S.L.G.E. Burgers

Farm factors associated with the use of antibiotics in pig production

The aim of this study was to investigate farm-level economic and technical factors that are associated with the use of antibiotics on pig farms. Identification of such factors, like farm size and net farm result, may help to increase epidemiological knowledge and to specify farm advice and policy making to reduce inappropriate use of antibiotics. The study used over 300 farm-year records collected during 2004 to 2007 from pig farms in the Netherlands. Data included economic and technical factors as well as antibiotic administration. Data were statistically analyzed for factors associated with antibiotic use, both for fattening pig and sow farms (piglets only), separately. The response variable was the average number of daily dosages per average pig year. Statistical analysis was performed on 16 and 19 potential explanatory factors for the fattening pig and sow farms, respectively. The results showed that, both on the fattening pig and sow farms, the average use of antibiotics increased from 2004 to 2006, but decreased during 2007, but the effect of year was not significant (P > 0.05). Use of antibiotics varied between individual farms. Large farm repeatability for the use of antibiotics in the different years was found. Factors associated (P < 0.05) with the use of antibiotics included: farm system, number of pigs, and population density in the region of the farm (for sow farms only). As these factors are easy to collect and to register, they can be used to specify farm advice and investigation, as well as for policy making. The majority of the technical and economic factors were not significantly (P > 0.05) related to the on-farm use of antibiotics. Therefore, it is recommended to focus future research on the potential role of socioeconomic factors associated with antibiotic use on pig farms.

Geographic and Temporal Variations in Population Dynamics of Ixodes ricinus and Associated Borrelia Infections in The Netherlands

In a countrywide investigation of the ecological factors that contribute to Lyme borreliosis risk, a longitudinal study on population dynamics of the sheep tick Ixodes ricinus and their infections with Borrelia burgdorferi sensu lato (s.l.) was undertaken at 24 sites in The Netherlands from July 2006 to December 2007. Study sites were mature forests, dune vegetations, or new forests on land reclaimed from the sea. Ticks were sampled monthly and nymphal ticks were investigated for the presence of Borrelia spp. I. ricinus was the only tick species found. Ticks were found in all sites, but with significant spatial and temporal variations in density between sites. Peak densities were found in July and August, with lowest tick numbers collected in December and January. In some sites, questing activities of I. ricinus nymphs and adults were observed in the winter months. Mean monthly Borrelia infections in nymphs varied from 0% to 29.0% (range: 0%-60%), and several sites had significantly higher mean nymphal Borrelia infections than others. Four genospecies of Borrelia burgdorferi s.l. were found, with B. afzelii being dominant at most sites. Borrelia infection rates in nymphal ticks collected in July, September, and November 2006 were significantly higher (23.7%, p<0.01) than those in the corresponding months of 2007 (9.9%). The diversity in Borrelia genospecies between sites was significantly different (p<0.001). Habitat structure (tree cover) was an effective discriminant parameter in the determination of Borrelia infection risk, as measured by the proportion of nymphal ticks infected with B. burgdorferi s.l. Thickness of the litter layer and moss cover were positively related to nymphal and adult tick densities. The study shows that Borrelia-infected ticks are present in many forest and dune areas in The Netherlands and suggests that in such biotopes, which are used for a wide variety of recreational activities, the infection risk is high.

Descriptive modelling to predict deoxynivalenol in winter wheat in the Netherlands

Predictions of deoxynivalenol (DON) content in wheat at harvest can be useful for decision-making by stakeholders of the wheat feed and food supply chain. The objective of the current research was to develop quantitative predictive models for DON in mature winter wheat in the Netherlands for two specific groups of end-users. One model was developed for use by farmers in underpinning Fusarium spp. disease management, specifically the application of fungicides around wheat flowering (model A). The second model was developed for industry and food safety authorities, and considered the entire wheat cultivation period (model B). Model development was based on observational data collected from 425 fields throughout the Netherlands between 2001 and 2008. For each field, agronomical information, climatic data and DON levels in mature wheat were collected. Using multiple regression analyses, the set of biological relevant variables that provided the highest statistical performance was selected. The two final models include the following variables: region, wheat resistance level, spraying, flowering date, several climatic variables in the different stages of wheat growing, and length of the period between flowering and harvesting (model B only). The percentages of variance accounted for were 64.4% and 65.6% for models A and B, respectively. Model validation showed high correlation between the predicted and observed DON levels. The two models may be applied by various groups of end-users to reduce DON contamination in wheat-derived feed and food products and, ultimately, reduce animal and consumer health risks.

Propagation of Uncertainties in Soil and Pesticide Properties to Pesticide Leaching

In the new Dutch decision tree for the evaluation of pesticide leaching to groundwater, spatially distributed soil data are used by the GeoPEARL model to calculate the 90th percentile of the spatial cumulative distribution function of the leaching concentration in the area of potential usage (SP90). Until now it was not known to what extent uncertainties in soil and pesticide properties propagate to spatially aggregated parameters like the SP90. A study was performed to quantify the uncertainties in soil and pesticide properties and to analyze their contribution to the uncertainty in SP90. First, uncertainties in the soil and pesticide properties were quantified. Next, a regular grid sample of points covering the whole of the agricultural area in the Netherlands was randomly selected. At the grid nodes, realizations from the probability distributions of the uncertain inputs were generated and used as input to a Monte Carlo uncertainty propagation analysis. The analysis showed that the uncertainty concerning the SP90 is 10 times smaller than the uncertainty about the leaching concentration at individual point locations. The parameters that contribute most to the uncertainty about the SP90 are, however, the same as the parameters that contribute most to uncertainty about the leaching concentration at individual point locations (e.g., the transformation half-life in soil and the coefficient of sorption on organic matter). Taking uncertainties in soil and pesticide properties into account further leads to a systematic increase of the predicted SP90. The important implication for pesticide regulation is that the leaching concentration is systematically underestimated when these uncertainties are ignored.

Odours of Plasmodium falciparum -infected participants influence mosquito-host interactions

Malaria parasites are thought to influence mosquito attraction to human hosts, a phenomenon that may enhance parasite transmission. This is likely mediated by alterations in host odour because of its importance in mosquito host-searching behaviour. Here, we report that the human skin odour profile is affected by malaria infection. We compared the chemical composition and attractiveness to Anopheles coluzzii mosquitoes of skin odours from participants that were infected by Controlled Human Malaria Infection with Plasmodium falciparum. Skin odour composition differed between parasitologically negative and positive samples, with positive samples collected on average two days after parasites emerged from the liver into the blood, being associated with low densities of asexual parasites and the absence of gametocytes. We found a significant reduction in mosquito attraction to skin odour during infection for one experiment, but not in a second experiment, possibly due to differences in parasite strain. However, it does raise the possibility that infection can affect mosquito behaviour. Indeed, several volatile compounds were identified that can influence mosquito behaviour, including 2- and 3-methylbutanal, 3-hydroxy-2-butanone, and 6-methyl-5-hepten-2-one. To better understand the impact of our findings on Plasmodium transmission, controlled studies are needed in participants with gametocytes and higher parasite densities.