Prevalence and Load of the Campylobacter Genus in Infants and Associated Household Contacts in Rural Eastern Ethiopia: a Longitudinal Study from the Campylobacter Genomics and Environmental Enteric Dysfunction (CAGED) Project.

In our previous cross-sectional study, multiple species of Campylobacter were detected (88%) in stool samples from children (12 to 14 months of age) in rural eastern Ethiopia. This study assessed the temporal fecal carriage of Campylobacter in infants and identified putative reservoirs associated with these infections in infants from the same region. The prevalence and load of Campylobacter were determined using genus-specific real-time PCR. Stool samples from 106 infants (n = 1,073) were collected monthly from birth until 376 days of age (DOA). Human stool samples (mothers and siblings), livestock feces (cattle, chickens, goats, and sheep), and environmental samples (soil and drinking water) from the 106 households were collected twice per household (n = 1,644). Campylobacter was most prevalent in livestock feces (goats, 99%; sheep, 98%; cattle, 99%; chickens, 93%), followed by human stool samples (siblings, 91%; mothers, 83%; infants, 64%) and environmental samples (soil, 58%; drinking water, 43%). The prevalence of Campylobacter in infant stool samples significantly increased with age, from 30% at 27 DOA to 89% at 360 DOA (1% increase/day in the odds of being colonized) (P < 0.001). The Campylobacter load increased linearly (P < 0.001) with age from 2.95 logs at 25 DOA to 4.13 logs at 360 DOA. Within a household, the Campylobacter load in infant stool samples was positively correlated with the load in mother stool samples (r2 = 0.18) and soil collected inside the house (r2 = 0.36), which were in turn both correlated with Campylobacter loads in chicken and cattle feces (0.60 < r2 < 0.63) (P < 0.01). In conclusion, a high proportion of infants are infected with Campylobacter in eastern Ethiopia, and contact with the mother and contaminated soil may be associated with early infections. IMPORTANCE A high Campylobacter prevalence during early childhood has been associated with environmental enteric dysfunction (EED) and stunting, especially in low-resource settings. Our previous study demonstrated that Campylobacter was frequently found (88%) in children from eastern Ethiopia; however, little is known about potential Campylobacter reservoirs and transmission pathways leading to infection of infants by Campylobacter during early growth. In the longitudinal study presented here, Campylobacter was frequently detected in infants within the 106 surveyed households from eastern Ethiopia, and the prevalence was age dependent. Furthermore, preliminary analyses highlighted the potential role of the mother, soil, and livestock in the transmission of Campylobacter to the infant. Further work will explore the species and genetic composition of Campylobacter in infants and putative reservoirs using PCR and whole-genome and metagenomic sequencing. The findings from these studies can lead to the development of interventions to minimize the risk of transmission of Campylobacter to infants and, potentially, EED and stunting.

Estimates of disease burden caused by foodborne pathogens in contaminated dairy products in Rwanda.

BACKGROUND: The Girinka program in Rwanda has contributed to an increase in milk production, as well as to reduced malnutrition and increased incomes. But dairy products can be hazardous to health, potentially transmitting diseases such as bovine brucellosis, tuberculosis, and cause diarrhea. We analyzed the burden of foodborne disease due to consumption of raw milk and other dairy products in Rwanda to support the development of policy options for the improvement of the quality and safety of milk. METHODS: Disease burden data for five pathogens (Campylobacter spp., nontyphoidal Salmonella enterica, Cryptosporidium spp., Brucella spp., and Mycobacterium bovis) were extracted from the 2010 WHO Foodborne Disease Burden Epidemiology Reference Group (FERG) database and merged with data of the proportion of foodborne disease attributable to consuming dairy products from FERG and a separately published Structured Expert Elicitation study to generate estimates of the uncertainty distributions of the disease burden by Monte Carlo simulation. RESULTS: According to WHO, the foodborne disease burden (all foods) of these five pathogens in Rwanda in 2010 was like or lower than in the Africa E subregion as defined by FERG. There were 57,500 illnesses occurring in Rwanda owing to consumption of dairy products, 55 deaths and 3,870 Disability Adjusted Life Years (DALYs) causing a cost-of-illness of $3.2 million. 44% of the burden (in DALYs) was attributed to drinking raw milk and sizeable proportions were also attributed to traditionally (16-23%) or industrially (6-22%) fermented milk. More recent data are not available, but the burden (in DALYs) of tuberculosis and diarrheal disease by all causes in Rwanda has declined between 2010 and 2019 by 33% and 46%, respectively. CONCLUSION: This is the first study examining the WHO estimates of the burden of foodborne disease on a national level in Rwanda. Transitioning from consuming raw to processed milk (fermented, heat treated or otherwise) may prevent a considerable disease burden and cost-of-illness, but the full benefits will only be achieved if there is a simultaneous improvement of pathogen inactivation during processing, and prevention of recontamination of processed products.

