Modeling and prediction of the 2019 coronavirus disease spreading in China incorporating human migration data

被引:45
|
作者
Zhan, Choujun [1 ]
Tse, Chi K. [2 ]
Fu, Yuxia [3 ]
Lai, Zhikang [3 ]
Zhang, Haijun [4 ]
机构
[1] South China Normal Univ, Sch Comp, Guangzhou, Peoples R China
[2] City Univ Hong Kong, Dept Elect Engn, Kowloon, Hong Kong, Peoples R China
[3] Sun Yat Sen Univ, Sch Comp Sci & Engn, Nanfang Coll, Guangzhou, Peoples R China
[4] Harbin Inst Technol, Shenzhen Grad Sch, Shenzhen, Peoples R China
来源
PLOS ONE | 2020年 / 15卷 / 10期
基金
美国国家科学基金会;
关键词
TRANSMISSION;
D O I
10.1371/journal.pone.0241171
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
This study integrates the daily intercity migration data with the classic Susceptible-Exposed-Infected-Removed (SEIR) model to construct a new model suitable for describing the dynamics of epidemic spreading of Coronavirus Disease 2019 (COVID-19) in China. Daily intercity migration data for 367 cities in China were collected from Baidu Migration, a mobile-app based human migration tracking data system. Early outbreak data of infected, recovered and death cases from official source (from January 24 to February 16, 2020) were used for model fitting. The set of model parameters obtained from best data fitting using a constrained nonlinear optimisation procedure was used for estimation of the dynamics of epidemic spreading in the following months. The work was completed on February 19, 2020. Our results showed that the number of infections in most cities in China would peak between mid February to early March 2020, with about 0.8%, less than 0.1% and less than 0.01% of the population eventually infected in Wuhan, Hubei Province and the rest of China, respectively. Moreover, for most cities outside and within Hubei Province (except Wuhan), the total number of infected individuals is expected to be less than 300 and 4000, respectively.
引用
收藏
页数:17
相关论文
共 50 条
  • [21] Coronavirus Disease 2019: First Data From Africa
    Venter, W. D. Francois
    Nel, Jeremy
    CLINICAL INFECTIOUS DISEASES, 2021, 73 (07) : E2016 - E2017
  • [22] Coronavirus Disease 2019: Latest Data on Neuroinvasive Potential
    Haddadi, Kaveh
    Asadian, Leila
    IRANIAN JOURNAL OF MEDICAL SCIENCES, 2020, 45 (05) : 325 - 332
  • [23] Reanalysis of quarantine for coronavirus disease 2019 with emerging data
    Cimolai, Nevio
    AMERICAN JOURNAL OF OBSTETRICS & GYNECOLOGY MFM, 2021, 3 (01)
  • [24] Lipidome is a valuable tool for the severity prediction of coronavirus disease 2019
    Zhang, Shan-Shan
    Zhao, Zhiling
    Zhang, Wan-Xue
    Wu, Rui
    Li, Fei
    Yang, Han
    Zhang, Qiang
    Wei, Ting-Ting
    Xi, Jingjing
    Zhou, Yiguo
    Wang, Tiehua
    Du, Juan
    Huang, Ninghua
    Ge, Qinggang
    Lu, Qing-Bin
    FRONTIERS IN IMMUNOLOGY, 2024, 15
  • [25] The pathological autopsy of coronavirus disease 2019 (COVID-2019) in China: a review
    Zhou, Baoyong
    Zhao, Wei
    Feng, Ruixi
    Zhang, Xiaohui
    Li, Xuemei
    Zhou, Yang
    Peng, Li
    Li, Yixin
    Zhang, Jinyan
    Luo, Jing
    Li, Lingyu
    Wu, Jingxian
    Yang, Changhong
    Wang, Meijiao
    Zhao, Yong
    Wang, Kejian
    Yu, Huarong
    Peng, Qiling
    Jiang, Ning
    PATHOGENS AND DISEASE, 2020, 78 (03):
  • [26] Prediction of adverse clinical outcomes in patients with coronavirus disease 2019
    Shi, Si
    Liu, Xiaohui
    Xiao, Jinling
    Wang, Hongwei
    Chen, Liyan
    Li, Jianing
    Han, Kaiyu
    JOURNAL OF CLINICAL LABORATORY ANALYSIS, 2021, 35 (01)
  • [27] Incorporating a virtual curriculum into ophthalmology education in the coronavirus disease-2019 era
    Mishra, Kapil
    Boland, Michael V.
    Woreta, Fasika A.
    CURRENT OPINION IN OPHTHALMOLOGY, 2020, 31 (05) : 380 - 385
  • [28] Outbreak Trends of Coronavirus Disease-2019 in India: A Prediction
    Tiwari, Sunita
    Kumar, Sushil
    Guleria, Kalpna
    DISASTER MEDICINE AND PUBLIC HEALTH PREPAREDNESS, 2020, 14 (05) : E33 - E38
  • [29] Flaws in the Development and Validation of a Coronavirus Disease 2019 Prediction Model
    Collins, Gary S.
    Riley, Richard D.
    van Smeden, Maarten
    CLINICAL INFECTIOUS DISEASES, 2021, 73 (03) : 557 - 558
  • [30] Association between population migration and epidemic control of coronavirus disease 2019
    Yu Ding
    Sihui Luo
    Xueying Zheng
    Ping Ling
    Tong Yue
    Zhirong Liu
    Jianping Weng
    Science China(Life Sciences), 2020, (06) : 936 - 939