Last updated: 23 December 2020
Every vessel has a comparative risk rating, which is an output of our Covid-19 model. The epidemiological model takes in several factors about a vessel’s history and daily incidence rates of Covid-19 in order to mathematically simulate contagion scenarios.
The colour of the vessel on the map represents the estimated comparative risk of crew onboard being infected with Covid-19. Red means higher risk, orange and yellow lower. The risk rating can also be found in the vessel report and on the vessel details panel.
Due to the unpredictable nature of real-world outbreaks, the rating is not meant to be definitive, but rather representative of the most-likely scenario. Note that a vessel with comparatively high risk rating will still have low absolute probability of infection (i.e. <1%).
Covid-19 information is updated daily at approximately 4 pm NZST.
The Covid-19 risk is assessed using an epidemiological model that mathematically estimates likely contagion scenarios based on a vessel’s travel history.
Our model is based on the work of public health experts Wilson et al. 2 and is derived from a stochastic version of the compartmental CovidSIM model 6, which assigns people to compartments based on their infection status (susceptible, exposed, infectious, and recovered/removed) and accounts for the unpredictable nature of real-world outbreaks.
The model is populated with parameters for SARS-CoV-2 transmission, historical infection rates across the globe, and shipping characteristics for each vessel. A list of parameters is found in Table 1.
For each vessel, we consider an initially uninfected crew of 20 at a time 30 days ago. At each subsequent port visit, there is the possibility that crew may become infected as a result of interaction with the community, due to either shore leave or routine contact with port staff, stevedores, maintenance workers, etc. Contagiousness for the duration a vessel was in port, as defined by the effective reproduction number, is 2.5 2. Historical infection rates at the time the vessel was in port for each port country are obtained from Johns Hopkins University 7.
During the subsequent voyage, any infected crew members can potentially infect others on board. Contagiousness aboard the vessel is set at 3.0 2. We assumed that 71% of infected Covid-19 cases develop clearly detectable symptoms 2.
This process is repeated sequentially until the present time, at which the number of infected crew members is counted. Due to the very high probability of zero infected crew members, the simulation is repeated one million times for each vessel. This results in a distribution, or histogram, showing the likelihood of different outcomes, i.e. the number of infected crew members. The very large number of simulations with zero infected crew is beyond the axis range of the plot and is therefore not shown.
The uncertainty (spread) around possible contagion scenarios is high 2, but by taking the average outcome over one million simulations, we can approximate the most likely scenario, i.e. the average number of infected crew (Figure 2).
The final step is to classify each vessel as high, medium or low risk. This is done by considering the vessel’s risk relative to all others calculated to date. High risk is assigned to vessels having a likelihood of infected crew in the top 10% relative to all others. Medium risk is assigned to those in the top 75–90%, and low risk is assigned to those vessels in the 0–75% bracket of risk. This is done by calculating a cumulative distribution function based on all vessel risks to date and identifying the corresponding brackets of risk.
Vessels and their estimated comparative risk are then visualised in Starboard and updated on a daily basis.
Currently we include all commercial (cargo/tanker) vessels within the vicinity of Aotearoa New Zealand. We do not currently consider crew change information, which would provide additional input to improve risk assessment. We intend to incorporate these additional features as the data become available.
|Parameter||Value(s) used||Further details|
|Incidence of SARS-CoV-2 infection||Variable||Based on daily incidence rates from Johns Hopkins University 7, adjusted for under-estimation by using a 10-fold difference between reported cases and infections 2, 8|
|Percent of infections that are asymptomatic||29%||See 2, 9|
|Latency period||5 days||See 2, 10|
|Prodromal period||1 day||See 2|
|Symptomatic period||10 days (split into 2 periods of 5 days each)||See 2, 11|
|Relative contagiousness in the prodromal period||100%||See 2, 10|
|Contagiousness after the prodromal period||100% (first 5 days), 50% (second 5 days)||See 2, 12|
|Effective reproduction number on board the ship||3.0||See 2|
|Effective reproduction number in the port||2.5||See 2, 10|
|Duration in port||Variable||Based on vessel transponder data|
|Voyage length||Variable||Based on vessel transponder data.|
|Crew size||20||See 2, 13.|