Geographical distribution and space-time clustering of human illnesses with major Salmonella serotypes in Florida, USA, 2017-2018.

Nontyphoidal salmonellosis is the leading reported foodborne illness in Florida. Although the diversity of Salmonella serotypes circulating in Florida has been identified, the geographical characteristics of the major serotypes are poorly described. Here we examined the geospatial patterns of 803 whole-genome sequenced Salmonella isolates within seven major serotypes (Enteritidis, Newport, Javiana, Sandiego, Braenderup, Typhimurium and I 4,[5],12:i:-) with the metadata obtained from Florida Department of Health during 2017-2018. Geographically, the distribution of incidence rates varied distinctively between serotypes. Illnesses with Enteritidis and Newport serotypes were widespread in Florida. The incidence rate for Javiana was relatively higher in the north compared to the south. Typhimurium was concentrated in the northwest, while I 4,[5],12:i:-, the monophasic variant of Typhimurium was limited to the south. We also evaluated space-time clustering of isolates at the zip code level using scan statistic models. Space-time clusters were detected for each major serotype during 2017-2018. The multinomial scan statistic found the risk of illness with Javiana was higher in the north and southwest in the fall of 2017 compared to other major serotypes. This serotype-specific clustering analysis will assist in further unpacking the associations between distinct reservoirs and illnesses with major serotypes in Florida.

Patient-related healthcare costs for diarrhoea, Guillain Barré syndrome and invasive non-typhoidal salmonellosis in Gondar, Ethiopia, 2020.

BACKGROUND: Globally, foodborne diseases result in a significant disease burden with low- and middle-income countries disproportionately affected. Estimates of healthcare costs related to foodborne disease can aid decision makers to take action to mitigate risks and prevent illness. However, only limited data on the African continent are available, especially related to more severe sequelae. We provide estimates of direct and indirect (non)-medical costs of patients with diarrhoea, Guillain-Barré syndrome (GBS), and invasive non-typhoidal salmonellosis (iNTS) in three healthcare facilities in Gondar, Ethiopia. METHODS: We used healthcare data from patient records, interviews with family caregivers and 2020 healthcare resource unit costs. Descriptive statistical analysis was performed. For diarrhoea, differences in mean and median transformed costs between healthcare facilities and etiologies (Campylobacter spp., enterotoxigenic Escherichia coli, non-typhoidal Salmonella enterica) were analysed with ANOVA and chi squared tests. Contribution of healthcare facility, dehydration severity, sex, age and living area to transformed costs was identified with linear regression. Results are in 2020 USD per patient. To extrapolate to national level, 2017 national incidence estimates were used. RESULTS: Mean direct medical costs were 8.96 USD for diarrhoea (health centre 6.50 USD, specialised hospital 9.53 USD, private clinic 10.56 USD), 267.70 USD for GBS, and 47.79 USD for iNTS. Differences in costs between diarrhoea patients were mainly associated with healthcare facility. Most costs did not differ between etiologies. Total costs of a diarrhoea patient in the specialised hospital were 67 USD, or 8% of gross national income per capita. For direct medical plus transport costs of a GBS and iNTS patient in the specialised hospital, this was 33% and 8%, respectively. Of the 83.9 million USD estimated national non-typhoidal Salmonella enterica related cost, 12.2% was due to iNTS, and of 187.8 million USD related to Campylobacter spp., 0.2% was due to GBS. CONCLUSION: Direct medical costs per patient due to GBS and iNTS were 30 respectively five times those due to diarrhoea. Costs of a patient with diarrhoea, GBS or iNTS can be a substantial part of a household's income. More severe sequalae can add substantially to cost-of-illness of foodborne hazards causing diarrheal disease.

