Susceptible Exposed Infected Recovered model (SEIR)

## Arguments

- name
String. Name of the virus.

- prevalence
Double. Initial proportion of individuals with the virus.

- transmission_rate
Numeric scalar between 0 and 1. Virus's rate of infection.

- incubation_days
Numeric scalar greater than 0. Average number of incubation days.

- recovery_rate
Numeric scalar between 0 and 1. Rate of recovery_rate from virus.

- x
Object of class SEIR.

- main
Title of the plot

- ...
Currently ignore.

## Value

The

`ModelSEIR`

function returns a model of class epiworld_model.

The `plot`

function returns a plot of the SEIR model of class
epiworld_model.

## Details

The initial_states function allows the user to set the initial state of the model. The user must provide a vector of proportions indicating the following values: (1) Proportion of non-infected agents who are removed, and (2) Proportion of exposed agents to be set as infected.

## See also

epiworld-methods

Other Models:
`ModelDiffNet()`

,
`ModelSEIRCONN()`

,
`ModelSEIRD()`

,
`ModelSEIRDCONN()`

,
`ModelSIR()`

,
`ModelSIRCONN()`

,
`ModelSIRD()`

,
`ModelSIRDCONN()`

,
`ModelSIRLogit()`

,
`ModelSIS()`

,
`ModelSISD()`

,
`ModelSURV()`

,
`epiworld-data`

## Examples

```
model_seir <- ModelSEIR(name = "COVID-19", prevalence = 0.01,
transmission_rate = 0.9, recovery_rate = 0.1, incubation_days = 4)
# Adding a small world population
agents_smallworld(
model_seir,
n = 1000,
k = 5,
d = FALSE,
p = .01
)
# Running and printing
run(model_seir, ndays = 100, seed = 1912)
#> _________________________________________________________________________
#> Running the model...
#> ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| done.
#> done.
model_seir
#> ________________________________________________________________________________
#> Susceptible-Exposed-Infected-Removed (SEIR)
#> It features 1000 agents, 1 virus(es), and 0 tool(s).
#> The model has 4 states.
#> The final distribution is: 0 Susceptible, 0 Exposed, 7 Infected, and 993 Removed.
plot(model_seir, main = "SEIR Model")
```