COVID-19 outbreak on the Diamond Princess cruise ship: estimating the epidemic potential and effectiveness of public health countermeasures

Rocklöv, J; Sjödin, H; Wilder-Smith, A

Models with interventions were calibrated to reports of total infection occurrence, while models simulating the counterfactual scenarios where left with the naïve parameter settings (no countermeasures). The net effects of the countermeasures where estimated as the difference between the counterfactual scenario and the model with the interventions. Model parameters are described in Table 1 are the results of the calibration to the observed cumulative incidence data. The contact rate between persons on the cruise ship was calibrated to give the best fit to data with a reduction of 70% The predicted cumulative number of cases over time from this model described the observed cases well, but overestimated the cumulative case incidence rate initially ( Figure 2 ). This allowed to compensate for reporting bias in the initial phase, given that the proportion of testing of all passengers was patchy while at the end of the study (19 th In a sensitivity analysis we modified the to 3.7 (and consequently ) as this has been reported the average basic reproduction number from studies of COVID-19 in China. 9 However, from our simulation, even in the absence of any intervention, such a low cannot explain the rapid growth of incident cases on the cruise ship ( Figure 3 ). This sensitivity scenario excluded countermeasures from the model making it unrealistic that such a low value could be the true value in the cruise ship situation with confined spaces and high homogeneous mixing of the same persons. The estimate with the lower value also omitted to consider the strong interventions put into place, making it even more unrealistic.