Attribution of Illnesses Transmitted by Food and Water to Comprehensive Transmission Pathways Using Structured Expert Judgment, United States.

Illnesses transmitted by food and water cause a major disease burden in the United States despite advancements in food safety, water treatment, and sanitation. We report estimates from a structured expert judgment study using 48 experts who applied Cooke's classical model of the proportion of disease attributable to 5 major transmission pathways (foodborne, waterborne, person-to-person, animal contact, and environmental) and 6 subpathways (food handler-related, under foodborne; recreational, drinking, and nonrecreational/nondrinking, under waterborne; and presumed person-to-person-associated and presumed animal contact-associated, under environmental). Estimates for 33 pathogens were elicited, including bacteria such as Salmonella enterica, Campylobacter spp., Legionella spp., and Pseudomonas spp.; protozoa such as Acanthamoeba spp., Cyclospora cayetanensis, and Naegleria fowleri; and viruses such as norovirus, rotavirus, and hepatitis A virus. The results highlight the importance of multiple pathways in the transmission of the included pathogens and can be used to guide prioritization of public health interventions.

Estimate of Burden and Direct Healthcare Cost of Infectious Waterborne Disease in the United States.

Provision of safe drinking water in the United States is a great public health achievement. However, new waterborne disease challenges have emerged (e.g., aging infrastructure, chlorine-tolerant and biofilm-related pathogens, increased recreational water use). Comprehensive estimates of the health burden for all water exposure routes (ingestion, contact, inhalation) and sources (drinking, recreational, environmental) are needed. We estimated total illnesses, emergency department (ED) visits, hospitalizations, deaths, and direct healthcare costs for 17 waterborne infectious diseases. About 7.15 million waterborne illnesses occur annually (95% credible interval [CrI] 3.88 million-12.0 million), results in 601,000 ED visits (95% CrI 364,000-866,000), 118,000 hospitalizations (95% CrI 86,800-150,000), and 6,630 deaths (95% CrI 4,520-8,870) and incurring US $3.33 billion (95% CrI 1.37 billion-8.77 billion) in direct healthcare costs. Otitis externa and norovirus infection were the most common illnesses. Most hospitalizations and deaths were caused by biofilm-associated pathogens (nontuberculous mycobacteria, Pseudomonas, Legionella), costing US $2.39 billion annually.

Parsimonious Mechanistic Modeling of Bacterial Runoff into Irrigation Ponds To Inform Food Safety Management of Agricultural Water Quality.

Pond irrigation water comprises a major pathway of pathogenic bacteria to fresh produce. Current regulatory methods have been shown to be ineffective in assessing this risk when variability of bacterial concentrations is large. This paper proposes using mechanistic modeling of bacterial transport as a way to identify improved strategies for mitigating this risk pathway. If the mechanistic model is successfully tested against observed data, global sensitivity analysis (GSA) can identify important mechanisms to inform alternative, preventive bacterial control practices. Model development favored parsimony and prediction of peak bacterial concentration events. Data from two highly variable surface water irrigation ponds showed that the model performance was similar or superior to that of existing pathogen transport models, with a Nash-Sutcliffe efficiency of 0.48 and 0.18 for the two ponds. GSA quantified bacterial sourcing and hydrology as the most important processes driving pond bacterial contamination events. Model analysis has two main implications for improved regulatory methods: that peak concentration events are associated with runoff-producing rainfall events and that intercepting bacterial runoff transport may be the best option to prevent bacterial contamination of surface water irrigation ponds and thus fresh produce. This research suggests the need for temporal management strategies. IMPORTANCE Preventive management of agricultural waters requires understanding of the drivers of bacterial contamination events. We propose mechanistic modeling as a way forward to understand and predict such events and have developed and tested a parsimonious model for rain-driven surface runoff contributing to generic Escherichia coli contamination of irrigation ponds in Central Florida. While the model was able to predict the timing of peak events reasonably well, the highly variable magnitude of the peaks was less well predicted. This indicates the need to collect more data on the fecal contamination inputs of these ponds and the use of mechanistic modeling and global sensitivity analysis to identify the most important data needs.

