Abstract
This study introduces the WiBISS model, a simulation tool designed to assess the economic and epidemiological impact of a hypothetical African Swine Fever (ASF) vaccination in wild boar in Northern Italy. Using real ASF outbreak data from January 2022 to June 2024, the model evaluates how prompt vaccination could reduce disease spread and economic losses. WiBISS integrates three modules: vaccination simulation, restriction zone estimation, and economic impact analysis. The first two use custom-built cellular automata (CA) in Python and ArcGIS Pro, modeling each ASF case as a cell that can be in one of three states: unvaccinated, infected, or vaccinated. Weekly iterations over 2.5 years simulate ASF progression and vaccination impact based on localized interactions and a defined vaccination radius. Three vaccination scenarios were tested: (1) a non-vaccination baseline; (2) an "ideal" scenario with immediate, 100% vaccination; and (3) multiple "realistic" scenarios with an 8-week delay and varied vaccination rates (25-75%) and radii (10-50 km). The most effective realistic scenarios (e.g., 75% vaccination rate, 50 km radius) showed a total loss of €601,800, close to the ideal scenario. WiBISS prioritizes usability over epidemiological complexity, omitting detailed virus transmission modeling to enhance applicability in data-scarce regions. Unlike detailed stochastic models, WiBISS offers rapid, economically grounded insights to guide initial outbreak response and resource allocation. Although it does not include domestic pigs due to differing transmission dynamics, WiBISS lays a foundation for phased, integrated wildlife vaccination planning that balances economic feasibility with ecological realism.