scieee AI-readable full text Open interactive document viewer

Software M code for exploring virus dynamics in multi-species systems

Adekunle, Familusi; Bidegain, Gorka; Ben-Horin, Tal

Abstract

In recent decades, the global expansion of Pacific oyster (Crassostrea gigas) aquaculture, driven by its adaptability and rapid growth, has coincided with the emergence of novel microvariants (vars) of the virulent Ostreid herpesvirus 1 (OsHV-1), causing significant industry losses. As a potential alternative, the American oyster (Crassostrea virginica) demonstrates lower susceptibility to 4OsHV-1. This study developed a transmission model for OsHV-1 in mixed oyster aquaculture systems, focusing on the impact of C. virginica introductions on transmission dynamics within established C. gigas systems. The model considers oyster growth, mortality, filtration, viral particle release, and environmental decay. Simulations, including monoculture and co-culture scenarios (10/90, 40/60, 50/50 proportions), were validated against experimental data. Results indicated that introducing C. virginica did not impede OsHV-1 progression; even in the 90/10 system, C. gigas mortality reached its maximum, albeit delayed by approximately 10 days. Co-culture scenarios did not provide a significant advantage for C. gigas, likely due to viral particle saturation in the water column. The model’s performance across diverse scenarios positions it as a valuable tool for understanding waterborne pathogen dynamics in mixed host-species systems, supporting investigations into aquaculture species introductions and their influence on disease dynamics.

Full text

Software M code for modelling virus dynamics in multispecies ecosystems Familusi Oluwatosin Adekunlea,b,c, Gorka Bidegainb,c, Tal Ben-Horind aInstitut des Sciences de la Mer, L’Universit´e du Qu´ebec `a Rimouski, All´ee des Ursulines, Rimouski, 3300, Qc, Canada bDepartment of Applied Mathematics, University of the Basque Country (UPV/EHU), Plaza Europa 1, Donostia, 20018, Gipuzkoa, Spain cResearch Centre for Experimental Marine Biology and Biotechnology, Plentzia Marine Station, University of the Basque Country (PiE-UPV/EHU), Areatza Pasealekua, Plentzia, 48620, Bizkaia, Spain dNorth Carolina State University, College of Veterinary Medicine, 303, College Circle, Morehead City, NC 28557, North Carolina, USA Abstract We present an M-code (MATLAB) modeling toolkit for waterborne viral transmission in mixed-species communities. The framework couples host processes—growth, background mortality, and filtration/clearance—with viral processes—shedding/release, environmental transport, and decay—and supports both monoand co-culture configurations. In contexts lacking coculture infection data, parameters can be calibrated to monoculture observations and then explored across species mixtures. We verify mathematical consistency and realistic behavior across wide composition gradients (e.g., 90/10 to 10/90). Using an oyster–herpesvirus (OsHV-1) case study with M. gigas and C. virginica, simulations show that adding a second, more tolerant host does not halt epidemic progression in the susceptible host; peak mortality still occurs but is delayed, consistent with saturation of viral particles in the water column that limits dilution benefits. The toolkit replicates observed monoculture dynamics and generalizes to multispecies scenarios, enabling hypothesis testing about species introductions, husbandry strategies, and environmental controls on transmission. Overall, it provides a transparent, extensible platform for investigating pathogen dynamics in multispecies ecosystems and for evaluating management options in aquaculture and beyond. Keywords: Modelling, Ostreid Herpesvirus 1, co-culture, C. virginica,M. October 16, 2025 gigas 1. Publication1 This code was developed and applied for the study ”Coculture with East-2 ern oysters is unlikely to reduce OsHV-1 impacts to farmed Pacific oysters: A3 modelling approach” published in Aquaculture Reports (Elsevier) https://4 www.sciencedirect.com/science/article/pii/S2352513424006550. This5 modelling work and parameter estimates are based on empirical research.6 2