Estimates of the 2015 global and regional disease burden from four foodborne metals - arsenic, cadmium, lead and methylmercury.

The impact of foodborne metals on the burden of disease has been largely overlooked, in comparison to the attention on acute diseases associated with infectious foodborne agents. Four articles in this special section describe in detail the burden of disease from foodborne lead, methylmercury, arsenic, and cadmium. Ingested lead and methylmercury are causally associated with lifelong intellectual disability. Long term ingestion of arsenic is causally associated with an increased risk of cancer. Long term ingestion of cadmium is causally associated with an increased risk of late stage chronic kidney disease. This article presents an overview of the burden of disease from these four foodborne metals and discusses them in the context of the World Health Organization's initiative to estimate the global burden of foodborne disease. The results indicate that in 2015, ingestion of arsenic, methylmercury, lead, and cadmium resulted in more than 1 million illnesses, over 56,000 deaths, and more than 9 million disability-adjusted life years (DALYs) worldwide. The greatest impact on DALYs was in the Western Pacific B subregion. All of the metals were found to have high DALYs per case in comparison with other foodborne disease agents, including infectious and parasitic agents. In addition, lead, arsenic, and methylmercury were found to have high DALYs per 100,000 population in comparison to other foodborne disease agents.

Molecular relatedness of ESBL/AmpC-producing Escherichia coli from humans, animals, food and the environment: a pooled analysis.

Background: In recent years, ESBL/AmpC-producing Escherichia coli (ESBL/AmpC-EC) have been isolated with increasing frequency from animals, food, environmental sources and humans. With incomplete and scattered evidence, the contribution to the human carriage burden from these reservoirs remains unclear. Objectives: To quantify molecular similarities between different reservoirs as a first step towards risk attribution. Methods: Pooled data on ESBL/AmpC-EC isolates were recovered from 35 studies in the Netherlands comprising >27 000 samples, mostly obtained between 2005 and 2015. Frequency distributions of ESBL/AmpC genes from 5808 isolates and replicons of ESBL/AmpC-carrying plasmids from 812 isolates were compared across 22 reservoirs through proportional similarity indices (PSIs) and principal component analyses (PCAs). Results: Predominant ESBL/AmpC genes were identified in each reservoir. PCAs and PSIs revealed close human-animal ESBL/AmpC gene similarity between human farming communities and their animals (broilers and pigs) (PSIs from 0.8 to 0.9). Isolates from people in the general population had higher similarities to those from human clinical settings, surface and sewage water and wild birds (0.7-0.8), while similarities to livestock or food reservoirs were lower (0.3-0.6). Based on rarefaction curves, people in the general population had more diversity in ESBL/AmpC genes and plasmid replicon types than those in other reservoirs. Conclusions: Our 'One Health' approach provides an integrated evaluation of the molecular relatedness of ESBL/AmpC-EC from numerous sources. The analysis showed distinguishable ESBL/AmpC-EC transmission cycles in different hosts and failed to demonstrate a close epidemiological linkage of ESBL/AmpC genes and plasmid replicon types between livestock farms and people in the general population.

Disability weights for infectious diseases in four European countries: comparison between countries and across respondent characteristics.

Background: In 2015, new disability weights (DWs) for infectious diseases were constructed based on data from four European countries. In this paper, we evaluated if country, age, sex, disease experience status, income and educational levels have an impact on these DWs. Methods: We analyzed paired comparison responses of the European DW study by participants' characteristics with separate probit regression models. To evaluate the effect of participants' characteristics, we performed correlation analyses between countries and within country by respondent characteristics and constructed seven probit regression models, including a null model and six models containing participants' characteristics. We compared these seven models using Akaike Information Criterion (AIC). Results: According to AIC, the probit model including country as covariate was the best model. We found a lower correlation of the probit coefficients between countries and income levels (range rs: 0.97-0.99, P < 0.01) than between age groups (range rs: 0.98-0.99, P < 0.01), educational level (range rs: 0.98-0.99, P < 0.01), sex (rs = 0.99, P < 0.01) and disease status (rs = 0.99, P < 0.01). Within country the lowest correlations of the probit coefficients were between low and high income level (range rs = 0.89-0.94, P < 0.01). Conclusions: We observed variations in health valuation across countries and within country between income levels. These observations should be further explored in a systematic way, also in non-European countries. We recommend future researches studying the effect of other characteristics of respondents on health assessment.

