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. A SEIQ(H)R (Susceptibility–Exposed– Infected–Quarantine–(Hospitalisation)–Removed/Recovered) model is developed and fit-tested to simulate the transmission dynamics of COVID-19 on board cargo vessels of up to 60 crew. Due to specific living and working circumstances on board cargo vessels, instead of utilising the reproduction number, we consider the crew members from the same country to quantify the transmission 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 convergence between simulation results and the data verifies the performance of the model. 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 ability to model the evolution of an outbreak, both in duration and severity, is essential to predict outcomes and to plan for the best response strategy. At the same time, if offers a higher degree of certainty regarding the return to trade, which in turn is of significant importance to multiple stakeholders.