Rows not being added to data frame in R - r

Question

So, I've been trying to do a simulation study about a SIR-model.
I have the following code (Tryed to clean it up):
# Initial parameters
N <- 1E6 # Total population
I <- 1 # Number of Infectious at time 0
S <- N-1 # Number of Susceptibles at time 0
R <- 0 # Number of Recovered at time 0
# Vector to store observations in
Df1 <- data.frame("final_size" = as.numeric(), "peak_size" = as.numeric())
# Setting a seed for reproducibility
set.seed(1996)
n_sim <- 100
# Setting different values for R0, the basic reproduction number
R0 <- seq(0.5,2.5, 1)
for(values in R0){
if(values == 0.5){
# Transmission parameters
R0 <- values # Basic Reproduction number
nu <- 1/6 # Recovery rate (in days)
b <- nu*R0/N # Infection rate (in days)
for(sim in n_sim){
temp <- NULL
# Binomial model
#----------------
# Initial states
Sold = S # Number of Susceptibles at time t=0
Iold = I # Number of Infectious at time t=0
Rold = R # Number of Recovered at time t=0
# Output vectors
Svec =Sold; Ivec = Iold; Rvec = Rold
stop = FALSE
# Loop - continue until stop=TRUE
while (!stop){
Ih = rbinom(1,Sold,(1-exp(-b*Iold)))
Rh = rbinom(1,Iold,(1-exp(-nu)))
Rh = nu*Iold
Sold = Sold-Ih
Iold = Iold+Ih-Rh
Rold = Rold+Rh
Svec = c(Svec,Sold)
Ivec = c(Ivec,Iold)
Rvec = c(Rvec,Rold)
if (Iold<=2e-5){stop=T}
}
peak_size_df <- max(Ivec)
final_size_df <- Rvec[length(Rvec)]/N
temp <- rbind(temp, c(final_size_df, peak_size_df))
colnames(temp) <- c("final_size", "peak_size")
Df1 <- rbind(Df1, temp)
}
}
}
I'm looking to store data in Df1. However, at the end of the loop, only 1 loop has been stored, I assume the last loop. Which I don't really properly understand. I've recoded it a few times and in those cases I ended up with 99 NA rows for final size and peak size. In this version, I only end up with 1 row (with values however). I plan on expanding the loop for different values of R0 as seen in the R0 seq. Due to it not working for the first value, I haven't expanded it yet.
Any suggestions? Improvements?
After comments from Gregory and Cath, the following adjustments:
# Setting a seed for reproducibility
#set.seed(1996)
n_sim <- 100
# Initial parameters
N <- 1E6 # Total population
I <- 1 # Number of Infectious at time 0
S <- N-1 # Number of Susceptibles at time 0
R <- 0 # Number of Recovered at time 0
# Vector to store observations in
Df1 <- data.frame("final_size" = rep(NA, n_sim), "peak_size" = rep(NA, n_sim))
Df2 <- NULL
Df3 <- NULL
# Setting different values for R0, the basic reproduction number
R0 <- seq(0.5,2.5, 1)
#plot(Svec, type = "l", ylim = c(0, 1000000), col = "red")
#lines(Rvec, type = "l", col = "blue")
#lines(Ivec, type = "l")
#max(Ivec)
for(values in R0){
if(values == 0.5){
# Transmission parameters
R0_value <- values # Basic Reproduction number
nu <- 1/6 # Recovery rate (in days)
b <- nu*R0_value/N # Infection rate (in days)
for(sim in n_sim){
# Binomial model
#----------------
# Initial states
Sold = S # Number of Susceptibles at time t=0
Iold = I # Number of Infectious at time t=0
Rold = R # Number of Recovered at time t=0
# Output vectors
Svec =Sold; Ivec = Iold; Rvec = Rold
stop = FALSE
# Loop - continue until stop=TRUE
while (!stop){
Ih = rbinom(1,Sold,(1-exp(-b*Iold)))
Rh = rbinom(1,Iold,(1-exp(-nu)))
Rh = nu*Iold
Sold = Sold-Ih
Iold = Iold+Ih-Rh
Rold = Rold+Rh
Svec = c(Svec,Sold)
Ivec = c(Ivec,Iold)
Rvec = c(Rvec,Rold)
if (Iold<=2e-5){stop=T}
}
peak_size_df <- max(Ivec)
final_size_df <- Rvec[length(Rvec)]/N
Df1[sim, "final_size"] <- final_size_df
Df1[sim, "peak_size"] <- peak_size_df
}
}
}
Which gives me 99 rows with NA and row 100 the last simulation with values.
Any idea what is causing the NA's?