Impact of infectious diseases on population health using incidence-based disability-adjusted life years (DALYs): results from the Burden of Communicable Diseases in Europe study, European Union and European Economic Area countries, 2009 to 2013.

Background and aimsThe Burden of Communicable Diseases in Europe (BCoDE) study aimed to calculate disability-adjusted life years (DALYs) for 31 selected diseases in the European Union (EU) and European Economic Area (EEA). Methods: DALYs were estimated using an incidence-based and pathogen-based approach. Incidence was estimated through assessment of data availability and quality, and a correction was applied for under-estimation. Calculation of DALYs was performed with the BCoDE software toolkit without applying time discounting and age-weighting. Results: We estimated that one in 14 inhabitants experienced an infectious disease episode for a total burden of 1.38 million DALYs (95% uncertainty interval (UI): 1.25-1.5) between 2009 and 2013; 76% of which was related to the acute phase of the infection and its short-term complications. Influenza had the highest burden (30% of the total burden), followed by tuberculosis, human immunodeficiency virus (HIV) infection/AIDS and invasive pneumococcal disease (IPD). Men had the highest burden measured in DALYs (60% of the total), adults 65 years of age and over had 24% and children less than 5 years of age had 11%. Age group-specific burden showed that infants (less than 1 year of age) and elderly people (80 years of age and over) experienced the highest burden. Conclusions: These results provide baseline estimates for evaluating infectious disease prevention and control strategies. The study promotes an evidence-based approach to describing population health and assessing surveillance data availability and quality, and provides information for the planning and prioritisation of limited resources in infectious disease prevention and control.

A summary index for antimicrobial resistance in food animals in the Netherlands.

BACKGROUND: The Dutch government has set targets for reduction of antimicrobial usage in food animals, stipulating a 50% reduction in usage (on a weight basis) in 2013 as compared to 2009 and a 70% decrease in 2015. A monitoring program has been instituted to evaluate the impact on antimicrobial resistance (AMR). The Dutch Ministry of Public Health Welfare and Sports has expressed the need for a summary index to present the results of the monitoring data concisely to policy makers. METHODS: We use data on AMR in bacteria from randomly collected samples from broiler chickens, fattening pigs, veal calves and dairy cows. Escherichia coli was selected for resistance monitoring because they are intrinsically susceptible to the antibiotics included in the test panel (ciprofloxacin, cefotaxime, tetracycline and ampicillin) and they are present in all samples, which facilitates proper randomization and trend analysis. The AMR summary index was calculated for each animal species as a weighted average over the four antibiotics, taking into account their clinical relevance. Weights were obtained by conjoint analysis, a pairwise comparison study involving infectious diseases professionals with clinical and public health backgrounds, with data analysis by conditional logistic regression. The AMR summary index was then computed by Monte Carlo simulation, accounting for sampling and regression uncertainty. RESULTS: The highest weights (0.35) were given to ciprofloxacin and cefotaxime followed by ampicillin (0.23) and tetracycline (0.07). Throughout the years, the AMR index was highest in broiler chickens, followed by pigs and veal calves, while the lowest values were consistently recorded in dairy cows. In all animal species, the index in 2014 was significantly lower than in 2009. CONCLUSIONS: We demonstrate that high-dimensional data on surveillance of antimicrobial resistance can be summarized in an index for evaluating trends between and within food animal species by a process involving decision makers and scientists to select and weight the most relevant antibiotics.

High relative humidity pre-harvest reduces post-harvest proliferation of Salmonella in tomatoes.

