Stakeholders making decisions in public health and world trade need improved estimations of the burden-of-illness of foodborne infectious diseases. In this article, we propose a Bayesian meta-analysis or more precisely a Bayesian evidence synthesis to assess the burden-of-illness of campylobacteriosis in France. Using this case study, we investigate campylobacteriosis prevalence, as well as the probabilities of different events that guide the disease pathway, by (i) employing a Bayesian approach on French and foreign human studies (from active surveillance systems, laboratory surveys, physician surveys, epidemiological surveys, and so on) through the chain of events that occur during an episode of illness and (ii) including expert knowledge about this chain of events. We split the target population using an exhaustive and exclusive partition based on health status and the level of disease investigation. We assume an approximate multinomial model over this population partition. Thereby, each observed data set related to the partition brings information on the parameters of the multinomial model, improving burden-of-illness parameter estimates that can be deduced from the parameters of the basic multinomial model. This multinomial model serves as a core model to perform a Bayesian evidence synthesis. Expert knowledge is introduced by way of pseudo-data. The result is a global estimation of the burden-of-illness parameters with their accompanying uncertainty.

Campylobacter species infections are a common cause of acute gastroenteritis, and may uncommonly be complicated by renal, neurological, and rheumatologic sequelae. Although excess summertime campylobacteriosis has been observed, environmental mechanisms driving disease seasonality are poorly understood. We sought to evaluate the relationship between environmental factors and campylobacteriosis risk in a major North American metropolitan area. We evaluated 1532 cases of campylobacteriosis reported in Philadelphia between 1994 and 2007. We constructed Poisson regression models with oscillatory smoothers, and also used case-crossover design, to evaluate the associations between environmental exposures and disease risk on weekly and daily time scales. Both methods control for confounding by seasonally oscillating environmental factors. Incidence was greatest in June and July, with annual periodicity. Weekly incidence was associated with increasing relative humidity, (incidence rate ratio (IRR) per % 1.017, 95% CI 1.008-1.025), temperature (IRR per degrees C 1.041, 95% CI 1.011-1.072), and decreasing Delaware River temperature during the same week (IRR per degrees C 0.922, 95% CI 0.883-0.962), and at 4-week lags (IRR per degrees C 0.953, 95% CI 0.919-0.990). No acute associations were identified in case-crossover analyses. Our findings affirm the summertime seasonality of campylobacteriosis in Philadelphia, and the link between warm, humid weather and disease risk. However, the link between low river temperatures and enhanced campylobacteriosis risk in humans described here is novel, consistent with known links between watershed temperature and Campylobacter survival, and implicates local watersheds as epidemiologically important reservoirs for foodborne pathogens.

In New Zealand Campylobacter infection rates have increased steadily since 1980, reaching a peak in 2003 (396/100,000 population). Compared to other nations, disease rates are unfavourably high (e.g. Australia 117/100,000 population, UK 85/100,000 population, USA 13/100,000 population). This ecological study investigated spatial variations in Campylobacter infection rates across New Zealand's Territorial Local Authorities (TLAs, n=73) for the period 1997-2005. Applying multiple linear regression, we examined whether geographical factors such as socio-demographic characteristics, climate, land use, water and the food environment were associated with local differences in the occurrence of Campylobacter infection rates. The results suggested significant variations in campylobacteriosis across TLAs (average annual rates ranging from 97 to 526/100,000 population), with higher rates in the South Island. Disease rates were associated with lower socio-economic deprivation (P<0.01), the proportion of the population aged 25-44 years (P<0.01) and fresh food outlet density (P<0.76). The results underline the role of area-level characteristics in explaining the spatial distribution of campylobacteriosis in New Zealand. In particular, the findings draw attention to the relatively unexplored role of fresh food outlets as a potential risk factor for increased Campylobacter notifications.

Campylobacter spp. is a widespread and important cause of human illness worldwide. Disease is frequently associated with foodborne transmission, but other routes of exposure, such as direct contact with live animals and person-to-person transmission, are also recognized. Identifying the most important sources of human disease is essential for prioritizing food safety interventions and setting public health goals. Numerous case-control studies of sporadic infections of campylobacteriosis have been published. These studies investigated a variety of potential risk factors for disease, often using different methodologies and settings. Systematic reviews (SRs) consist of a formal process for literature review focused on a specific research question, and include the identification of relevant literature, quality assessment of relevant studies, summarization or statistical analysis of data, and conclusions. With the objective of identifying the most important risk factors for human sporadic campylobacteriosis, we performed a SR of case-control studies of human sporadic cases and a meta-analysis of the obtained results. A combined SR focusing on Salmonella and Campylobacter studies was performed and the results analysed separately. From 1295 identified references, 131 passed the relevance screening, 73 passed the quality assessment stage, and data was extracted from 72 studies. Of these, 38 focused on campylobacteriosis. Information on exposures of cases and controls, and estimated odds ratios for investigated risk factors were collected and analysed. In the meta-analysis, heterogeneity between the studies and possible sources of bias were investigated, and pooled odds ratios for identified risk factors were estimated. Results suggest that travelling abroad, eating undercooked chicken, environmental sources, and direct contact with farm animals were significant risk factors for campylobacteriosis. Sub-analyses by geographical region, age group, and study period were performed, and differences were discussed.

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.