Evaluations of COVID-19 epidemic models with multiple susceptible compartments using exponential and non-exponential distribution for disease stages  

作　　者：Yan Chen Haitao Song Shengqiang Liu 

机构地区：[1]School of Mathematical Sciences,Tiangong University,Tianjin,300387,China [2]Complex Systems Research Center,Shanxi University,Taiyuan,030006,China

出　　处：《Infectious Disease Modelling》2022年第4期795-810,共16页传染病建模（英文）

基　　金：supported by the National Natural Science Foundation of China(12271401,11871179,11771128,12171291);the Fund Program for the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province(20200001);the Fundamental Research Program of Shanxi Province(202103021224018).

摘　　要：Mathematical models have wide applications in studying COVID-19 epidemic transmission dynamics,however,most mathematical models do not take into account the heterogeneity of susceptible populations and the non-exponential distribution infectious period.This paper attempts to investigate whether non-exponentially distributed infectious period can better characterize the transmission process in heterogeneous susceptible populations and how it impacts the control strategies.For this purpose,we establish two COVID-19 epidemic models with heterogeneous susceptible populations based on different assumptions for infectious period:the first one is an exponential distribution model(EDM),and the other one is a gamma distribution model(GDM);explicit formula of peak time of the EDM is presented via our analytical approach.By data fitting with the COVID-19(Omicron)epidemic in Spain and Norway,it seems that Spain is more suitable for EDM while Norway is more suitable for GDM.Finally,we use EDM and GDM to evaluate the impaction of control strategies such as reduction of transmission rates,and increase of primary course rate(PCR)and booster dose rate(BDR).

关 键 词：Mathematical models COVID-19 Exponential distribution Gamma distribution Peak time 

分 类 号：R563.1[医药卫生—呼吸系统]