A more complex SHLIR model flow diagram, treatment,reinfection, and simple demographics for those who have recovered from active disease.

SHLITR_demographics_ode(t, x, params)

## Arguments

t The timestep over which to calculate derivatives A numeric vector of compartment populations. A named vector of parameter values.

## Value

A vector of derivatives

## Examples


## initialise
inits <- c(
# General population
S = 800,
H = 0,
L = 0,
I = 0,
Tr = 0,
R = 0
)

parameters <- c(
beta = 3, # Rate of transmission
gamma_H = 1/5, # Rate of progression to active symptoms from high risk latent
nu = 1/2, #Rate of progression from high to low risk latent
gamma_L = 1/100, # Rate of progression to active symptoms for low risk latent
epsilon = 1/3, # Rate of treatment
tau = 1/2, # Rate of recovery
mu = 1/81 # Rate of natural mortality
)

SHLITR_demographics_ode(1, inits, parameters)#> [[1]]
#>  S  S  H  H  I Tr
#>  0  0  0  0  0  0
#>