A modified SEIR model with a jump in the transmission parameter applied to COVID‐19 data on Wuhan. Issue 1 (23rd December 2022)

• Record Type: Journal Article
• Authors: Bai, Tian; Wang, Dianpeng; Dai, Wenlin
• Is Part Of: Stat. Volume 11:Issue 1(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-12-23
• Subjects: COVID‐19 -- model selection -- SEIR model -- time‐varying parameter; Statistics -- Periodicals; 519.2
• DOI: 10.1002/sta4.511
• Languages: English
• ISSNs: 2049-1573

Abstract

Abstract : In December 2019, Wuhan, the capital of Hubei Province, was struck by an outbreak of COVID‐19. Numerous studies have been conducted to fit COVID‐19 data and make statistical inferences. In applications, functions of the parameters in the model are usually used to assess severity of the outbreak. Because of the strategies applied during the struggle against the pandemic, the trend of the parameters changes abruptly. However, time‐varying parameters with a jump have received scant attention in the literature. In this study, a modified SEIR model is proposed to fit the actual situation of the COVID‐19 epidemic. In the proposed model, the dynamic propagation system is modified because of the high infectivity during incubation, and a time‐varying parametric strategy is suggested to account for the utility of the intervention. A corresponding model selection algorithm based on the information criterion is also suggested to detect the jump in the transmission parameter. A real data analysis based on the COVID‐19 epidemic in Wuhan and a simulation study demonstrate the plausibility and validity of the proposed method.