Taking account of asymptomatic infections: A modeling study of the COVID-19 outbreak on the Diamond Princess cruise ship.

Lucia Dunn,Li Li,Mai He,Li-Shan Huang

doi:10.1371/journal.pone.0248273

Abstract

The COVID-19 outbreak on the Diamond Princess (DP) cruise ship has provided empirical data to study the transmission potential of COVID-19 with the presence of pre/asymptomatic cases. We studied the changes in R0 on DP from January 21 to February 19, 2020 based on chain binomial models under two scenarios: no quarantine assuming a random mixing condition, and quarantine of passengers in cabins—passengers may get infected either by an infectious case in a shared cabin or by pre/asymptomatic crew who continued to work. Estimates of R0 at the beginning of the epidemic were 3.27 (95% CI, 3.02–3.54) and 3.78 (95% CI, 3.49–4.09) respectively for serial intervals of 5 and 6 days; and when quarantine started, with the reported asymptomatic ratio 0.505, R0 rose to 4.18 (95%CI, 3.86–4.52) and 4.73 (95%CI, 4.37–5.12) respectively for passengers who might be exposed to the virus due to pre/asymptomatic crew. Results confirm that the higher the asymptomatic ratio is, the more infectious contacts would happen. We find evidence to support a US CDC report that “a high proportion of asymptomatic infections could partially explain the high attack rate among cruise ship passengers and crew.” Our study suggests that if the asymptomatic ratio is high, the conventional quarantine procedure may not be effective to stop the spread of virus.

Highlights

The COVID-19 outbreak has developed into an international public health emergency
We investigated the changes in R0 for COVID-19 on the Diamond Princess (DP) from January 21 to February 19 with a chain binomial model [19,20,21] at different times under two scenarios: no quarantine assuming a random mixing condition before February 5, and quarantine of passengers in cabins from February 5 to 19—passengers may get infected either by an infectious case in a shared cabin or by pre/asymptomatic crew who continued to work
We developed some R [25] code by modifying some R-functions in [20] for the chain binomial model and the maximum likelihood (ML) step was carried out using the R-package bbmle [26]

Summary

Introduction

The reproductive number (R0) of COVID-19 is a key piece of information for understanding an epidemic. Current intervention methods focus on quarantine methods with either mitigation or suppression strategies aimed at reducing the reproduction number R0 and flattening the curve [1]. Asymptomatic or pre-symptomatic infectious cases are less likely to seek medical care or to be tested and quarantined, contributing to the infectious potential of a respiratory virus [2,3]. Clinical findings have suggested that the viral load in asymptomatic patients is similar to that in symptomatic patients [4]. Evidence suggests that these pre/asymptomatic patients can infect others before they manifest any symptoms [5,6,7].

Methods

Results

Conclusion