Global Events

Global events are functions that are executed at each time step of the simulation. They are useful for implementing interventions, such as vaccination, isolation, and social distancing by means of tools.

Usage

globalevent_tool(tool, prob, name = get_name_tool(tool), day = -99)

globalevent_tool_logit(
  tool,
  vars,
  coefs,
  name = get_name_tool(tool),
  day = -99
)

globalevent_set_params(
  param,
  value,
  name = paste0("Set ", param, " to ", value),
  day = -99
)

globalevent_fun(fun, name = deparse(substitute(fun)), day = -99)

add_globalevent(model, event, action = NULL)

rm_globalevent(model, event)

Arguments

tool: An object of class tool.
prob: Numeric scalar. A probability between 0 and 1.
name: Character scalar. The name of the action.
day: Integer. The day (step) at which the action is executed (see details).
vars: Integer vector. The position of the variables in the model.
coefs: Numeric vector. The coefficients of the logistic regression.
param: Character scalar. The name of the parameter to be set.
value: Numeric scalar. The value of the parameter.
fun: Function. The function to be executed.
model: An object of class epiworld_model.
event: The event to be added or removed. If it is to add, then it should be an object of class epiworld_globalevent. If it is to remove, it should be an integer with the position of the event in the model (starting from zero).
action: (Deprecated) use event instead.

Value

The globalevent_set_params function returns an object of class epiworld_globalevent_set_param and epiworld_globalevent.
globalevent_tool returns an object of class epiworld_globalevent_tool and epiworld_globalevent.
globalevent_tool_logit returns an object of class epiworld_globalevent_tool_logit and epiworld_globalevent.

The function add_globalevent returns the model with the added event

The function rm_globalevent returns the model with the removed event.

Details

The function globalevent_tool_logit allows to specify a logistic regression model for the probability of using a tool. The model is specified by the vector of coefficients coefs and the vector of variables vars. vars is an integer vector indicating the position of the variables in the model.

The function globalevent_set_param allows to set a parameter of the model. The parameter is specified by its name param and the value by value.

The function globalevent_fun allows to specify a function to be executed at a given day. The function object must receive an object of class epiworld_model as only argument.

The function add_globalevent adds a global action to a model. The model checks for actions to be executed at each time step. If the added action matches the current time step, the action is executed. When day is negative, the action is executed at each time step. When day is positive, the action is executed at the specified time step.

Examples

# Simple model
model_sirconn <- ModelSIRCONN(
  name                = "COVID-19",
  n                   = 10000,
  prevalence          = 0.01,
  contact_rate        = 5,
  transmission_rate   = 0.4,
  recovery_rate       = 0.95
)

# Creating a tool
epitool <- tool(
  name = "Vaccine",
  prevalence = 0,
  as_proportion = FALSE,
  susceptibility_reduction = .9,
  transmission_reduction = .5,
  recovery_enhancer = .5,
  death_reduction = .9
)


# Adding a global event
vaccine_day_20 <- globalevent_tool(epitool, .2, day = 20)
add_globalevent(model_sirconn, vaccine_day_20)

# Running and printing
run(model_sirconn, ndays = 40, seed = 1912)
#> _________________________________________________________________________
#> |Running the model...
#> |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| done.
#> | done.
model_sirconn
#> ________________________________________________________________________________
#> Susceptible-Infected-Removed (SIR) (connected)
#> It features 10000 agents, 1 virus(es), and 1 tool(s).
#> The model has 3 states.
#> The final distribution is: 2012 Susceptible, 0 Infected, and 7988 Recovered.
plot_incidence(model_sirconn)


# Example 2: Changing the contact rate -------------------------------------
model_sirconn2 <- ModelSIRCONN(
  name                = "COVID-19",
  n                   = 10000,
  prevalence          = 0.01,
  contact_rate        = 5,
  transmission_rate   = 0.4,
  recovery_rate       = 0.95
)

closure_day_10 <- globalevent_set_params("Contact rate", 0, day = 10)
add_globalevent(model_sirconn2, closure_day_10)

# Running and printing
run(model_sirconn2, ndays = 40, seed = 1912)
#> _________________________________________________________________________
#> |Running the model...
#> |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| done.
#> | done.
model_sirconn2
#> ________________________________________________________________________________
#> Susceptible-Infected-Removed (SIR) (connected)
#> It features 10000 agents, 1 virus(es), and 0 tool(s).
#> The model has 3 states.
#> The final distribution is: 2083 Susceptible, 0 Infected, and 7917 Recovered.
plot_incidence(model_sirconn2)

# Example using `globalevent_fun` to record the state of the
# agents at each time step.

# We start by creating an SIR connected model
model <- ModelSIRCONN(
  name              = "SIR with Global Saver",
  n                 = 1000,
  prevalence        = 0.01,
  contact_rate      = 5,
  transmission_rate = 0.4,
  recovery_rate     = 0.3
)

# We create the object where the history of the agents will be stored
agents_history <- NULL

# This function prints the total number of agents in each state
# and stores the history of the agents in the object `agents_history`
hist_saver <- function(m) {

  message("Today's totals are: ", paste(get_today_total(m), collapse = ", "))

  # We use the `<<-` operator to assign the value to the global variable
  # `agents_history` (see ?"<<-")
  agents_history <<- cbind(
    agents_history,
    get_agents_states(m)
  )

}

Usage

Arguments

Value

Details

See also

Examples