Load package:
library(deSolve)
library(dplyr)##
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
##
## filter, lag
## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union
library(tidyr)
library(ggplot2)
library(SIRdiagrams)SIR model:
out_SIR <- run_model()
plot_sim(out_SIR)
SIR model with birth (no more R):
out_SIR2 <- run_model(parms=c(mu=1/52, beta=2, gamma=1),
tvec=seq(0, 52*2, by=0.1))
plot_sim(out_SIR2, vars = c("S", "I"))
SIR model with higher birth (no more R):
out_SIR3 <- run_model(parms=c(mu=1/52*2, beta=2, gamma=1),
tvec=seq(0, 52*2, by=0.1))
plot_sim(out_SIR2, vars = c("S", "I")) 
Overlay:
plot_sim(out_SIR3, vars = c("S", "I")) +
geom_line(data=out_SIR2, aes(time, S), col="red", alpha=0.5, lty=2) +
geom_line(data=out_SIR2, aes(time, I), col="blue", alpha=0.5, lty=2)
Seasonal SIR
out_SIR4 <- run_model(
model=seasonalSIRmodel,
parms=c(mu=1/52/50, beta0=17/2, theta=0.1, gamma=1/2),
tvec=seq(0, 52*22, by=0.1),
yini=c(S=0.05, I=1e-4, R=0))
plot_sim(out_SIR4, vars = c("I"), ylim=c(0, 0.005), deltat=52, tunit="(year)") 