Type: Package
Title: A 'shiny' Wrapper of the R Package 'epiworldR'
Version: 0.2.3
Date: 2025-04-30
Description: R 'shiny' web apps for epidemiological Agent-Based Models. It provides a user-friendly interface to the Agent-Based Modeling (ABM) R package 'epiworldR' (Meyer et al., 2023) <doi:10.21105/joss.05781>. Some of the main features of the package include the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Recovered (SIR), and Susceptible-Exposed-Infected-Recovered (SEIR) models. 'epiworldRShiny' provides a web-based user interface for running various epidemiological ABMs, simulating interventions, and visualizing results interactively.
URL: https://github.com/UofUEpiBio/epiworldRShiny/, https://uofuepibio.github.io/epiworldRShiny/,
BugReports: https://github.com/UofUEpiBio/epiworldRShiny/issues/
License: MIT + file LICENSE
RoxygenNote: 7.3.2
Encoding: UTF-8
Suggests: knitr
Imports: utils, DT, ggplot2, epiworldR, plotly, bslib
Depends: R (≥ 4.1.0), shiny
NeedsCompilation: no
Packaged: 2025-05-13 21:58:12 UTC; runner
Author: George Vega Yon ORCID iD [aut], Derek Meyer ORCID iD [aut], Andrew Pulsipher ORCID iD [aut, cre], Centers for Disease Control and Prevention [fnd] (Award number 1U01CK000585; 75D30121F00003), Lindsay Keegan ORCID iD [ctb], Karim Khader ORCID iD [ctb], Damon Toth ORCID iD [ctb], Randon Gruninger [ctb], Matthew Samore ORCID iD [ctb], Jay Love ORCID iD [ctb], Kristina Stratford [ctb]
Maintainer: Andrew Pulsipher <pulsipher.a@gmail.com>
Repository: CRAN
Date/Publication: 2025-05-14 14:50:02 UTC

epiworldRShiny App Launcher

Description

Fires up the R Shiny App. You can find more examples and documentation at the package's website: https://UofUEpiBio.github.io/epiworldRShiny/.

run_app is a wrapper for the epiworldRShiny function. It is a convenience function to run the app.

Usage

epiworldRShiny(custom_models_path = NULL, ...)

run_app(custom_models_path = NULL, ...)

Arguments

custom_models_path

Optional path to custom model files (see details).

...

Currently ignored.

Details

When custom_models_path is specified, the function will look for valid model files at the specified path. These will be added to the list of available models. The function expects R files named ⁠shiny_<model_name>.R⁠ which contain the model. The function will also look for optional Markdown files named ⁠shiny_<model_name>.md⁠ which contain the model description.

Value

Loads and opens the R shiny app for the epiworldR package

Access to the epiworldR environment.

Description

This function is for internal use only.

Usage

epiworldRenv()

Value

Returns the epiworldR_env environment.

epiworldRShiny UI builder functions

Description

All functions in this section are for internal use only. They are used to build the UI for the epiworldRShiny app.

Usage

text_input_disease_name(model_name)

slider_prevalence(model_name)

numeric_input_ndays(model_name)

slider_input_rate(model_name, rate_name, value, maxval = 1, input_label = NULL)

network_input(model_name)

npis_input(model_name)

seed_input(model_name)

models_setup(custom_models_path = NULL)

population_input(model_name)

simulate_button(model_name)

Arguments

model_name

Name of the epiworldR model.

rate_name

Name of the rate.

value

Initial value for the slider.

maxval

Maxiumum value for the slider.

input_label

Aids in creating the appropriate slider name.

custom_models_path

Optional path to custom model files (see details).

Details

When custom_models_path is specified, the function will look for valid model files at the specified path. These will be added to the list of available models. The function expects R files named ⁠shiny_<model_name>.R⁠ which contain the model.

Value

Examples

text_input_disease_name("SEIRD")
slider_prevalence("SEIRD")
numeric_input_ndays("SEIRD")
slider_input_rate("SEIRD", "transmission", value = 0.3, maxval = 1,
input_label = NULL)
network_input("SEIRD")
npis_input("SEIRD")
seed_input("SEIRD")
# Setup with default models only:
models_setup()
# Setup with default and custom models:
## Not run: models_setup(custom_models_path = "path/to/custom/models")
population_input("SEIRD")
simulate_button("SEIRD")

Find the right plotting-scale

Description

This function determines the scale of the y-axis for plot_epi.

Usage

find_scale(x)

Arguments

x

The maximum value found in the model state counts

Value

An integer representing the scale for the y-axis. A max counts value of 10000 will return a scale of 1, 100000 will return a scale of 1000, 1000000 will return a scale of 10000.

See Also

Other Server side functions: plot_epi(), plot_reproductive_epi(), pop_generator()

Examples

find_scale(100000)

NPI adding function

Description

NPI adding function

Usage

interventions_add_all(model, modelname, input)

Arguments

model

epiworldR model.

modelname

Specified model.

input

User epiworldR model selection.

Value

Returns an object of class epiworld_model, where model is substituted with the model name.

See Also

Other interventions: npi_add_masking(), npi_add_school_closure(), pi_add_vaccine()

Masking intervention (non-pharmaceutical intervention)

Description

Masking intervention (non-pharmaceutical intervention)

Usage

npi_add_masking(model, preval, transmission_reduction)

Arguments

model

epiworldR model.

preval

Prevalence of masking within the population.

transmission_reduction

Reduction in transmission probability due to masking

Value

Returns an object of class epiworld_model, where model is substituted with the model name.

