African Swine Fever Detection and Transmission Estimates Using Homogeneous Versus Heterogeneous Model Formulation in Stochastic Simulations Within Pig Premises
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
Research Square
Abstract
This study aimed to assess the impact on within-herd transmission dynamics of African swine
fever (ASF) when the models used to simulate transmission assume there is homogeneous
mixing of animals within a barn. Barn-level heterogeneity was explicitly captured using a
stochastic, individual pig-based, heterogeneous transmission model that considers three types of
infection transmission, 1) within-pen via nose-to-nose contact; 2) between-pen via nose-to-nose
contact with pigs in adjacent pens; and 3) both between- and within-pen via distance independent
mechanisms (e.g., via fomites). Predictions were compared between the heterogeneous and the
homogeneous Gillespie models. Results showed that the predicted mean number of infectious
pigs at specific time points differed greatly between the homogeneous and heterogeneous models
for scenarios with low levels of between pen contacts via distance independent pathways and the
differences between the two model predictions were more pronounced for the slow contact rate
scenario. The heterogeneous transmission model results also showed that it may take
significantly longer to detect ASF, particularly in large barns when transmission predominantly
occurs via nose-to-nose contact between pigs in adjacent pens. The findings emphasize the need
for completing preliminary explorations when working with homogeneous mixing models to
ascertain their suitability to predict disease outcomes.
Description
Keywords
African swine fever, Gillespie algorithm, Heterogeneity, Transmission models, Homogeneous mixing
Citation
Ssematimba, A., Malladi, S., Bonney, P. J., Charles, K. M. S., Boyer, T. C., Goldsmith, T., ... & Culhane, M. R. (2022). African swine fever detection and transmission estimates using homogeneous versus heterogeneous model formulation in stochastic simulations within pig premises. https://doi.org/10.21203/rs.3.rs-1420329/v1