title: Complex system modelling for veterinary epidemiology.
abstract: The use of mathematical models has a long tradition in infectious disease epidemiology. The nonlinear dynamics and complexity of pathogen transmission pose challenges in understanding its key determinants, in identifying critical points, and designing effective mitigation strategies. Mathematical modelling provides tools to explicitly represent the variability, interconnectedness, and complexity of systems, and has contributed to numerous insights and theoretical advances in disease transmission, as well as to changes in public policy, health practice, and management. In recent years, our modelling toolbox has considerably expanded due to the advancements in computing power and the need to model novel data generated by technologies such as proximity loggers and global positioning systems. In this review, we discuss the principles, advantages, and challenges associated with the most recent modelling approaches used in systems science, the interdisciplinary study of complex systems, including agent-based, network and compartmental modelling. Agent-based modelling is a powerful simulation technique that considers the individual behaviours of system components by defining a set of rules that govern how individuals ("agents") within given populations interact with one another and the environment. Agent-based models have become a recent popular choice in epidemiology to model hierarchical systems and address complex spatio-temporal dynamics because of their ability to integrate multiple scales and datasets.
authors.affiliation: Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, University of Tennessee, 2407 River Drive, Knoxville, TN 37996, USA; National Institute for Mathematical and Biological Synthesis, University of Tennessee, 1122 Volunteer Blvd, Knoxville, TN 37996, USA. Electronic address: clanzas@utk.edu.
authors.forename: Cristina
authors.initials: C
authors.lastname: Lanzas
authors.affiliation: Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, University of Tennessee, 2407 River Drive, Knoxville, TN 37996, USA.
authors.forename: Shi
authors.initials: S
authors.lastname: Chen
mesh_terms: D000818:Animals; D001699:Biometry / Q000379:methods; D003141:Communicable Diseases / Q000453:epidemiology / Q000635:transmission / Q000662:veterinary*; D016358:Contact Tracing / Q000379:methods / Q000662:veterinary; D004196:Disease Outbreaks / Q000662:veterinary; D004812:Epidemiologic Methods / Q000662:veterinary*; D008954:Models, Biological; D008962:Models, Theoretical; D014730:Veterinary Medicine
keywords: Agent-based model; Complex systems; Mathematical modelling; Network; Veterinary epidemiology