Outbreaks of human illness caused by enteric pathogens such as Salmonella are increasingly linked to the consumption of fruits and vegetables. Knowledge on the factors affecting Salmonella proliferation on fresh produce therefore becomes increasingly important to safeguard public health. Previous experiments showed a limited impact of pre-harvest production practices on Salmonella proliferation on tomatoes, but suggested a significant effect of harvest time. We explored the data from two previously published and one unpublished experiment using regression trees, which allowed overcoming the interpretational difficulties of classical statistical models with higher order interactions. We assessed the effect of harvest time by explicitly modeling the climatic conditions at harvest time and by performing confirmatory laboratory experiments. Across all datasets, regression trees confirmed the dominant effect of harvest time on Salmonella proliferation, with humidity-related factors emerging as the most important underlying climatic factors. High relative humidity the week prior to harvest was consistently associated with lower Salmonella proliferation. A controlled lab experiment confirmed that tomatoes containing their native epimicrobiota supported significantly lower Salmonella proliferation when incubated at higher humidity prior to inoculation. The complex interactions between environmental conditions and the native microbiota of the tomato crop remain to be fully understood.

Burden of salmonellosis, campylobacteriosis and listeriosis: a time series analysis, Belgium, 2012 to 2020.

Salmonellosis, campylobacteriosis and listeriosis are food-borne diseases. We estimated and forecasted the number of cases of these three diseases in Belgium from 2012 to 2020, and calculated the corresponding number of disability-adjusted life years (DALYs). The salmonellosis time series was fitted with a Bai and Perron two-breakpoint model, while a dynamic linear model was used for campylobacteriosis and a Poisson autoregressive model for listeriosis. The average monthly number of cases of salmonellosis was 264 (standard deviation (SD): 86) in 2012 and predicted to be 212 (SD: 87) in 2020; campylobacteriosis case numbers were 633 (SD: 81) and 1,081 (SD: 311); listeriosis case numbers were 5 (SD: 2) in 2012 and 6 (SD: 3) in 2014. After applying correction factors, the estimated DALYs for salmonellosis were 102 (95% uncertainty interval (UI): 8-376) in 2012 and predicted to be 82 (95% UI: 6-310) in 2020; campylobacteriosis DALYs were 1,019 (95% UI: 137-3,181) and 1,736 (95% UI: 178-5,874); listeriosis DALYs were 208 (95% UI: 192-226) in 2012 and 252 (95% UI: 200-307) in 2014. New actions are needed to reduce the risk of food-borne infection with Campylobacter spp. because campylobacteriosis incidence may almost double through 2020.

Intervention strategies to reduce human Toxoplasma gondii disease burden.

Infection with Toxoplasma gondii is acquired through consumption of undercooked infected meat, or by uptake of cat-shed oocysts. Although congenital toxoplasmosis is generally considered to contribute most to the disease burden of T. gondii, ocular disease from acquired infection was recently shown to add substantially to the burden. In addition, toxoplasmosis in immune-compromised individuals usually results from reactivation of an infection acquired earlier in life. Nevertheless, prevention of toxoplasmosis commonly targets mainly pregnant women. We summarize current prevention strategies of congenital toxoplasmosis and evaluate options to improve protection of the general population (including pregnant women). To protect the general population, freezing of meat destined for raw or undercooked consumption is the most readily applicable option, especially when limited to meat from animals originating from nonbiosecure husbandry systems. In the long term, more health benefits are expected from cat vaccination; therefore, development of a cat vaccine and evaluation of its implementation is a research priority.

World Health Organization Global Estimates and Regional Comparisons of the Burden of Foodborne Disease in 2010.

