The aim of this paper is first to establish a general prediction framework for turning(period)term structures in COVID-19 epidemic related to the implementation of emergency risk man-agement in the practice,which allows us to conduct the reliable estimation for the peak period based on the new concept of"Turning Period"(instead of the traditional one with the focus on"Turning Point")for infectious disease spreading such as the CO VID-19 epidemic appeared early in year 2020.By a fact that emergency risk management is necessarily to implement emergency plans quickly,the identification of the Turning Period is a key element to emergency planning as it needs to provide a time line for effective actions and solutions to combat a pandemic by reducing as much unexpected risk as soon as possible.As applications,the paper also discusses how this"Turning Term(Period)Structure"is used to predict the peak phase for COVID-19 epidemic in Wuhan from January/2020 to early March/2020.Our study shows that the predication framework established in this paper is capa-ble to provide the trajectory of COVID-19 cases dynamics for a few weeks starting from Feb.10/2020 to early March/2020,from which we successfully predicted that the turning period of COVID-19 epi-demic in Wuhan would arrive within one week after Feb.14/2020,as verified by the true observation in the practice.The method established in this paper for the prediction of"Turning Term(Period)Structures"by applying COVID-19 epidemic in China happened early 2020 seems timely and accu-rate,providing adequate time for the government,hospitals,essential industry sectors and services to meet peak demands and to prepare aftermath planning,and associated criteria for the Turning Term Structure of CO VID-19 epidemic is expected to be a useful and powerful tool to implement the so-called"dynamic zero-COVID-19 policy"ongoing basis in the practice.

Lan DI;Yudi GU;Guoqi QIAN;George Xianzhi YUAN

School of Artificial Intelligence and Computer Science,Jiangnan University,Wuxi 214122,China;Center of Information Construct and Management,Jiangnan University,Wuxi 214122,China;School of Mathematics&Statistics,University of Melbourne,Melbourne VIC 3010,Australia;Business School,East China University of Science and Technology,Shanghai 200237,China;Business School,Chengdu University,Chengdu 610106,China;Business School,Sun Yat-sen University, Guangzhou 510275,China

系统科学与信息学报（英文版）

[1]Lan DI;Yudi GU;Guoqi QIAN;George Xianzhi YUAN-.A Prediction Framework for Turning Period Structures in COVID-19 Epidemic and Its Application to Practical Emergency Risk Management)[J].系统科学与信息学报（英文版）,2022(04):309-337

predication

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