Table II.
Input parameters used to model BTV-8 surveillance using stochastic scenario trees. The SSC considered are: SEROFARM = individual blood serology on farm; BMT = bulk milk testing on dairy cattle farm; CLIN = passive clinical surveillance in sheep and cattle farms, respectively; ABT = abortion testing.
| Description of input parameter | Value | Source |
|---|---|---|
| Design prevalence P*H | 0.002 | Set arbitrarily |
| Sensitivity of blood serology for SEROFARM | RiskPert (0.99; 0.995; 1.00) | Personal opinion (based on data for c-ELISA) |
| Sensitivity of milk serology for BMT | RiskPert (0.99; 0.995; 1.00) | Personal opinion (based on data for ID Screen®) |
| Probability for abortions in cattle due to BTV-8 | RiskPert (0.00; 0.016; 0.30) | [2] |
| Probability for clinical symptoms in cattle due to BTV-8 | RiskPert (0.039; 0.07; 0.47) | [2] |
| Probability for clinical symptoms in sheep due to BTV-8 | RiskPert (0.047; 0.15; 0.48) | [2] |
| Probability that cattle farmer calls veterinarian | RiskPert (0.1; 0.2; 0.3) | Low estimated disease awareness |
| Probability that veterinarian suspects BTV-infection in cattle | RiskPert (0.1; 0.2; 0.3) | Low estimated disease awareness |
| Probability that sheep farmer calls veterinarian | RiskPert (0.1; 0.2; 0.3) | Low estimated disease awareness |
| Probability that veterinarian suspects BTV-infection in sheep | RiskPert (0.4; 0.5; 0.6) | Medium estimated disease awareness |