Development of a mathematical model to predict the health impact and duration of SARS-CoV-2 outbreaks on board cargo vessels

Abstract

The Coronavirus Disease (COVID-19) pandemic has brought significant impact onto the maritime activities worldwide, including disruption to global trade and supply chains. The ability to predict the evolution and duration of a COVID-19 outbreak on cargo vessels would inform a more nuanced response to the event and provide a more precise return-to-trade date. This paper presents the SEIQ(H)R (Susceptibility–Exposed–Infected–Quarantine–(Hospitalisation)–Removed/Recovered) model, which is the first deterministic mathematical model developed and fit-tested to describe the transmission dynamics of COVID-19 on board cargo vessels of up to 60 crew members. Due to specific living and working circumstances on board cargo vessels, instead of utilising the reproduction number, we consider the highest fraction of crew members who share the same nationality to quantify the transmissibility of the disease. The performance of the model is verified using case studies based on data collected during COVID-19 outbreaks on three cargo vessels in Western Australia during 2020. The simulations show that the model can forecast the time taken for the transmission dynamics on each vessel to reach their equilibriums, providing informed predictions on the evolution of the outbreak, including hospitalisation rates and duration. The model demonstrates that (a) all crew members are susceptible to infection; (b) their roles on board are a determining factor in the evolution of the outbreak; and (c) an unmitigated outbreak could affect the entire crew and continue on for many weeks. The ability to model the evolution of an outbreak, in both duration and severity, is essential to predict outcomes and to plan for the best response strategy. At the same time, it offers a higher degree of certainty regarding the return to trade, which is of significant importance to multiple stakeholders.

COVID Pandemics and Inland Transportation in the Brazilian Amazon: A Note on the Risks of Infection in Typical Passenger Vessels

“…On the other hand, recent engineering studies have investigated adequate layout of passengers and cargo areas of passenger vessels using numerical methods [33,34], as well as the duration and health impact of COVID-19 outbreaks in cargo vessels using mathematical approaches [35]. Huang et al [33,34] used computational fluid dynamics methods to evaluate the dispersion of airborne fluids, such as those derived from coughing, and proposed guidance on the recommended passenger distribution to avoid interaction with the fluid.…”