See Also

Other interventions: interventions_add_all(), npi_add_school_closure(), pi_add_vaccine()

Examples

library(epiworldR) # for ModelSEIRCONN function
model <- ModelSEIRCONN("COVID-19", n = 1000, prevalence = 0.05,
                       contact_rate = 4, transmission_rate = 0.1,
                       incubation_days = 7, recovery_rate = 0.14)
run(model, ndays = 100, seed = 123)
npi_add_masking(model, preval = .8, transmission_reduction = .7)

School closure intervention (non-pharmaceutical intervention)

Description

School closure intervention (non-pharmaceutical intervention)

Usage

npi_add_school_closure(model, preval, day, transmission_reduction)

Arguments

model

epiworldR model.

preval

Prevalence of school closure within the population.

day

Day in the simulation where school closure goes into effect.

transmission_reduction

Reduction in transmission probability due to school closure.

Value

Returns an object of class epiworld_model, where model is substituted with the model name.

See Also

Other interventions: interventions_add_all(), npi_add_masking(), pi_add_vaccine()

Examples

library(epiworldR) # for ModelSEIRCONN function
model <- ModelSEIRCONN("COVID-19", n = 1000, prevalence = 0.05,
                       contact_rate = 4, transmission_rate = 0.1,
                       incubation_days = 7, recovery_rate = 0.14)
run(model, ndays = 100, seed = 123)
npi_add_school_closure(model, preval = .8, transmission_reduction = .3, day = 10)

Vaccination (pharmaceutical intervention)

Description

Vaccination (pharmaceutical intervention)

Usage

pi_add_vaccine(
  model,
  preval,
  susceptibility_reduction,
  transmission_reduction,
  recovery_enhancer,
  death_reduction
)

Arguments

model

epiworldR model.

preval

Initial prevalence of the vaccine.

susceptibility_reduction

Reduction in susceptibility probability due to vaccine.

transmission_reduction

Reduction in transmission probability due to vaccine.

recovery_enhancer

Probability increase in recovery due to vaccine.

death_reduction

Reduction in death probability due to vaccine.

Value

Returns an object of class epiworld_model, where model is substituted with the model name.

See Also

Other interventions: interventions_add_all(), npi_add_masking(), npi_add_school_closure()

Examples

library(epiworldR) # for ModelSEIRCONN function
model <- ModelSEIRCONN("COVID-19", n = 1000, prevalence = 0.05,
                       contact_rate = 4, transmission_rate = 0.1,
                       incubation_days = 7, recovery_rate = 0.14)
run(model, ndays = 100, seed = 123)
pi_add_vaccine(model, preval = .8, susceptibility_reduction = .9,
                transmission_reduction = .5, recovery_enhancer = .5,
                death_reduction = .9)

Plot daily incidence

Description

This function generates a plot of the model states over time

Usage

plot_epi(model, mark_max)

Arguments

model

The number of individuals in the population.

mark_max

The state which will have a mark at the peak

Value

A plot displaying each state from the model over the course of the simulation

See Also

Other Server side functions: find_scale(), plot_reproductive_epi(), pop_generator()

Examples

library(epiworldR) # for ModelSEIRCONN function
model <- ModelSEIRCONN("COVID-19", n = 1000, prevalence = 0.05,
                       contact_rate = 4, transmission_rate = 0.1,
                       incubation_days = 7, recovery_rate = 0.14)
run(model, ndays = 100, seed = 123)
plot_epi(model, mark_max = "Infected")

Plot Rt

Description

This function generates a plot of the reproductive number over time

Usage

plot_reproductive_epi(model)

Arguments

model

The model object

Value

A plot displaying the reproductive number for the model over the course of the simulation

See Also

Other Server side functions: find_scale(), plot_epi(), pop_generator()

Examples

library(epiworldR) # for ModelSEIRCONN function
model <- ModelSEIRCONN("COVID-19", n = 1000, prevalence = 0.05,
                       contact_rate = 4, transmission_rate = 0.1,
                       incubation_days = 7, recovery_rate = 0.14)
run(model, ndays = 100, seed = 123)
plot_reproductive_epi(model)

Population generator

Description

This function generates a population matrix with specified characteristics.

Usage

pop_generator(
  n,
  prop_hispanic = 0.5,
  prop_female = 0.5,
  prop_19_59_60plus = c(0.3, 0.6)
)

Arguments

n

The number of individuals in the population.

prop_hispanic

The proportion of individuals who are Hispanic. Default is 0.5.

prop_female

The proportion of individuals who are female. Default is 0.5.

prop_19_59_60plus

A vector of length 3 representing the proportions of individuals in the age groups 0-19, 20-59, and 60+. Default is c(0.5, 0.3, 0.2).

Value

A matrix representing the generated population, with columns for age groups (0-19, 20-59, 60+), NotHispanic, and Female.

See Also

Other Server side functions: find_scale(), plot_epi(), plot_reproductive_epi()

Examples

pop_generator(n = 1000, prop_hispanic = .5, prop_female = .5,
              prop_19_59_60plus = c(.3, .6))