An Agent-Based Model of Plant Disease Diffusion and Control: Grapevine Leafroll Disease

The grapevine leafroll disease (GLRD) threatens grape harvests in the United States and the world. This viral disease reduces yield, delays fruit ripening, and affects wine quality. The disease ecology is still under study and the spatial-dynamics of the spread process remains poorly understood. Moreover, little is known about cost-efficient strategies to control the disease. In an effort to address this gap in the literature, we model GLRD diffusion in a vineyard and evaluate bioeconomic outcomes under alternative disease control strategies. We employ agent-based modeling (ABM) tools and contribute to bioeconomic literature on agricultural disease control in several ways. First, our model relaxes the assumption of agent homogeneity and allows instead agents to be heterogeneous in age and infection states, thus in their economic values. Second, we make the model inherently spatial-dynamic by combining the ABM with a cellular automaton system. Third, we incorporate realism when modeling the spread process by making the disease onset and its transmission stochastic. That is, initial infections follow a random spatial distribution and stochastic agent interaction gives rise to Markov process-type disease diffusion. Finally, we formulate novel control strategies consisting of roguing and replacing infected grapevines based on their age and infection states. We evaluate these strategies and identify those that perform best at extending the expected vineyard half-life and at maximizing the vineyard expected net present values relative to the baseline of no control. The model results underscore the ecological and economic tradeoffs implied by disease control strategies based on age and infection states.