A five-compartment model of age-specific transmissibility of SARS-CoV-2

Background:The novel coronavirus,severe acute respiratory syndrome coronavirus 2(SARS-CoV-2,also called 2019-nCoV)causes different morbidity risks to individuals in different age groups.This study attempts to quantify the age-specific transmissibility using a mathematical model.Methods:An epidemiological model with five compartments(susceptible-exposed-symptomatic-asymptomatic-recovered/removed[SEIAR])was developed based on observed transmission features.Coronavirus disease 2019(COVID-19)cases were divided into four age groups:group 1,those≤14years old;group 2,those 15 to 44years old;group 3,those 45 to 64years old;and group 4,those≥65 years old.The model was initially based on cases(including imported cases and secondary cases)collected in Hunan Province from January 5 to February 19,2020.Another dataset,from Jilin Province,was used to test the model.Results:The age-specific SEIAR model fitted the data well in each age group(P<0.001).In Hunan Province,the highest transmissibility was from age group 4 to 3(median:β43=7.71×10-9;SAR43=3.86×10-8),followed by group 3 to 4(median:β34=3.07×10-9;SAR34=1.53×10-8),group 2 to 2(median:β22=1.24×10-9;SAR22=6.21×10-9),and group 3 to 1(median:β31=4.10×10-10;SAR31=2.08×10-9).The lowest transmissibility was from age group 3 to 3(median:β33=1.64×10-19;SAR33=8.19×10-19),followed by group 4 to 4(median:β44=3.66×10-17;SAR44=1.83×10-16),group 3 to 2(median:β32=1.21×10-16;SAR32=6.06×10-16),and group 1 to 4(median:β14=7.20×10-14;SAR14=3.60×10-13).In Jilin Province,the highest transmissibility occurred from age group 4 to 4(median:β43=4.27×10-8;SAR43=2.13×10-7),followed by group 3 to 4(median:β34=1.81×10-8;SAR34=9.03×10-8).Conclusions:SARS-CoV-2 exhibits high transmissibility between middle-aged(45 to 64 years old)and elderly(≥65 years old)people.Children(≤14 years old)have very low susceptibility to COVID-19.This study will improve our understanding of the transmission feature of SARS-CoV-2 in different age groups and suggest the most prevention measures should be applied to middle-aged and elderly people.

Effectiveness of potential antiviral treatments in COVID-19 transmission control:a modelling study

Background:Novel coronavirus disease 2019(COVID-19)causes an immense disease burden.Although public health countermeasures effectively controlled the epidemic in China,non-pharmaceutical interventions can neither be maintained indefinitely nor conveniently implemented globally.Vaccination is mainly used to prevent COVID-19,and most current antiviral treatment evaluations focus on clinical efficacy.Therefore,we conducted population-based simulations to assess antiviral treatment effectiveness among different age groups based on its clinical efficacy.

Feasibility of controlling hepatitis E in Jiangsu Province, China: a modelling study

Background:Hepatitis E,an acute zoonotic disease caused by the hepatitis E virus(HEV),has a relatively high burden in developing countries.The current research model on hepatitis E mainly uses experimental animal models(such as pigs,chickens,and rabbits)to explain the transmission of HEV.Few studies have developed a multi-host and multiroute transmission dynamic model(MHMRTDM)to explore the transmission feature of HEV.Hence,this study aimed to explore its transmission and evaluate the effectiveness of intervention using the dataset of Jiangsu Province.