应急状态下新冠流行曲线预测的方法学研究——基于北京市百度搜索和传统流感样病例监测

作     者：Ting Zhang Liuyang Yang Xuan Han Guohui Fan Jie Qian Xuancheng Hu Shengjie Lai Zhongjie Li Zhimin Liu Luzhao Feng Weizhong Yang Ting Zhang;Liuyang Yang;Xuan Han;Guohui Fan;Jie Qian;Xuancheng Hu;Shengjie Lai;Zhongjie Li;Zhimin Liu;Luzhao Feng;Weizhong Yang

作者机构：School of Population Medicine and Public HealthChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100730China Department of management science and information systemFaculty of Management and EconomicsKunming University of Science and TechnologyKunming 650504China WorldPopSchool of Geography and Environmental ScienceUniversity of SouthamptonSouthampton SO171BJUK The Third Affiliated Hospital of Kunming Medical UniversityKunming 650118China 

出 版 物：《Engineering》 (工程（英文）)

年 卷 期：2023年第31卷第12期

页      面：112-119页

核心收录：

学科分类：1004[医学-公共卫生与预防医学(可授医学、理学学位)] 100401[医学-流行病与卫生统计学] 10[医学] 

基　　金：supported by grants from the Chinese Academy of Medical Sciences(CAMS)Innovation Fund for Medical Sciences(2021I2M-1-044)。 

主　　题：COVID-19 Epidemic curve Baidu search engine Influenza-like illness Deep learning Transmission dynamics model 

摘      要：Surveillance is an essential work on infectious diseases prevention and control.When the pandemic occurred,the inadequacy of traditional surveillance was exposed,but it also provided a valuable opportunity to explore new surveillance methods.This study aimed to estimate the transmission dynamics and epidemic curve of severe acute respiratory syndrome coronavirus 2(SARS-Co V-2)Omicron BF.7 in Beijing under the emergent situation using Baidu index and influenza-like illness(ILI)surveillance.A novel hybrid model(multiattention bidirectional gated recurrent unit(MABG)-susceptible-exposed-infected-removed(SEIR))was developed,which leveraged a deep learning algorithm(MABG)to scrutinize the past records of ILI occurrences and the Baidu index of diverse symptoms such as fever,pyrexia,cough,sore throat,anti-fever medicine,and runny nose.By considering the current Baidu index and the correlation between ILI cases and coronavirus disease 2019(COVID-19)cases,a transmission dynamics model(SEIR)was formulated to estimate the transmission dynamics and epidemic curve of SARS-Co V-2.During the COVID-19 pandemic,when conventional surveillance measures have been suspended temporarily,cases of ILI can serve as a useful indicator for estimating the epidemiological trends of COVID-19.In the specific case of Beijing,it has been ascertained that cumulative infection attack rate surpass 80.25%(95%confidence interval(95%CI):77.51%-82.99%)since December 17,2022,with the apex of the outbreak projected to transpire on December 12.The culmination of existing patients is expected to occur three days subsequent to this peak.Effective reproduction number(Rt)represents the average number of secondary infections generated from a single infected individual at a specific point in time during an epidemic,remained below 1 since December 17,2022.The traditional disease surveillance systems should be complemented with information from modern surveillance data such as online data sources with advanced technical support.Modern surveillance channels should be used primarily in emerging infectious and disease outbreaks.Syndrome surveillance on COVID-19 should be established to following on the epidemic,clinical severity,and medical resource demand.