Illness and death from diseases caused by contaminated food are a constant threat to public health and a significant impediment to socio-economic development worldwide. To measure the global and regional burden of foodborne disease (FBD), the World Health Organization (WHO) established the Foodborne Disease Burden Epidemiology Reference Group (FERG), which here reports their first estimates of the incidence, mortality, and disease burden due to 31 foodborne hazards. We find that the global burden of FBD is comparable to those of the major infectious diseases, HIV/AIDS, malaria and tuberculosis. The most frequent causes of foodborne illness were diarrheal disease agents, particularly norovirus and Campylobacter spp. Diarrheal disease agents, especially non-typhoidal Salmonella enterica, were also responsible for the majority of deaths due to FBD. Other major causes of FBD deaths were Salmonella Typhi, Taenia solium and hepatitis A virus. The global burden of FBD caused by the 31 hazards in 2010 was 33 million Disability Adjusted Life Years (DALYs); children under five years old bore 40% of this burden. The 14 subregions, defined on the basis of child and adult mortality, had considerably different burdens of FBD, with the greatest falling on the subregions in Africa, followed by the subregions in South-East Asia and the Eastern Mediterranean D subregion. Some hazards, such as non-typhoidal S. enterica, were important causes of FBD in all regions of the world, whereas others, such as certain parasitic helminths, were highly localised. Thus, the burden of FBD is borne particularly by children under five years old-although they represent only 9% of the global population-and people living in low-income regions of the world. These estimates are conservative, i.e., underestimates rather than overestimates; further studies are needed to address the data gaps and limitations of the study. Nevertheless, all stakeholders can contribute to improvements in food safety throughout the food chain by incorporating these estimates into policy development at national and international levels.

World Health Organization Estimates of the Global and Regional Disease Burden of 22 Foodborne Bacterial, Protozoal, and Viral Diseases, 2010: A Data Synthesis.

BACKGROUND: Foodborne diseases are important worldwide, resulting in considerable morbidity and mortality. To our knowledge, we present the first global and regional estimates of the disease burden of the most important foodborne bacterial, protozoal, and viral diseases. METHODS AND FINDINGS: We synthesized data on the number of foodborne illnesses, sequelae, deaths, and Disability Adjusted Life Years (DALYs), for all diseases with sufficient data to support global and regional estimates, by age and region. The data sources included varied by pathogen and included systematic reviews, cohort studies, surveillance studies and other burden of disease assessments. We sought relevant data circa 2010, and included sources from 1990-2012. The number of studies per pathogen ranged from as few as 5 studies for bacterial intoxications through to 494 studies for diarrheal pathogens. To estimate mortality for Mycobacterium bovis infections and morbidity and mortality for invasive non-typhoidal Salmonella enterica infections, we excluded cases attributed to HIV infection. We excluded stillbirths in our estimates. We estimate that the 22 diseases included in our study resulted in two billion (95% uncertainty interval [UI] 1.5-2.9 billion) cases, over one million (95% UI 0.89-1.4 million) deaths, and 78.7 million (95% UI 65.0-97.7 million) DALYs in 2010. To estimate the burden due to contaminated food, we then applied proportions of infections that were estimated to be foodborne from a global expert elicitation. Waterborne transmission of disease was not included. We estimate that 29% (95% UI 23-36%) of cases caused by diseases in our study, or 582 million (95% UI 401-922 million), were transmitted by contaminated food, resulting in 25.2 million (95% UI 17.5-37.0 million) DALYs. Norovirus was the leading cause of foodborne illness causing 125 million (95% UI 70-251 million) cases, while Campylobacter spp. caused 96 million (95% UI 52-177 million) foodborne illnesses. Of all foodborne diseases, diarrheal and invasive infections due to non-typhoidal S. enterica infections resulted in the highest burden, causing 4.07 million (95% UI 2.49-6.27 million) DALYs. Regionally, DALYs per 100,000 population were highest in the African region followed by the South East Asian region. Considerable burden of foodborne disease is borne by children less than five years of age. Major limitations of our study include data gaps, particularly in middle- and high-mortality countries, and uncertainty around the proportion of diseases that were foodborne. CONCLUSIONS: Foodborne diseases result in a large disease burden, particularly in children. Although it is known that diarrheal diseases are a major burden in children, we have demonstrated for the first time the importance of contaminated food as a cause. There is a need to focus food safety interventions on preventing foodborne diseases, particularly in low- and middle-income settings.

Data-driven methods for imputing national-level incidence in global burden of disease studies.

