An aqua agent-based model to simulate fish disease dynamics with reference to Norwegian aquaculture

Disease in fish populations is a dynamic phenomenon; oscillations in occurrence and impact are dependent on the interactions among fish (host), pathogen, and environment. While most of the previous models to simulate disease dynamics are based on the assumption that populations are homogeneous, we build an aqua agent-based model that simulate the contiguous disease transmission as a result of interactions between fish, pathogens and their environment in time-space context. This heterogeneous model gives a realistic representation of the system and tackle naturally stochastic nature of the infectious process. The model combines most important factors in the fish disease process, environmental factors, fish swimming behavior and infection process parameters. The simulation experiments are designed to explore the impact of sea currents and swimming behavior on the disease dynamics. The results show that the attack rate increases when the sea current speed decreases, and when the fish swim in a regular pattern (circular or in school). The model can be applied to different applications due to its ability to show the disease progression based on the individuals' interactions. This can help in understanding of disease-spread dynamics and yield to take better steps towards the prevention and control of a disease outbreak.