key: cord-1027548-etl9uwt7
authors: Zhuang, Zian; Zhao, Shi; Lin, Qianying; Cao, Peihua; Lou, Yijun; Yang, Lin; Yang, Shu; He, Daihai; Xiao, Li
title: Preliminary estimating the reproduction number of the coronavirus disease (COVID-19) outbreak in Republic of Korea and Italy by 5 March 2020
date: 2020-03-06
journal: nan
DOI: 10.1101/2020.03.02.20030312
sha: 7fb7c0c48b30e66dfaea5fdec16d999ed52d1ee0
doc_id: 1027548
cord_uid: etl9uwt7

The novel coronavirus disease 2019 (COVID-19) outbreak and Italy has caused 6088 cases and 41 deaths in Republic of Korea and 3144 cases and 107 death in Italy by 5 March 2020. We modeled the transmission process in Republic of Korea and Italy with a stochastic model and estimated the basic reproduction number R0 as 2.6 (95% CI: 2.3-2.9) or 3.2 (95% CI: 2.9-3.5) in Republic of Korea, under the assumption that the exponential growth starting on 31 January or 5 February 2020, and 2.6 (95% CI: 2.3-2.9) or 3.3 (95% CI: 3.0-3.6) in Italy, under the assumption that the exponential growth starting on 5 February or 10 February 2020. Estimates of dispersion term (k) were 10 (95% CI: 5-56) or 22 (95% CI: 8-61) in Republic of Korea, and 13 (95% CI: 5-61) or 37 (95% CI: 13-61) in Italy, and all of which imply few super-spreading events.

The coronavirus disease 2019 (COVID-19) first emerged in Wuhan, China in the end of 2019 and spread to more than 60 foreign countries as of 1 March 2020 [1] . On 20 January 2020, the first imported COVID-19 case was detected in Republic of Korea, and the epidemic curve appeared steadily until 15 February. In the second half of February, the number of reported cases increased rapidly with more than 1200 cases a week. As of 5 March 2020, there were 6088 cases confirmed including 41 deaths [1] .

In Italy, the first case was reported on 6 February 2020 and the epidemic curve was steadily by 21 February. Then the number of reported cases soared rapidly, reaching 3142 reported cases and 107 deaths until 5 March 2020 [1] . To date, there are 14768 confirmed cases in the world except China, which means that more than 60 per cent of cases outside China are from Republic of Korea and Italy [1] .

In this study, we modelled the early outbreak of COVID-19 in Republic of Korea and Italy to estimate the basic reproduction number under different exponential growth starting date.

We collect time series of reported COVID-19 cases in Republic of Korea from 20 January to 1 March 2020 and cases in Italy from 5 February to 5 March 2020.

Following [2, 3] , we assumed that number of secondary cases associated with a primary COVID-19 case follows a negative binomial (NB) distribution, with means R0 and dispersion parameter k [3] . Here, the R0 is the basic reproduction number of COVID-19. The k measures the likelihood of occurrence of super-spreading events (or other factors) which could vary the growth rate. If k is smaller than 1, these data indicate occurrence of super-spreading events (larger proportion of 'super-spreaders' or 'dead-ends' in infected individuals) or some other factors which could vary the growth rate; otherwise if k is larger than 1, these data do not indicate occurrence of super-spreading events [4] .

The onset date of each secondary case is the summation of the onset date of the primary case (t) plus the serial interval (SI). In this work, the SI was assumed as a . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint . https://doi.org/10.1101/2020.03.02.20030312 doi: medRxiv preprint Gamma distribution with a 4.5-day mean and a 3.1-day standard deviation (SD) [5] [6] [7] [8] .

The transmission process was simulated stochastically.

Since the number of early reported cases are stable, which appears no sign of the outbreak in January 2020, we consider the sustaining exponential growth might start since February 2020. Hence, we simulated the exponential growth starting on • 31 January and 5 February 2020 for Republic of Korea .

(1)

Here, the l(·) is the overall log-likelihood and T is the total number of days since the start of exponential growth. The nt represents number of cases reported on t-th day. We calculated 95% confidence intervals (95%CI) by using the profile likelihood estimation approach determined by a Chi-square quantile.

In Table 1 which set the exponential growth starting date on 20 January 2020 and the onset date data were considered. Here we use laboratory confirmation date data which covered . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint . https://doi.org/10.1101/2020.03.02.20030312 doi: medRxiv preprint both symptomatic and asymptomatic cases. In addition, the R0 estimates from two countries were largely consistent with those estimates based on the epidemic curve in China [10, 11] . If there were evidences suggesting that the exponential growth started earlier, we note that the R0 estimates would decrease. Public activities in the late date and cold weather in our study period could have speed up the transmission which explains the higher estimates.

The ongoing COVID-19 outbreak in Republic of Korea and Italy could be amplified due to large-scale gathering activities [12, 13] . Without public health control or selfprotective measures, the epidemic was likely to grow in a relatively large rate. The R0 estimates and the rapid growth of epidemic curves both indicates the disease transmissibility. Thus, control measures as well as self-administered protective actions are crucial to reduce the transmissibility of COVID-19 and thus mitigate the outbreak size and prevent for further burden. Given the superspreading is unlikely to occur, we can be confident to control the COVID-19 outbreak by reducing the reproduction number to below unity. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint . https://doi.org/10.1101/2020.03.02.20030312 doi: medRxiv preprint respectively. Panels (c) and (d) show the results in Italy with the exponential growth starting date on 5 February and 10 February 2020 respectively. In all panels, the grey curves are 1000 simulations, the blue bold curve is the simulation median, and the blue dashed curves are the 95%CI.

Open-source analytics tools for studying the COVID-19 coronavirus outbreak

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Half of Republic of Korea's coronavirus cases are linked to a controversial religious organization

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None.

The funding agencies had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

The ethical approval or individual consent was not applicable.

. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.02.20030312 doi: medRxiv preprint All data and materials used in this work were publicly available.

Not applicable. 

Research project. Other authors declare no competing interests.

All authors conceived the study, carried out the analysis, discussed the results, drafted the first manuscript, critically read and revised the manuscript, and gave final approval for publication.. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.

The copyright holder for this preprint . https://doi.org/10.1101/2020.03.02.20030312 doi: medRxiv preprint