Predicting the Time to Detect Moderately Virulent African Swine Fever Virus in Finisher Swine Herds Using a Stochastic Disease Transmission Model

Abstract

Background: 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.

African Swine Fever Detection and Transmission Estimates Using Homogeneous Versus Heterogeneous Model Formulation in Stochastic Simulations Within Pig Premises

“…In this section, we evaluate the predicted time to ASF detection under various transmission scenarios to understand how heterogeneous transmission, transmission in clusters due to adjacent pen spread, and barn size impacts the time to detection via daily mortality trigger thresholds. We previously estimated the transmission parameters for moderately virulent ASFV strains using data presented in (de Carvalho Ferreira et al, 2013) in previous work (Malladi et al, 2022).…”

“…Analysis of mortality data from five flows and 248 finisher herds indicated that a daily mortality trigger threshold of 5 per 1000 finisher pigs results in a low frequency of false triggers (Malladi et al, 2022). The time to detection was then calculated as the earliest day when the simulated daily mortality exceeded a specified fraction of the herd (i.e., daily mortality trigger threshold).…”

“…The authors would like to acknowledge the informal contributions and support of the entire Secure Food Systems team at the University of Minnesota, which also includes Catherine Table 1 and based on Malladi et al (2022). Two barn configurations and population sizes were evaluated, specifically: 1) a growing pig barn with two rows of pens separated by a central alleyway with each row having 15 pens, each holding 40 pigs with a total population of 1,200 pigs; and 2) a hypothetical growing pig barn with two rows of 120 pens each, again separated by a central hallway and each pen holding 40 pigs, but with a larger total population of 4,800 pigs.…”

“…A similar approach is used by Nielson et al (2017) who assume ASFV can be transmitted to non-adjacent pens according to a distance-dependent scaling factor. On the other hand, Barongo et al (2016) and Malladi et al (2022) assume homogeneous mixing of the pigs in the population.…”