Modeling the Impact of Exposed Cases in a Hantavirus Outbreak on a Cruise Ship

TL;DR

This study presents a stochastic model to understand hantavirus transmission on a cruise ship, emphasizing hidden infections and the importance of rapid testing and quarantine to control outbreaks.

Contribution

It introduces a novel discrete-time stochastic model calibrated with real data to estimate hidden infections and outbreak risk in confined settings.

Findings

Estimated basic reproduction number of 2.76 indicating high transmission potential.

Identified that symptom-based surveillance may miss many exposed individuals.

Highlight the need for rapid testing and active monitoring to prevent onboard outbreaks.

Abstract

The emergence of a hantavirus variant aboard a commercial cruise ship presents a significant public health concern. This study develops a discrete-time stochastic Susceptible-Exposed-Infectious-Recovered-Dead model to estimate transmission dynamics, hidden exposed infections, and outbreak risk among passengers and crew. Epidemiological parameters and latent disease states were inferred using an Ensemble Adjustment Kalman Filter calibrated to reported case data from WHO and ECDC situation reports. The estimated basic reproduction number was 2.76, with a 95\% confidence interval of 2.52-2.99, indicating substantial potential for sustained onboard transmission before strict quarantine measures. Simulations further suggest that several exposed individuals may remain unidentified during the early outbreak phase, creating a hidden reservoir that symptom-based surveillance alone may fail to detect. These findings highlight the importance of rapid surveillance, widespread testing, targeted quarantine, and active monitoring of exposed individuals in confined travel settings. The proposed modeling framework can support timely outbreak assessment and intervention planning for infectious-disease events in similarly dense and spatially constrained populations.