netherlands and proton-pump inhibitor use - an ecological study.

The Netherlands saw an unexplained increase in campylobacteriosis incidence between 2003 and 2011, following a period of continuous decrease. We conducted an ecological study and found a statistical association between campylobacteriosis incidence and the annual number of prescriptions for proton pump inhibitors (PPIs), controlling for the patient's age, fresh and frozen chicken purchases (with or without correction for campylobacter prevalence in fresh poultry meat). The effect of PPIs was larger in the young than in the elderly. However, the counterfactual population-attributable fraction for PPIs was largest for the elderly (ca 45% in 2011) and increased at population level from 8% in 2004 to 27% in 2011. Using the regression model and updated covariate values, we predicted a trend break for 2012, largely due to a decreased number of PPI prescriptions, that was subsequently confirmed by surveillance data. Although causality was not shown, the biological mechanism, age effect and trend-break prediction suggest a substantial impact of PPI use on campylobacteriosis incidence in the Netherlands. We chose the ecological study design to pilot whether it is worthwhile to further pursue the effect of PPI on campylobacteriosis and other gastrointestinal pathogens in prospective cohort studies. We now provide strong arguments to do so.

Impact of acquired immunity and dose-dependent probability of illness on quantitative microbial risk assessment.

Dose-response models in microbial risk assessment consider two steps in the process ultimately leading to illness: from exposure to (asymptomatic) infection, and from infection to (symptomatic) illness. Most data and theoretical approaches are available for the exposure-infection step; the infection-illness step has received less attention. Furthermore, current microbial risk assessment models do not account for acquired immunity. These limitations may lead to biased risk estimates. We consider effects of both dose dependency of the conditional probability of illness given infection, and acquired immunity to risk estimates, and demonstrate their effects in a case study on exposure to Campylobacter jejuni. To account for acquired immunity in risk estimates, an inflation factor is proposed. The inflation factor depends on the relative rates of loss of protection over exposure. The conditional probability of illness given infection is based on a previously published model, accounting for the within-host dynamics of illness. We find that at low (average) doses, the infection-illness model has the greatest impact on risk estimates, whereas at higher (average) doses and/or increased exposure frequencies, the acquired immunity model has the greatest impact. The proposed models are strongly nonlinear, and reducing exposure is not expected to lead to a proportional decrease in risk and, under certain conditions, may even lead to an increase in risk. The impact of different dose-response models on risk estimates is particularly pronounced when introducing heterogeneity in the population exposure distribution.

Quantifying the sources of Salmonella on dressed carcasses of pigs based on serovar distribution.

Salmonella serotyping data, qualitatively described by van Hoek et al. (2012), were used to quantify potential sources of Salmonella in a Dutch pig slaughterhouse. Statistical tests to compare per-day Salmonella prevalence and serotyping data from multiple points in the chain were used to find transmission pathways. A statistical model based on serotyping data was developed to attribute Salmonella on dressed carcasses to the most likely source. Approximately two-third of dressed carcasses carrying Salmonella on the medial surface had been contaminated by house flora. For carcasses carrying Salmonella on the distal surface, transient Salmonella from incoming pigs was a more important source. The relevance of the different sources of Salmonella varied within and between sampling days. Results were compared to those of another modeling approach, in which Salmonella concentration data from the same samples were used (Smid et al., 2012). They mostly agreed. The approach chosen by an individual slaughterhouse depends on the data that are collected.

Campylobacteriosis in returning travellers and potential secondary transmission of exotic strains.

SUMMARY: Multilocus sequence types (STs) were determined for 232 and 737 Campylobacter jejuni/coli isolates from Dutch travellers and domestically acquired cases, respectively. Putative risk factors for travel-related campylobacteriosis, and for domestically acquired campylobacteriosis caused by exotic STs (putatively carried by returning travellers), were investigated. Travelling to Asia, Africa, Latin America and the Caribbean, and Southern Europe significantly increased the risk of acquiring campylobacteriosis compared to travelling within Western Europe. Besides eating chicken, using antacids, and having chronic enteropathies, we identified eating vegetable salad outside Europe, drinking bottled water in high-risk destinations, and handling/eating undercooked pork as possible risk factors for travel-related campylobacteriosis. Factors associated with domestically acquired campylobacteriosis caused by exotic STs involved predominantly person-to-person contacts around popular holiday periods. We concluded that putative determinants of travel-related campylobacteriosis differ from those of domestically acquired infections and that returning travellers may carry several exotic strains that might subsequently spread to domestic populations even through limited person-to-person transmission.

Attribution of human Salmonella infections to animal and food sources in Italy (2002-2010): adaptations of the Dutch and modified Hald source attribution models.

