Modeling infectious disease dynamics on cruise ships: an enhanced SIR framework with risk index assessment

Abstract

Cruise ships, with their dense populations and constant passenger movement, present highly dynamic conditions for the spread of infectious diseases. Although strict health protocols 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 epidemic dynamics in cruise-ship environments. The proposed framework extends the classical SIR model by incorporating ship-specific factors such as transmission rates and confined-space contact structures. Building on this formulation, we introduce a new infection-risk index that quantifies the likelihood of disease transmission and 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 the MS Voyager COVID-19 outbreak (2021) and an influenza outbreak (2014). Numerical simulations demonstrate that the enhanced model provides more accurate short-term forecasts and facilitates the identification of effective intervention strategies. These results highlight the value of SIR-based modeling approaches for assessing and mitigating epidemic risks in closed, mobile populations such as cruise ships.