Geographic determinants of reported human Campylobacter infections in Scotland

<p><b>Background:</b> Campylobacteriosis is the leading cause of bacterial gastroenteritis in most developed countries. People are exposed to infection from contaminated food and environmental sources. However, the translation of these exposures into infection in the human population remains incompletely understood. This relationship is further complicated by differences in the presentation of cases, their investigation, identification, and reporting; thus, the actual differences in risk must be considered alongside the artefactual differences.</p> <p><b>Methods:</b> Data on 33,967 confirmed Campylobacter infections in mainland Scotland between 2000 and 2006 (inclusive) that were spatially referenced to the postcode sector level were analysed. Risk factors including the Carstairs index of social deprivation, the easting and northing of the centroid of the postcode sector, measures of livestock density by species and population density were tested in univariate screening using a non-spatial generalised linear model. The NHS Health Board of the case was included as a random effect in this final model. Subsequently, a spatial generalised linear mixed model (GLMM) was constructed and age-stratified sensitivity analysis was conducted on this model.</p> <p><b>Results:</b> The spatial GLMM included the protective effects of the Carstairs index (relative risk (RR) = 0.965, 95% Confidence intervals (CIs) = 0.959, 0.971) and population density (RR = 0.945, 95% CIs = 0.916, 0.974. Following stratification by age group, population density had a significant protective effect (RR = 0.745, 95% CIs = 0.700, 0.792) for those under 15 but not for those aged 15 and older (RR = 0.982, 95% CIs = 0.951, 1.014). Once these predictors have been taken into account three NHS Health Boards remain at significantly greater risk (Grampian, Highland and Tayside) and two at significantly lower risk (Argyll and Ayrshire and Arran).</p> <p><b>Conclusions:</b> The less deprived and children living in rural areas are at the greatest risk of being reported as a case of Campylobacter infection. However, this analysis cannot differentiate between actual risk and heterogeneities in individual reporting behaviour; nevertheless this paper has demonstrated that it is possible to explain the pattern of reported Campylobacter infections using both social and environmental predictors.</p&gt

Seasonality in Human Zoonotic Enteric Diseases: A Systematic Review

BACKGROUND: Although seasonality is a defining characteristic of many infectious diseases, few studies have described and compared seasonal patterns across diseases globally, impeding our understanding of putative mechanisms. Here, we review seasonal patterns across five enteric zoonotic diseases: campylobacteriosis, salmonellosis, vero-cytotoxigenic Escherichia coli (VTEC), cryptosporidiosis and giardiasis in the context of two primary drivers of seasonality: (i) environmental effects on pathogen occurrence and pathogen-host associations and (ii) population characteristics/behaviour. METHODOLOGY/PRINCIPAL FINDINGS: We systematically reviewed published literature from 1960-2010, resulting in the review of 86 studies across the five diseases. The Gini coefficient compared temporal variations in incidence across diseases and the monthly seasonality index characterised timing of seasonal peaks. Consistent seasonal patterns across transnational boundaries, albeit with regional variations was observed. The bacterial diseases all had a distinct summer peak, with identical Gini values for campylobacteriosis and salmonellosis (0.22) and a higher index for VTEC (Gini  0.36). Cryptosporidiosis displayed a bi-modal peak with spring and summer highs and the most marked temporal variation (Gini = 0.39). Giardiasis showed a relatively small summer increase and was the least variable (Gini = 0.18). CONCLUSIONS/SIGNIFICANCE: Seasonal variation in enteric zoonotic diseases is ubiquitous, with regional variations highlighting complex environment-pathogen-host interactions. Results suggest that proximal environmental influences and host population dynamics, together with distal, longer-term climatic variability could have important direct and indirect consequences for future enteric disease risk. Additional understanding of the concerted influence of these factors on disease patterns may improve assessment and prediction of enteric disease burden in temperate, developed countries

EFSA Panel on Biological Hazards (BIOHAZ) Panel; Scientific Opinion on the risk posed by pathogens in food of non-animal origin. Part 1 (outbreak data analysis and risk ranking of food/pathogen combinations)

