Modeling Infectious Disease Dynamics on Cruise Ships:An Enhanced SIR Framework with Risk Index Assessment

Cruise ships, with their dense populations and constant passenger movement, presenthighly dynamic conditions for the spread of infectious diseases. Although strict healthprotocols and monitoring systems are widely implemented, their operational effectiveness often varies. In this study, we develop and analyze an improved Susceptible-Infected-Recovered (SIR) model using early outbreak data to characterize epidemicdynamics in cruise-ship environments. The proposed framework extends the classicalSIR model by incorporating ship-specific factors such as time-dependent transmissionrates and confined-space contact structures. Building on this formulation, we introduce a new infection-risk index that quantifies the likelihood of disease transmissionand serves as an early indicator of outbreak severity. To evaluate the model’s predictive performance and epidemiological relevance, we apply it to empirical data from theMS Voyager COVID-19 outbreak (2021) and an influenza outbreak (2014). Numericalsimulations demonstrate that the enhanced model provides more accurate short-termforecasts and facilitates the identification of effective intervention strategies. These results highlight the value of SIR-based modeling approaches for assessing and mitigatingepidemic risks in closed, mobile populations such as cruise ships.