A more complex SHLIR model flow diagram, with risk groups, treatment, and reinfection for those who have recovered from active disease

SHLITR_risk_demographics_ode(t, x, params)

Arguments

t

The timestep over which to calculate derivatives

x

A numeric vector of compartment populations.

params

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, ## High risk population S_H = 199, H_H = 0, L_H = 0, I_H = 1, Tr_H = 0, R_H = 0 ) parameters <- c( beta = 3, # Rate of transmission beta_H = 6, # High risk 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 p = 0.2, # proportion of new births that are high risk M = 0.2 # Between group mixing ) SHLITR_risk_demographics_ode(1, inits, parameters)
#> [[1]] #> S S H H I Tr S_H #> -0.9600000 0.9600000 0.0000000 0.0000000 0.0000000 0.0000000 -1.1816543 #> S_H H_H H_H I_H Tr_H #> 1.1940000 0.0000000 -0.3456790 0.3333333 0.0000000 #>