Literature DB >> 34149967

The Prediction for COVID-19 Outbreak in China by using the Concept of Term Structure for the Turning Period.

George X Yuan1,2,3,4, Lan Di5, Zheng Yang6, Guoqi Qian7, Xiaosong Qian4, Tu Zeng3.   

Abstract

This study aims to develop a general framework for predicting the duration of the Turning Period (or Turning Phase) for the COVID-19 outbreak in China that started in late December 2019 from Wuhan. A new concept called the Term Structure for Turning Period (instead of Turning Point) is used for this study, and the framework, implemented into an individual SEIR (iSEIR) model, has enabled a timely prediction of the turning period when applied to Wuhan's COVID-19 epidemic, and provided the opportunity for relevant authorities to take appropriate and timely actions to successfully control the epidemic. By using the observed daily COVID-19 cases in Wuhan from January 23, 2020 to February 6 (and February 10), 2020 as inputs to the framework it allowed us to generate the trajectory of COVID-19 dynamics and to predict that the Turning Period of COVID-19 outbreak in Wuhan would arrive within one week after February 14. This prediction turned out to be timely and accurate, which has provided adequate time for the government, hospitals and related sectors and services to meet peak demand and to prepare aftermath planning. We want to emphasize that emergency risk management entails the implementation of an emergency plan, where timing the Turning Period is key to express a clear timeline for effective actions. Our study confirms the observed effectiveness of Wuhan's Lockdown and Isolation control program imposed since January 23, 2020 to the middle of March, 2020 and resulted in swiftly flattened epidemic curve, and Wuhan's success offers an exemplary lesson for the world to learn in combating COVID-19 pandemic.
© 2021 The Author(s). Published by Elsevier B.V.

Entities:  

Keywords:  Coronavirus (COVID-19); Emergency Plan; Isolation control program; Lockdown; Multiplex network; Outbreak of Epidemic Infectious Disease; Supersaturation Phenomenon; Term Structure for Turning Phase; iSEIR Model

Year:  2021        PMID: 34149967      PMCID: PMC8197400          DOI: 10.1016/j.procs.2021.04.064

Source DB:  PubMed          Journal:  Procedia Comput Sci


  12 in total

1.  Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia.

Authors:  Qun Li; Xuhua Guan; Peng Wu; Xiaoye Wang; Lei Zhou; Yeqing Tong; Ruiqi Ren; Kathy S M Leung; Eric H Y Lau; Jessica Y Wong; Xuesen Xing; Nijuan Xiang; Yang Wu; Chao Li; Qi Chen; Dan Li; Tian Liu; Jing Zhao; Man Liu; Wenxiao Tu; Chuding Chen; Lianmei Jin; Rui Yang; Qi Wang; Suhua Zhou; Rui Wang; Hui Liu; Yinbo Luo; Yuan Liu; Ge Shao; Huan Li; Zhongfa Tao; Yang Yang; Zhiqiang Deng; Boxi Liu; Zhitao Ma; Yanping Zhang; Guoqing Shi; Tommy T Y Lam; Joseph T Wu; George F Gao; Benjamin J Cowling; Bo Yang; Gabriel M Leung; Zijian Feng
Journal:  N Engl J Med       Date:  2020-01-29       Impact factor: 176.079

2.  Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study.

Authors:  Joseph T Wu; Kathy Leung; Gabriel M Leung
Journal:  Lancet       Date:  2020-01-31       Impact factor: 79.321

3.  Forecasting and Evaluating Multiple Interventions for COVID-19 Worldwide.

Authors:  Zixin Hu; Qiyang Ge; Shudi Li; Eric Boerwinkle; Li Jin; Momiao Xiong
Journal:  Front Artif Intell       Date:  2020-05-22

4.  Epidemiological research priorities for public health control of the ongoing global novel coronavirus (2019-nCoV) outbreak.

Authors:  Benjamin J Cowling; Gabriel M Leung
Journal:  Euro Surveill       Date:  2020-02-11

5.  The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study.

Authors:  Kiesha Prem; Yang Liu; Timothy W Russell; Adam J Kucharski; Rosalind M Eggo; Nicholas Davies; Mark Jit; Petra Klepac
Journal:  Lancet Public Health       Date:  2020-03-25

6.  The inflection point about COVID-19 may have passed.

Authors:  Chaolin Gu; Jie Zhu; Yifei Sun; Kai Zhou; Jiang Gu
Journal:  Sci Bull (Beijing)       Date:  2020-03-03       Impact factor: 11.780

7.  Prediction of the Epidemic Peak of Coronavirus Disease in Japan, 2020.

Authors:  Toshikazu Kuniya
Journal:  J Clin Med       Date:  2020-03-13       Impact factor: 4.241

8.  Estimating clinical severity of COVID-19 from the transmission dynamics in Wuhan, China.

Authors:  Joseph T Wu; Kathy Leung; Mary Bushman; Nishant Kishore; Rene Niehus; Pablo M de Salazar; Benjamin J Cowling; Marc Lipsitch; Gabriel M Leung
Journal:  Nat Med       Date:  2020-03-19       Impact factor: 53.440

9.  Real-time forecasts of the COVID-19 epidemic in China from February 5th to February 24th, 2020.

Authors:  K Roosa; Y Lee; R Luo; A Kirpich; R Rothenberg; J M Hyman; P Yan; G Chowell
Journal:  Infect Dis Model       Date:  2020-02-14

10.  A data driven time-dependent transmission rate for tracking an epidemic: a case study of 2019-nCoV.

Authors:  Norden E Huang; Fangli Qiao
Journal:  Sci Bull (Beijing)       Date:  2020-02-07       Impact factor: 11.780

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.