A 1-year cross-sectional study was carried out to determine the prevalence, risk factors for carriage, and genetic diversity of Campylobacter spp. in healthy dogs and cats in Switzerland. Veterinary practitioners collected samples from 1268 animals (all ages) presented for vaccination. The prevalence of Campylobacter spp. in 634 dogs and 596 cats that were eligible for the study was 41.2% (confidence interval 95%: 37.3-45.1%) and 41.9% (CI 95%: 37.9-46%), respectively. Risk factors identified for carriage of Campylobacter jejuni were found to be different from risk factors for C. upsaliensis/C. helveticus. Young animals (< or =3 years) had significantly higher odds of carrying C. upsaliensis/C. helveticus than older animals (OR 1.8-3.3), whereas for C. jejuni carriage, the age was not a risk factor. Amplified fragment length polymorphism (AFLP) genotyping revealed heterogeneity among C. jejuni strains and was found to clearly separate C. helveticus from C. upsaliensis. It was shown that cats more often carry C. helveticus with an estimated prevalence of 28.2%, whereas dogs mainly are carrying C. upsaliensis.
Spatiotemporal disease mapping models have been used extensively to describe the pattern of surveillance data. They are usually formulated in a hierarchical Bayesian framework and posterior marginals are not available in closed form. Hence, the standard method for parameter estimation is Markov chain Monte Carlo algorithms. A new method for approximate Bayesian inference in latent Gaussian models using integrated nested Laplace approximations has recently been proposed as an alternative. This approach promises very precise results in short computational time. The aim of the paper is to show how integrated nested Laplace approximations can be used as an inferential tool for a variety of spatiotemporal models for the analysis of reported cases of bovine viral diarrhoea in cattle from Switzerland. Conclusions concerning the problem of under-reporting in the data are drawn via a multilevel modelling strategy. Furthermore, a comparison with Markov chain Monte Carlo methods with regard to the accuracy of the parameter estimates and the usability of both approaches in practice is conducted. Approaches to model choice using integrated nested Laplace approximations are also presented.
The aim of this study was to describe the prevalence, serotypes, and virulence genes of Shiga toxin-producing Escherichia coli (STEC) isolated from raw milk cheese samples collected at the producer level with the purpose of determining whether raw milk cheeses in Switzerland represent a potential source of STEC pathogenic for humans. Raw milk cheese samples (soft cheese, n = 52; semihard and hard cheese, n = 744; all produced from Swiss cows', goats', and sheep's milk) collected at the producer level throughout Switzerland within the national sampling plan during the period of March 2006 to December 2007 were analyzed. Of the 432 cheese samples obtained in the year 2006 and the 364 samples obtained in the year 2007, 16 (3.7%) and 23 (6.3%), respectively, were found to be stx positive. By colony dot-blot hybridization, non-O157 STEC strains were isolated from 16 samples. Of the 16 strains, 11 were typed into 7 E. coli O groups (O2, O15, O22, O91, O109, O113, O174), whereas 5 strains were nontypeable (ONT). Among the 16 STEC strains analyzed, stx(1) and stx(2) variants were detected in 1 and 15 strains, respectively. Out of the 15 strains with genes encoding for the Stx2 group, 4 strains were positive for stx(2), 6 strains for stx(2d2), 2 strains for stx(2-O118), 1 strain for stx(2-06), 1 strain for stx(2g), 1 strain for stx(2) and stx(2d2), and 1 strain for stx(2) and stx(2g). Furthermore, 3 STEC strains harbored E-hlyA as a further putative virulence factor. None of the strains tested positive for eae (intimin). Results obtained in this work reinforce the suggestion that semihard raw milk cheese may be a potential vehicle for transmission of pathogenic STEC to humans.
Food is an important vehicle for transmission of Shiga toxin-producing Escherichia coli (STEC). To assess the potential public health impact of STEC in Swiss raw milk cheese produced from cow's, goat's, and ewe's milk, 1,422 samples from semihard or hard cheese and 80 samples from soft cheese were examined for STEC, and isolated strains were further characterized. By PCR, STEC was detected after enrichment in 5.7% of the 1,502 raw milk cheese samples collected at the producer level. STEC-positive samples comprised 76 semihard, 8 soft, and 1 hard cheese. By colony hybridization, 29 STEC strains were isolated from 24 semihard and 5 soft cheeses. Thirteen of the 24 strains typeable with O antisera belonged to the serogroups O2, O22, and O91. More than half (58.6%) of the 29 strains belonged to O:H serotypes previously isolated from humans, and STEC O22:H8, O91:H10, O91:H21, and O174:H21 have also been identified as agents of hemolytic uremic syndrome. Typing of Shiga toxin genes showed that stx(1) was only found in 2 strains, whereas 27 strains carried genes encoding for the Stx(2) group, mainly stx(2) and stx(2vh-a/b). Production of Stx(2) and Stx(2vh-a/b) subtypes might be an indicator for a severe outcome in patients. Nine strains harbored hlyA (enterohemorrhagic E. coli hemolysin), whereas none tested positive for eae (intimin). Consequently, semihard and hard raw milk cheese may be a potential source of STEC, and a notable proportion of the isolated non-O157 STEC strains belonged to serotypes or harbored Shiga toxin gene variants associated with human infections.
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