Dolphin morbillivirus (DMV) has been responsible for recurrent mass strandings and deaths within many cetacean populations, including the striped dolphin (Stenella coeruleoalba) population in the Mediterranean Sea.
We simulate the striped dolphin population using an individual-based small-world network model (Watts-Strogatz). In this structure we simulate the transmission of the DMV infection with a basic reproductive ratio (Ro) equal to 2.0, where Ro is the average number of secondary infections caused by an infectious individual in a fully susceptible population. However, as the epizootic progresses through the population, the actual number of secondary infections is expected to decrease, resulting in an empirical, or realized, Ro (rRo). We assess rRo at the peak of the epizootic and compare the rate of decline in rRo across different network structures. Since striped dolphins have complex and dynamic social interactions, we tested the rates of decline of rRo across different networks ranging from a regular structure (circulant with P ≈ 0) to a network close to having random interactions (P ≈ 1).
Results/Conclusions
We found that as the epizootic progresses rRo decreases. However, the rate of decrease depends both on time and the network structure (P). The change in rRo, assessed during the epizootic peak, suggests that when dolphins are relatively social (high levels of mixing) DMV spreads rapidly while the rate of actual secondary infections (rRo) decreases rapidly. This work suggests the importance of rRo as a tool for understanding the dynamics of epizootics.
