Abstract
The outbreak of COVID-19 on the Diamond Princess Cruise Ship provides an unprecedented opportunity to estimate its original transmissibility with basic reproductive number (R0) and the effectiveness of containment measures. We developed an ordinary differential equation-based Susceptible-Exposed-Infected-Recovery (SEIR) model with Bayesian underpinning to estimate the main parameter of R0 determined by transmission coefficients, incubation period, and the recovery rate. Bayesian Markov Chain Monte Carlo (MCMC) estimation method was used to tackle the parameters of uncertainty resulting from the outbreak of COVID-19 given a small cohort of the cruise ship. The extended stratified SEIR model was also proposed to elucidate the heterogeneity of transmission route by the level of deck with passengers and crews. With the application of the overall model, R0 was estimated as high as 5.70 (95% credible interval: 4.23–7.79). The entire epidemic period without containment measurements was approximately 47 days and reached the peak one month later after the index case. The partial containment measure reduced 63% (95% credible interval: 60–66%) infected passengers. With the deck-specific SEIR model, the heterogeneity of R0 estimates by each deck was noted. The estimated R0 figures were 5.18 for passengers (5–14 deck), mainly from the within-deck transmission, and 2.46 for crews (2–4 deck), mainly from the between-deck transmission. Modelling the dynamic of COVID-19 on the cruise ship not only provides an insight into timely evacuation and early isolation and quarantine but also elucidates the relative contributions of different transmission modes on the cruise ship though the deck-stratified SEIR model.
Highlights
The ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first identified in Wuhan, Hubei, China in December 2019 (WHO 2020; Huang et al 2020; Guan et al 2020; Li et al 2020), and declared as a Public Health Emergency of International Concern (PHEIC) on January 30th, 2020 and a global pandemic on March 11st, 2020 (WHO 2020)
We developed an ordinary differential equation-based Susceptible-Exposed-Infected-Recovery (SEIR) model with Bayesian underpinning to estimate the main parameter of reproductive number 5.70 (R0) determined by transmission coefficients, incubation period, and the recovery rate
Note that the figure of 0.75/day is a reflection of transmission coefficient that takes into account the instantaneous change of the SEIR model as depicted in a series of differential Eqs. (2) in contrast the average rate of 0.2/day on COVID-19 occurrence up to Feb-19
Summary
The ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first identified in Wuhan, Hubei, China in December 2019 (WHO 2020; Huang et al 2020; Guan et al 2020; Li et al 2020), and declared as a Public Health Emergency of International Concern (PHEIC) on January 30th, 2020 and a global pandemic on March 11st, 2020 (WHO 2020) To contain such rapid and wide spread of COVID-19 outbreak, it is imperative to unbiasedly estimate the basic reproductive number (R0) defined as the average number of secondary cases generated from a primary case, a useful indicator of infectious disease transmission, locally and globally.
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