Maximum Entropy Method for Estimating the Generation Interval Distribution of COVID-19
GAO Yuandong, LI Hualong, WANG Xiaohua, CHEN Duanbing, LIANG Yijuan, WEN Tao, ZHOU Tao, TAO Yong
1. College of Economics and Management, Southwest University, Chongqing 400715, China; 2. Big Data Research Center, University of Electronic Science and Technology of China, Chengdu 611731, China
Abstract：The intergenerational τ has important theoretical and practical value to explore the law of virus transmission, but the probability distribution function is unknown. Therefore, this paper tries to infer the most probable form of the intergenerational interval distribution function by using the maximum entropy method, and analyzes the information of 4 986 cases of novel coronavirus from 20 countries in the world in detail, and estimates the mean and variance of the intergenerational interval of the virus on the basis of fully considering the diversity of samples. Then, based on this method, the global intergenerational interval distribution function of novel coronavirus was deduced and the basic reproduction number of China is calculated. The conclusion of this study is helpful for further objective analysis of the transmission characteristics of the virus, and provides important reference value for the formulation of regular epidemic prevention and control countermeasures and related research.
高远东, 李华龙, 王小华, 陈端兵, 梁义娟, 温涛, 周涛, 陶勇. 基于最大熵的新型冠状病毒代际间隔分布估计[J]. 复杂系统与复杂性科学, 2023, 20(2): 20-28.
GAO Yuandong, LI Hualong, WANG Xiaohua, CHEN Duanbing, LIANG Yijuan, WEN Tao, ZHOU Tao, TAO Yong. Maximum Entropy Method for Estimating the Generation Interval Distribution of COVID-19. Complex Systems and Complexity Science, 2023, 20(2): 20-28.
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