COVID-19 in Japan: What could happen in the future?

Shao, Nan; Pan, Hanshuang; Li, Xingjie; Li, Weijia; Wang, Shufen; Xuan, Yingli; Yi, Yan; Jiang, Yu; Liu, Keji; Yu, Chen; Xu, Boxi; Shen, Christopher Y.; Zhong, Min; Xu, Xiang; Xu, Chen; Lu, Shuai; Ding, Guanghong; Cheng, Jin; Chen, Wenbin

doi:10.1101/2020.02.21.20026070

Cited by 9 publications

(21 citation statements)

References 17 publications

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“…Since the first case of pneumonia caused by COVID-19 was reported from Wuhan, COVID-19 patients had rapidly been diagnosed in other cities of China and the neighboring countries including Thailand, South Korea, Japan, and even to a few Western countries. [10][11][12] On January13 2020, the Ministry of Public Health of Thailand reported the first imported case of lab-confirmed novel coronavirus (2019-nCoV). 13 As of Feb28 2020, cases had been reported in 52 countries and territories.…”

Section: Introductionmentioning

confidence: 99%

COVID-19 Epidemic Outside China: 34 Founders and Exponential Growth

Meng

Yin

et al. 2020

Preprint

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Background: In December 2019, pneumonia infected with a novel coronavirus burst in Wuhan, China. Now the situation is almost controlled in China but is worse outside China. We aimed to build a mathematical model to capture the global trend of epidemics outside China. Methods: In this retrospective, outside-China diagnosis number reported from Jan 21 to Feb 28, 2020 was downloaded from WHO website. We develop a simple regression model on these numbers: log10 (Nt+34)=0.0515*t+2.075 where Nt is the total diagnosed patient till the ith day, t=1 at Feb 1. Findings: Based on this model, we estimate that there have been about 34 unobserved founder patients at the beginning of spread outside China. The global trend is approximately exponential, with the rate of 10 folds every 19 days.

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Section: Introductionmentioning

confidence: 99%

COVID-19 Epidemic Outside China: 34 Founders and Exponential Growth

Meng

Yin

et al. 2020

Preprint

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“…The parameters identified by model, as well as the evolution trend are compared, as we continue to add one datum day by day in this period. We need to mention here that the growth rates r in almost all the selected periods are identified between the interval [0.33, 0.34], which is consistent with the isolation rate in China discussed in [27], so we just spare the space to study the isolation rate. From the figure we can observe that the isolation rate 1 levels up from 0.049556 on Feb 1 to 0.46146 on Feb 3, possibly indicating that Singapore might have begun its quarantine measures in a very early stage of its epidemic.…”

Section: Covid-19 In Singaporementioning

confidence: 69%

“…Accepted manuscript to appear in IJMI have deeply studied the isolation rate and the change day t l of quarantine strategy, and found that all the selected areas had strengthened their quarantine strategy in mid January, which could be seen from a level-up of 2 (compared to 1 ) in Table 1 in [27]. Therefore, we should conclude that China has indeed made great great efforts to control the epidemic.…”

Section: Accepted Manuscriptmentioning

confidence: 95%

“…In a previous work [27], we have analyzed the current situation of the epidemic in mainland China. Our model has been performing well predicting the trend of COVID-19.…”

Section: A Brief Cast On Covid-19 In East Asiamentioning

confidence: 99%

“…The Fudan-CCDC model revealed the importance of early and effective quarantine measures. The authors later applied the model to analyze the epidemic in Japan and drew conclusions that a possible rapid outbreak might happen in Japan if no effective quarantine measures were carried out immediately [27]. Other models could be found in [24,22,31,34,19,32,23].…”

Section: Introductionmentioning

confidence: 99%

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COVID-19 in Singapore: Another story of success

Pan

Shao

et al. 2020

Int. J. Math. Ind.

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In this paper, we develop the Fudan-CCDC model by adding a source term to describe the imported infectors. The model is applied to analyze the situation of COVID-19 in East Asia, and then in Singapore. By data fitting, our model reveals that Singapore has a much higher isolation rate and earlier quarantine measures compared to other countries. We conclude that Singapore has been doing extraordinarily well on epidemic prevention and control. Finally we discuss the specific measures in Singapore’s success, and suggest other countries to learn from the Singapore’s style, so as to be well prepared in the future.

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Dynamic models for Coronavirus Disease 2019 and data analysis

Shao

Zhong

et al. 2020

Math Meth Appl Sci

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In this letter, two time delay dynamic models, a Time Delay Dynamical-Novel Coronavirus Pneumonia (TDD-NCP) model and Fudan-Chinese Center for Disease Control and Prevention (CCDC) model, are introduced to track the data of Coronavirus Disease 2019 (COVID-19). The TDD-NCP model was developed recently by Cheng aŕs group in Fudan and Shanghai University of Finance andEconomics (SUFE). The TDD-NCP model introduced the time delay process into the differential equations to describe the latent period of the epidemic. The Fudan-CDCC model was established when Wenbin Chen suggested to determine the kernel functions in the TDD-NCP model by the public data from CDCC. By the public data of the cumulative confirmed cases in different regions in China and different countries, these models can clearly illustrate that the containment of the epidemic highly depends on early and effective isolations.

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COVID-19 in Japan: What could happen in the future?

Cited by 9 publications

References 17 publications

COVID-19 Epidemic Outside China: 34 Founders and Exponential Growth

COVID-19 Epidemic Outside China: 34 Founders and Exponential Growth

COVID-19 in Singapore: Another story of success

Dynamic models for Coronavirus Disease 2019 and data analysis

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