Food of non-animal origin (FoNAO) is consumed in a variety of forms, and a major component of almost all meals. These food types have the potential to be associated with large outbreaks as seen in 2011 associated with VTEC O104. A comparison of the incidence of human cases linked to consumption of FoNAO and of food of animal origin (FoAO) was carried out to provide an indication of the proportionality between these two groups of foods. It was concluded that outbreak data reported as part of EU Zoonoses Monitoring is currently the only option for EU-wide comparative estimates. Using this data from 2007 to 2011, FoNAO were associated with 10% of the outbreaks, 26% of the cases, 35% of the hospitalisations and 46% of the deaths. If the data from the 2011VTEC O104 outbreak is excluded, FoNAO was associated with 10% of the outbreaks, 18% of cases, but only 8% of the hospitalisations and 5% of the deaths. From 2008 to 2011 there was an increase in the numbers of reported outbreaks, cases, hospitalisations and deaths associated with food of non-animal origin. In order to identify and rank specific food/pathogen combinations most often linked to human cases originating from FoNAO in the EU, a model was developed using seven criteria: strength of associations between food and pathogen based on the foodborne outbreak data from EU Zoonoses Monitoring (2007-11), incidence of illness, burden of disease, dose-response relationship, consumption, prevalence of contamination and pathogen growth potential during shelf life. Shortcomings in the approach using outbreak data were discussed. The top ranking food/pathogen combination was Salmonellaspp. and leafy greens eaten raw followed by (in equal rank) Salmonellaspp. and bulb and stem vegetables, Salmonellaspp. and tomatoes, Salmonellaspp. and melons, and pathogenic Escherichia coli and fresh pods, legumes or grain

EFSA Panel on Biological Hazards (BIOHAZ); Scientific Opinion on public health risks represented by certain composite products containing food of animal origin

This Opinion reviews the factors that affect microbial survival and growth in composite products, and in foods in general. It concludes that the main factors to be considered are: water activity, pH, temperature and duration of storage, processing, and intensity and duration of other non-thermal physical processes applied. Prevalence and concentration of the pathogens in food are important to determine the risk for consumers. The opinion presents a review of the quantitative microbiology models and databases that can be used to provide quantitative estimations of the impact of the above factors on the survival and growth of the main bacterial pathogens. In composite products, migration and diffusion of moisture and substances among the ingredients may change their physico-chemical parameters, particularly at the interfaces. Therefore, the assessment of the risk posed by composite products needs to consider the combinations of parameters most permissive to survival and growth of pathogens. Two complementary approaches are proposed for the identification and profiling of microbiological hazards in different specific composite products. The first one is based on past outbreaks and prevalence of hazards in the products and leads to the conclusion that the most frequent hazard-composite product combinations are Salmonella in cakes and bakery products. The second one consists in decision tools based on the impact on the pathogens of food composition and food processing. Categorisation of the risk for composite products requires information on their composition, processing and further handling, which can largely differ for foods belonging to the same category. Further conditions may influence the risk and should be verified, i.e. hygienic conditions during preparation of the composite products and their ingredients, shelf-life conditions, and reliability of cooking by consumers to inactivate pathogens. The decision tools developed apply to all composite products considered by the mandate, as well as to all other foods. © European Food Safety Authority, 201

A national case-control study of risk factors for listeriosis in Australia

Listeriosis is a foodborne disease associated with significant mortality. This study attempts to identify risk factors for sporadic listeriosis in Australia. Information on underlying illnesses was obtained from cases' treating doctors and other risk factors were elicited from the patient or a surrogate. We attempted to recruit two controls per case matched on age and primary underlying immune condition. Between November 2001 and December 2004 we recruited 136 cases and 97 controls. Of perinatal cases, living in a household where a language other than English was spoken was the main risk factor associated with listeriosis (OR 113, 95% CI 15-undefined). Of non-perinatal cases we identified the following risk factors for listeriosis: prior hospitalization (OR 43, 95% CI 10-183), use of gastric acid inhibitors (OR 94, 95% CI 24-374), and consumption of camembert (OR 47, 95% CI 11-206). Forty percent of cases with prior hospitalization were exposed to high-risk foods during hospitalization

Risk factors for infection with Campylobacter jejuni flaA genotypes

We aimed to explore Campylobacter genotype-specific risk factors in Australia. Isolates collected prospectively from cases recruited into a case-control study were genotyped using flaA restriction fragment-length polymorphism typing (flaA genotyping). Exposure information for cases and controls was collected by telephone interview. Risk factors were examined for major flaA genotypes using logistic and multinomial regression. Five flaA genotypes accounted for 325 of 590 (55%) cases – flaA-6b (n=129), flaA-6 (n=70), flaA-10 (n=48), flaA-2 (n=43), flaA-131 (n=35). In Australia, infections due to flaA-10 and flaA-2 were found to be significantly associated with eating non-poultry meat (beef and ham, respectively) in both case-control and inter-genotype comparisons. All major genotypes apart from flaA-10 were associated with chicken consumption in the case-control comparisons. Based on several clinical criteria, infections due to flaA-2 were more severe than those due to other genotypes. Thus genotype analysis may reveal genotype-specific niches and differences in virulence and transmission routes