title: Spatial patterns of bovine corona virus and bovine respiratory syncytial virus in the Swedish beef cattle population.
abstract: BACKGROUND
  Both bovine coronavirus (BCV) and bovine respiratory syncytial virus (BRSV) infections are currently wide-spread in the Swedish dairy cattle population. Surveys of antibody levels in bulk tank milk have shown very high nationwide prevalences of both BCV and BRSV, with large variations between regions. In the Swedish beef cattle population however, no investigations have yet been performed regarding the prevalence and geographical distribution of BCV and BRSV. A cross-sectional serological survey for BCV and BRSV was carried out in Swedish beef cattle to explore any geographical patterns of these infections.
  
  
  METHODS
  Blood samples were collected from 2,763 animals located in 2,137 herds and analyzed for presence of antibodies to BCV and BRSV. Moran's I was calculated to assess spatial autocorrelation, and identification of geographical cluster was performed using spatial scan statistics.
  
  
  RESULTS
  Animals detected positive to BCV or BRSV were predominately located in the central-western and some southern parts of Sweden. Moran's I indicated global spatial autocorrelation. BCV and BRSV appeared to be spatially related: two areas in southern Sweden (Skaraborg and Skåne) had a significantly higher prevalence of BCV (72.5 and 65.5% respectively); almost the same two areas were identified as being high-prevalence clusters for BRSV (69.2 and 66.8% respectively). An area in south-east Sweden (Kronoberg-Blekinge) had lower prevalences for both infections than expected (23.8 and 20.7% for BCV and BRSV respectively). Another area in middle-west Sweden (Värmland-Dalarna) had also a lower prevalence for BRSV (7.9%). Areas with beef herd density > 10 per 100 km(2) were found to be at significantly higher risk of being part of high-prevalence clusters.
  
  
  CONCLUSIONS
  These results form a basis for further investigations of between-herds dynamics and risk factors for these infections in order to design effective control strategies.
authors.affiliation: ONIRIS, UMR Bioagression, Epidémiologie et Analyse de Risque, Nantes, France. francois.beaudeau@oniris-nantes.fr
authors.forename: Francois
authors.initials: F
authors.lastname: Beaudeau
authors.forename: Camilla
authors.initials: C
authors.lastname: Björkman
authors.forename: Stefan
authors.initials: S
authors.lastname: Alenius
authors.forename: Jenny
authors.initials: J
authors.lastname: Frössling
mesh_terms: D000818:Animals; D000914:Antibodies, Viral / Q000097:blood; D002417:Cattle; D002418:Cattle Diseases / Q000453:epidemiology / Q000821:virology*; D016000:Cluster Analysis; D018352:Coronavirus Infections / Q000453:epidemiology / Q000662:veterinary* / Q000821:virology; D017938:Coronavirus, Bovine / Q000302:isolation & purification*; D003430:Cross-Sectional Studies; D004797:Enzyme-Linked Immunosorbent Assay / Q000662:veterinary; D018357:Respiratory Syncytial Virus Infections / Q000453:epidemiology / Q000662:veterinary* / Q000821:virology; D018112:Respiratory Syncytial Virus, Bovine / Q000302:isolation & purification*; D012141:Respiratory Tract Infections / Q000453:epidemiology / Q000662:veterinary* / Q000821:virology; D016036:Seroepidemiologic Studies; D013548:Sweden / Q000453:epidemiology
chemical_list: D000914:Antibodies, Viral