Analysis of the epidemic growth of the early 2019-nCoV outbreak using internationally confirmed cases
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Abstract
Background
On January 23, 2020, a quarantine was imposed on travel in and out of Wuhan, where the 2019 novel coronavirus (2019-nCoV) outbreak originated from. Previous analyses estimated the basic epidemiological parameters using symptom onset dates of the confirmed cases in Wuhan and outside China.
Methods
We obtained information on the 46 coronavirus cases who traveled from Wuhan before January 23 and have been subsequently confirmed in Hong Kong, Japan, Korea, Macau, Singapore, and Taiwan as of February 5, 2020. Most cases have detailed travel history and disease progress. Compared to previous analyses, an important distinction is that we used this data to informatively simulate the infection time of each case using the symptom onset time, previously reported incubation interval, and travel history. We then fitted a simple exponential growth model with adjustment for the January 23 travel ban to the distribution of the simulated infection time. We used a Bayesian analysis with diffuse priors to quantify the uncertainty of the estimated epidemiological parameters. We performed sensitivity analysis to different choices of incubation interval and the hyperparameters in the prior specification.
Results
We found that our model provides good fit to the distribution of the infection time. Assuming the travel rate to the selected countries and regions is constant over the study period, we found that the epidemic was doubling in size every 2.9 days (95% credible interval [CrI], 2 days—4.1 days). Using previously reported serial interval for 2019-nCoV, the estimated basic reproduction number is 5.7 (95% CrI, 3.4—9.2). The estimates did not change substantially if we assumed the travel rate doubled in the last 3 days before January 23, when we used previously reported incubation interval for severe acute respiratory syndrome (SARS), or when we changed the hyperparameters in our prior specification.
Conclusions
Our estimated epidemiological parameters are higher than an earlier report using confirmed cases in Wuhan. This indicates the 2019-nCoV could have been spreading faster than previous estimates.
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SciScore for 10.1101/2020.02.06.20020941: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our analysis should be viewed in terms of its limitations. The international cases are only “shadows” of the epidemic in Wuhan and we relied on the assumption that they form a representative sample. We used a simple exponential growth model for the new infections and did not account for the dynamics of the epidemics like a SEIR model. We assumed a constant rate of travel in the study period which might not approximate the travel …
SciScore for 10.1101/2020.02.06.20020941: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our analysis should be viewed in terms of its limitations. The international cases are only “shadows” of the epidemic in Wuhan and we relied on the assumption that they form a representative sample. We used a simple exponential growth model for the new infections and did not account for the dynamics of the epidemics like a SEIR model. We assumed a constant rate of travel in the study period which might not approximate the travel pattern in Wuhan---a transportation hub in central China---very well. In particular, millions of people (substantial proportion of the Wuhan population) traveled back home from Wuhan before the Lunar New Year, which we did not consider in our model. Finally, our estimates are relatively but not entirely insensitive to the incubation period which are crucial in simulating the infection time. Despite these potential limitations, we convincingly demonstrated that a simple theoretical model --- exponential growth with correction for the travel ban on January 23 --- provides very good fit to the internationally confirmed cases with detailed case trajectories. Our results suggest that the early outbreak of 2019-nCoV could have been spreading much faster in Wuhan than previous estimates. This has important implications in designing prevention measures to control the outbreak in other cities in China and around the world. On the more positive side, our simulated infection rates in January 21 to 23 showed visually significant departure from the previous growth...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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