1. Geographical pattern of Q fever in Danish dairy cattle farms An epidemiological study of serological data from 2007 Material and methods Until 2003 antibodies against Q fever were detected by complement fixation test (CFT). In 2003 a commercial ELISA kit from Pourquier was evaluated and found more sensitive than CFT. Since then the ELISA technique has been used in analysis for antibodies against Q fever. In 2007 a commercial milk ELISA kit from IDEXX was introduced into the laboratory. At first the milk test was used in combination with a testing of blood samples from a small number of cattle with fertility problems. Later on the vets often submitted milk samples only. Both commercial kits are operating with a negative and a positive cut off, values between these cuts are ‘dubious’. The test results are expressed as S/P values. S is the titre of the sample; P is the titre of the positive control used in the actual test. Bulk tank milk samples from 742 dairy farms were analysed for antibodies against Q fever (figure 1b). From 51 farms blood samples were submitted as well. The spatial pattern of submission rates was examined using spatial scan statistics. Similarly the proportion of positive test results among the submitted samples was tested for geographically clustering using spatial scan statistics. Finally four potential risk factors for Q fever were tested in a logistic regression analysis. To adjust for the observed geographical clustering of infected farms the country was divided into 6 regions which were included as fixed effects in the analysis (table). Discussion and conclusions The samples did not represent random samples as they were submitted for diagnostic purposes or because the vet or the farmer wanted to know if antibodies were present in bulk tank milk. Geographical areas with significantly increased and decreased submission rates were identified (figure 1a). 57% of the tested farms were positive in the milk ELISA. In 51 farms, which had submitted blood samples as well, 35 farms (68%) were tested positive in the milk ELISA, while the blood samples tested 13 farms (25%) positive. Using spatial scan statistics a strong geographical trend was identified with relatively more positive farms in the western part of the country (figure 1c). In a multivariate logistic regression analysis the geographical region and the size of the farm were identified as independent significant risk factors for the presence of Q fever antibodies in Danish dairy farms (table). Anna-Bodil Christoffersen and René Bødker Introduction Blood samples from cattle with abortions were systematically tested for antibodies against Q fever since 2003. During the period 2003-2006 antibodies against Q fever were found in 15-35% of the blood samples. The blood samples were submitted for diagnostic purpose, either because of abortion, endometritis or problems with fertility. Since 1989 the National Veterinary Institute has registrated a very low level of Q fever positive blood samples (1-5%) from healthy heifers, for export. Anna-Bodil Christoffersen, Serologist, DVM, Phone +45 35 88 62 26, anchr@vet.dtu.dk René Bødker, Epidemiologist, PhD, MSc in biology, Phone +45 45 35 88 63 66, rebo@vet.dtu.dkanchr@vet.dtu.dkrebo@vet.dtu.dk Bülowsvej 27 DK-1790 Copenhagen V Denmark Logistic regression analysis of four potential risk factors for Q fever. First each risk factor was analysed in four separate univariate analysis. Secondly the four risk factors were analysed jointly in a multivariate analysis including six geographical regions as a risk factors (six regions as fixed effects). Herds positive for Q fever Herds negative for Q fever Odds ratioCI 95% odds ratio (422)(315)lowerupper The results of the individual univariate analysis of each of the four risk factors S. Dublin > 25 ODC %16.8%9.2%1.9951.2603.157 Herd size (mean)287.0226.5*1.004*1.0031.006 Number of different herds supplying animals (mean) 2.11.51.0771.0131.145 Number of purchased animals (mean)29.517.11.0061.0021.010 The result of the corresponding multivariate analysis including six geographical regions. (non-significant risk factors were removed from the model using backward logistic regression) Herd size (mean)287.0226.5*1.004*1.0031.006 East Jutland (number of herds)13390- **-- Bornholm (number of herds)4410.064**0.0220.188 Funen (number of herds)35300.688**0.3851.228 Seeland (number of herds)20250.570**0.2951.102 South Jutland (number of herds)105670.842**0.6201.431 West Jutland (number of herds)125621.304**0.8611.967 * Equivalent to an odds ratio of 1.53 per 100 extra animals in the herd. ** East Jutland is reference region for the odds ratio. Figure 1c Clusters of farms where the number of positive bulk tank milk samples are significantly high (red) or significantly low (blue) compared to all bulk tank milk submissions. All submissions are marked red, blue or grey. Figure 1a Red, blue, and grey circles indicate all 5,156 cattle dairy farms in 2007 in Denmark. 12 different geographical clusters were identified with significant more (red circles) or less (blue circles) farms submitting bulk tank milk samples for testing. Figure 1b Farms that submitted bulk tank milk samples during 2007. Positive farms are marked with red circles, negative farms are marked with blue circles, and dubious are marked with yellow circles. 423 (57.0%) farms were positive, 46 (6.2%) were dubious, and 273 (36.8%) were negative. Technical University of Denmark National Veterinary Institute