OBJECTIVE: To develop transparent and reproducible methods for imputing missing data on disease incidence at national-level for the year 2005. METHODS: We compared several models for imputing missing country-level incidence rates for two foodborne diseases - congenital toxoplasmosis and aflatoxin-related hepatocellular carcinoma. Missing values were assumed to be missing at random. Predictor variables were selected using least absolute shrinkage and selection operator regression. We compared the predictive performance of naive extrapolation approaches and Bayesian random and mixed-effects regression models. Leave-one-out cross-validation was used to evaluate model accuracy. FINDINGS: The predictive accuracy of the Bayesian mixed-effects models was significantly better than that of the naive extrapolation method for one of the two disease models. However, Bayesian mixed-effects models produced wider prediction intervals for both data sets. CONCLUSION: Several approaches are available for imputing missing data at national level. Strengths of a hierarchical regression approach for this type of task are the ability to derive estimates from other similar countries, transparency, computational efficiency and ease of interpretation. The inclusion of informative covariates may improve model performance, but results should be appraised carefully.

Assessing disability weights based on the responses of 30,660 people from four European countries.

BACKGROUND: In calculations of burden of disease using disability-adjusted life years, disability weights are needed to quantify health losses relating to non-fatal outcomes, expressed as years lived with disability. In 2012 a new set of global disability weights was published for the Global Burden of Disease 2010 (GBD 2010) study. That study suggested that comparative assessments of different health outcomes are broadly similar across settings, but the significance of this conclusion has been debated. The aim of the present study was to estimate disability weights for Europe for a set of 255 health states, including 43 new health states, by replicating the GBD 2010 Disability Weights Measurement study among representative population samples from four European countries. METHODS: For the assessment of disability weights for Europe we applied the GBD 2010 disability weights measurement approach in web-based sample surveys in Hungary, Italy, Netherlands, and Sweden. The survey included paired comparisons (PC) and population health equivalence questions (PHE) formulated as discrete choices. Probit regression analysis was used to estimate cardinal values from PC responses. To locate results onto the 0-to-1 disability weight scale, we assessed the feasibility of using the GBD 2010 scaling approach based on PHE questions, as well as an alternative approach using non-parametric regression. RESULTS: In total, 30,660 respondents participated in the survey. Comparison of the probit regression results from the PC responses for each country indicated high linear correlations between countries. The PHE data had high levels of measurement error in these general population samples, which compromises the ability to infer ratio-scaled values from discrete choice responses. Using the non-parametric regression approach as an alternative rescaling procedure, the set of disability weights were bounded by distance vision mild impairment and anemia with the lowest weight (0.004) and severe multiple sclerosis with the highest weight (0.677). CONCLUSIONS: PC assessments of health outcomes in this study resulted in estimates that were highly correlated across four European countries. Assessment of the feasibility of rescaling based on a discrete choice formulation of the PHE question indicated that this approach may not be suitable for use in a web-based survey of the general population.

Improved correlation of human Q fever incidence to modelled C. burnetii concentrations by means of an atmospheric dispersion model.

BACKGROUND: Atmospheric dispersion models (ADMs) may help to assess human exposure to airborne pathogens. However, there is as yet limited quantified evidence that modelled concentrations are indeed associated to observed human incidence. METHODS: We correlated human Q fever (caused by the bacterium Coxiella burnetii) incidence data in the Netherlands to modelled concentrations from three spatial exposure models: 1) a NULL model with a uniform concentration distribution, 2) a DISTANCE model with concentrations proportional to the distance between the source and residential addresses of patients, and 3) concentrations modelled by an ADM using three simple emission profiles. We used a generalized linear model to correlate the observed incidences to modelled concentrations and validated it using cross-validation. RESULTS: ADM concentrations generally correlated the best to the incidence data. The DISTANCE model always performed significantly better than the NULL model. ADM concentrations based on wind speeds exceeding threshold values of 0 and 2 m/s performed better than those based on 4 or 6 m/s. This might indicate additional exposure to bacteria originating from a contaminated environment. CONCLUSIONS: By adding meteorological information the correlation between modelled concentration and observed incidence improved, despite using three simple emission profiles. Although additional information is needed - especially regarding emission data - these results provide a basis for the use of ADMs to predict and to visualize the spread of airborne pathogens during livestock, industry and even bio-terroristic related outbreaks or releases to a surrounding human population.