Modelling the spread of Salmonid Rickettsial Septicaemia and assessing regional control strategies for saltwater salmon farms in Aysén, Chile.

Salmonid Rickettsial Septicaemia (SRS) is a highly infectious, endemic disease that spreads among saltwater salmonid farms in Chile, making control efforts challenging. Here, we present a model that simulates SRS transmission between saltwater salmonid farms in the Aysén region of Chile, using the state-transition model framework InterSpread Plus (ISP). In ISP, the status (e.g., susceptible or infectious) of farms is individually defined, and the simulation determines the transition of the farms' state over time. Farm characteristics, such as fish species and production size, were incorporated into the model. The model parameters were estimated based on data collected from 432 farms between 2011 and 2020, expert opinions, and literature reviews. The simulation included an average of 150 active farms per week, with a total of 46,380 active farm-weeks. The model had a one-year simulation period and was used to simulate the annual spread of P. salmonis between salmonid farms for each year from 2013 to 2019 (i.e., six one-year model simulations, each starting in September of the respective year). Model accuracy was estimated based on 1 minus the cumulative difference between the simulated and observed weekly SRS prevalence at the regional level. The average annual model accuracy for the six one-year models was 95.0 % (range: 91.7 - 96.0 %). The baseline model was used to explore a total of 19 "what-if" control scenarios addressing one of the three following strategies: (i) depopulation of infected farms, (ii) reducing number of farms in neighbourhoods, and (iii) vaccination. The impact of these scenarios was assessed based on the estimated annual incidence rate of SRS over 6 years (i.e., 2013-2019). The three most effective scenarios for reducing the annual incidence rate of SRS were: (i) immediate depopulation of infected farms, (ii) strategic removal of 30 % of highly connected farms per neighbourhood, and (iii) industry-wide implementation of a hypothetical vaccine with at least 75 % efficacy for a minimum of 9 months. However, the estimated number of fish harvested and the estimated use of antibiotics for each of these control scenarios, compared to the baseline models, suggested that they may not be cost-effective for the industry. Future research should include cost-effectiveness analyses to identify the most economical measures for the industry. The ISP model in this study introduces a novel application of this software for managing SRS in the Chilean Aysén region and could serve as a decision-support tool for policymakers, epidemiologists and fish health professionals.