Simulation of Premovement Active Surveillance Protocols for Moving Finishing Pigs to a Harvest Facility from a Control Area during an Outbreak of African Swine Fever in the United States

• Published in: Transboundary and emerging diseases Vol. 2024; no. 1
• Main Authors: Bonney, Peter J., Malladi, Sasidhar, Ssematimba, Amos, O’Hara, Kathleen C., Remmenga, Marta D., Farr, Michelle, Leonard, Mickey, Alexander, Catherine Y., Blair, Benjamin, Martin, Sylvia Wanzala, Culhane, Marie R., Corzo, Cesar A.
• Format: Journal Article
• Language: English
• Published: Berlin Hindawi Limited 01.01.2024
• Subjects: Active control; African swine fever; Barns; Binomial distribution; Biosecurity; Critical components; Disease control; Disease transmission; Farm buildings; Farms; Fever; Harvesting; Hogs; Morbidity; Mortality; Motion perception; Movement; Outbreaks; Sampling; Simulation; Stochasticity; Strains (organisms); Surveillance; Swine; Virulence; United States > US
• ISSN: 1865-1674; 1865-1682
• DOI: 10.1155/2024/6657600

Movement restrictions are a critical component of response plans for an African swine fever (ASF) outbreak in the United States. These restrictions are likely to include requiring permits to move animals and products within, into, and out of 5‐km control areas (CAs) established around confirmed positive farms. For quarantined finishing farms located within a CA, diagnostic testing is an expected criterion for receival of a permit to move pigs to a harvest facility or removal of quarantine. A stochastic disease transmission and active surveillance model were used to evaluate premovement active surveillance protocols varying by the number of samples and timing of sample collection before movement. Surveillance protocol scenarios were evaluated for several different sampling prioritization schemes; virus strains of medium or high virulence; barn sizes of 1,200, 2,400, and 4,800 pigs; and farms with average to high mortality and morbidity during routine production. Surveillance protocols that included prioritization schemes targeting dead pigs and pigs with clinical signs resulted in the highest probabilities of detection and the lowest numbers of infectious pigs at the time of movement in barns that went undetected. There was some evidence that targeting sick pigs prior to dead pigs may be more effective for moderately virulent strains. However, in most scenarios, including all highly virulent strain scenarios and moderately virulent strain scenarios in barn sizes of 1,200 with average farm performance, prioritization of dead versus sick pigs first did not have a large impact on the predicted outcomes. Increasing sample sizes improved outcomes, though only marginal gains were achieved once the available dead and sick were sampled. Predicted outcomes may be further improved by sampling the available dead and sick pigs in a barn across multiple days, though the associated increase in the probability of detection was minor.