title: Mean effective sensitivity for Mycobacterium avium subsp. paratuberculosis infection in cattle herds.
abstract: BACKGROUND
  Mycobacterium avium subsp. paratuberculosis (MAP) infections in cattle are generally challenging to detect and cost-effective test strategies are consequently difficult to identify. MAP-specific antibody ELISAs for milk and serum are relatively inexpensive, but their utility is influenced by a number of factors such as herd size, herd composition and diagnostic sensitivity. The sensitivity of the test increases with the age of the tested animal, and therefore the general, or "mean effective sensitivity" (defined as the mean of the sensitivities for all animals within a population, MES), for detecting MAP within a herd is dependent upon the age distribution of the herd. For this study we used a dataset of cattle from 4,259 dairy herds and 4,078 non-dairy herds. The aim was to investigate the MES for groups of cattle considered to be reasonable entities for MAP surveillance and control, in order to assist the decision-makers in planning and optimizing these programs economically. We compared six different groups of cattle (three dairy and three non-dairy) in Denmark by calculating the MES for each herd in each group.
  
  
  RESULTS
  The distribution of MES showed a large variation within and between groups, and in some groups we found a bimodal distribution of MES. Dairy herds generally showed higher MES than non-dairy herds. Dairy herds in a control programme for paratuberculosis showed a MES similar to all other dairy herds from which animals > 2.0 years were tested (both groups had a median MES = 0.60). For the non-dairy groups, the sensitivity became much higher when animals < 2.0 years and herds with less than 25 cattle were excluded, resulting in a median MES of 0.65.
  
  
  CONCLUSIONS
  The results showed that MES could indicate the effectivity of testing different cattle groups for MAP, given that the data used are unbiased.
authors.affiliation: National Veterinary Institute, Technical University of Denmark, Bülowsvej 27, DK-1870, Frederiksberg C, Denmark. ckir@vet.dtu.dk.
authors.forename: Carsten
authors.initials: C
authors.lastname: Kirkeby
authors.affiliation: Department of Applied Mathematics and Computer Science, Technical University of Denmark, DK-2800, Lyngby, Denmark. kagr@dtu.dk.
authors.forename: Kaare
authors.initials: K
authors.lastname: Græsbøll
authors.affiliation: National Veterinary Institute, Technical University of Denmark, Bülowsvej 27, DK-1870, Frederiksberg C, Denmark. tahbh@vet.dtu.dk.
authors.forename: Tariq
authors.initials: T
authors.lastname: Halasa
authors.affiliation: National Veterinary Institute, Technical University of Denmark, Bülowsvej 27, DK-1870, Frederiksberg C, Denmark. ntoft@vet.dtu.dk.
authors.forename: Nils
authors.initials: N
authors.lastname: Toft
authors.affiliation: Department of Large Animal Sciences, University of Copenhagen, Grønnegårdsvej 8, DK-1870, Frederiksberg C, Denmark. saxmose@sund.ku.dk.
authors.forename: Søren Saxmose
authors.initials: SS
authors.lastname: Nielsen
mesh_terms: D000818:Animals; D001431:Bacteriological Techniques / Q000379:methods / Q000662:veterinary*; D002417:Cattle; D002418:Cattle Diseases / Q000175:diagnosis* / Q000453:epidemiology / Q000382:microbiology; D003627:Data Interpretation, Statistical; D003718:Denmark / Q000453:epidemiology; D016927:Mycobacterium avium subsp. paratuberculosis / Q000302:isolation & purification*; D010283:Paratuberculosis / Q000175:diagnosis* / Q000453:epidemiology / Q000382:microbiology; D011159:Population Surveillance; D012307:Risk Factors; D012680:Sensitivity and Specificity