Reaction to the COVID-19 pandemic in Seoul with biostatistics  

作　　者：Seungpil Jung Seung-Sik Hwang Kyoung-Nam Kim Woojoo Lee 

机构地区：[1]Department of Public Health Sciences,Graduate School of Public Health,Seoul National University,08826,Republic of Korea [2]Department of Preventive Medicine and Public Health,Ajou University School of Medicine,Suwon,16499,Republic of Korea

出　　处：《Infectious Disease Modelling》2022年第3期419-429,共11页传染病建模（英文）

基　　金：This studywas exempted from review by the Institutional ReviewBoard(IRB)of Seoul National University(SNU IRB no.21-08-109)because the data were aggregated and anonymized;This work was supported by the National Research Foundation of Korea(BK21 Center for Integrative Response to Health Disasters,Graduate School of Public Health,Seoul National University)(NO.4199990514025);Woojoo Lee was supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(no.2021R1A2C1014409).

摘　　要：This paper discusses our collaboration work with government officers in the health department of Seoul during the COVID-19 pandemic.First,we focus on short-term forecasting for the number of new confirmed cases and severe cases.Second,we focus on understanding how much of the current infections has been affected by external influx from neighborhood areas or internal transmission within the area.This understanding may be important because it is linked to the government policy determining nonpharmaceutical interventions.To obtain the decomposition of the effect,districts of Seoul should be considered simultaneously,and multivariate time series models are used.Third,we focus on predicting the number of new weekly confirmed cases for each district in Seoul.This detailed prediction may be important to the government policy on resource allocation.We consider an ensemble method to overcome poor prediction performance of simple models.This paper presents the methodological details and analysis results of the study.

关 键 词：Count time series model COVID-19 Endemic-epidemic model 

分 类 号：R563.1[医药卫生—呼吸系统]