The Dutch and modified Hald source attribution models were adapted to Italian Salmonella data to attribute human infections caused by the top 30 serotypes between 2002 and 2010 to four putative sources (Gallus gallus, turkeys, pigs, ruminants), at the points of animal reservoir (farm), exposure (food), and both combined. Attribution estimates were thus compared between different models, time periods and sampling points. All models identified pigs as the main source of human salmonellosis in Italy, accounting for 43-60% of infections, followed by G. gallus (18-34%). Attributions to turkeys and ruminants were minor. An increasing temporal trend in attributions to pigs and a decreasing one in those to G. gallus was also observed. Although the outcomes of the two models applied at farm and food levels essentially agree, they can be refined once more information becomes available, providing valuable insights about potential targets along the production chain.

Relative risk of irritable bowel syndrome following acute gastroenteritis and associated risk factors.

SUMMARY: A prospective cohort study using electronic medical records was undertaken to estimate the relative risk (RR) of irritable bowel syndrome (IBS) following acute gastroenteritis (GE) in primary-care patients in The Netherlands and explore risk factors. Patients aged 18-70 years who consulted for GE symptoms from 1998 to 2009, met inclusion/exclusion criteria and had at least 1 year of follow-up data were included. Patients with non-GE consultations, matched by age, gender, consulting practice and time of visit, served as the reference group. At 1 year, 1·2% of GE patients (N = 2428) had been diagnosed with IBS compared to 0·3% of the reference group (N = 2354). GE patients had increased risk of IBS [RR 4·85, 95% confidence interval (CI) 2·02-11·63]. For GE patients, concomitant cramps and history of psycho-social consultations were significantly associated with increased risk. GE patients had increased risk of IBS up to 5 years post-exposure (RR 5·40, 95% CI 2·60-11·24), suggesting there may be other contributing factors.

Increased risk for Campylobacter jejuni and C. coli infection of pet origin in dog owners and evidence for genetic association between strains causing infection in humans and their pets.

We compared Campylobacter jejuni/coli multilocus sequence types (STs) from pets (dogs/cats) and their owners and investigated risk factors for pet-associated human campylobacteriosis using a combined source-attribution and case-control analysis. In total, 132/687 pet stools were Campylobacter-positive, resulting in 499 strains isolated (320 C. upsaliensis/helveticus, 100 C. jejuni, 33 C. hyointestinalis/fetus, 10 C. lari, 4 C. coli, 32 unidentified). There were 737 human and 104 pet C. jejuni/coli strains assigned to 154 and 49 STs, respectively. Dog, particularly puppy, owners were at increased risk of infection with pet-associated STs. In 2/68 cases vs. 0.134/68 expected by chance, a pet and its owner were infected with an identical ST (ST45, ST658). Although common sources of infection and directionality of transmission between pets and humans were unknown, dog ownership significantly increased the risk for pet-associated human C. jejuni/coli infection and isolation of identical strains in humans and their pets occurred significantly more often than expected.

Estimating the true incidence of campylobacteriosis and salmonellosis in the European Union, 2009.

We estimated the true incidence of campylobacteriosis and salmonellosis in the European Union (EU) in 2009. The estimate was based on disease risks of returning Swedish travellers, averaged over the years 2005-2009, and anchored to a Dutch population-based study on incidence and aetiology of gastroenteritis. For the 27 EU member states the incidence of campylobacteriosis was about 9·2 (95% CI 2·8-23) million cases, while the incidence of salmonellosis was 6·2 (95% CI 1·0-19) million cases. Only 1/47 (95% CI 14-117) cases of campylobacteriosis and one 1/58 (95% CI 9-172) cases of salmonellosis were reported in the EU. The incidence rate of campylobacteriosis in EU member states varied between 30 and 13 500/100 000 population and was significantly correlated with the prevalence of Campylobacter spp. in broiler chickens. The incidence rate of salmonellosis in EU member states varied between 16 and 11 800/100 000 population and was significantly correlated with the prevalence of Salmonella Enteritidis in laying hens.

Community incidence of pathogen-specific gastroenteritis: reconstructing the surveillance pyramid for seven pathogens in seven European Union member states.

By building reconstruction models for a case of gastroenteritis in the general population moving through different steps of the surveillance pyramid we estimated that millions of illnesses occur annually in the European population, leading to thousands of hospitalizations. We used data on the healthcare system in seven European Union member states in relation to pathogen characteristics that influence healthcare seeking. Data on healthcare usage were obtained by harmonized cross-sectional surveys. The degree of under-diagnosis and underreporting varied by pathogen and country. Overall, underreporting and under-diagnosis were estimated to be lowest for Germany and Sweden, followed by Denmark, The Netherlands, UK, Italy and Poland. Across all countries, the incidence rate was highest for Campylobacter spp. and Salmonella spp. Incidence estimates resulting from the pyramid reconstruction approach are adjusted for biases due to different surveillance systems and are therefore a better basis for international comparisons than reported data.

