Infection with the classical swine fever virus (CSFV) causes a disease in pigs that ranges from a hyperacute form in which animals die in a few hours to subclinical disease. Due to this wide range of virulence, several complementary surveillance strategies should be implemented for the early detection of the disease. The objective of the present study was to determine the sensitivity of the surveillance system to detect CSFV outbreaks in a free zone (Zone 1) and in a zone undergoing an eradication process (Zone 2) in Colombia. Stochastic scenario tree models were used to describe the population and surveillance structures and to determine the probability of CSFV detection. The total sensitivity of the surveillance system in the case of a single infected farm in Zone 1 was 31.4% (CI 95%: 7.2–54.1) and in the case of 5 infected farms was 85.2% (CI 95%: 67.3–93.7), while in Zone 2 the sensitivities were 27.8% (CI 95%: 6.4–55.1) and 82.5% (CI 95%: 65–92.9), respectively. The on-farm passive surveillance shows the highest sensitivity for detection of a single CSFV infected farm in both zones (22.8% in Zone 1 and 22.5% in Zone 2). The probability of detection was higher in a family / backyard premise than on a commercial farm in both zones. The passive surveillance at slaughterhouse had a sensitivity of 5.3% and 4.5% for the detection of a single infected farm in Zone 1 and 2, respectively. Active surveillance presented a range of sensitivity between 2.2% and 4.5%. In conclusion, the sensitivity of the surveillance in the two studied zones was quite high, one of reasons for this good sensitivity being the sentinel network based on the voluntary participation of 5,500 collaborators that were trained for the identification and notification of diseases of national interest.
|Journal||Transboundary and emerging diseases|
|Publication status||Accepted in press - 2021|
- scenario tree
- stochastic modelling