我必须使用SIR模型来模拟流行病

Question

图形出来时我的代码有问题，我不知道错误在哪里？

simulation_epidemie_SIR<-function(taille1,suspect1,infect1,remov1,alpha1,beta1)


{
 taille<-taille1  #population
 suscept<-rep(0,taille)   #suspect
 infect<-rep(0,taille)   #infected persons
 remov<-rep(0,taille)    #non infected
 time<-rep(0,taille)     #time
 nvcas<-rep(0,taille)  #new cases
 suscept[1]<-suspect1   #my nombre of suspect
 infect[1]<-infect1
 remov[1]<-remov1
 beta<-beta1          #infectious rate/day
 alpha<-alpha1         #recovery rate/day
 for(i in 1:(taille-1))      #from here it's my teacher code 
 {
   if(infect[i]!=0)             # i did'nt change any thing here 
   {
     s<--log(runif(1))/(beta*suscept[i]*infect[i]+alpha*

     infect[i])
     time[i+1]<-time[i]+s
     rand<-runif(1)                        #
     proba<-beta*suscept[i]*infect[i]/(beta*suscept[i]*infect[i]+alpha*infect[i])
     if (rand<=proba)
     {
       suscept[i+1]<-suscept[i]-1             #
       infect[i+1]<-infect[i]+1                #
       remov[i+1]<-remov[i]
       nvcas[i+1]<-1                             #
     }
     if (rand>proba)
     {
       suscept[i+1]<-suscept[i]      #the method of my teacher i did'nt change any thing here 
       infect[i+1]<-infect[i]-1
       remov[i+1]<-remov[i]+1          #
       nvcas[i+1]<-0                   #
     }
  }       ##
}         #
  suscept_red<-suscept[suspect=!0]              #from here i write it
  infect_red<-infect[suscept=!0]                # for starting
  remov_red<-remov[suscept=!0]                  # i could do better here 
  time_red<-time[suspect=!0]                    # i think here ther eis a proplem
  par(mfrow=c(2,3))                             #with this 4 codes
  plot(time_red,suscept_red,type = "l",col= "red",xlab = "Temps",ylab = "Nb de cas susceptible",main = "Evolution des patients suspects")    #i have a problem with this graphic
  plot(time_red,infect_red,type = "l",col= "blue",xlab = "Temps",ylab = "Nb de cas infectés",main = "Evolution des patients infectés")      #and this one
  plot(time_red,remov_red,type = "l",col= "green",xlab = "Temps",ylab = "Nb de cas retirés",main = "Evolution des patients suspects")        #also this one
  tnvcas<-rep(0,365)     #for one year from day one
  for (i in 1:365)     
 tnvcas[i]<-sum(nvcas[(i-1)<time & time<=i])  
  plot(1:365,tnvcas,type = "l",col = "purple",xlab = "Jours", ylab = "Nb de nouveau cas"
   ,main = "Evolution du Nb de nouveau cas par jours", font.main = 1.5,font.lab = 3
   ,font.sub = 3,cex.main = 1.8, cex.lab = 1.5, cex.sub = 1.5)   #plot of new cases
  sum(nvcas)     #to sum new cases
  sum(tnvcas)
  incidence<- tnvcas/taille1    #here to calculte the impact = new cases/ population
  incidence_red<-incidence[incidence=!0]   #here to calculate the decrease in incidence
  return(list(taille=sum(tnvcas),incidence=incidence,durée=length(incidence_red)))  #
                                                                                    #
}
simulation_epidemie_SIR2<-simulation_epidemie_SIR(100000,10000,5,90000,0.4,0.0000524)  #
#these are the chiffres i have to use them