Predicting the time to detect moderately virulent African swine fever virus in finisher swine herds using a stochastic disease transmission model
Loading...
Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
BMC Veterinary Research
Abstract
African swine fever (ASF) is a highly contagious and devastating pig disease that has caused extensive
global economic losses. Understanding ASF virus (ASFV) transmission dynamics within a herd is necessary in order
to prepare for and respond to an outbreak in the United States. Although the transmission parameters for the highly
virulent ASF strains have been estimated in several articles, there are relatively few studies focused on moderately
virulent strains. Using an approximate Bayesian computation algorithm in conjunction with Monte Carlo simulation,
we have estimated the adequate contact rate for moderately virulent ASFV strains and determined the statistical distributions
for the durations of mild and severe clinical signs using individual, pig-level data. A discrete individual based
disease transmission model was then used to estimate the time to detect ASF infection based on increased mild clinical
signs, severe clinical signs, or daily mortality.
Results: Our results indicate that it may take two weeks or longer to detect ASF in a finisher swine herd via mild
clinical signs or increased mortality beyond levels expected in routine production. A key factor contributing to the
extended time to detect ASF in a herd is the fairly long latently infected period for an individual pig (mean 4.5, 95% P.I.,
2.4 - 7.2 days).
Conclusion: These transmission model parameter estimates and estimated time to detection via clinical signs
provide valuable information that can be used not only to support emergency preparedness but also to inform other
simulation models of evaluating regional disease spread.
Description
Keywords
Surveillance, Mortality triggers, Modeling, Clinical signs detection, African Swine Fever, Moderately virulent strain
Citation
Malladi, S., Ssematimba, A., Bonney, P. J., St Charles, K. M., Boyer, T., Goldsmith, T., ... & Culhane, M. R. (2022). Predicting the time to detect moderately virulent African swine fever virus in finisher swine herds using a stochastic disease transmission model. BMC Veterinary Research, 18(1), 1-9. https://doi.org/10.1186/s12917-022-03188-6