Title:	LiveWild
DNr:	NAISS 2025/5-548
Project Type:	NAISS Medium Compute
Principal Investigator:	Tom Lindström <tom.lindstrom@liu.se>
Affiliation:	Linköpings universitet
Duration:	2025-10-01 – 2026-10-01
Classification:	10611
Keywords:

Abstract

The project will have two potentially overlapping scopes: Livestock Epidemiology and Wildlife Management. For Livestock Epidemiological Modeling, we focus on transboundary animal diseases (TADs), which are a major threat to the agricultural system, potentially affecting food security and the economy. Many tools used to understand potential disease spread and the effect of response actions inherently require an underlying model. We have developed three models that we currently work with: the Animal Movement Model (AMM); the Disease Outbreak Simulation (DOS); and a specialized model for exploring bovine tuberculosis (bTB) in Michigan, U.S. Our team has significant expertise and previous successes with livestock shipment and TAD modeling. AMM is a Bayesian hierarchical model and uses incomplete samples of cattle shipments in a Markov Chain Monte Carlo (MCMC) algorithm to predict the complete cattle shipment networks in space and time at the national scale. DOS is a model for simulating TADs in nation-wide agricultural systems on the level of the individual premises or herd. It takes two transmission routes into account: long-range due to shipments informed by AMM and local spread using a spatially implicit, density-dependent kernel parameterized from published disease outbreak data. Our bTB model is a Bayesian hierarchical state-space model that fits parameters of a within-herd model of the spread of bTB to multi-year test data while taking long-term population dynamics of the herds into account. The model is informed using data from a certain subset of the cattle farm population of Michigan, where bTB is a large problem. We continuously work on refining and expanding the models to include new features, specific scenarios, additional data, and the like in order to facilitate more detailed risk assessment, application to a wider range of diseases, a wider range of disease models. Because of the recent outbreak of Highly Pathogenic Avian Influenza in the US, we will, for the coming years, primarily shift our focus with AMM and DOS to this emergent disease. With the bTB model, we will determine test sensitivity and specificity for the diagnostic procedures used in the bTB eradication program in the U.S. bTB is notoriously difficult to diagnose, as there is no gold standard for determining infection. This also means that accurately determining the sensitivity and specificity of diagnostic tests is nontrivial and requires a sophisticated modeling approach. Because the group and scope have grown lately, we ask that computational needs for future projects will not be solely based on previous utilization to avoid bottlenecks and challenges to meet tight deadlines.