tool {epiworldR}R Documentation

Tools in epiworld

Description

Tools are functions that affect how agents react to the virus. They can be used to simulate the effects of vaccination, isolation, and social distancing.

Usage

tool(
  name,
  susceptibility_reduction,
  transmission_reduction,
  recovery_enhancer,
  death_reduction
)

set_name_tool(tool, name)

get_name_tool(tool)

add_tool(model, tool, proportion)

add_tool_n(model, tool, n)

rm_tool(model, tool_pos)

tool_fun_logit(vars, coefs, model)

set_susceptibility_reduction(tool, prob)

set_susceptibility_reduction_ptr(tool, model, param)

set_susceptibility_reduction_fun(tool, model, tfun)

set_transmission_reduction(tool, prob)

set_transmission_reduction_ptr(tool, model, param)

set_transmission_reduction_fun(tool, model, tfun)

set_recovery_enhancer(tool, prob)

set_recovery_enhancer_ptr(tool, model, param)

set_recovery_enhancer_fun(tool, model, tfun)

set_death_reduction(tool, prob)

set_death_reduction_ptr(tool, model, param)

set_death_reduction_fun(tool, model, tfun)

## S3 method for class 'epiworld_agents_tools'
print(x, max_print = 10, ...)

Arguments

name

Name of the tool

susceptibility_reduction

Numeric. Proportion it reduces susceptibility.

transmission_reduction

Numeric. Proportion it reduces transmission.

recovery_enhancer

Numeric. Proportion it improves recovery.

death_reduction

Numeric. Proportion it reduces probability of death.e

tool

An object of class epiworld_tool

model

Model

proportion

In the case of add_tool, a proportion, otherwise, an integer.

n

A positive integer. Number of agents to initially have the tool.

tool_pos

Positive integer. Index of the tool's position in the model.

vars

Integer vector. Indices (starting from 0) of the positions of the variables used to compute the logit probability.

coefs

Numeric vector. Of the same length of vars, is a vector of coefficients associated to the logit probability.

prob

Numeric scalar. A probability (between zero and one).

param

Character scalar. Name of the parameter featured in model that will be added to the tool (see details).

tfun

An object of class epiworld_tool_fun.

x

An object of class epiworld_agents_tools.

max_print

Numeric scalar. Maximum number of tools to print.

...

Currently ignored.

Details

The name of the epiworld_tool object can be manipulated with the functions set_name_tool() and get_name_tool().

The add_tool function adds the specified tool to the model of class epiworld_model with specified proportion.

In the case of set_susceptibility_reduction_ptr, set_transmission_reduction_ptr, set_recovery_enhancer, and set_death_reduction_ptr, the corresponding parameters are passed as a pointer to the tool. The implication of using pointers is that the values will be read directly from the model object, so changes will be reflected.

Value

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
)

# Running and printing
run(model_sirconn, ndays = 100, seed = 1912)
plot(model_sirconn)

epitool <- tool(
  name = "Vaccine",
  susceptibility_reduction = .9,
  transmission_reduction = .5,
  recovery_enhancer = .5, 
  death_reduction = .9
)

epitool

set_name_tool(epitool, 'Pfizer') # Assigning name to the tool
get_name_tool(epitool) # Returning the name of the tool
add_tool(model_sirconn, epitool, .5)
run(model_sirconn, ndays = 100, seed = 1912)
model_sirconn
plot(model_sirconn)

# To declare a certain number of individuals with the tool
rm_tool(model_sirconn, 0) # Removing epitool from the model
add_tool_n(model_sirconn, epitool, 5500)
run(model_sirconn, ndays = 100, seed = 1912)

# Adjusting probabilities due to tool
set_susceptibility_reduction(epitool, 0.1) # Susceptibility reduction 
set_transmission_reduction(epitool, 0.2) # Transmission reduction
set_recovery_enhancer(epitool, 0.15) # Probability increase of recovery
set_death_reduction(epitool, 0.05) # Probability reduction of death
run(model_sirconn, ndays = 100, seed = 1912) # Run model to view changes


# Using the logit function --------------
sir <- ModelSIR(
  name = "COVID-19", prevalence = 0.01, 
  transmission_rate = 0.9, recovery_rate = 0.1
  )

# Adding a small world population
agents_smallworld(
  sir,
  n = 10000,
  k = 5,
  d = FALSE,
  p = .01
)

# Creating a tool
mask_wearing <- tool(
  name = "Mask",
  susceptibility_reduction = 0.0,
  transmission_reduction   = 0.3, # Only transmission
  recovery_enhancer        = 0.0,
  death_reduction          = 0.0
)

add_tool(sir, mask_wearing, .5)

run(sir, ndays = 50, seed = 11)
hist_0 <- get_hist_total(sir)

# And adding features
dat <- cbind(
  female = sample.int(2, 10000, replace = TRUE) - 1,
  x      = rnorm(10000)
)

set_agents_data(sir, dat)

# Creating the logit function
tfun <- tool_fun_logit(
  vars  = c(0L, 1L),
  coefs = c(-1, 1),
  model = sir
)

# The infection prob is lower
hist(plogis(dat %*% rbind(.5,1)))

tfun # printing


set_susceptibility_reduction_fun(
  tool  = get_tool(sir, 0),
  model = sir,
  tfun  = tfun
  )
  
run(sir, ndays = 50, seed = 11)
hist_1 <- get_hist_total(sir)

op <- par(mfrow = c(1, 2))
plot(hist_0); abline(v = 30)
plot(hist_1); abline(v = 30)
par(op)
[Package epiworldR version 0.1-0 Index]