The protective effects of temporary immunity under imposed infection pressure.

The aim of this paper is to show in explicit detail that, due to the effects of waning and boosting of immunity, an increasing force of infection does not necessarily lead to an increase in the incidence of disease. Under certain conditions, a decrease of the force of infection may in fact lead to an increase of the incidence of disease. Thus we confirm and reinforce the conclusions from Águas et al. (2006), concerning pertussis. We do so, however, in the context of Campylobacter infections in humans deriving from animal reservoirs. For such an externally 'driven' epidemic we can ignore the transmission feedback cycle and treat the force of infection as a parameter. As this parameter is, to a certain extent, under public health control, our findings constitute an important warning: reducing exposure may not necessarily lead to a reduction in the occurrence of clinical illness. In a second part of the paper we relate the model parameters to the available data concerning campylobacteriosis.

A biotracing model of Salmonella in the pork production chain.

In biotracing systems, downstream chain information and model-based approaches are used to trace the sources of microbial contamination in a food chain. This article includes the results of a biotracing model for Salmonella in the pork slaughter process chain. A Bayesian belief network model was used in which information on the Salmonella level at different locations in the slaughterhouse were used in combination with prior knowledge about the dynamics of Salmonella throughout the slaughter line. Data collected in a Dutch slaughterhouse were used to specify prior beliefs about the model inputs and to iteratively refine the distributions of the parameters in the model to obtain an optimal description of that specific slaughterhouse. The primary purpose of the model is to trace the sources of contamination for individual Salmonella-positive carcasses at the end of the slaughter line. The model results indicated that house flora on or in the carcass splitter was the source of contamination for many carcasses, especially for those that carried contamination on the cutting side. The results also indicated that the parameter values of the model may be subject to temporal variation and can be used as a tool to provide estimates of such trends. This model illustrates the concept of biotracing, gives insight into the dynamics of Salmonella in the slaughter line, and indicates the sites in the line where data collection is most effective for biotracing. This biotracing model was implemented as an interactive computer application, which is a step in the process toward an operational biotracing system by which a stakeholder can initiate immediate responses to Salmonella contamination and other hazards in the pork slaughterhouse.

The burden of infectious intestinal disease (IID) in the community: a survey of self-reported IID in The Netherlands.

In 2009, a 1-year retrospective survey was performed in The Netherlands to estimate the incidence and the disease burden of infectious intestinal disease (IID) in the community, to study the selection of patients consulting a general practitioner and to identify potential risk factors for IID in the community. A questionnaire was sent to 6000 persons selected at random from the population registries of 28 municipalities, with 500 persons being approached per month. A total of 1975 (33%) persons participated. The incidence rate of IID was 964/1000 person-years. Potential risk factors associated with IID in the community were young age (0-4 years) [odds ratio (OR) 3.9, 95% confidence interval (CI) 1.5-10.5], having asthma as a child (OR 3.4, 95% CI 1.1-10.3) and use of gastric acid suppressive medication by persons aged ≥ 45 years (OR 2.8, 95% CI 1.4-5.6). Of the 146 cases with IID, 11 (8%) consulted a physician. Cases with a long duration of symptoms, blood in the stool, children with IID and cases with a low level of education were more likely to consult a physician. Two cases had a stool sample taken and one was admitted to hospital. In conclusion, IID is common and has a significant burden of illness in The Netherlands. Our data indicate that about 15.9 million episodes of IID occur in The Netherlands per year. The incidence rate is substantially higher than the rate of 283/1000 person-years as estimated in 1999 in The Netherlands. This is probably largely due to the retrospective nature of the present study and, to a lesser extent, to differences in case definitions.

A practical framework for the construction of a biotracing model: application to Salmonella in the pork slaughter chain.

A novel purpose of the use of mathematical models in quantitative microbial risk assessment (QMRA) is to identify the sources of microbial contamination in a food chain (i.e., biotracing). In this article we propose a framework for the construction of a biotracing model, eventually to be used in industrial food production chains where discrete numbers of products are processed that may be contaminated by a multitude of sources. The framework consists of steps in which a Monte Carlo model, simulating sequential events in the chain following a modular process risk modeling (MPRM) approach, is converted to a Bayesian belief network (BBN). The resulting model provides a probabilistic quantification of concentrations of a pathogen throughout a production chain. A BBN allows for updating the parameters of the model based on observational data, and global parameter sensitivity analysis is readily performed in a BBN. Moreover, a BBN enables "backward reasoning" when downstream data are available and is therefore a natural framework for answering biotracing questions. The proposed framework is illustrated with a biotracing model of Salmonella in the pork slaughter chain, based on a recently published Monte Carlo simulation model. This model, implemented as a BBN, describes the dynamics of Salmonella in a Dutch slaughterhouse and enables finding the source of contamination of specific carcasses at the end of the chain.